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Input substitution and rent dissipation in a limited entry fishery : a case study of the British Columbia… Dupont, Diane Pearl 1988

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INPUT SUBSTITUTION CASE  STUDY  AND  O F THE  RENT DISSIPATION BRITISH  COLUMBIA  IN  A  LIMITED ENTRY  COMMERCIAL SALMON  by DIANE B.A.(Honours), M.A.,  A  THESIS THE  The  P.  DUPONT  Carleton  University  SUBMITTED  IN  1978  Toronto,  1979  PARTIAL  REQUIREMENTS DOCTOR  of  University,  FULFILMENT  FOR THE  OF  DECREE  OF  PHILOSOPHY  in THE  FACULTY  OF  GRADUATE  Department  We  accept to  THE  this  the  of  Economics  thesis  required  UNIVERSITY  OF  January  © Diane  P.  STUDIES  as  conforming  standard  BRITISH  COLUMBIA  1988  Dupont.  1988  OF  FISHERY FISHERY  In  presenting  degree freely  at  the  available  copying  this  of  department publication  of  in  partial  fulfilment  University  of  British  Columbia,  for  this or  thesis  reference  thesis by  this  for  his  and  scholarly  or  thesis  for  her  of  Economics  The University of British C o l u m b i a 1956 Main Mall Vancouver, Canada V 6 T 1Y3 Date  DE-6(3/81)  20  January  1988  I  I further  purposes  gain  the  shall  requirements  agree  that  agree  may  representatives.  financial  permission.  Department  study.  of  be  It not  that  the  be  Library  an  advanced  shall  permission for  granted  is  for  by  understood allowed  the  make  extensive  head  that  without  it  of  copying my  my or  written  ABSTRACT Entry-limiting of a  regulations  encouraging fishermen cost  upon  by the of  society  fishery.  substitution  The  thesis  Columbia  demand degree  functional  types  three that  the  1982  a  major  advantage  between estimates. restricted fish  subject  translog pairs The  is of  salmon.  flexible  its  This  Estimates  of  heretofore used  rent  Four  fisheries  input  of  the to  while  the  of  the  to  total  be  form  normalized,  imposing  ii  in  are  calculated  a  the  rent  value  for of  to  input greater  theoretical to  be  1982  is  the  landed  the  thesis.  million.  in  by  Diewert  degrees in  prices  three  the  and  restricted  entire  profit  of  input  upon  variable  correspond to for  of  observed  quadratic,  output,  British  America  exhibit  developed  convexity  the  elasticities  differing  used which be  one  for  North  proposed  samples  to  in  -$42.8  is  for  rent  estimates  Potential  is estimated  allows  quantitative  assumed  distinguish  are  generated  elasticities  fishery  restrictions  functional  rent  cross-price  dissipation. 44%  suspected  inputs. This imposes  technology  been  in  been  rent dissipation.  given. These  ability  inputs,  function  inputs.  to  of  have  resource  provide  first  season is estimated  uses  the  to  of  harvest  the  represents  model The  the  are  regulated  amount  done  of  types  resource This  of  has  firm  over  substitution  than  a fishing  (1987).  been  one  intensity  vessel  million.  reduced  fisheries  for  associated degree  controls.  of  four of  $73.1  empirical  function  most  has  fishery,  entry  the  a  estimates  salmon  property  unregulated  of  the  first  rent for the  of  Ostensoe  and  the  common  research  substitutability of  be  Actual  form  elasticities  for  model  The  of  Two  to  no  on  substitute  the  limited  input  responsible  to  possibilities and  with  and  literature.  catch.  Almost  commercial  of  shown  in  provides  experiment  A  imposed  the  the  inputs, vessel  fleet,  as  well  as for  The  study  rent  of  that  generated  optimal  number four  an  and  a change  catch  The  amount  thesis  a  fleet.  each  In  Commission to  on be  of in  scenario with  rent dissipation. In  Policy  substitutability  preventing  some  with  of  being  iii  the  per  the  number  of  would  be  efficient is  calculate  vessel types. actual  minimum  each  scenarios,  vessel than  fleet,  determined.  the  for  of  the  including  actually  found  A comparison  rent from  fishermen  redundancy  may  and  of  predicted  that  vessel  implications research  for  endorse  recommendation  a royalty that  each to  the  rent of  the  issue  an  the  of  1982  cause  a  inefficient  problem.  the  (1982)  suggests  rent from  the  the  for  alternative  fleet  of  in conjunction  two  addition,  discussion  Fisheries  for  the  a  costs  This is d o n e  of  with  Pacific  harvest.  activities  to  findings  used  the  contribute  the  for  of  to  particular,  then  estimate  found  using  potential  substitutability  an  of  the  important  by  characteristics  catch among  input-substituting  used  are 1982  of  that  are  input  of  to  fleet  tonnage  repeated  degree  established  the  net  the  addressing the  total  compared  vessel  is  distribution  is  determine  take  exercise  greater  concludes  management.  to  by  calculate  is  To  rent  restricted)  for  each  of  to  This  (the  This  in  distribution  successful  of  in the  suggests  evidence  1982.  levels  of  generated  scheme  in  vessel  efficient  types.  assumption  substantial  each  is completed  amount  vessels required  the  fishery  fishery  actual  amount  vessel  rents  of  output of  components.  salmon  fished  by  Predicted  the  The  demands  vessels  of  the  dissipation.  input  the  each  a  tax  on  vessel  dissipated.  effective the  of  a  fisheries  (Pearse) fleet  catch.  On  the  quota  restriction  Royal  reduction  other  hand,  might  be  TABLE  OF  CONTENTS  Abstract Table  "  of Contents  iv  List of Tables  .  vi  Acknowledgement I.  II.  Introduction A. Overview B. Hypotheses to be Tested C . Findings of the Research D. Conclusions .'.  1 1 4 6 10  The British Columbia Commercial Salmon Fishery A. Description of the Fishery B. History of License Limitation 1. Pre-License Limitation 2. The License Limitation Program  13 13 15 15 16  C. III.  x  18  Conclusions  License Limitation: Theory and Practice A. The Theory Behind License Limitation Programs 1. A Survey of the Theoretical Literature 2. Requirements for an Effective Program B. Empirical Studies of License Limitation Programs 1. Non-Production Function Studies 2. Production Studies  20 20 20 24 32 32 35  IV. Modeling the Behaviour of the Regulated Fishing Firm A. T h e Direct Harvest Production Function 1. Specification of the Direct Harvest Production Function 2. Problems with the Direct Production Function Approach B. The Dual Approach: The Restricted Profit Function 1. A Short-Run, Restricted Profit Maximizing M o d e l  37 38 38 41 44 44  2. Relationship Between the Primal and the Dual Characterizing Technology Using Duality 1. Supply and Demand Functions 2. Elasticities of Interest 3. Shadow Prices of Restricted Factors  51 53 53 54 56  C.  V.  Econometric Technique and Results A. Econometric M o d e l 1. The Normalized, Quadratic, Restricted Profit Function 2. Data B. Econometric Technique 1. Linear Case 2. Nonlinear Case C . Econometric Results 1. O w n - and Cross-Price Elasticities of Supply and Demand 2.  58 58 59 65 71 71 77 85 85 102  Elasticities of Intensity iv  D. VI.  3. Returns Conclusions  Measuring  Fishery  118 123  Scale  Rent  124  Dissipation  125 125 129  A.  The  B.  Methodology to Obtain Estimates of Fishery Rent 1. Determining the Optimal Levels of Variable Quantities 2. Calculating the Optimal Net Tonnage Fishery Rent and Rent Dissipation 1. Within Sample Rent a. Case I: Actual 1982 Rent b. Case II: Optimal Tonnage Per Vessel c. Case III: An Increase in Substitution Possibilities  C.  Calculation of Fishery Resource Rent 1. Theoretical Measures of Fishery Rent 2. Empirical Measures of Fishery Rent  2.  D. VII.  to  Industry Rent a. Case I: Actual 1982 Rent b. Case II: Optimal Tonnage Per Vessel c. Case III: An Increase in Substitution Possibilites d. Case IV: Single Vessel Type Harvesting  Directions  for  Future  162 164 176 179 182  186  Research  192  Bibliography Appendix  ,  183  Conclusions  Conclusions and  136 137 143 149 150 150 154 160  1 : Data  209  Construction  A.  Data Sources 1. The 1982 Survey of Pacific Coast Vessel Owners 2. Sales Slip Data for 1982 B. Vessel Selection and Data Transformation 1. Vessel Selection 2. Data Generation a. The Labour Variable. Price and Quantity b. The Fuel Variable: Price and Quantity c. The Gear Variable: Price and Quantity d. The Output Variable: Price and Quantity e. Restricted or Fixed Inputs C. Is 1982 A Representative Year?  Appendix  2  Appendix  3 : Parameter  Appendix  4  Appendix  5 : Calculations  : Parameter  Estimates  -  Nonlinear  Estimates, Tests, A n d  : Elasticity A n d  Shadow  Value  For Chapter  Formulae  6  242  Case Results  209 210 211 212 212 214 215 222 223 227 228 231  -  Linear Case  248 265 269  v  LIST Table  5.1-.--Eigenvalues  from  linear  Table  5.2:-Eigenvalues  from  nonlinear  Table  5.3:--Testing  constant  Table  5.4:--Coodness of  Table  5.5:-A  Table  5.6:--Nonlinear  Table  for  fit:  comparison of  5.7:--Nonlinear  OF  estimation:  four vessel types  estimation:  returns  to  vessel types  the  linear of  three vessel  of  types  76  and  79 81  nonlinear  output-variable  estimates  74  scale: four vessel types  four  estimates  TABLES  log-likelihood  own-  output-variable  and  own-  functions  cross-price  and  83  elasticities:  cross-price  elasticities:  gillnet(crs) Table Table  5.8:-Linear  seine 86  88 estimates  of  output-variable  5.9:~Nonlinear estimates gillnet-troll(non-crs)  of  own-  and  output-variable  cross-price  own-  and  elasticities: troll cross-price  Table  5.10:-Nonlinear  estimates  of  output-constant  price  elasticities: seine  Table  5.11:--Nonlinear  estimates  of  output-constant  price  elasticities: gillnet(crs)  Table  5.12:-Linear  estimates  of  output-constant  estimates  94 ....96  elasticities: troll  Table  5.14:--NonIinear estimates  of  elasticities  of  intensity:  seine  103  Table  5.15:—Nonlinear  of  elasticities  of  intensity:  gillnet(crs)  105  Table  5.16:-Linear  Table  5.17:—Nonlinear  of  estimates  price  elasticities:  98  5.13:—Nonlinear  estimates  output-constant  elasticities: 92  Table  estimates  of  price  90  gillnet-troll(non-crs) 100  elasticities: troll of  elasticities  of  107 intensity:  gillnet-troll(non-crs)  109  Table  5.18:-Nonlinear gilinet(non-crs)  estimates  of  output-variable  own-  and  cross-price  elasticities: 111  Table  5.19:-Nonlinear gillnet-troll(crs)  estimates  of  output-variable  own-  and  cross-price  elasticities: 113  Table  5.20:-Nonlinear  estimates  of  output-constant  price  elasticities: gillnet(non-crs)  ....115  Table  5.21:-Nonlinear  estimates  of  output-constant  price  elasticities: gillnet-troll(crs)  ....117  Table  5.22:-Nonlinear  estimates  of  elasticities  of  intensity:  gilinet(non-crs)  119  Table  5.23:-Nonlinear  estimates  of  elasticities  of  intensity:  gillnet-troll(crs)  121  vi  Table  6.1:--Estimated  market  rental  prices  and  shadow  prices  per  net  ton:  four  vessel types  148  Table  6.2:--Total within  sample  rents  (using  Table  6.3:--Total within sample  rents  (using all vessels): all vessel types, all cases  Table  6.4:-Sample vessel:  mean  net  tonnage  and  mean  vessel): all vessel types,  predicted  optimal  mean  net  .151 153  per  all cases  155  6.5:--1982 salmon catch and  Table  6.6:--Actual number of vessels and estimated minimum number (using mean vessel): all vessel types, all cases 6.7:-Estimated actual and optimal fleet net tonnage (using mean vessel types, all cases  landed  (using  by vessel type  6.8:--Estimated  total  fishery  Table  6.9:--Estimated  fishery  rent  Table  6.10:--Estimated  Table  6.11:--Actual number of vessels and estimated (using all vessels): all vessel types, all cases  fishery  rent  value,  Table  Table  cases  tonnage  Table  Table  all  mean  per vessel (using  rent per ton  and  optimal  (using  fleet  vessel):  mean  all  157 of  vessels  vessel):  vessel  types,  all  all  vessel): all cases  net  tonnage  163 cases 165 167  mean vessel): all cases minimum  161  169  number  of  vessels 171  6.12:~Estimated  actual  (using  all  vessels):  vessel types,  all cases  Table  6.13:—Estimated  fishery  rents  Table  6.14:--Estimated  fishery  rent per vessel (using all vessels): all cases  Table  6.15:--Estimated  fishery rent per  all 173  (using all vessels): all vessel types,  ton  (using  vii  all vessls): all cases  all cases  175 177 180  Table A1.1:--Vessel characteristics  and  expenditures:  seine  234  Table  A1.2:--Vessel characteristics  and  expenditures:  gillnet  235  Table  Al.3:--Vessel characteristics  and expenditures:  troll  Table  A l . 4 : ~ V e s s e l characteristics  and expenditures:  gillnet-troll  Table  A1.5:-Average  weekly  earnings,  Table  A1.6:--Average  weekly  earnings  Table  A1.7:--Fuel  Table  A1.8:--Representative  Table  A2.1:--Nonlinear  parameter  estimates:  seine  243  Table  A2.2:--Nonlinear  parameter  estimates:  gillnet(crs)  244  Table  A2.3:--Nonlinear  parameter  estimates:  gillnet(non-crs)  Table  A2.4:-Nonlinear  parameter  estimates:  gillnet-troll(crs)  246  Table  A2.5:-Nonlinear  parameter  estimates:  gillnet-troll(non-crs)  247  Table  A3.1:--Linear  parameter  estimates:  seine  255  Table  A3.2:--Linear  parameter  estimates:  gillnet(crs)  256  Table  A3.3:—Linear  parameter  estimates:  troll  257  Table  A3.4:--Linear  parameter  estimates:  gillnet-troll(non-crs)  258  Table  A3.5:--Linear  parameter  estimates:  gillnet(non-crs)  259  Table  A3.6:--Testing  for  symmetry:  Table  A3.7:-Testing  for  constant  Table  A3.8:--Linear estimates seine  ••••236  British Columbia, current and  unemployment  237 year  rate by  dollars  .-238  region  239  prices by region bonus  of  240 rates  (%)  by species  and gear  type  241  .  all samples (linear estimates) returns  to  scale:  output-variable  all samples (linear  own-  and  cross-price  245  260 estimates) 260 elasticities: 261  viii  Table A3.9:-Linear estimates gillnet(crs) Table  A3.10:~Linear  estimates  of  output-variable  own-  and cross-price elasticities: 261  of  output-variable  own-  and cross-price elasticities:  gillnet-troll(non-crs) Table A3.11:-Linear  estimates  of  262 output-variable  own-  and cross-price elasticities:  gillnet(non-crs)  262  Table A3.12:-Linear  estimates  of  elasticities of  intensity:  seine  263  Table A3.13:--Linear  estimates  of  elasticities  of  intensity:  gillnet(crs)  263  Table  A3.14:--Linear  estimates  of  elasticities of  intensity:  gillnet-troll(non-crs)  Table A3.15:-Linear  estimates  of  elasticities  intensity:  gillnet(non-crs)  of  ...264 264  Table A5.1:--Mean predicted quantities and vessel), all samples: Case I  expenditures  per vessel (using  mean 269  Table  expenditures  per vessel (using  all  A5.2:--Mean  predicted  vessels),  quantities  and  all samples: Case  I  270  Table  A5.3:--Mean predicted quantities and expenditures per vessel (using vessel and using all vessels), seine: Case II  mean 271  Table  A5.4:—Mean predicted quantities and expenditures per vessel (using vessel and using all vessels), gillnet: Case II  mean 272  Table A5.5:--Mean predicted quantities and expenditures per vessel (using vessel and using all vessels), troll: Case II  mean 273  Table  A5.6:—Mean predicted quantities and expenditures per vessel (using vessel and using all vessels), gillnet-troll: Case II  mean 274  Table  A 5 . 7 : - M e a n predicted quantities and expenditures per vessel (using vessel and using all vessels), seine: Case III  mean 275  Table  A5.8:--Mean predicted quantities and expenditures per vessel (using vessel and using all vessels), gillnet: Case 111  mean -. .276  Table  A5.9:--Mean predicted quantities and expenditures per vessel (using vessel and using all vessels), troll: Case III  mean 277  Table A5.10:--Mean predicted quantities and expenditures per vessel (using vessel and using all vessels), gillnet-troll: Case III  ix  mean 278  ACKNOWLEDGEMENT  For  providing  thesis, and  the  I would  Bill  guidance  like  Schworm.  U.B.C.  have  offered  Wales.  Many  thanks  and to  Oceans, Frank  Flynn,  list  would  This the of  in  former many  other  assistance, are also  be  and  and my  of  including  Heather  husband,  in  finish.  It  in  my ability  is to him that  to  Don  Fletcher,  the  David  taken  to  (supervisor),  Department  Paterson,  without  a  C-wing,  especially  Finally,  Steven  Steven, especially, has shared belief  of  the personnel  MacGregor,  thanks.  years  of  Erwin  the  Reid,  complete  G o r d o n Munro,  of  Economics  Diewert,  Department  and Paul  this  and  at  Terry  of Fisheries  MacGillivray, and  computing centre advisors.  complete  Mary  the  Phil Neher  members  due to  are my colleagues  Dupont,  his  As well,  not  his share  over  my committee,  one of U B C ' s  years,  support  to thank  particular,  deserves  me.  and  I dedicate  who  never  I want  Renzetti, my joys  overcome  mention  to  for their  friends  Shelley gave  thank  this thesis.  and family.  Among  Phipps, my office  up  hope.  my parents, unfailing  and sorrows, failures  any problems  x  of  has given  As well, Frank  support  mate Bunti  and A d a  and faith  in  and successes, and me the  courage  to  I.  A.  OVERVIEW  My  thesis  rent  dissipation  British  entry  allowable  the  they  do  raise  the  The an  since  upper  use of  rent  distinct,  ways.  output  the  dissipating  unregulated a given  the fish  cross-price elasticities  variable  and  underlying which demand  restricted  production  inputs  are  functions  alternative  quantity  of  I  has seen  the fishery.  Does a  examine  factors. function  These for  for  are used to calculate By comparing  these  this  issue  is characterized in turn,  salmon  another. fishery rents  are  and  Second, resource it  rents  yield  puts  effectively  statistics the  available obtain  but  of the  estimates  intensity  estimated  is possible to  amount  that  by means  indicate  the  that  interrelated,  of  summary  asserted  the  program,  two  aim is  action may  harvesting,  and the elasticities  measures  1  in  This  a  the  is believed  reducing  in  to  on  is often It  access  used  functions. They,  harvesting  one  input  technology  demand  it  ones.  thereby  a restricted  key  restrictions  and  is the  subject  of controls, whose  for regulated  from  study  been  of the program.  catch,  substitution  case  salmon,  of  demand  input  the  level  harvesting  input  substituted  scenarios.  has  catch  inputs  of  behaviour?  supply and variable  to  input  chosen  fishery  and  the intentions  is the following.  on  First,  The  This  1969  inputs  to subvert  harvesting  interest  bound  between  industry.  fishery.  resource rent that may be obtained  issue of  relationship  of each vessel since 1971. In spite  excessive  of  the  regulated  program  are able  costs  a  of  salmon  so by substituting  forestall  the  in  commercial  net tonnage  prevent  study  firms  licensing  that fishermen  of  by  Columbia  limited  to  is an empirical  INTRODUCTION  of  between of  ease  the with  supply and under  several  estimates  of  Introduction the  amount  ability  The  to  of  substitute  model  in  competitive, inputs.t  amount  of  abundance  In  Chapter  obtain  gillnet-troll,  and  representative not  unlike  gillnet.  of  those  of  most  decade  of  the  1970's.  higher  than  in  previous  are  lower  The  availability  the  technology  tFor  of to  convenience,  interchangeably.  both be the  from the  of  fixed  Thus,  the  of  three  the  from  of  fishing  firm's  profit-maximizing,  the  variable  arise  number  a  on  choosing  use  of  several  quantity  of  output  inputs a  fishing  the  1982  (labour,  regulation days, and  in one  In  years.  To  they  might  be  output  and  input  terms  brief,  the  the  fuel,  on the  fishing  the given  the  I)  are:  are  the  that  of  of  is true,  seine,  whether  and  stock  the  much  costs  this  the  discusses  exception  rates  expect  extent  types  technology  constructed for  species prices  interest  might  vessel  (Appendix  years, with 1982  of  fishing season are  These  appendix  seasons.  specified by  parameters  fishery.  previous  beginning  than  restrictions by  the  input.  behaviour  behaviour  a  of  data  fishing  However,  1982  in  The  other  to  profits  firm's  a key  including  season.  data  operating  on  quantities  vessel,  channels,  short-run  subject  estimates  1977-1979.  for  the  per  micro-level  types  is  the  fish during the  to  vessel  on  the  seasonal  and  tonnage  cross-sectional, four  maximizes  several  a restriction  describes which  salmon)  net of  order  4  Constraints  through  against  firm  firm  (landed  gear).  dissipated inputs  fishing  The  supplied and  rent  / 2  some the  troll,  1982 levels  boom  higher  the  is are  years  of  than  in  the  inputs  to  be  rents  calculated  in previous years.  data  a short-run,  vessel-owner,  for  each  vessel in  restricted  fishing  firm,  profit and  the  sample  function  that  fisherman  are  allows is  dual used  Introduction to  the  underlying  represent  the  quadratic  harvest  short-run  (Diewert  restricted  and  as defined  For  type  using The of  vessel  either  an  estimated variable  Their  example,  linear  parameters  are  can  if  and  be  the  the  use  substitutes  nor  complements  be  other  effective  hand,  different  regulators  the  form  thereby  of  some  evidence  of  might  obtain  a royalty  that  They  include  knowledge  a change  in the  Choosing  the  of  the  form  the  the  of  other  1979,  effort.  the  is  chosen  the  to  normalized  convexity  in  able  and  discussed  variable  in  without  designated then  upon  input  has entry  or  quantitative,  price,  control.  landed  However, the  the  catch to  the  neither program  substitution.  direct,  of  of  by  favour  or  factors.  merely  input  of  pairs  For  firm  limited  5.  program.  in  indirect, price  a  Chapter  fixed  entry  fishing  estimated  between  and  limited a  through  inevitable  Crutchfield  is  of  the  choice  regulation  tFlexibility means that the function substitution of the many inputs.  is  is specified  the  argues  an  net  appropriate  of  inputs,  relying  reduces the  of  and  with  This  output  substitutability  fishing  type  imposing  between  dissipation  success  of  form  cross-price elasticities  success  input,  rent  vessel  function  routine.  intensity the  key  behaviour and  rate (Scott  correct  of  Instead  excessive  profit  generate  control  input  scheme.  to  among  preventing  discouraging  problems. detailed  at  regulatory  the  of  given  functional  (1974).t  nonlinear  evaluate  can  restricting  will  or  The  is capable  restricted  elasticities  regulator  a  It  Diewert  used  used to  of  1987).  a separate  iterative  inputs  values  by  function.  profit  Ostensoe  loss in flexibility  each  production  / 3  On  use  the of  a  controls, This  takes  fisherman,  this  tool  is  not  without  its  tax  rate  in  the  absence  of  administrative  lags associated with  1979).  the to  fishery distinguish  has  been  among  a the  large  part  of  elasticities  of  Introduction the  theoretical  Crutchfield of  to  1979).  potential  thesis  addition  Scott  in  inefficient among  in  the  British  supply  the  empirical  past  debate  of  two  is to  estimates  estimates  A  harvest of  the  of  decades examine  the  four  harvest  technology,  this  thesis  (Scott  the  fishing  the  extent  Columbia  and  input  revenues,  tonnage  are  involve  1.  of  the  1979,  effectiveness  technology. technologies  This used  comparison  and  of  the  fleet  II  from  rents  redundancy,  and  is  each  They an  In  are  done  incorrect  for  yields  input  first  (Munro  5  case  are  the  Chapter  Chapter  This in  sources.  dissipation  fishery.  rents.  potential four  rent  salmon  equations  fishery  attributable to  restrictions,  Type  commercial  demand  costs,  of  provides  6  used  and the to  several estimates  substitutability,  catch  distribution  vessel types.  turn,  four  for  resolving  empirical  rent dissipation  B. HYPOTHESES There  first  the  cases. II  light  examination  projected  Type  of  examining  output  alternative  way  fisheries  4  British Columbia.  empirical  estimated  of  to  1985)  obtain  in  on  in  the  salmon  complete  One  schemes  generates  take  In  literature  /  are  a  TO  number  along  with  statistical not  What  BE of  inputs?  testing  the  In  specific hypotheses that  this  role  research.  the  statistical are  TESTED  of  and  to  1974)  they  significantly  this the  estimated  relate to  the  issue of  answer  between  in of  relationships  order  have  parameters  tests  (Diewert are  they  thesis  the  different  between this  the  question  variable from  and zero.  The harvest  evaluate  fixed  They  first  are  three  discussed hypotheses  technology.  The  last  rent dissipation.  restricted I  tests.  factors  factors the  and  elasticities  and test to  the  variable  of  intensity  see  whether  Introduction Are  pairs  of  salmon?  An  variable  inputs  examination  elasticities  of  elasticities  of intensity,  of  input  Are  firms  the  demand  gives  these  sensitive  quantities  questions royalties Is  of  or  signs  complements  and  Used  elasticities  indicate  the probable  vary  are  to  changes  when  important  or taxes which  for  output  First, a solution to the optimal  is  evidence  minimum  How of  to  actual  the  of  cross-price  conjunction  have  of  dissipation  Several  with  success  the  or failure  authors  fleet of  the  fleet  the  substitutability  degree  harvest  of  If  of  how d o to  these  respond  different  net tonnage  values  is  to  from  per vessel  are compared.  optimal,  then  the  this  If  the  provides  could  occured  H o w does  halved.  to  reduced  (1984)  by  presence  could  number  of  too  be reduced  of  many  without  Pearse (1982) suggests  contends  80-90%.  that  For the  the  seine  gillnet  fleet,  is redundant.  dissipation  in the harvest technology?  actual  exceeds the minimum,  For example,  Hilborn  rent  the  the fleet  15-50% of the fleet observed  the  number  due  ability.  be  British Columbia salmon, can the  the actual  asserted that  be  of  firms  tonnage)  level  than  computed?  harvesting  (1975) estimates that does  1982  have  could  and  Answers  fishing  (net  tonnage  tonnage  minimum?  size  output  in the fishery.  may have  on its aggregate  the  more  vessels be  to this  of  changes?  how  factor  and optimal  of the total  number  component Loose  found  compare  vessels.  that  the  size  rent  impact  Then,  regulated  of overcapitalization  the  then  harvesting  the net supply price.  level?  vessels  in  price  price  understanding  lower the  the  optimal  found.  of  the  in  level  Given  of  answer.  actual  fishery  magnitudes  the  the  the  is  in  restrictions imposed o n the fishing firm.  fishing  input  input  substitutes  / 5  depend  upon  the  degree  Introduction 7.  What  amount  of  types  used  the  suggest  C.  for  FINDINGS  One  each  of  the  commercial quadratic applied as  a  are  to  form  (Diewert  and  Ostensoe  1987).  project  is  (Lawrence  hypothesis. accepted  This A  in  only  one.  entails  maximum  has  this  been  the  1982).  four  vessel  does  is  estimation  of  tested  This  is  this  in for  is used  done  the  for  on  a  normalized  in  one  prices each  set  iterative  salmon  only  imposed  new  technique  linear  is  adopted  a  a  Columbia study  subsequently  likelihood  using  homogeneity  prices is  al.  British  for  Linear  It  et  harvest  in  of  fishery? What  estimated  (Judge  It  1987).  salmon  are  chosen  Convexity  procedure  nonlinear  parameter  input  may  estimates be  demand  and  elasticities  that  these  two  are  the  least the  fleets  the  are  price  responsive to  the  appropriate  by  means  elasticities  largest  in  respond most  regulated own  from  characterized  own-price  not  used  each  is  other  imposed  of  the  upon  four  the  of  equations  to  obtain  three which  the  new  cases,  the  estimates.  technology  are  types  equations  to  vessel types?  demands  functional  nonlinear.  however,  input  simultaneous vessel  attributable  particular  The  samples.  Using  three  of  basis.  and  parameter  of  four  maintained  other  RESEARCH  and  is  Columbia commercial  THE  for  research  samples  British  regulation  supply  technique  dissipation  further  OF  output  Zellner  in  rent  / 6  the to  components elasticity  of  of  changes in the  of  nonlinear  the  own-  intensity.  troll  and  In  gear  the  price of  cross-price  general,  the  elasticities  values It  input  output  prices, as  and  commercial  fleet.  is  of  fleets.  entire  is very  and  linear  gillnet-troll  changes in of  and  In  small. This suggests that  gear.  the  expected  all  they cases,  fishermen  Introduction Whereas  the  gillnet-troll evidence these and  troll  fleet of  gillnet,  is  Elasticities the  of  the  a great to  deal  exploit  limited  entry  may the  still use  harvesting  In  of  rent  of  than  is  A  to  in  fishery.  the  exploit  seine  direct  substitutes  for  net  a net  tonnage  can be  At  the  for  rent  by  of  variable  restriction  per  subvert  opposite  they rent  to  have  end  no  of  vessel. fleets  the  attempting  to  increase  inputs  a  given  for  amount  technology  which  indicate  However,  fuel  variable  by virtue of  the  scale  are  is  a  inputs  is  their  ability  British Columbia the  net  levels.  tonnage,  that  suggests that of  fleets.  output of  between  samples  three  by these  their  heavily  inputs.  substitutes for  dissipating activities  area  more  This finding  intentions  of  direct  all  seine  of  relationships  troll  tonnage.  two  the  the  and  more  dissipated by these  Given that  less scope  that  variable  the  analysis of  terms  the  7  give  fisheries,  in  by  fleets  An  net  fisheries  examine  the  means  The  harvesting  among the  to  gillnet  inputs.  response a  Results for  This  troll  substitution,  and  variable  natural  order  input  seine  the  the  are  substitution  technology in order  more  in  variable the  among  operation.  calculated  inputs.  program.  hand,  conditions  fleet  of  factors.  dissipate  gillnet  and  tonnage,  there  However,  they  This  leads  thereby  to  raising  costs.  general,  harvesting  of  vessels.  much  are  other  regulated  the  are  these  face  the  gillnet-troll seems  to  with  allowed  fixed  gear  the  degree  substitution  degree  intensity and  and  in  a greater  of  of  heavily  segments  complement used  more  some  On  amount  of  variable  labour  none.  times  demonstrates  shows  consonant  are  and  regulated  has  some  results  openings  fleet  /  the  elasticity  technology  estimates  possesses  a  provide greater  evidence degree  of  that  the  commercial  substitution  than  has  salmon been  Introduction suggested amount  Using  by  of  observers. Therefore,  fishery rent  the  estimated  methodology rent.  I  is  first  estimates  of  1982  and  profit  is defined  net  is  output  harvest  and  given  regulatory  revenue; each  output  To  multiplied  by the  minus  static,  one  different  the  is  by  generate  of  per  mean  estimates  price.  the  on  Total  fixed  market fixed  period  net  cost  rental costs.  profit  However,  profit  profit  minus  for  The  for  the  each  of  precludes  of  the  each variable variable  cost  yields an  associated  with  price  of  Hence,  rent  per  vessel.  is capable  is  Thus, of  it  actual  vessel,  for  where  net  associated with  the  optfmal  decisions  are  optimal  gives  sum  of of  vessel Rent  an the  Multiplying estimate  of  quantity  of on  seasonal profit  per  net  a vessel  defined neither  distinguishing the  estimated  expenditures  the  to  measures  the  solution.  is equal to  as  rent  predict  price  each  vessel,  obtain  to  estimate  a ton.  used to  using  first-best  the  a  fishery  cost  input  input  5  by  5  and  Chapter  potential  the  each  vessel  a  vessels  fixed  Chapter  output  (flow)  per it  corresponds to  net  245  from  and  rent  the  the  sample-specific output  expenditure  its  that  actual  for  equations  vessel.  equations  rent  determined  demand  the  determine  This  sum  environment  total  externalities.  to  to  Revenue minus variable cost  obtain  profit  Actual  times  inputs.  vessel.  as  variables  likewise, the  input  variable  stock  these  is  demand  fishery  technology.  input  of  step  input 6  as seasonal (restricted)  quantities  predicted  Chapter  sample  Seasonal profit  supply  a  in  within  generated  tonnage.  supply and  developed  the  next  8  actually dissipated.  output  calculate  the  /  in  tonnage  is  is seasonal  this  thesis, is  congestion  inframarginal  nor  rents  of  1982  in  vessels.  within  sample  rent  for  245  vessels  is estimated  to  be  -$572,000  for  Introduction current  dollars.  industry  rent.  fleet  4528  of  The  within  This  is  vessels  rents  may  1982  fishing season it  total  fleet,  rents  may  the  be  rent  for  seen to  From  the  in  I  1982. to  employed  most  varies troll  by  fleet  approximately total fishery Lb.  25% rents  Fleet  of to  then  extrapolated  -$42,789,000 this  Case  landed The  for  I.a.  value  troll  negative  of  fleet, rent.  The fixed  vessel  type  as  shown  by  the  estimated  at  -$33,017,000.  for  the  An  the  fleet.  redundancy  of  is  major  salmon  to  fishing  these  negative  salmon  catch.  For  the  of  the  25%  of  large  negative  variable  costs,  although  tables Only  total  of  finding  is  clear  in  the  number  that of  vessels out  $12,477,000,  a  it  the  Taking these  increase to  entire  9  Appendix  5.  gillnet-troll  The  fleet  is  $804,000.  industry,  estimate  determine  comprising about  of  equal to  to  extent  the  proportion  rent  the  The  high  is  fishery.  the  are  the  generated  the  call total  to  because of  results in  the  be  is $164,933,000.  produce a positive  the  Case  to  contributes  proportion  results  estimated  compared  arise  sample  /  an  to  of  the  many  surplus the  increase of  contributor  too  vessels are  vessels  is  1078,  fishery would  cause  $55,266,000. loss  of  I call this  potential  fishery  rent.  A  second exercise  potential  fishery  per  vessel were  This  represents  latter cases, 1982  is performed  rent  could  relaxed an  be  the  industry  increased, if  (Case  increase  for  II).  of  Total  is achieved by keeping each vessel at Case harvest  l.b  and  Case  II,  is used in the  the  minimum  rent calculation.  determine  restrictions  industry  $18,910,000  to  in  rent  would  rent  from  its actual number  on  of  the  the  extent  use  of  net  increase to the  level of  Case net  to  tonnage  $31,387,000.  l.b,  since  tonnage.  vessels required  which  to  In take  this both the  Introduction The  third  potential  case  examines  fishery  rent.  possibilities previous the  A  discussion  final  exercise,  been  vessels types.  I  catch  a  in  all-gillnet  D.  by  the  of  input  particular,  industry  a  rent  substitution  simulated  to  elasticities,  IV,  is  many  fall  the  a  resource  to  in  leading  doubling  -$5,878,000.  greatest  fleet. The  seine  next  troll  fleet  of  as  of  harvesters  rent  The  performed  observers  efficient  that  1982.  role  amount  to  of  the  As  of  the  10  loss  of  substitution  suggested  by  the  rent  is  dissipated  of  answering  a  question  The  question  by  fleets.  more  find  generate  the  of  means  fishery.  the  salmon  harvesting  $73,090,000 largest  fleet  a  or  rent,  is found  the 44%  than  entire of  the  $27,198,000,  never to  whether  seine  the  three  other  vessel  1982  catch  alone  could  total  would  generate  is  that  landed be  value  of  the  by  an  generated  a positive  resource  rent.  CONCLUSIONS  The  findings  found  called of  of  Case  asked  are  In  total  seine and troll  has  is  causes  the  /  the  to  for  be  a  by  harvest  methodology scenarios.  This  (1970) is  the  important useful  and, use  for  one  for  each  restricted  factors.  This  which  can  permits  a  empirical by  of  restricted  profit  a  inputs of  a  optimal may model  estimates  comparison of  the  Munro  complete  be  of  lends  fishery  partial  and  static  of  Scott to  exploration  calculated,  approach  studies  function  seasonal  also  the  fisheries  recently,  type  generate  reasons. First,  more  vessel-owner's  the  two  for  technology. This allows  on  these  are  potentially  aspects  prices of  thesis  Zellner  controls  shadow levels  this  novel  underlying input  of  the  type  (1985).  One  characterize  of  the In  along  with  the  readily  to  rent  under  equilibrium  a  the  impacts  behaviour.  itself  taken  of  addition, optimal a  new  variety  level  of  of  rents  Introduction (obtained  by  equilibrium factors)  using  level  the  made  of  short-run  management for  other  the  harvest  rent other  many  to  is  lost.  channels  an  50%  of  choice the at  salmon.  the of  the  target.  $0.05 The  or  more  The of  are,  distribution  wisdom.  Fleet  vessels.  $0.10  findings  In  this  be  catch  this  period.  lost.  of  landed  indicate  of  research to  be  the  and,  by  are  extension,  estimates  of  The  calculated  been  previously  through  highlights  They  optimal  the  the  and  which role  of  presence  of  the  regulator's  across vessel types.  fleet  salmon  research  calls  this  appears  fishery.  This  conducted  the  imposition  depending royalty  on  may  the serve  to  finding  supports  suggests a similar  for  catch  redundancy  (1982) suggests phasing  (1982)  that  for  has  restrictions,  Pearse  The  Pearse  static  restricted  comparison  conduit  thesis  thesis,  Committee  addition,  thesis  in  area  fishery.  than  one  The  For example,  year  pound  be  tonnage  the  full  the  empirical  salmon  Columbia commercial  Reduction  per of  done  British  10  of  first  substitution  others.  inefficient  fishery,  the  Columbia  may  a  implications  salmon  may  rent  of  fruitful  allows  the  11  1986).  provides  inputs  which  of  a  it  to  levels  particularly  since  input  however,  calculations  over  a  factors)  optimal  have  British  substitute  accepted  fleet  number  is  in the  is  thesis  there  inefficient  rent  This the  use  the  commercial  in  through  the  the  Columbia  There  using  fishery,  used  to  a serious problem  accords with  set  ability  a  restricted  themselves  fisheries.  that  the  solutions (Capalbo  results  British  by  of  long-run  entry  vessels,  of  According  in  the  of  1979). This  nature  technologies  The  adoption  Christensen  and  indicate  believed.  be  of  levels  (obtained  empirical  limited  elasticities  several  rents  and  the  fisheries  actual  intertemporal  Second,  too  of  (Brown  given  the  /  out his  reduction  of  royalties  species to  of  reduce  the  quantity  impact  of  inputs  upon the  fleet.  This  maintain  Given  output  policy  the  level  that  catch  vessel,  his  of  onus  allocation.  is then  types.  form  major  salmon might  about  fishery. render  be  of  on  a  between stock  the  Nonetheless,  ineffective  has  has  levels  to  two  is  a number  to  arguable  of  in  a  a  solution  for  use  stems about  sources of  the  troll  worlds,  ie.,  two  of  this  12  the  a  might the  on  catch  the  from  the  and  use  Pearse of  the  taking to  the  vessel in  the  fishery.  The  greater  a  of  among  halibut  of  currently  found  for  allowable  adoption  is  cost  be  rejected  total  restrictions  amount  the  rent an  tool  given  to  system,  (Moloney  in  the  lead  royalty  minimize  and  that  little  activities  take  considered  adopted  have  quantitative  of  fisheries  of  is  distribution  and, therefore, it  best  fisheries literature  traded,  been  been  It  vessel-owner to  be  would  exception  usefulness of  allowed  suboptimal  regulation it  the  the  inherent  potential  in the  but  with the  substitution  suggested.  is  output,  /  inputs.  difficulties  vessel  quotas  with  although  difference  uncertainty  input  interest  put  By allowing  fishery,  and  each  of  achieve  employing fewer  may  of  Since  associated  salmon  to  administrative  amount  inefficiency This  then,  or vessel quotas. The  1982).  the  the  regulation  great  Copes  harvest,  given  level  each vessel type,  seem,  restrictions  form  1979,  would  tonnage  alternative  a  supply of  catch while  and  generating  catch a given  of  dissipation  per  used to  Introduction  degree catch  quota  rent dissipating behaviour.  in  of the  system  II. THE BRITISH COLUMBIA COMMERCIAL SALMON FISHERY  A. DESCRIPTION  OF  The  commercial  and  important  accounted value.t  for  salmon fishery.  of  the  gross  FISHERY  fishery In  only 40%  Although  percent  THE  in  1982  of  British the  Columbia  total  total quantity  wholesale  provincial  value  of  product,  is  quantity  (in  1982  the  of  metric  the  the  province's  commercial  tonnes), salmon  regional  most  but  salmon  69%  catch  lucrative  of  the  represents  importance  of  landed  this  landed  only  one  fishery  is  significant.  More  importantly,  potential Salmon This Of  many  resource  have  rent  generating  is a highly valued  suggests that course,  the  administer  the  may  quite  be  generating  a  the  fishery  fishery  in  British  harvesting  an  substantial.  and  sockeye.  However,  the  three  five  Typically,  since the  must  rent.  1970's  has the  potential  a  be  great  it  Many  gear  types  is  one there  tProvince of British Columbia. Fisheries Production Statistics of  type  not  observers  of  has been  (Scott to  of  the  argue  capacity is directed  species, ie., gear  is  a trend  and  troll)  pink,  employed toward  at  the  chum, upon  the  Canada.  These  are  are  cost.  necessary  the  there  the  1981).  low  for  1981).  whether that  at  rent  costs  Neher  certain  Neher  caught  resource  and  gillnet,  highly among and  be  against  (Scott  (seine,  salmon  deal  weighed  much harvesting  Pacific Coast only  Canada  manner  Currently,  fishery ranks very  in  yield  efficient  resource  Columbia of  may  rent  licensed vessels and that too  In  fisheries  resource and  potential  positive  suggested that the  to  costs  fishery too  is  many  fishery.  used  in  the  chinook,  coho,  fishing  vessel.  a  use of  multiple  Ministry of Environment. Marine Resources British Columbia 1982. Victoria, 1983.  gear  Branch.  The types the  on  a vessel.  vessel  particular type  called  species at  exhibits  and of  is  gillnet lines,  at  where  the  salmon  vessels  are  deliver  their  specific  harvesting  Trailers  have  the  and  A  sockeye, canning  large  small-scale  bait  part  to  at  vessels  salmon,  entice  the  salmon.  to  freezers.  sea prior to to  the  fishes  spawning  They  maintain  home  or  The  the of  to  troll  lines;  upon  used.  two  salmon's high  a  Seine  vessels make  often  14  Each vessel  gear  vessel  off-shore  catch.  troll  target  the  More  packing  and  to  former  the  Fishery /  regulations.  miles  runs.  landing  port  able  whereas  many  the  official  are  gillnets  according to  the  latter  is  changes in  entrap  the  prior  in  use types  the  than  areas  not  quality  over  troll the  Net-equipped vessels  vessels  as  frequently  as  conditions warrant.  traditionally  recently  to  mouths;  catches  fresh/frozen  pink,  nets  feed  spent  These  frequently  characteristics that vary  equipped with  weeks  sockeye  use  river  most  responding especially to  of  and  used  gillnet-troller.  will,  vessels hooks,  combination a  a variety  congregate  many  The  British Columbia Commercial Salmon  to  their  market and  caught targeted  as  chum  chinook  final  coho,  species. These  products.  comprise  and  the  The  major  but  have  catches  are  predominantly inputs  into  added mostly  pinks destined  net-caught  the  species  and for of  secondary processing  industry.  of  the  operators.  processing companies.  fleet, Some  particularly 10%  of  the total  gillnet licensed  and  troll  vessels  vessels, are  is  owned  owned by  a  by few  The B. HISTORY  OF  This  gives  section  fishermen. in  LICENSE a  Interested  Sinclair  (1978),  and Wilen  (1979).  British Columbia Commercial  Salmon  Fishery /  15  LIMITATION  brief  history  readers  are  Morehouse  of  regulation  advised to  and  Rogers  in  the  fishery  and  consult  more  thorough  (1980),  Fraser  (1977,  responses of discussions 1979),  and  the  found Pearse  1. Pre-License Limitation Prior  to  1969  unrestricted.t of  annual  defined  as  the of  should meant  for be  the  effort,  In  1960  a  the  limited  restrictions.  spawning  to  total  the  time. the  catch  commercial  total  It  argued  to  the  a  which harvest  derived  of  In  was  from  fisheries  the  fishery  practice,  optimum. face  means  required  dominated rate  was  TAC,  the  was  yield.  in the  by  or  and  tool  biological  decline  catch,  size  sustainable  achieve  fish stocks continued  model  that  maximum to  run  fishery  managed  allowable  management  growth  salmon  fishery was  estimated  biological  provide  annual  annual  of  The  purposes. This  Schaefer  period  Columbia purposes the  between  of  In  this  spite  of  a great  deal  salmon  and  capacity.  a commission headed fisheries.  British  catch  the  regulated  excess fishing  support  of  long  of  halibut  for  the  conservation  'difference  fish  a  setting  regulatory  for  allowable  prescriptions  research  into  However,  total  escapement the  entry  Its  major  continued  licensing  Sol Sinclair was  objective  viability  system  by  be  of  the  was  to  fisheries.  introduced  to  created  make  to  study  long-term  Sinclair  (1960,  control  the  the  recommendations 1978)  number  proposed of  boats  to "that and  t A licensing system was adopted in 1882, but it did not effectively restrain the entry of new vessels. In 1889 a limited number of licenses were created; again the program proved to be ineffective. The program was finally abandoned in 1917 (Sinclair 1978, Scott and Neher 1981, Rettig 1984).  The fishermen."t the  in  order  introduction  of  to  pay  for  "meaningful"  British Columbia Commercial Salmon the  administration  of  the  program  Fishery / he  16  suggested  license fees.  2. The License Limitation Program Almost  ten  years  passed  proposals.+  in  1969  of  in  the  vessels  established Copes but  further  1982 plans  although the  on  fleet,  in  of  led in  which  to  the made  the  freeze  were  fallen  to  any  called  more  for  At  then  the of  to  Sinclair's  the  number  vessels  with  program's  and  an  1979,  (Scott  licenses were  fishing  uncertain  to  reduce  only  6100  aspect  an  responded  "grandfathering"  than  4638.* other  competed  and  issued  practice  operation  control  still  prices  vessels  began  and  a  generation  manner  added  to  their to  the  to  rise  buy-back  of  predicted  additions  incidentally  a  to  government  issued,  inception  effort.  no  Fishermen,  unspecified  share  of  catch.  salmon new  of  had  to  number,  1970's  vessel-owners ones  made  Licenses  fishery,  year  Canadian  introduced  fleet.  number  were  entry  this  incentive  first  the  was  the  total allowable  the  the  in  the  this  fewer  annual  During  In  plan  salmon  presence  1980).  by  a  before  positive a  decade  rapidly. program resource earlier  old vessels and/or total  fishing  Together to  reduce  rents. by  with  the  the  size  of  Responding  Scott  (1962),  purchased larger  capability  restriction  of  the  to  the this  individual and  fleet.  In  newer 1971  tCanada. Fisheries and Oceans Canada. _A_ Licencing and Fee System for the Coastal Fisheries of British Columbia Volumes I and II by S. Sinclair, Ottawa, 1978. p.26. t U n d e r the British North America Act ocean fisheries were administered by the federal government, not by individual provincial governments. * Canada. Fisheries and Oceans Canada. Turning the Tide: _A New Pacific Fisheries. Final Report of the Royal Commission on Pacific P. Pearse. Ottawa. 1982 p. 80. Also, op.cit., Fisheries Production Columbia 1982. Table 22. The reduction in the number of attributed to several causes including: a buy-back program in the reduction in the number of temporary licenses as their invalidation  Policy for Canada's Fisheries Policy by Statistics of British licenses can be early 1970's and a dates came due.  The regulators  attempted  tonnage  of  replacing  The  speaking,  measure  of  replacement Fishermen  the  continued  (and  vessel.  This  more  of  fishing  shorter  fishing In  net  tonnage  was  a  subvert and  than  time.  In  to  use  the  particular  way  the  number  vessel.  of  fishing days  were  per  not  net  of  well  the  defined.  tonnage  and  It  from  increasing.  by  into  on  certain  retiring  two  single  new  a  to  could  of  larger  so  in  vessel  a the  closing specific  periods  reduced, and  a  do  each  consisted  during  ton-for-ton  travelling  restrictions  was  the  regulations  vessels,  be  tonnage  vessel  of  tool.  could  net  capable  tonnage  fleet  the  17  increasing the  Unfortunately,  the  previous  the  of  capacity; gross tonnage  combined  management of  hold  generally  to  on  tonnage  their  form  tonnage  of  intentions  addition  segments of  gross  the  two  the  restriction  net  was  the  another  to  of  the  vessel  took  measure  pyramiding  areas  areas  this  stop  powerful  of  began  not  a and  displacement  to  licenses)  period  regulator  of  did  that  announced  concepts  total  rule  investments  They  net  vessels  number  stem  fleet.  vessel.  Loosely a  the  to  British Columbia Commercial Salmon Fishery /  of  access  the  to  year.  the  fish  controlled.  From  1977  more  difficult  the  entry  powerful  to (in  of in  1980 1977)  seine the  entire  replacement  counteract  the  Canadian a  and  origin.  procedure  series and  illegal  fleet. rule  difficulty  of  monitoring. However,  which  of  vessels into  ton-for-ton  information  a  In to  was  introduced  (in  This  effectively  1980).  fleet.  the  incorporate on  This  act  the  year  a  length  Canada  dealt  vessels over  official  to  with 15  confirmation  net of  1979  saw  Shipping  largest a  tonnage.  and  revision  This  Act  were  pyramiding  moratorium  as  registration  tons net  a  the  restriction.  the  make  put  These vessels were  addition,  relying  only  required  the  regulations  was a of  required This  on most  of  the  done  to  source  of  vessels  of  to  register,  included  most  The seiners  and  some  gillnet-trollers, the  very  had  the  length-for-length  claim  a larger  net  to disprove.  During  the  period by  Among  many  licensing  of  the  in  by  government  royalties  the  not  receive  and  Oceans.  One  important  fishing  on  of  committee  observation the  net  can  tonnage  intention  of  the  restrictions.  regulated  inputs.  The  equipment, move  the  vessel,  fishermen This  unregulated more vessel  and faster  seem occurs  inputs  fishery  to  was  on  a  one  a  for  fishery  to  to  suggested  gear larger  by  these the  latterly,  the  types,  form  new  more  number  of  the  this  way  be the  the  fishermen.  In  the  imposition  of  on  the  of  of  recommendations  the  of  Fisheries  total  number  to  of  effective  avoid  the  unregulated  for  bigger engines, manpower, fishing  did  of  number ways  substitution  the  (1982).  years and  Department  on  found  10 In  from  subjects  Policy  revamping  take  restrictions  have  via  to  rent  main  Fisheries  licenses.  Pearse  and  the  major  half. This was  Despite  of  Pacific  suggested  can take  different  to  claims were  established  per  Prior  records these  Unfortunately,  made.  it.  official  auction  be  exercise  Without  in  salmon.  to  and  incentive  scheme,  of  not  trailers,  boats had an  appropriate  catch  gillnetters,  18  smaller  Pearse  reduction  a  chose  Commission  competitive  most  Fishery /  the  salmon  a  vessel,  to  the  of  fleet  most  boat.  salmon fleet  per  fuel  their  to  vessels,  many of  the  days  electronic  rule  Royal  able  support  CONCLUSIONS  vessels,  be  the  C.  of  cut  landed  the  register;  1981-1982  means  with  on  for  (Pearse)  would  conjunction  to  Smaller  recommendations,  system to  phased  option  tonnage  investigated  trailers.  replacement  difficult  his  large  British Columbia Commercial Salmon  and  grounds.  more more The  The fishermen  have  limited  entry  them  away.  vessel-owners Some  program. In  provide  It  their  an empirical  these  fishery  attempts  to  basis  resources,  that  (Fraser  by which  make  permits  believe  behaviour  means  to  use too many  researchers  dissipating  other  incentives  British Columbia Commercial  a  substitutions or scarcity  appropriate thereby  limited  1977).t  for testing  entry  The  main  the  input  because  rents  to  the  fish  program  may  substitution  but does  for  the  of  Fishery / 19  of the nature  arise  dissipating  objectives  Salmon  this  not tax  themselves,  potential even  of the  the  fishery  rent.  accelerate  rent  thesis  hypothesis  are  and to  to find  rent may be dissipated.  tTownsend (1985) explicitly incentives faced by fishermen  recognizes this which encourage  behaviour in a discussion them to dissipate rent.  of  six  III. The  purpose  which survey  is  this  relevant  the  surveys  of  rationale  limitation  scheme  are  A.  THEORY  to  thesis.+  review  Given  examining  for  and  into  programs  enumerated.  the  literature  Munro  is divided  license  is  to  fisheries  (1978), and  chapter  THE  the  itself  the  Hannesson  chapter  to  confines  modeling  This  of  LICENSE LIMITATION: THEORY AND PRACTICE  The  BEHIND  and  two  the  of  scope  part  efficacy  of  available  Scott  (1985).  of  of  in  the  the  and  the  LIMITATION  fisheries  limitation  the  the  economics  literature  Clark  sections. In  second discusses  fisheries  license  are  examined  LICENSE  set  that  major  is  a  the  programs.  theoretical for  empirical  a  this with  General  Anderson  requirements  relevant  literature,  concerned  (1976),  first,  literature  (1977),  basis of successful  literature.  PROGRAMS  1. A Survey of the Theoretical Literature The  basis for  the  programs  is  fishery  socially  Gordon nature  is  the  (1954) of  a  belief  defines  revenue  and  the  that  Scott stock  this  combined  cost  license  tThe literature concerning the chapter 4. The set of studies is surveyed in chapter 6.  state  conclusion  These  works  with  resource of  limitation  equilibrium  This  (1955).  fishery  total  of  the  sub-optimal.  and  fish  Gordon  development  harvest  rent  easy as  effort.^  is  and of  other  an  derived  demonstrate capture the He  fisheries  unregulated  open  from  seminal  how  the  may  generate  difference  between  then  management  argues  that  general design of production studies which examines the measurement of  access  articles  by  self-reproducing resource the the  rent.  sustainable presence  of  is reviewed in rent dissipation  +The sustainable revenue is the sustainable (biological) yield curve multiplied by the assumed constant price of fish. This curve often has the familiar parabolic shape because it adopts the Shaefer logistic growth function for the fish stock.  20  License positive  resource  in the  level  of  characterized  rents effort  by  stock  bionomic  equilibrium  analysis  total  below  and  an  maintain  a larger biomass.  optimum  is the  of  tenure,  in  the  the is  it  unable future  An  important  harvest to  of  rights  stock, so  the of  feature  the  a function  1976,  Anderson  is linear  model in  of of  size.  Gordon  framework.  In  either  fishery  to  his  the  static  could  unregulated  in  positive of  equilibrium  a  open  increase rents  his  persist.  activities,  reduction shows  case,  from  Since there  efforts  to  either  on  that  this  extends  rents  leave  catch  a  he  is  and  the  social  is no  to  Furthermore,  the  equilibrium  resource  fishery  in  Scott  the  equilibrium  access  increase  in this fishery is  model;  yield  fish stock.  in an  a  21  security any  fish  portion not  -or  fishermen  or  on  characterization  of  the  other  does  of  stock.  these  function.  output  as  impact the  of  as  growth  long  Equilibrium  of  Practice /  induces an  and  the  continues  units.  context  pay a participant  fisherman  production  modeled  property  not  availability  produce  (Clark  lack  fishery  rents  the  of  toconsider  the  because  access  and  resource  the  divergence  Each  uncertain  in  open fishing  of  the  does  sea.  new  a dynamic  sub-optimal  for  or  unharvested  to  to  basis  of  is sub-optimal  thought  The  form  dissipation  its  findings  be  unrestricted  in the  the  resource  the  in  Limitation: Theory  and  This  subsequent  is  landed an  1977).  the fish.  aggregate Other  for  the  biological  effort,  and  a perfectly  means  by  Typically, index  features  production elastic  studies  of  which  the  of  this  fishermen  output  input  function,  market  is the  use  of  a  demand  the  labelled  literature cost curve  combine fishing "fishing  include: of  effort  for  fish.  the  inputs unit  is  effort" Schaefer  function  that  License Before  going  fundamental meant  by  facets  of  access. rent  on  the  dissipation  this  identify  that  is  biomass growth.  Class  occurs  if  and  it  fishery  is  of  their  catch  is  risen to  The  tA  boats.  increased. the  level  rent.t  fishery  fish  higher  are  Class  I  regulated, new  the  the  vessels. be  from  able  Eventually  this  may  of  forms  responses to  the  two  problems  on the  discussion  fish  of  caught  to  to  is given  If  form  level.  of  open This  is  economic to  future  entry  controlled  returns  in  the  increase the  harvesting  capabilities  necessary  harvest  to  of  not  the  vessels is  total  available  where  complete  rent dissipation.  substantially.  important It  costs  because  has been  season solves the  6.  the  situation  differ  in chapter  maintain  is  average  dissipation is  any  to  that  new  a  if  dissipation  as  access  rent  in  two  when  this  rent  so  above  even  total revenue. This represents  two  of  is  controlled  contribute  describes  arising.  cost  lead  identify  occurs  to  what  as the  sustainable  sea  harvest,  Further,  minimum  This  the  costs.  presence  the  complete  in  total  problem  problem  consequence  problem  the  work.  optimal  One  property  restricts  property  its  left  the  quota  imperfectly  below  case,  of  or  seminal  harvesting  vessel-owners may any  access  22  to  clarify  free  his  few  to  (1985)  in  rent.  important Scott  Gordon  stock  is  literature  and  common  sustainable  of  it  economic  Practice /  Munro  with  between  an overall  more  In  entry  Scott,  the  of  common  the  and  of  I type  government  imperfectly  existing  a  fish  too  of  prevent  distinction  regulatory that  the  encourages  prohibited,  the  This implies  type  when  biomass or  II  that  in  by  drive  response  resource  Class  maximizes  overexploitation  The  of  described  competitors  level  the  the  Gordon  phenomenon  dissipation  the  consider  conclusions of  They  access  to  Limitation: Theory and  have  the  suggested  biological aspect  License of  the  overfishing  allowable fish. to  In  catch  the  entry  entry  access  number  of  most  The  of  royalty  at  the  fishery  some  used  of  those  output  of  and  a  the  Practice  /  optimal  total  prescribed  sustainable  resource  with rents  23  quantity  of  resource  a  rent  restriction  on  continue  to  will  rents.  of  rent The  necessary  methods  the  conjunction  1961).  level  only  allows  in  type  (Crutchfield  on  it  and  determines  take  presence  second  advocated tax  is  the  minimum  to  because  TAC  units,  regulator  operators  dissipation  the  the  optimal the  to  royalty  tax  the  rent  regulates  by  the  and  royalties  the a  out is  public.  calculating tax  a  forcing  resource  priori  to  is,  Theory  of the  dissipating regulator  to  take  achieving setting  tries  the  to  to the  T A C . The  objective  quantitative  is  control  available  this  of  behaviour  are  the  restrictions  on  use.  thereby  of  the  frequently  imposition input  fishing  and  boats  is  unless  solution  regulate  That  permits  policy  new  apparent  two  this  and  However, of  encourage  The  (TAC)  theory,  emerge.  problem.  Limitation:  marginal  captured  by  indirectly  operators. the  optimal  regulator.  The  disadvantages  correct  royalty  been  the  proposed  Columbia  salmon  fishery  fishermen  has prevented  reducing scheme  government  the  in  by  This  Second,  reduction  has  access  number  tax  and  level  of  the  that of  of  effort.  between  Despite  these  (Pearse  1982).  The into  practice.  for  the  advantages. resource  not include the  be  First, on  the  behalf  difficulty  imposition a  including  obvious  catch,  determined  the  problems,  fisheries,  scheme's  price  the  need  time  commercial  put  two  program  several  being  net  manages  for  it from  has  boats  this  lag  the  of  of  the  system the  unpopularity  a  of  British with  License The  quantitative  fishery this  by  defining  program,  input, the  a  because  of  input  will  fishery.t.  The  1979,  of  directly  (Anderson relevant  on  The  to  of  1977).  of  license  a  the  program group  still  have  for  the  license  of  and  order  desired  to  scheme  is  easy  the  established of  is  that  the  adminster  the  of  the  bound to  on  enforce can  "part-time"  resource  rent  stay  in  the  intentions  of  the  debate  the  permitted  subvert  the  fishermen  excluding  fact  in  quantity upper  24  to  inputs.  includes  many  articles  system  (Crutchfield  include: about  that  the  choice  which  distributional  in  1979, of  groups  Scott  licensed  should are  be  nature  and  not  effort,  is considered.  this thesis.  section the  usual definition  disaggregated  neo-classical production  view  should  be  a  of is  the  key  fishing input,  presented  models.  tThe government collects only a nominal licence fee ^Ideally, this fisherman.  employed  an  fishermen  are  this  with  in  Practice /  puts  means  decisions  In  more  the  addition,  licensing  Requirements for an Effective Program  a  In  this  controlled  issues  input.  program  contention  licenses,  inputs  incentives to  a  of  lies  and  of  to  a  of  limitation  aspects  In  as  2.  Next,  equal  observed.  the  These  specified  limitation  scheme  areas  quantity  Theoretically,  readily  of  the  licenses,  whichever  various  trading  use  input.  substitutes  1980).  free  a  fishermen  literature  Copes  licensed  to  by finding  the  are  disadvantage  merits  input*,  way  support  accrue  controls  of  licensed  to  economic  specific  number  this  Furthermore,  regulators  directly  maximum  quantities  The  probably  In the  convinced  fishermen.  the  fixed  is created.  amount  be  restriction  Limitation: Theory  The  a small input;  implications  portion in  which  of  practice,  the it  fishing  brings of  the  input  potential is  usually  discussion  into  line  substitution  between  rent  form  of  or  the  the  in the vessel  License components  in  then  clear.  made  licence  Since  the  limitation  The  fish.  of  It  is derived as  catch:  one  average  unit  simple  obscures  per  channels  through  fact,  fisherman  the  the  intentions These quality  dissipation. literature available  with  most  single  input  concern with points  out,  of the  license  and  limitation  requirements  Practice /  25  programs  for  eg.,  economists have  adopted  used by fishermen  in the  the  impact  "...fishing  nonnominal  harvest  nature  effort  In  the  effort  of  the  many  fishing may  inputs  regulations. substitution  the  of  His of  are  a  successful  the  biologist's  single  unrestricted  input,  The  first  and  responses have  cross-sectional  data,  Norton it  is  to  therefore,  restricted  and  1980, not  for  technical  the  fish  in  terms  of  the  fraction  of  the  defined  number  of  on  numerical  Townsend to  at  the  of  mortality.  in  (constant)  traps  per  fisherman's  function  limited has  and  license  many  take  ways  three  restricted change.  generated  possible  tB.J. Rothschild, "An Exposition on the Bulletin. 7(3) United States. Department Service. 1972. 671-679. p.671.  defined  been  input  production  the  (McConnell  has  trawling,  responses may  and  is  capture  year,  1980).  of  third  this  respond  and  harvesting  effort  practice,  as  of  is simply the  ton-hours  fishermen  uses  the  1954  is caught."+  which  of are  success  Roy, Schrank and Tsoa  of  true  in  vessel,  1978,  notion  the  or  that  units  This  his  real  population  (Hannesson  the  concludes  as the  (1972)  of  etc.,  least.  article  from  Rothschild  standardized  for  Theory  scheme.  fishing effort  Thus,  bundle  section  Gordon's seminal  notion  the  effort  Limitation:  the 1986).  explore  reduces  of  inputs,  most  a  may  second  In  subverting forms,  at  change  in  cause  discussion in  However, the  the  restrictions.  different  Each  disposal  given and  Definition of Fishing Effort" in of C o m m e r c e . National Marine  rent the the third  Fishing Fishery  License responses.  It  attempt  subvert  to  is  certain  Discussions  about  the  use  key  This  depends on  a  substitution  The  in  before  likely  ability  the  to  alter  entry fishing  that  in  of  even He  labour  a  in the  to  inputs.  an  deal  use  (1962),  on  how successfully  positive  there  is  may and  of  input  of  limited  resource  a  great  the  deal  the  of  entire  inputs.t  substitutability. entry,  rents.  permits  dissipate  costly  substituting  of  that  on  the  the  As  fisheries  one  other  incentives  limited  entry  additional  fishery, but  centre  participants  matter  and  limited  predicts  fishermen  input  early  as  economists for  another  Crutchfield (1961) asserts that substitution is not  Scott  great  which  if  unrestricted  a system of  the  by  maintain  For,  open-access fishermen article,  26  ways  underlying fishing technology  modern  techniques  with  also  the  programs  as  licensed  on  fishery.  of  is still  the  regulated  the  a later  1969  so  excessive use of  divided  fishing  there  vessel.  for  the  entry  restricted which  important  Practice /  regulations.  limited  to  enhanced under  situation,  capital for  In  the  technology,  controlled  adoption  claims  degree  constitute  of  of  be  possibility of  a  are  can  advent  1956).  in  processes the  appears  the  (Crutchfield  efficacy  the  rent through  recognize  as  the  they  intentions  unregulated  literature  1956,  the input  of  substitutability resource  the  that  Limitation: Theory and  to  entry.  program  for  to  alter  input  restriction licensing  provides no  tThis is usually thought of as leading to Class II is no total allowable catch policy, it may also dissipation.  adopt  argues new  Pearse (1972),  scope  vessel  hand,  British  fishing on  hastens  explanation  that  technical  writing  Columbia power  the the  in  tonnage  the  after  salmon, a  limited of  substitution  the of  for this assertion.  rent dissipation, although cause the Class I type  if there of rent  License Copes  (1980),  number  of  participants  nature  of  confer  upon  the  for  the  on an  the  property  fisherman  the  increasing  resource.  right  open-access situation. the  the  fish  in  fishing  argues  that  to  sea.  capability  of  are  In  suggests  of  the  To  do  the  many  does  that  not  particular,  even  change  restricted  remaining so  vessel,  forms  though  in  of  of  their  other  substitution  limiting  the  the  fundamental  access fish.  tries  one's  every  27  does  As a  numbers are  fishermen  before  Practice /  merely  a pre-specified number  fishermen,  Each  the  there  phenomenon,  open-access fishery  still exists among the  himself  (1974)  in  common  the  competition from  commenting  Limitation: Theory and  to  not  result,  reduced  appropriate  competitors  requires  possible way.  Christy  available  to  limited  entry  competitors.  Even  the  regulators  attempt  number  of  participants,  eg.,  still  able  of  if  be  actual  hold  rent  1980,  Rettig  1984,  entry  equipment,  and  and  of  a  faster. more  mix  the  regulations  of  imposed,  all the  inputs  the in  fisherman  argue  type 1980, For  fisherman  of  may  use  he  may  fisherman order  to  uses an  alter the  optimizes catch  in  In  more  if  fish. of  the  may  discussions  potential  for  Copes  1980,  Scott  1981,  Pearse  1982,  tonnage  fuel  and  way  a  (a  measure  labour  purchase more this  fishermen  Recent  of  limited  1979,  net  more  using an  increasing amount  the  the  (Scott  fisherman's optimal by  used by  etc.,  favour  and  example,  may  inputs  components.  activity  Neher  sophisticated type.  of  length,  restricted  Alternatively,  with vessel-specific restrictions to  the  this  1985).  the  amount  programs  Norton  Scott  is restricted, time  from  through and  the  vessel's tonnage,  management  McConnell  turnaround  control  each  away  dissipation  Munro  capacity)  make  substitute  limited  substantial Munro  to  to  gear  limited  services to  or entry  the  electronic program  expansion path.  increasing amount  After  input  a subset of  of  of  Prior some  restriction  inputs along  is  with  License the  fixed  amount  of  assumes  that  possible,  for example,  fisherman increase is  the  suboptimal.  (given  (1984)  whatever  the  the  describes  component  it  of  effort  authors  Other  authors  associated manifest  that, in  face  (1979)  variable  If  catch.  level.  remains  unchanged, then  without  this  This  output  inputs  many  in  inputs  the  This  sufficient  a  is not the  concomittant  (along  ratio  of  the degree  faces),  with  is  restricted  "capital-stuffing".  capital  is the  the  it  expenditure  ability  of  to  effective  is reduced.  complete  notion  he  this behaviour  effort  time,  the  which  "seepage"  the nominal  with  constraints  (1979) terms  increase  but question  admits  the existence  doubt that  about  fishermen  a vessel or tonnage  having  little with  variability. the  vessel  production  and/or  In  face  of  rent  dissipation will occur.  substitution  to which  the  possibilities  and  phenomenon may  function  a  sharply  only is  be  to exhaust increasing  He views  he appears  to  in  the use of inputs in  the entire marginal  However,  he  rent in this way.  cost  the fishing platform  subscribe to  employed  Leontief  to expand  vessel-specific constraints.  ability  restriction.  fact,  may  of incentives  additional  the fisherman's  against  harvest  of fish  and  too  is limited.  principle  of license limitation  argues  used  use of  uses  an  given  dissipation,  stock  his  his  itself.  expresses He  agree  rent  Crutchfield the  believe  increase  to  and Practice / 28  rent dissipation. Although the fisherman's decision  fishing effort to increase whenever  Many  order  increase  Crutchfield  as  Theory  in  incentives  The fisherman catch.  to  the total  This constitutes  optimal  inputs  able  increased  input) for the realized Rettig  is  because  has ex posf  privately  restricted  fisherman  in output.  socially  the  Limitation:  of  expanding  as fixed,  the view  that  all  in  fixed  proportions,  ie.,  nature.  This  implies  there  that  or as inputs  that is  the no  License incentive  to  amount  of  is as if  the  to  this  the  the  Anderson  (1976)  input,  Adasiak (1979)  and  Anderson (1976,  of  the  fishing  that  the  focuses on  by  the  average  the  firm  an  labour,  Anderson's  firm  amount catch  the fish.  capital,  work  analysis for  permit levels In  is  a  the of  an  assumption claiming the  the  of  input  effort  against cannot  at  of  variable  exchange  with  of  as  Anderson view  It  1982,  Practice /  restrictions  increase.  his disposal.+ 1985).  fishery  these  and  In  It  29  on  the  theory,  Other  it  adherents  is often  not  its  with  production  catch  the  a  function etc.  However,  that the  Lee  effort several  effort  fisherman  (1976).  among  of  The  They  function. the  fixed  called  in  address the  Huang  and  theoretical  to  theory.  He  this  is  of  competitors.  the  fishing  firm  produced by traditional  the  inputs,  becomes  in  control.  argue  in  favour  require  inputs  to  particular,  Anderson (1978) stresses the output.  and tries  since  index  may  They  several  inputs,  rate,  number  Anderson calls the  other  authors,  fishing firm  micro  fishing firm.  production  intermediate does  of  control  fuel,  substitution and  individual  realm  the  is  input  Huang  inputs  an  uses.  gear,  single variable  the  conjunction to  product.  by  the  in  it  of  directly  is given  generalized  effort  into  fish,  materials,  elasticities the  behaviour  cannot  of  rate  criticized  more  the fishery  intermediate  to  output  variable  fishing  need  expected  inputs  one  amount  This  unrestricted  only  can control the  eg.,  of  because  has  analysis  determined Thus,  are  use  and  vessel capacity assumption.  the  argues  fixed  the  fisherman  view  fixed  bring  increase  Limitation: Theory  Lee  of  this  function  depend the  upon  stock  validity  (1978)  the  of  of  his  counter  by  possibility and  practical  tClark (1980, 1982) makes this assumption explicit in a series of models that attempt to describe both competitive and oligopolistic behaviour of fishermen in a limited entry fishery.  License reality of variable  In  1982  adopts  Anderson, the  limiting  fixed  one.  license  for  supply  made  the  by  of  adopt  correct  fleet  appears  behaviour  encouraged  substitute  vessel  capacity  to  by  the  shifting  of  unregulated  inputs.  From  The  of  may  authors  believe  the  who  accomodate  substitution  that of  there  can  the  many  that  work  tThe two scenarios describe situations fishing industry.  the  system,  that  it  complete per  from  marginal  that,  This  costs  factors. once He  again.  dissipation  boat.  restricted  is a  benefits  assumption once  effort  asserts  share  the  is  of the  do  not  With  his  regulators  argues  that  the  continuing  for  rent  resource  incentives rent.  curves  notion  constant  the  the  may  be  marginal  costs and  increasing  to  be  harvest  analysis use  views  the  production These  associated  Thus,  of  non-existent.  summarized.  costs  fisherman.  dissipating  static  Anderson  inputs  that  inputs  the  to that  unrestricted  by  Anderson's  due  appear  increasing  used of  a  asserting  capital-stuffing.  between  inputs  in  fishing firms.  the  substantially  30  the  and  with  of  the  would  restricted  Practice /  subsequent actions of  supply it  the  increasing  from  of  firm's  substitution  various  cost  ignore  the  and  compares  adopts  Anderson then  disagree  are  which  concludes that  ie.,  away  entry  concludes by  he  he  existence  his  possibilities between  function  the  individual  substitution  those  they  discount  but  marginal  (1979),  limited  (1985),  analysis  Theory  stock-dependent.  of  scenarios,+  to  the  views  article  increasing  size,  be  impacts  size incorporates  Anderson  ignores  later  demand  fleet  may  assumption,  Crutchfield  fixed  initial choice of  the  different  an  fisherman  the  on  a  two  by  assumption  in  and  stemmed  assertion allow  writing  However,  static is  proportions that  vessel capacity  limitation  Using rents  input  Limitation:  few,  if  increasing costs for  with any, the  License substitution Leontief  possibilities  fixed  exist  proportions  between  production  pairs  Limitation: Theory  of  inputs,  function  is  a  and  valid  and  Practice /  therefore,  description  the of  31  so-called  the  fishing  technology.  It  is now  in  a  possible to  limited  upper such  entry  bound  vessel  may  prevent  its  have  upper  neither  fishermen  be  For it  bound  unrestricted  this  way  the  is  nor  inputs  fisherman  may  a  Next  for  preventing  must  net  by  constraint  than  among  reduced  set  the  it  of  dissipation of  a key  per  must  input  vessel this be  other  variable  input  rigidly  amount  intentions  of  inputs. inputs  of  the  the  and  rent  put  restriction  is necessary that  the  increasing the  subvert  the  controlling  increasing. Finally,  the  identify  tonnage  that  the  complements  over  rather  regulator  believed  from  re-optimize  the  requirements  example,  controlled.  substitutes  will  the  First, the  use.  because  also  the  fishery.  on  candidate  discuss  an  is  one  output  per  controlled the  If  it  and  key  input  does,  then  use  restricted  regulations  to  more  of  factor.  In  and  dissipate  rent.  Conflicting individual  views  are  If  the  effectiveness  possibilities  substantial,  rent dissipation must  A  resolution  of  is  ultimately  an  This  the  assessments regarding  technology. inputs  on  thesis  the  then be  the  called  issue of  empirical  proposes  to  of  restricted  the  substitution  for  substitution  efficacy into  input  matter perform  of  access  possibilities in between  restricted  programs the  underlying  unregulated  access  arise  and  programs  in  from harvest  regulated preventing  question.  substitutability  that  must  this  task  be  and  the  answered  for  the  concommitant on  British  loss  of  a fishery-specific Columbia  rent basis.  commercial  License salmon the  fishery.  In  appropriate  past  efforts  Chapter  4  framework.  to  conduct  a model The  of  current  empirical  Limitation:  individual chapter  studies  of  Theory  vessel  behaviour  continues  the  issues  and  with  a  related  to  Practice /  32  is suggested  as  consideration  of  license  limitation  programs.  B. EMPIRICAL In  this  STUDIES  section  research  may  the  be  production  efficacy  of  of  the  statistics  units  dissipation. (the  limitation  as  They  license)  on  often as  of  estimate papers with  integrates  calculations  means  of  number of  the  the  in  two  the  the  important  surveyed  categories Studies  of  the  effort  units  or  of  the  inability on  the  incomplete  ie.,  amount objective  These  the  studies  estimation  of  the  the  right  fish  in Chapter  In the  second  methods  inputs.  This  to  contrast,  None  substitution  dissipated.  power rent  econometric of  typically  fishing  constitute  pairs  the  prevent  dissipation.  use  of  an  to  rent which  evaluate  relative  programs  The  whether  kind  value  They  rent  on  evaluated.  upon  trend  between  of  first  fashion.  studies,  minority.  and  depending  indirect  possibilities  methods,  estimate  achieving this  of  is  an  production  substitution  the to  of  harvest  in  information  evidence  are  broad  programs  PROGRAMS  evidence  estimated.  include  research,  directly  two  is  evidence  empirically-orientated, category  the  LIMITATION  empirical  into  function  license  annual  LICENSE  available  divided  harvest  cite  OF  of  to the  parameters  thesis  proposes  a  6.  1. Non-Production Function Studies Before Wyner have  discussing (1978), had  with  these  studies  is offered.  In  limited  entry,  an  observation,  a comparison these  of  authors  made  by  Cicin-Sain,  the, experiences  which  complain  there  that  Moore,  many have  and  countries been  no  License systematic  evaluations  neglecting  to  such  this to and  In  fisheries  general,  The  (Fraser  McConnell  the  this  1977,  all  Huppert  Campbell  (1973)  licensing  program.  Recall from  licensing  first  vessels,  on  increasing  the  the  sophisticated increasingly  it  amount  been  regulated  by  toward  the  equipment regulator  use on  has  number of  a  board.  article  limited  the  of more  the  Meany  pots  fishing  in  Chapter  argue of  per  that  larger  of  rock  researcher  relevant  vessel per  evidence  of  Meanyt  Australian  However,  Munro  literature  especially  bears  in out  Kirkley,  Columbia  commercial  salmon  2 that  began  1979,  it The  and  the  authors  1969  by  comment  use  of  more  salmon  fleet  is  being  greater  than  boats  with  licenses  to  a fish  rent,  taken  have  Sinclair  acquired  claims  that  Since  1963  place.  in  Australia.  program have  greater increased concludes  prawn  in  the  Vessels a  interested  Strand,  licensing  engine,  support  respect  fishery  vessel.  to  with  resource  lobster  necessary  vessel.  has nonetheless  the  the  vessels,  Although  season.  discusses  entry program.  data  British  They  this  for  the  powerful to  programs  1984).  bigger  used  the  Rettig  and  a  criticize  1982,  tonnage  of  33  Meany  emergence  means  Practice /  1979,  net  Coast  and  data,  capacity.  West  the  Theory  suitable  Wilen  direction  the  of  of  discussion  newer  Reacting  shortened  same  a successful  the  rent dissipation  the  the  Byrne  fishing  examines  on  1982,  indicates of  lack  of  plagues  review  and  the  (1979)  has  the  which  the  they  quality  still  (1978) evaluate  of  in  A  Pearse  then  in  or  data  1982).  equipment.  increase  values,  restrictions  tin  use  skewed  a substantial  Meany  Sinclair  electronic  proportionate positive  and  of  cite  1979;  Furthermore,  quantity  lack  (Pearse  articles  1981,  programs.  either  research  assertion. costs  these  generate  analyses.  doing  of  Limitation:  with  exhibited  tonnage, fishing that  fishery  (1982) argues  additional  and  trend more  capacity,  there  as an  a  has  the been  example  of  that its success is  License excessive place.  reinvestment  This  (1982)  is despite  studies  this  in  gear  the  fishery  dissipate the  The  fishery in two  (1982)  and  factor It  in  Stanistreet  both  this  unlicensed  factors the  crew  inception of  Fraser  (1982)  licensing licensed  factor  the  vessel to  and  in  vessel  different  the  but  be  use  by  the  and  less  countries  this  the  rent  dissipation  to  take  increasing license values. Rogers  convinced  per  is the  the  of  case and  licensed  input the  abalone  diver.  subject  fisherman  form  Australian  each  British  1974.  of  of  (or  the  ability  of  restriction  authors  industryt  offer  is  the  for  diver  increased  Huppert  the  licensed  are  very  different.  no  enlightenment.  exhibits  analysis  has  research by  diver)  Huppert's  The  Columbia program  individual fisherman.  used. of  is  caused  34  little  the  increase  California  substantially  since  in  case the  program.  since  is the  has  positive  Although  the  used  evaluates  system  the  used  this  Practice /  rent.  should be  concludes that  1976  well,  (1982).  Stanistreet  that  as  of  fisheries, reactions to  is unclear why  shows  that  presence  fishermen to  abalone  and  Limitation: Theory and  Fraser cites  electronic  has increased.* However,  undertaken.  Furthermore,  time which  might  justify  there  is  a formal no  an increase in  herring  unlike  fishery*,  that  Nonetheless, the  increases  equipment.  is  roe  He  in  the  also  analysis to  discussion  for  salmon  fisherman  power  argues  of  that  substantiate  about  the  which  has  because  must  labour  these  abundance  a the  designate  participating the  had  vessels  used  per  claims is  not  of  fish  over  harvesting capacity.  t(cont'd) attributable to a government engineered bilateral monopoly. tAfter beginning in 1963-64, this fishery was licensed in 1968. *This is the second largest fishery in British Columbia and many of its fishermen participate in the salmon fishery as well. *This is the likely response to increasingly shortened seasons for the fishery. For example, the Kitkatla roe herring seine fishery for 1987 lasted an historic 6 minutes.  License These  studies  micro  production  the  point  importance  restricted  to  of  upon  and  2. Production  level  of  the  They  are  important,  Byrne  studies  dummy  at  estimates  in  to  a  given  vessel it  provide  to  may  is the is  indicating  50%  he  in  unless  the  of In  of  the  the  fisherman.  role  about  the  Practice /  behaviour  particular, played  by  the  in  this  35 the  exhibit  prices  means  the  of  they  by  Only  technology  evidence  the  and  way  of  is  it  standard  degree  of  effects  of  Strand,  entry  fishery  explicitly  Kirkley,  and  McConnell  analysis that  used  to  evaluate  input  an  restricted  input.  His  model  use  to  vessel  of  a single  that the  area  and  rates Byrne's  relative  can provide the  at  estimates  efficacy  of  the  1981). of  limited  the entry  restrictions.  of  the  Furthermore,  of  limited  power  related  catch  1982,  level be  a  fishing  finds  one  within  (Byrne  is this  that  area  function  least  of  model  program.  production  production  relative  vessel  irrelevant.  related  and  for  the  variable  However, are  underlying  model  possibilities  production by  decision-making  the  individual  The  limitation  examination  with vessel-specific input  Australia. vessel  license  formal  and  Studies  two  programs  the  a more  Theory  associated rent dissipation.  Only  substitution  a  for  complete  techniques  substitution  need  under  a  estimate  econometric  the  unit  factors  possible  to  Limitation:  of  length,  average  over  100%  these  finding prices.  average  or  For  says that  rig.  fishing power in  the  horsepower,  double  another  vessels of  prawn-trawling  are  increased example,  per  for  catch  fishing  Using  vessel rate  time  in per  and  a  a Cobb-Douglas  vessel has increased  the  constant, productive  period these  1970-1978. observations  efficiency  a technological  is  innovation  not in  License fishing  The  may  second  fishery.  paper  Strand,  production gross  increase fishing  Kirkley,  function  registered  Isoquants  for  Leontief  fixed  possibilities complete  is  the  deals  for  of  calculated.  analysis.  with  surf  horsepower,  these  lower  inputs  (1981)  clams. length are  Once  again,  of  inputs  estimate  Output of  plotted  assumption.  and  Practice /  36  costs.  substitution  McConnell  Atlantic  proportions not  and  outright  and  tonnage,  pairs  power  Limitation: Theory  and  blade  found the  cost  a  limited  cross-sectional,  specified  dredge  However, input  is  a  in  are  a  and  not  degree data  as  of not  translog  function hours  to  entry  of  fished.  support  the  substitution available  to  IV. MODELING THE BEHAVIOUR OF THE REGULATED FISHING FIRM In  this  chapter  a  model  fishing firm  that  the  some  use  the  of  degree  operates  of  quantitative  evidence  thereby  that  the  order  adopted. Indeed,  recent  In  be  a  little  made  for  1985, 1985  section of  In  the  technology  statistics  of  the  this  enumerates which  and  for  paid  chapter  the  the  of  describe  Opaluch  typical  this  effects  is  advantages the  for  A  and  1983,  For,  if  the  provides  resource  restricted  rents  factors.  production  the  motivations of  Conrad  this  1984,  is In  theory  analyzing  most  of  second objective  the  economic  on  testing  inputs, this fishery  researchers  representation  approach are  describing the  means  approach  the  dissipate  fishing firms  of  price  analysis. By using duality by  technology.  regulations.  to  restrictions  empirical  regulated  values  to  competitive  are  fishery.  underlying  work  is very  Kirkley  1984,  1987b).  method  particular,  into  section  been  to  the  microeconomic  approach  Shortcomings of  incorporated  development  has  from  Bockstael and  this  an alternative  harvest  common  for  a small  is subject  fishing  entry  shadow  by individual competitive 1979,  owner.  deriving  of  basis for  the  fishermen limited  and  a  unregulated  of of  behaviour  fishery  in  techniques  attention  for fish is discussed.  boat  of  not  of  ability intent  This  first  search  the  goal,  is  model  possibilities  the  capable  Squires 1984,  the  of  this  (Wilen  1986,  serves as  achieve  very  decisions  The  substitution  undermine  model  to  the  describing the entry  substitution  permits  out  in a limited  inputs.  technology  and  is set  of  a  the of  this  relationships  approach between  37  harvest  enumerated.  changes  techniques  of  the  and it  input  the in  profit  second  and  of  inputs  a  individual  controls  The  the (both  are  describe  function.  section.  a discussion  output  the  is possible to  restricted  function  This leads to  fishing behaviour of  short-run,  subject  of  The third  summary variable  Modeling and  fixed)  this  function  A.  THE  that  may  be  obtained  is particularly  DIRECT  the from  well-suited  HARVEST  Behaviour the  to  of  restricted  studying  PRODUCTION  the  Regulated  profit  the  Fishing Firm /  function.  behaviour  of  It  is  seen  regulated  38 that  firms.  FUNCTION  1. Specification of the Direct Harvest Production Function Before  describing  function fishery and  it  inherently  become  production fish  in  alone  the  which  is  are  upon  the  Tugwell  (1979)  studies.  Conrad  research  and  the  (1984)  to  concludes that  Much  of  the  fisheries  biologists  and  mathematicians,  it  research.  As  period  (1984)  maintain  the  of  the  (Schaefer both  the  of  fish  produce  last  and  result,  the  the  is  assumption the  this  than  of  firm.  this  the  fishery  Both  1957,  Beverton  (Clark  types  of  and  models  in  reflects Holt the  in  second how  function the  fish  available  to  analyst  to  Henderson their for  assumptions 1976,  and  of  the  assumption  many  decades  latter  a  nature  describes  fish  allows  to  The  dynamics  assumption of  it  this  stock  of  eggs which  1957).  fisherman; It  of  three  Holt  output.  time  the  exploitation  adult  appropriateness  models  production  is attributable  This  decisions  harvest  first  a  of  the  The  commercial  is less stringent  literature  dictate  the  of  commercial  Beverton  exogenous.  in capital-theoretical  interests  of  how  input  discusses  The  functions.  1957,  any  be  Bj0rndal  results  Their  at  matter.  profit-yielding  this  so that  specification  dictates  into  to  obtain  1985).  It  domain  intra-seasonal and  one  (Schaefer  interest  the  production  converted  assumed  to  clarify  two  is in  are of  is  to  adults  ignored  fisherman  relating  time-dependent.  function sea  focus  by  fertile  the  population  work  necessary  is constrained  is  turn  is  past  and  empirical empirical used  to  concerns  of  1985).  the 1957, level  Clark of  1976,  analysis.  Modeling Because  of  the  growth  models  fishing  stock  biologist's the  of  role  a  Fisheries mathematicians optimal can  control  not  1985;  deal  exhibited access  the  by  (Clark  ultimate  concern  growth  Y(t)  In  this  (E)  at  to  describe  is  =  t  and  the  Y(t)  (1981)  and  included.  In  is  of  realistic  relegated  to  fishing  effort  called  the  intertemporal  state  and  of  focuses  two  on  exploitation,  and  Heal  the  nature  control  impact  of  a  ie.  39  population  impact  on  (Rothschild  of  the  the  1972).  fishery  variables  the  comparison  monopoly  1978,  Wilen  is of  the  of  and  (Clark  the  (Clark  1985).  aggregate  production function  is the  an  harvest  to  as  Anderson  Bj0rndal  (1984)  practice,  it  is  rate  of  individual  (Anderson  refered  although  development  Fishing Firm /  1976,  1979).t  biomass (stock  technology  inputs,  Regulated  catch form  In  1976)  and  either  case,  upon  given  behaviour  the  open the  population  in equation  (4.1).  g(E(t),S(t))  either  usually  the  the  assumption as a necessary simplification. They use  two  Dasgupta with  variable  analysis  forms  harvest  equation  industry E(t)  is  rate. The  (4.1)  of  polar  1980b,  than  the  exploitation  analyze  Munro  level  two  this  to  more  Clark, Clarke, and  Traditionally  human  adopt  Behaviour of  with  economic  techniques with  concern  of  single  the  fish)  with  ill-defined  (1977),  Byrne  indicate made  time (S)  vessel's  1977), an  at  that  at  t.  It  time  is a function t.  This  production E(t)  composite (1982), a  operational  by  bundle  of  form the  other a  and inputs  standardized  tHowever, numerical analysis may be used to infer the properties of optimization models, even though they cannot be solved analytically.  effort  is used aggregate  The  capital  Kirkley,  of  defining  or  fishing  appropriately.  Strand,  number  general  function  specified  of  variable  and  labour  McConnell are  often  vessel-day  such  dynamic  Modeling measure one  (Roy,  unit  of  effort.  Use  notion  of  is,  if  into  Shrank,  all  effort of  a  this  inputs  practice,  production  is  are  the  function  =  to  be  constant  and  the  Loose  is  in  the  strictly  population  to  its  by  then  by  one  appealing  (Munro  proportions  Fishing Firm /  catchability.  caught  justified  technology  fixed  Regulated  reference  usually  production  B.C.  in  most  equation  in equation  the  and they  can  That  is,  vessel-day's  to  Scott  40  Leontief's 1985).  be  That  aggregated  respect  to  the  the  catchability  across  all  coefficent  fishery,  effort  literature (Clark  is  for  the  general  C o b b - D o u g l a s (Clark  fisheries  and  Munro  b  this  salmon  (4.1)  adopted  (4.2).  as  same  allows  commonly  but  production function. The  with  theoretical  form  is defined  (1975)  the  aggregate output  variable  a  q  of  effort  q.E(t) -S(t)  equation  the  of  given  this  of  through  fraction  functional  In  analysis  1980)  the  variable.t  Y(t)  vessel.  Behaviour of  the  used  1975). This is shown  (4.2)  Tsoa  fixed-proportions  a single  In  and  the  and  and  vessels, to then  stock.  in  vary  the  across  imposes  parameters  Munro  coefficient.  a and  These  are  This case  is of  vessels  constancy b  are  often  the set  usually assumed more  in for  his  than  theoretical  estimation  partial equal  one  of  elasticities to  one  in  1975).  t i n fact, what is being assumed is that inputs are (1987a) discusses the conditions under which fishing consistent aggregate.  additively separable. Squires effort can be used as a  Modeling  the  Behaviour of  the  Regulated  Fishing Firm /  41  2. Problems with the Direct Production Function Approach There  are  several  production  function  undesirable  format  regulated is that  fishery. it  isoquants  optimal price  for  not  pairs  incentives  which  production  function.  A  problem  related  that  subject that  to  they  notion suggest result,  to  that the this  second  inputs.  the  fishermen  fishermen  behave  in  type  models  of  model  difficulty  that  incentive of the  with  the  rent  any  notion an  or  economically  describe short-run, system  agents  should  be  flaw  seek  maximizing way.  explicitly  it  This on  with  the  direct  is usually are  to  good  optimize  (1986)  behaviour  profit-maximizing  the  assumption  Wilen  This  a  prices  the  There  Eales and  rational  of  behaviour  who  of  point(s).  concerned  profits.  in  technical  shapes  input  an  function  the  behavioural  individual  maximize  profit  the  relative  of  it  dissipation  describes  is  direct  make  production  serious  type  For example, of  rent  equilibrium  a  the  features  derive  in  is  economic  face.  can  with  direct  dissipation  this  of  costs are  they the  of  and  the  economic studies of  neither  use  lack  one  changes  overfishing,  minimize  constraints  of  It  not  of  issue  the  In  role.  but  impact  the  a  Thus,  inputs,  reject  decision-making  A  that  whatever can  and  either  believe  substitution  merely  from  assumed  (4.2). These  play  to  encourage  e c o n o m i c motives.  input  or  prices  Since  regarding  reasons  of  (4.1)  empirical,  the  of  stems  agents  either  and  shortcoming of  reflect  allocation.  theoretical  theoretical  output  cannot  by  study  permit  between  input  the major  between  methodology  both  as specified  The  does  relationships  problems,  leads  nor  the  them  to  behaviour.  incorporated  find  As a  into  the  from  the  fisherman.  typical  production  function  formulation  stems  Modeling assumption no  that  distinction  factor and  is  is fixed, fixed  both  made  and  factors,  that  the  control  the  information the  restricted  Finally, rent of  it  the  is  the  the  regulations  function  use  one as the  production  dissipation. To  do  so  direct  even key  if  the  input.  is an  production input For  missing, (Varian  due  the  factor to  the  estimation  1978).*  function  their  true values.  The  direct  producton  a  it  success of  may  be  the  function  some  their  but  fish or the  cannot  model  rate  data  parameters  the set.  usually  and  of  difficult  (1967)  of  leave  of  other  to  and  an  to  suggest  variable there  inputs  under  lack of  price  prices  of  that  an  the  of  interaction  are  be  nature.  First,  observations on skipper able this  omitted  elasticities may  a  estimates  input prices.  when  having  as  obtain  empirical  vessel. They  specifed  one  when  shadow  obtain  However,  as  the  the  Thus,  least  between  incorporate  output  shortcomings  is often  at  behaviour  used  can  of  sought.  42  licenced vessel characteristics.  be  which  Huang  is made  describe  estimates  is  where  is combined with  obtain  characterized  is  to  Fishing Firm /  solution  short-run,  inputs  feature  has  and  quality  Estimates of  used  alone  also  Comitini  in the  be  prevailing set  is expanded,  example,  important  hypothesis  set  distinction  stock of  production possibilities with the  The  no  not  requires  long-run  Since  this  function  Regulated  the  of  can  a  the  of  cannot  fisherman. W h e n  factors, such  since  modeling  the  that  Behaviour of  variable  long-run.t  restrict  clear  direct  are  between  of  are  of  inputs  the  a  knowledge to  test  this  information  is  variable  bias  biased away  from  Cobb-Douglas,  or  less  tThere are a few exceptions (Bradley 1970, McKelvey 1983, Conrad 1984). All of these papers assume that the stock of fish is fixed for the period of interest. tThis means that the right hand side variables are not independent of the error term.  Modeling frequently  as a CES, functional  1982).t  One  estimate  a  exception translog  Cobb-Douglas with  input  between  and  undesirable between 1985). scale  as  it  on  be  carried  out.  Estimation  must direct  of  of  (Diewert  1973,  quantities  of  estimation decision tComitini CES  since maker, and  In  advantage  prices  Huang  are  be  Plourde  of  area  of  recovered  the  of usually  cannot  the  a  assumed are  not.  reject  concerned of  is  particularly  of  substitution 1984,  increasing  Scott  this  procedure  Wilen  returns  suggests  the  appropriate  duality  function  avoiding  the  elasticity  Rettig  and  representing  from  to  dual  But  of  to  decreasing  (1985) is  argue  that  often  not  exception.  is not  means  1981,  (1971)  Munro  They  C o b b - D o u g l a s goes  degrees  of  (1981).  the  restriction  assumption  tested.  function  quantities  (1967)  the  contrast  as arguments,  This  Neher  1987a) is an  be  The  Scott  contrast,  can  constant.  Byrne  study  restrict  different  and  a  43  1985;  properties  for  forms  one.  assumption.  alternative  1982).  whereas  formulation.  In  several  unattractive  be  1982,  McConnell  qualitatively  impose  scale  may  to  Fishing Firm /  1980b,  and  are  Both  be  1979;  production  function  the  to  observe  1985,  them  inputs  advances in the  1974,  has  to  Strand,  dissipation.  variable  1977,  to  an  Recent  inputs  rent  Regulated  Clark  There  make  appropriate  direct  Therefore,  used.  which  the  1984,  Kirkiey,  function.  technology.  more  the  by  authors  returns  production  approach  many  Squires (1984,  study. be  a  paper  elasticities  (Fraser  fishing  question  this  pairs  the  may  all  is c o m m o n  Furthermore,  (Bj0rndal  and  pairs of  restricts  input  returns the  CES forms  Behaviour of  form,  production  substitutability  substitution further  and  is the  the  the  depends  the  purposes  fishing  that  estimation  production  be  The  the  indicate  potential to  for  a dual  function, upon  fruitfulness  Cobb-Douglas  to  of form  in  a  function uses  prices. This bias  the  this  of  which  input  simultaneity  exogenous  technology  knowledge  of  of  in  the  individual  direction favour  of  of a  Modeling research  for the  Squires the  (1984)  New  function (1986)  fishery  has recently  uses a restricted  England  with  otter  three  the  England,  Georges  estimates  a  describes  the  behaviour  of fishing firms.  dual  B. THE DUAL  model  fishery.  three  recognized  outputs,  fishery.  He  (translog)  function  APPROACH:  to  He  examine  specifies  two the  a  revenue for  a  single  THE RESTRICTED  thesis  harvest  dissertations.  technology restricted  dummy  fixed  The  investigate  of  profit  variable.  input  function.  to  PROFIT  doctoral  by fishermen  maximization this  Fishing Firm / 44  (translog)  choices made  specifies  chosen  in  and a technology  output-maximizing  Bank  multi-output  been  profit  trawl  inputs,  focuses upon  the Behaviour of the Regulated  Kirkley  in the New model next  the  and  section  harvesting  FUNCTION  1. A Short-Run, Restricted Profit Maximizing Model This in the  model  the  represents  limited  number  unregulated,  entry of  have  at  begining  assuming is  better  a season allows  It  than  would  season  Cournot  that  o n the to  In  the regulator  owns  It  a  competitive  is assumed  the  of  fishing  firm  throughout  that  operators  past,  a  fixed  Licenses are renewed  part  form  of  number  payment  intertemporal  a fishing firm  the  fishermen.  d o not seek  the fact  fishery.  attract.  upon  behaviour  me to neglect  is assumed that  less  fishery  each  fishermen  off. As well,  is  a season  salmon  issued to qualifying  of  individual  within  Columbia  participants  been  assumed that  behaviour  British  open-access  licenses the  the  of  a  nominal  of  each  fixed  fisherman.  coalitions which  controls the total  might  which  an  number  of  automatically fee.  I  am  Therefore, make  allowable  it  them  catch  in  considerations.  o n e vessel  and that  there  is no  horizontal  Modeling integration taker as  in  both  the  the  between output  quantity  five  inputs,  vessels. and  variable  of  and  function.  It  is possible to  define  in  this  no  new  is on  insights contrasts  decisions  in  a  the  may  side.  be  that  input.  It  vessel-owner  that  season.  These  the  services, the  gear  fishermen  these fuel  and  inputs, the  increasing means  to the  the are  services.+ either  that  the  may  with fish  the  may  or  is able travel  to to  biomass. be  To  entice  brought  to  a  on  His  vary  is the fish. more  greater  Or,  and  is  using  an  according  to  the  on  board  the  of  focus  use  both nets, By  fish.  on  of  lures, the  For example, of  fishing  amount  faster.  In  interest provides This  allocation  this  area  inputs  he  within  skipper, etc., use by  of  labour  addition,  fuel  used  by  any  of  using  grounds, of  of  production  output  and  of  types  side  in  crew lines,  defined  the  three  increasing  greater much  is  is  price  substitution.  behaviour  the  but  output  input  a  45  agreggate two  number a  it  of  analysis  including  catch  This  be  Application  highlight  the  output  to  using this framework  (1986).  input  Fishing Firm /  assumed  landed.  output  an  is free  latter  is  complexity  to  services,  The  entrap  fisherman  vessel-owner contact  labour  the  Regulated  one  salmon.  Adding  framework.  specifies a single fixed  is only  problem  Kirkiey  the  owner  salmon  yields  applied  of  multi-species  of  exploited  (fixed),  of  vessel There  pounds)  input  with  is assumed  the  a multi-output  that  approach  in  restricted  Behaviour  markets.  commercially  or transformation  thesis  well,  input  (measured  species  As  the  more  thereby services this  may  tThe assumption of the existence of the appropriate rental markets for the latter input appears reasonable for British Columbia. O n e need only look at the numerous advertisements for the sale of second-hand gear. Squires (1984, 1987a, 1987b) assumes labour, fuel and capital to be variable inputs; he claims that capital (the vessel) is completely malleable because of the existence of rental markets.  permit  the  specialization  having  more  navigation  or  repairs.  This  on  total  the  The  men  The  tonnage  number  Nature  the  the  and  controls  access  by  periods.  In  biomass  originally  fact,  in  fishery.  This  insofar  as the  great is  that  fishery,  as  perpetuation Allowable  of  Catch.  tin fact, nature stochastic nature  the  nets  larger in  firm  Fishing Firm /  catch.  particular  less time  fishing  controlled  is  For  46  example,  tasks,  such  as  lost  to  in-season  to  a  restriction  is subject  fish.  fishing days.  to  Second,  fix  providing fishing  most  fishing  a only  first  in  in  no  both  regulator, cases the seasons for  provides a stochastic input of this variable, since I do  vessel,  the  net  the  of  fisht;  the  regulator  areas of  and  fish  (1970),  this  and  overall impact  far  depend  called the not model  Loose  two  level upon  (1975)  upon  make in  the First,  stock  is so  of  for  even  the  the  reasons.  escapement  exceeds  time  from  his output.  Catch  desired  escapement  reduced  for  Allowable  the  specified  decision-making  study  the  for  is  monopoly  salmon  of  number  Total  and  the  because  for  appreciable  the  by  or  level  is concerned,  have  regulations,  fisherman,  some  Bradley  consideration  the  at  stock  intra-seasonal  by  factor  given  the  season  encountered  certain  (1983),  with  level  the  the  progresses  includes  In  of  of  vessel-owner  by  because  number  deal  that  the  fish  important  in  or  within  of  McKelvey  that  biomass  the  a  stock  season  an  permitted  to  Regulated  specialize  more  short,  interact by  the  individual  total  the  the  available.  not  when  lead  to  using  not  too  permitting  reductions  because  is  and  models  is  are  are  so  as  will  the  days fished.  regulator does  Behaviour of  them  by  important  factors  Nature  explicit  Finally,  season  vessel,  the  permits  factors  season.  this  which  labour  board  of  (fixed)  fixed  of  of  is especially  because  nature.  the  fish-finding.  restricted  either  on  Modeling  the for the  This entire the Total  characteristics  stock of fish. I the intertemporal  ignore the problem.  Modeling of  the  pass  fish  themselves.  through  within  The  any  period  chapter  2.  tonnage place. uses  area  levels  constrains  That  than Over  by  given  stock  regulator  For most  is,  the  each  vessel  time  the a  associated  with  larger  the  hand,  other  smaller  vessel.  Finally,  nature  a  and  fishing days that come  in  restricts periods  It  is  to the  of  the  use  the  net  tonnaget  used  at  and of  act  use.  hence,  Fishing Firm /  Columbia runs  a  vessel  by  not  use  try  that  to  he a  together Nature  1982).  fishing  days  by  objective  of  each  to  prices,  the  fellow by  47  of  fish  Therefore,  the  as  with  restrictions the  net  also  discussed a  participant  control the  be  declaring  the  in  the  during  caught. certain  The areas  put  into  that  a  he  license,  fishery.  building  maximum  times  net  tonnage  purchase  in  larger  were  commissioning the  to  to  decree,  vessel  must  controls  liable  a  increase  tonnage  are  British (ESSA  time  from  the  in  Regulated  period  of  However,  decrease  regulator  salmon  may  may  the  much.  the  tonnage,  a vessel may  number  On of  number  which  closed  of  the  regulator  a  fish  further  for  given  time.  that  profit of  between  fluctuate  vessel.  net  may  spawn  assumed  restricted  not  he  of  two-week  license-holder  larger  he  a  vessel-owner  buying  Behaviour  species of  within  do  the  the  assumption tRecall from capacity.  subject  some  total and the  the  inputs.  seasonal that  of  given  Restricted revenue the  discussions  (or and  exogeneity in  chapters  fishing  a  firm  production  seasonal) total  profit  cost  of  of  the  prices  2  and  3  that  is  to  maximize  function, is  and  defined the  variable  appear this  as  is  to a  be  seasonal  restrictions the  on  difference  inputs. valid  measure  or  in of  This the hold  Modeling British  Columbia  commercial  owner-operators  and  the  the  markets  The  for  solution  since  the  upon  the  1987). static  actual  It  levels of  contrasts with  equilibrium.  any  the  given  situation. net  In  tonnage  The  factors  are  success  of  In  net  this  is optimal  of  fixed the  provides  the  firm  cannot to  Furthermore, since to  it  allow  the  is the  not it  the  alter the  the  hand.  regulator's  recruitment  for  of  the  of  the  task  to  future  profit  all  rental  inputs  regulator ensure  periods.  48  small  addition,  static  the  Finally,  is  relaxed  this  to  the  existence  the  factor  unconstrained the  actual  tonnage.+  given  that  concerned  current  full with  fixed  whether  season.  escapement if  is  1985,  ie.,  some  with  profit-maximization  the  assures the  Kulatilaka  an  reasonable firm  dependent  variable,  in  net  of  equilibrium,  are  of  price  relative  sufficient  level  of  fishing  changing firm  In  static  are  question  decisions for  individual  partial  chosen  seems  solves a  by  market.  assumption  be  the  the  firm  allocation  year's  would  behaviour  mostly  Christensen 1979,  equilibrium  market  Thus,  The  and  answer  current  season.  next  to  are  quantities  is possible that the that  myopic  optimal  presence  one  is a  input  in which  partial  possible  for the  size  this  the  is  season at  this  (Brown  because it  short-run, for  and  due  is  way  factors  world  Fishing Firm /  competitive.  variable  situation  a  problem  and  Regulated  participants  on  be  output  6  the  The  sold  appear to  a long-run  tonnage  is  maximization  fixed  chapter  time  assumption  partly  constrained of  fishery.  product  inputs  choices  Behaviour of  salmon  salmon  variable  this  optimal  respect to at  to  the  the  the  problem  This assumes that catch size of  in the  current  level. of  fish  This is  the  fleet.  next  year,  current season  period is  not  tThis does not propose to offer the final word on the subject, since current-day investment decisions may also depend upon the vessel-owner's expectations about future regulations. They do not enter into the analysis done in this thesis.  Modeling favourable,  the  market  vessels and  The  for  production  output, (x  y  x ,  1 (  2  eg.,  The They  x )  of  = all  this  for  the the  F(>c,  of  express  (4.3)  that  The and  relationship  F(y,x,z) and T are  T  =  production are  given  {  (y,  option  x  vector  is  by  dual  ;  the  : y  set,  defined given  is  Fishing Firm /  out.  The  the  maximum  as  that  (z  x,  z)  defines  it  z )  2  3  the  presence  49  of  a production  z); z <  assumed  to  of  shows set,  amount  amounts the  vector  (1974)  possibilities  of  has  z ,  1 y  Diewert  production  T,  selling  =  As  F(x,  Regulated  z  w=(y,  <  the  a  possibility.t  is  representations  z)  possibilities  and  output.  of  this  produce  inputs  the  for  fisherman  can  variable  Behaviour of  the  the  firm  z).t  inputs  has  licenses allows  function  ,  3  y  seven)  Thus,  vessel-owner  the  T,  ~x  fixed  (with  of =  inputs,  dimension  another defined  way by  to  (4.3).  technology.  0 } 3  satisfy  four  regularity  conditions.  in (4.4).  (4.4) (T1)  T  is a closed,  non-empty  (T2)  T  is a convex  set,  (T3)  if w'  e T  (T4)  if  x, z)  (y,  from  The  first  condition  is  a  and w"  ^  e T, then  w', the  subset of  then  w"  the  4 +3-dimensional  space,  e T,  components  of  (y,  x)  are  bounded  above.  mathematical  regularity  condition.  It  simply  says that  tThere appears to be such a market for the British Columbia salmon fishery. $ M u c h of the material for this discussion comes from Diewert (1974).  output  Modeling can to  be  produced  produce  have the  a  positive  Finally,  the  of variable  of  the  constraints  fourth  w;  amount  z)  p  The  than  zero.  Output,  constrained  of  also  positive  a  requires  the  given  Fishing Firm /  amount  whereas  called  for  of  the  condition  of  fixed  way.  It's  inputs  technology three  monotonicity  set  the  50  to  implies  requirement.  inputs,  the  set  above.  restated  seasonal  and  fixed not  y,  2  (max[p-(F(x;z))  where  z,<  the  known  is  z ,  of  and three z , 3  of  output  in  a  formal  profit  are  is  a  that  it  can  restricted  earn  subject  profit to  the  generate  comparative  ~ ^  2  and  z  certain  certain  inputs, x , ,  problem From  and  However,  statics  wx] 2a  <  ~  output  input x , 2  price  and  prices, w,  x , 3  strictly  greater  is also strictly  greater  are variable,  is  whereas,  the  three  fixed.  supply  simple  -  z<  u  and  multipliers.  factors.  exercise  z  known  maximization  method  implicit  =  vector  inputs, z , ,  Lagrange  prices  is  Regulated  second  transformation,  and  be  some  The  suggests that,  can  the  —• —' (p,  equation  obtain  requires  output.  is b o u n d e d from  maximum  zero.  The  it  of  disposal  problem  than  other  of  Behaviour of  it faces.  7T  this  but  rates  condition  firm's  R (4.5)  free  quantities  fishing  equals  In  amount  non-increasing marginal possibility  The  in some way,  the  one.  In  derived the  input if the turn,  results, eg.,  from  first  (4.5)  order  demand  functions  how  implicit  does the  be  conditions  production function these  may  that  it  is  equations for  by  possible  depend  is very  demand  solved  upon  complicated  may an  be input  used  the to the the to  change  Modeling when on  the level the  of a restricted  production  comparative empirical  statics  estimates  factor  function, results  the Behaviour of the Regulated  F(x;  changes. z),  or  are ambiguous  knowledge  in  sign.  of the production function  2. Relationship Between the Primal  However,  z), one may appeal  restricted  profit  function  function  of the output  In this  equation,  theory  (Samuelson  price, three  R —» —* 7T (p, w; z ) =  (4.6)  w  to duality  max  {  for  p>0,  T is the production  p«y -  w x; T  w>>0 , 3  possibilities  The  function  in (4.6) is dual to the underlying  the  production  outlined  in McFadden  set defined  (1970),  parameters,  is necessary  many  to  many questions of  production  1968).  This  prices, and three fixed  the transpose of the vector of input  possibilities  it  restrictions  obtain  interest.  Lau (1972)  in  (v,x,z)  z<0  is  an  explicit  eT}  3  set defined  in equation  (4.3) and  prices, w.  if  it  and Diewert  fulfills (1973,  a  F(x ; z), and to set  1974).  of They  properties are the  following. (4.7) R (7r1)  7T  —' — (p, w; z) is a non-negative  w > > R (7T2)  it  (7r3)  it  0 ,  function  and any z,  3  —r  —r  (p, w; z) is non-decreasing in p, R  a  factors, as in (4.6).  production function,  (4.3),  function for  1973, 1974, 1982) and define  Gorman  indicates  T  it's  of a direct  (Diewert  1953-54,  input  x,y  Thus,  known  and the Dual  Instead of specifying and solving (4.5) by means F(x;  without of  to answer  Fishing Firm / 51  —- —• (p, w; z) is non-increasing in w,  for p >  0,  (7T4)  These  The  prices  and  higher  input  that  R  (ir6)  IT  imply  and  that  all  is  —  —  (p,  w;  not  is  a fixed  is convex  z)  to  a  price  profits.  small profit  p and  w,  and  w.  corresponds  to  price  the  prices,  p  a  maximization.  with  fixed  opposite  input  is true  Condition  condition  given  in  profit  factors.  Finally,  each  of  output  in  fixed  first  notion  fixed  changes for  every  whereas  and  one  w,  The  higher  increase,  double  maximum  p and  the  Fishing Firm / 52  degree  in z for  with  that  Regulated of  assumptions.  output  for  the  in  is concave  imply  prices will  a  z)  profit  of  is homogeneous  inconsistent  well-behaved  there  Behaviour  following  causes  with  of  _  conditions  factors  prices  z)  _  w;  R  is  w;  (p,  the  that  third  fixed  function  asserts  —  — (p,  7T  a doubling  profit  R 7r  condition  second  the  (w5)  conditions  regularity  Modeling  four  for says  five  says that  the  whereas  condition  six  vector  of  prices  and  fixed  satisfying  the  conditions  set,  satisfying  inputs.  Diewert in  (1973,  (4.7),  there  conditions Diewert means  in  that  the  shadow  The  F  and  that  a  that  given  unique  Alternatively,  then  n  it  T may  are  F(x;  are  used  to  interest,  as  well  prices of  fixed  factors  may  be  technologies  the  dual  using  satisfies  a  set  describe as  the  of  from  are  several.  profit  of  6  conditions, of  each  statics  and  4  given  in  and  obtain  results,  the  other.  technology,  technology  comparative  derived  restricted  T,  representations  representations  approach  the  7T  possibility  equivalent  of  of  z)  equivalent  be  function  production if  IT  and  any  elasticities  advantages  complex  proves  exists  (4.4).  (1974),  importantly, of  1974)  This more  estimates  in  addition,  n .  First,  function,  it than  is by  easier using  to the  specify direct  Modeling production prices  function.  which  results are  C.  Second,  reduces  readily  the  the  Behaviour of  dual  econometric  restricted  the  profit  computation  Regulated function  costs.  Fishing Firm /  is  Finally,  usually  53  linear  comparative  in  statics  generated.  CHARACTERIZING  TECHNOLOGY  USING  DUALITY  1. Supply and Demand Functions Comparative in  (4.6).  the  static  This  restricted  with  respect  Hotelling's  results are  begins  by  profit  function  to  the  Lemma  defining  (1932) 1968).  (4.8)  w*;  Equation  (4.8)  and fixed  (4.9)  In  given that  (p*,  R  equation prices,  the  downward. respect  defines  inputs  97T  this  (p*,  R  to  p*,  supply  z*)/9p  differentiating  output the  the  =  prices  at  following  y(p*,  restricted  input  in  (4.7)  p*>0,  output  w*;  profit-maximizing  the  supply and  conditions  quantity  yields  the  the  by  satisfies  variable  functions (Gorman  37T  obtained  profit  demand and  is  w*>>0 , and  equations.  If  differentiable then  3  supply  function  using  input  demand  p*,  w*  i is obtained  for  z*)  level  of  output  (y)  given  prices  i=  1,  3  z*.  w*;  x^,  z*)/9w.  the  w*,  Furthermore,  x.(p*,  profit-maximizing  and  function  =  fixed slopes  the  all prices is symmetric  amount  inputs,  z*.  upward  matrix  of  w*;  The  and  z*)  of  variable  convexity  the  second-order  and positive  for  input partial  semidefinite.  2,  input property  demand  in  (4.7)  insures  equations  derivatives  of  n  slope with  Modeling In  chapter  estimated input  5  jointly  demand  depend and  form  to  a empirical  a  into  optimal in  of  the  levels  the  as  levels.  6  degree  chosen  for  from  a  mean  supply  it  and  and  is  input  estimates  and  of  values  equations,  Regulated  the  (4.9).  of  upon for  to  and  to  of  input  prices  factors  predictions  predicted fishery  and  functions  given  fixed  obtain  amount  rent dissipation attributable  These  54 are  supply  exogeneously  demands. These the  equations  output  model.  prices  possible  Fishing Firm / The  optimal  profit-maximizing  If  actual  the  (4.8)  description  parameters  obtain  of  Behaviour of  estimated  output to  is  derived  estimated  of  chapter  determine  obtain  set  factor  substituted  used  functional  functions,  upon  fixed  the  a  the  are  about  values  rent  are  and  to  substitution.  2. Elasticities of Interest Given  the  profit  functions harvest  defined  to  a  to  quantities. elasticity  The of  They  respect  to  cross-price  is  and  and  in  example, an  is  and are  of  These  may  all  be  elasticities  of  it  possible  is  does  exogenous  factor,  in  two  called  with  used  to  upon inputs  are  demand  sets  the  elasticities  fixed  elasticities  and  how  predicated  levels of  (4.6)  (4.9)  second is defined  given  set  in  defined  contained  intensity.  production,  first  For  prices  fishery.  The  (4.8)  change  information  respect  in  in  technology.  respond This  function  own-  output to  the  supply and  examine demand  either  a  or  The  fixed  indicate  the  degree  examine  the  issue  actual  or  cross-price the  conditions  the  of  in  a a  first  the  of  the input  restricted  input.  is  defined  and  of  variable  of  dissipation  fishery,  with  is called  substitution rent  demand  variable  elasticity  factors of  input  structure  for  price  elasticities.  respect to  that  the  inputs in  the  is,  with  own-  and  and prices.  defined or  of  the  in  supply  equation with  (4.10),  respect  to  both  for  changes  in  variable  Modeling quantity  prices. They  in  price  the  demanded. quantities of  of  fuel  may  The  sign  of  should  output  elasticities  (4.10)  to  explains  positive,  ik  a  (Varian  x%  1978).  change  cross-price  or complements  indicating  by some  that  percentage.  The with  x^)with =  quantity.  if negative,  elasticity  (  quantity  (either  the  quantity  signifies  1%  a 1% change of  whether  gear  input  the  input  The own-price  increase  in  O n the other  supply,  the  hand,  elasticity  output the  price  own-price  If  £. . =  y,  respect to price, p^  9x./3 l  p, )• ( p , /x.) k k l  for  i,k  =  1,..,4  in the level the  elasticity  of a fixed is  positive,  of intensity  (Diewert  factor  effects  this  indicates  1974).t This  the supply/demand a  complementary  a substitution relationship.  of  variable  quantity  (either  respect to a change in the quantity  •i]  For example,  (negative).  a  Fishing Firm / 55  demand should be negative.  how a 1% change  variable  in  elasticity  (4.11) defines the non-normalized elasticity  relationship;  (4.11)  to  this  increase  demand, e  a  be  of input  or  of  lead  The elasticity of variable  Equation  interpreted  are substitutes (positive)  supply  causes  are easily  the Behaviour of the Regulated  supply  of the fixed  (y)  or  demand  (x.)  factor, z_.  (3x./3 z > (z ,/x.) i for  : : i j = 1,2,3 and  i = 1,..,4  tDiewert (1974) defines the normalized elasticity elasticity divided by the input share of the fixed  of intensity factor.  as the  non-normalized  Modeling  the Behaviour of the Regulated  Fishing Firm / 56  3. Shadow Prices of Restricted Factors The  dual  of  restricted  the shadow  given  prices  They of  of  fixed  the  factor  restricted  variable  profit  is possible  to  increase  =  the  of the fixed  this  manner  the  researcher to predict whether less  factors.  the actual  than  the  of the to  fixed  justify  price  If  o n e can examine  ie.,  space  optimal  quantity  long-run  profit  Christensen  then  R.  >  (Kulatilaka  of  the  It  estimates  the  increase  fixed  factors.  in the  quantity  by  differentiating  substituting  of the fixed  where  m.  actual  value  of the restricted  quantity m.,  in  obtained  factor  factor  is the  prices in  permits  should be  current  market  3  the fisherman  should increase the quantity  used  if the sign is reversed. This indicates that return  o n the amount  of  the fixed  factor  the price  space,  amount.  the  question  1985).  restricted  for the fishing firm  1979).  by  D  a sufficient  the current  Alternatively, quantity  of  are obtained  for a unit  the optimal  actual.  is not making  maintaining  for a marginal  in (4.12)  factor. The converse is true  fisherman  levels  A comparison of the shadow  market  of the "jth" fixed factor,  that  obtain  z)/ 3z_.  3 price  given  measures  expression  quantities  or  These  w;  R  and  with  can be used to  by each of the restricted factors, z . .  a7T (p,  evaluate  and for  in profit  1974).  function  in (4.6)  factors. These shadow prices are defined for  quantities  (Diewert  Rj  greater  defined  prices for the restricted  (4.12)  It  function  describe the marginal  the  the  profit  In  this  factor  by using the dual instance, as  that  for given current  is possible that  the  levels  of  the  which rental  to  researcher maximizes market  the fixed  solves for the the  total  or  prices (Brown and  factors  at  any given  Modeling the time a  are  not  vessel-owner  and  more  combined for  the  obtain the  those  fishing  restricted  other  Having  days,  however,  nature  he  and the  optimal  and  the  various  the  Regulated  available  biomass,  not  to  is  able In  level of  Fishing Firm /  57  unconstrained situation. Presumably,  chapter  The framework  the  functions Lau  next of  1973)  the  the  This is the  is  one  a  do  greater so  6 this  in that  net  tonnage,  because  of  the  hypothesis is tested  chapter  factor while  is  to  wide;  quadratic  facilitates  subject  elasticities  of  the  that  choose  restricted  generalized  normalized This  and  step  available  parameters.  costs.  functions  estimation  1978), and the in  the  shows how  holding the  to  levels of  factors constant.  relationship,  Jorgenson  an  regulator.  the  profit  computing  larger  expression for  permits  linear  a  tonnage.  restricted  all  have  chosen in  net  defined  (Cowing  to  be  factor,  fixed  production which  wishes  actions of  an  that would  Behaviour of  it  profit  a  describe particular  function  includes  the  Leontief  (Diewert  (Diewert  and  the next  estimation chapter.  in  the  underlying  functional (4.6).  translog 1973),  The  form set  (Christensen, the  quadratic  Ostensoe 1987). They procedure  of  and  are  reduces  V. ECONOMETRIC TECHNIQUE AND RESULTS This  chapter  represent  begins  the  desirable  in  the  and  The  is  parameters. in  detail.  the  analyzed.  and  the  as  given  returns  in  The  vessel; by  to  separate  the  scale  or  restricted  previous  function  to  these analysis  size  profit  to  the  Chapter brief  be  the  discussion  by  functions are  of  is  harvest  of  between and  the  they  are  are  data  is  two  types.  in  some  nonlinear  are described is  elasticities  presented  of  intensity  restrictions o n specified pairs  of  measures  four  to  the  technology  the  chosen  why  techniques which  demand; of  and  There  second  effectiveness of  each  4  form  description  about  relationships  elasticities  functional  estimated.  the  of  results for the of  in  estimation  structure a  the  variable of  vessel  the  types  inputs, type  for  of  which  defined.  MODEL  chapter  represent  outlines the  fish  pairs  of  elasticities  functional  form  to  represent  1974).t  the  of  a  whereas  different  exhibited  individual  (Diewert  Next,  equations  includes  cross-price  A. ECONOMETRIC The  section  defined  thesis.  the  require  section  an  properties  parameters,  they  final  the  function this  by  all  implications of  per  of  is followed  As such, In  profit  context  linear  and  inputs  discussing  restricted  presented first  by  the  conditions  necessary  for  a  harvesting technology. Since it between the  inputs,  restricted  For this thesis the  it  is  profit  normalized,  quadratic,  restricted  is desirable to  necessary  function  dual  to  defined restricted  choose in  profit  estimate a  flexible  equation  profit  (4.6)  function is  tA functional form is said to be flexible if it can provide a second-order approximation to an arbitrary twice differentiate function (Diewert 1974). Flexibility implies that the function is capable of defining separate elasticities of substitution between pairs of inputs. Furthermore, it does not restrict these elasticities to adopt prespecified values.  58  Econometric Technique and Results / 59 adopted  (Diewert  representation  and  Ostensoe  of the true restricted  1987)t profit  and  is  function  assumed  (White  to  be  an  exact  1980).+  1. The Normalized, Quadratic, Restricted Profit Function Arguments outputs  and  quadratic, output the  in  the  restricted  inputs,  function  and quantities,  restricted  price  profit  profit  of salmon)  function  of is given  and the first  fixed  are the in  prices, (M)  *(F,z>  =  M-i  the  factors.  (5.1).  (N)  The  The  variable  normalized,  first  (the stock of fish)  °i i?/i  price  (the  are chosen as  p  Ostensoe  (1987)  i = 1,...,N  flexibility.  a . ,  and Diewert  parameters  Diewert  is the fixed  the  factor  (1986)  a . . .  B. ,  and Wales  suggests an a priori  vector for the first  p  i  p  k  b  M  b ., ,  (1987)  may be arbitrarily  (  1  N  are  a  "i i?=i 5=i 3 <  + s ,s " parameters  i-i ik  z  * hi  +  B^,  of  numeraires.  (5.1,  The  fixed  equation  factor  P^,  c.  c  note  preset  z  /  z j  p  '  i>/ z  .P.z.  . . , that  by the  however, the  a.. ,  researcher  choice for the  observation.  >  Likewise, the  Diewert  j = 1,...,M and without  is 1/z', B.  and  losing  where  z_j  is set equal  to  tThe authors suggest the form should be called the Generalized Fuss restricted profit function because it generalizes a functional form given by Fuss (1977). tThe chosen flexible functional form may be defined either as an exact representation of the true function, or as an approximation. This distinction is important whenever tests of the structure of technology are undertaken, for example, separability or aggregation tests. The problem with assuming that the functional form is an approximation is that one can no longer interpret the estimation error as simply a deviation from the profit-maximizing value of profit. Instead, the error may include a component attributable to approximation error.  Econometric 1/p'.  In  This convention is adopted  order  for  technology, These in  fixed  output  satisfy  throughout a  fixed  the  signs  imposed  of  price  an  form  required  is  demand  First,  it  upon  the  is  homogeneity  arbitrary  predicted  the  this  is  parameters.  columns for  is tested  There  another  all  in  demands  k=1,...,N,  noted  a as  is  and  test  The  requirement  that  are  the  the  taken  characteristic  characteristics. monotonicity  prices for  each  equation  (5.1)  in  function  is  a  first to  be  row  that  the  obtained  from  the  cannot  be  be  and  vectors  linear  column of  zeroes.  estimating  a well-behaved  of  for  by checking  monotonicity  of  choice  numeraire  is verified  supply  Thus,  x  hypothesis. The of  linearly  price, P .  cross-price terms  and subsequently imposed upon the  important  in  first  choice  and  Because  60  production  symmetric  as symmetric with components equal  k = 1,...,N. matrix  the  by the  output  statistical  A  that  condition  a  certain  function  maintained  not  and  the  profit  monotonicity  by defining matrix A = [ a . , ] i = 1,...,N  is  have  convexity  normalized  decision,  the  input  is  underlying  cross-price terms,  functions, and restricted  the  to  of  Results /  described in this thesis.  describe  prices, symmetry  Acceptance of  the  condition  is  to  requirements.  linear  procedure;  a ^  function  quadratic,  research  parameters,  through  these  factors.t  is obtained  between  input  empirical work  in prices because all prices are the  estimation  in  normalized,  of  numeraire  the  functional  supply and  all  profit  homogeneity  The  homogenous  of  chosen  linear  factor.  may  restricted  the  are  the  a  for the  Technique and  to  the  relationships A,  ee.,  The  a„ .  symmetry  equations.  restricted  profit  funtion  tThe choice of numeraires may affect the results obtained. However, there have been no M o n t e Carlo studies done yet to evaluate the robustness of the parameter estimates and elasticities when different numeraires are chosen. Preliminary work that I have done reveals that the choice of price numeraire makes little difference either to the parameter estimates or to the elasticities derived from these estimates.  Econometric should  exhibit,  locally)  with  matrix of  is  the  ie., the to  matrix  without  loss  has  advantage  an  locally  of  of  flexible  function  the  A  matrix  E  matrix  is  quadratic,  satisfy  over  In  other to  impose  parameters  (Diewert  1976) In  product  lower  triangular  associated  with  profit  to  be  destroys  global  on  becomes  and  is  in  first  that  the  some  of  column.  in  the  a  less  individual quadratic (1973).  A= EE .  The  However,  the  T  normalized, the  be  Bramble ie.,  form  only  to  normalized  Schmidt,  its  can  identify  T  in  functional  leads  its transpose, E ,  zeroes  nonlinear  the  A  imposed  reduction  to  (and  the  be  latter  This  61  components  may  a  ability  convexity  convexity  it  to  estimated. the  E and  with  estimated  The  lead  globally  whenever  quadratic  translog.  convexity  impose  matrix  the  requirement,  the  may  a matrix  function  if  as described in Wiley,  of  imposing  function  that  profit  Results /  is accepted  normalized,  as  global  and  order  the  such  prices  However,  convexity  respect,  forms,  by the  a  this  this  in  restricted  semidefinite.  is reparameterized  is replaced  restricted  not  substitution.  It  cost  do  independent  of  prices. Convexity  positive  attempts  number  elasticities  be  flexibility.  convex;  in  normalized,  found A  convexity  Technique and  quadratic,  parameters  to  be  estimated.  Since to  convexity reject  is an  it.  Convexity  profit-maximization the  may  the  wrong  input  to  profit-maximizing  and  not  be  that  occur. output  in If  so  It  may as  to  non-satisfaction  condition, it prices the  be  ie.,  of  one  of  function  is  input  they  possible  increase  is worthwhile  is  profit  supply and  well-behaved,  slopes.  decisions,  suggests  important  his  convexity  demand  may for  have  the  profit. in  to  the not  prices  accepted convex,  functions  are  discontinuities  producer On  discuss what  to  alter  it  means  tenets  for  this  means  that  not  well-defined  or  kinks his  or  have  output  and  the  other  hand,  Wales  may  simply  reflect  the  (1977)  fact  that  Econometric Technique and the  functional  sample  form  range  chosen  used.  He  be  obtained  whenever  not  be  close to  the  equations  dissipation  in  convexity  is  the  not  continues  still  demand  does  the  provide  by  remarking  profit  true values.  Given that  in  this  fisher)',  is  desirable  imposed  whenever  is  used  they  linear  for  good  the  data  elasticity  convex,  estimated  are  that  fit  not  the  chapter  the  good that  function  generated it  a  however,  output  indicate  the may  they  may  supply and  well-behaved.  estimates  over  estimates  subsequently to  be  Results / 62  input  calculate  For, this that  it  rent  reason is  not  accepted.*  In  addition  profit than  to  its  function  has  the  has  for  the  the  parameters  two  options.  equations; of  variable  the  market  costlessly model problem  to  discussed the  impose  other  are  estimated  needed  The  first  to is  to in  that  their  In  Option  other  optimal  Chapter  the  4,  second option  so  a  it  is  useful  desirable  to  words,  the  levels. This  is  option  variable  profit  not  are  estimating  the  likely  not  obtain  valid  the  in  example, because the  fixed  researcher input  share  along with  a set  equilibrium fixed  not  form  parameter  possible since it  levels of most  and  restricted  functional  then  function,  factors  is  for  intensity,  is often  fixed  quadratic,  more  of  of  restricted  in  a  translog form,  for  is that,  it  set  one  this  normalized,  elasticities  estimate  markets  if  in the  calculate to  the  make  First,  terms  estimate  prices.  that  translog.  share equations. assume  convexity,  features  cross-fixed factor  rental  adjusted  with  to  second is to  input  researcher  current  two  commonly  estimates these  ability  factors  the  for  restricted  requires at may  case for  this  thesis.  profit  their be the The  function,  tThere are other reasons why the estimated profit function may not accept convexity in prices. Insufficient price variation and too few observations may lead to poor parameter estimates. These estimates may then lead to the rejection of convexity in prices. Furthermore, aggregating over a number of items, either inputs or outputs, may lead to the rejection of price convexity.  Econometric Technique and the  researcher  there  may  not  parameters problems occurs down may  have  has  been  profit  be  and  with  to  profitable is  equations, This  bias.t  In  The  are take  As the  entire for  if  along  unknown  the  that  advantage  are  available  expressed for  advantage  the of  equation  minimum  number  the  all  the  form  log  profits  parameters  by  in  do  not  the  adopted  demand of  leads  two  season and  and  On  function  using the  number  the  sample  the  output  a negative  to  shut  vessel-owner  fact,  estimates.  profit  these  of  encountered. This  is  input  the  restricted  ignore  be  addition,  number  because the  parameter  negative  quadratic,  of  of as  the  of  not  Columbia  fact.  (5.1)  normalized  levels,  output rent  normalized,  parameters  Since  commercial  analysis of  the  quadratic  shares.  Furthermore,  in levels facilitate the  in  in  to  whether,  the  replace  large  a season and is  In  63  other  selectivity  the  researcher  complete  set  of  supply equations.  British this  bias  of  the  may  functional  some  exhibit  normalized,  in  determining  packages  of  difficulty  profits  translog  problems.  decides  industries. This  with  econometric  observations  negative  the  because  researcher  a further  other  If  estimated most  in  multicollinearity  freedom  season before  him.  and output  second  defined  the  unbiased estimates  demand  expressed  Even  firms  causes an  using  obtain  quantities  of  second option,  fish the  dropping  input  the  data-based  degrees  estimated.  competitive  hand,  may  with  vessel-owners experience  do  zero.  faced  sufficient  use  function  supply  be  be  to  when as  may  Results /  is  that  price  salmon and  and fishery  input  input quantity it  necessary  for  restricted it  to  is  demand  dissipation in chapter  quadratic,  and  information desirable  to  predictions  6.  profit be  output  function  flexible  t O n e might expect the finding of negative profits to be fairly c o m m o n , there is n o discussion of the associated problems in the literature.  has  when  however,  Econometric representing Ostensoe  a  constant  1987).  returns  The  to  number  ((N(N-1)/2) + (M(M-1)/2) + NM).  Thus,  and  has components  given  row  and column  also vectors  non-constant  are  returns  three  more  sets of  three  terms  are  (5  -  adds M + N  returns =b  to  scale  =... = b  2  compared  of  constant  Since  a  version restricted  a  the  to  the  of  c  1  the  value  degree  B=[b^ ], 1  b^, If,  to  fixed  factors  like  matrix  j = 1,...,M  however, of  those  in  it  and  (Diewert this  A,  the  restricted  already  in  to  Its  allow  profit  equation  is  symmetric  1 = 1,...,M.  is desirable  and  case  is  64  first for  function,  (5.1). These  * S.^oOiV/z, + J^C.P.  +  / Z l  to  be  estimated.  is set  equal  factors  for  is  to  test  acceptance  returns  They are zero.  easily  This  Alternatively, of  M  parameters  context  added  =... = 0^ = 0.  scale.  function,  zeroes.  in  Results /  (5.2).t  b,  fixed  critical  returns of  the  and  to  test of  in  =0  z  that  matrix  be  parameters  is noted  the  within  must  b  independent  parameters  in equation  new  It  be  I  terms  of  the  scale  p  i = 1,...N.  0  by  ?=>i i ? = i j j  2)  This  b  to  given  scale technology  Technique and  a to  (5.1)  equations,  consisting  The  tested.  or  an  log-likelihood  and  is  rejection  is  of  j = 2,...,M,  hypothesis  It  generates  scale  equations  bj,  is  of  single  of  joint  F-statistic  of  the  null  ratio  test  may  interest,  (5.2),  a  b  taken  as  the the  ,  0  and  constant test  that  which  may  hypothesis be  more  used. general  description  of  profit.  estimate  a  system  variable  input  function  (equations  of  demands. (5.1)  These and  equations  (5.2))  by  tThese terms are obtained by adding function and setting it equal to a Ostensoe 1987).  are  applying  a  obtained  output from  Hotelling's  an additional constant for  fixed each  supply  and  three  the  restricted  profit  Lemma  (Hotelling  1932,  factor, eg., observation  Z , to the (Bfewert and  Econometric Technique and Gorman the  1968). This states that the  output  profit  with  equations in  price  the  is  respect derived  second  section with  the to  output  an  from  first  section  price  this  of  the  an  restricted The  input  quadratic,  chapter. data  of  equation. is  normalized,  of  a discussion  supply  input  the  derivative  65  with respect  to  first  derivative  of  demand  equation.  The  restricted  Before  profit  Results /  profit  discussing  restricted  function  them  I  specific  are  given  conclude  this  used in the research.  2. Data The  data  demand of  all  requirements behaviour  variable  restricted so  micro  level  to  the  as  are  a  and  output,  Furthermore,  to  permit  a  of  this  associated  information  has  expenditure  model  of  output  necessary components their  sufficient  production study  lack  profit-maximizing  substantial. The  inputs  factors.  units,  of  number  never  been  must of  attempted  price  information  of  data,  although  in  of for  the  and  available  degrees  and  include  quantities, be  supply  general,  for  unit  prices  levels  enough This  fishery,  let  input  the  freedom. this  and  alone  of  micro  type  due  of  largely  for  specific  vessels.  There Oceans Branch  is  no is  the  have  background permitting a  single  source  major  been  most  material. the  expenditure supplements  The  use of  cross-sectional  first  Economists  generous  output  by by  in  Economics  survey  information the  one.  of  data.  There  providing  The  the  access  Statistics are  Coast  two  major  is  and  the output  of  Planning, to  Branch  fishermen  second  revenue  Department  Program,  providing  and  Pacific  vessel.  in  the  survey has  for 1982  and data  been  sets of  Fisheries  Economics and  other  instrumental  data. The first  1982. Sales  and  This Slips  information.  An  in is a  provides file  which  important  Econometric Technique part  of  this  preserves  the  component to  work  is  samples  fish  salmon  seine  salmon.  the  is  entire  new  kind  that of In  sample  has  the  reasons outlined  and fixed  each  inputs,  tLabour  can  net  is treated  as a fixed  the  types  gillnets  the  uses  first  in  nets  size  Finally,  and  There  of  each  now  given  troll  are  only. Vessels that  60  sample  but  The  the  vessels fishing  for  21. is  the  seine  second  smallest  size  herring  has  The  to  the  sample falls  in  are  in the  boats. and  gillnet-troll  observations  catch  The  behind  Its  to  contains  the  lines.  used  troll sample  lines  the  vessels  ie.,  to  many  of  largest  is 80.  to  coast.  is  that  is a  between  this  sample.  excluded  for  1.  data  labourt  tonnage,  attached  66  manner  calculation  observations,  next  a  description  four  are  also  is  vessel.  is salmon  and  in  Results /  follow.  observations  both  a gillnet  in Appendix  inputs,  use  brief  the  of  type  and  cruises along  A  The  Columbia. The  fish  of  hooks  output  variable  number  sources  set.  that  to  number  vessel  baited  vessel a complete  three  least  is  vessel that  case the  the  84,  vessel as it  of  correspond  entrap  1.  results  British  data  data  Appendix  observations, by  two  each  empirical  This  fleet. The  a troll vessel and  each  For  fleet.  these  of  waters of to  of  of  in  They  nets  capture  the  the  use  salmon  of  detail  coastal  gillnet  means  in  estimated.  the  the  number  of  nature  that  largest  side  confidential  are  This  sample  linking  analysis of  in  boats  the  described  facilitate the  Four  is  and  set ,  includes fuel,  the  and  fishing  days,  and  input,  rather  than  This is because most gillnet vessels are the sample used in this thesis 19 out addition to the skipper.  quantity  gear, fish  as  and  well  stock  a variable  as  price the  of  levels  abundance.  one,  for  one  the  of  output three  Output  gillnet  is  fleet.  small and owner-operated. For example, of 80 vessels used one crew member  in in  measured  Since  as a positive number  the  salmon,  framework  it  catch  for  slips  data,  the  which  In  of  opportunity Tsoa  share  of  the  importantly, using  actual  simultaneity  The  unit as  has  for  an  for  province  cost  The  been  i.e.,  total  the  obtained. can  is  set  index.  the  or  done  to  the  to  catch  for  rate.  crew  the  alternative  It  quantity  From  equal  of  a  to  the  1982  Divisia  1.00  is obtained  Quantity  is  the  by  measured  or  sales  index  for  67  landed  a single output  generate  quantity  is  composite category  British  Columbia  on  is  is not  estimated  seine sample quantity  the  necessary other  of first  dividing  in  to  10,000  construct  fisheries  (Roy,  1987a;  Bj0rndal  1984).  in  form  a  the from  an  to  of  This  and the  is  pre-specified  year  and  more  introducing  a  by  potential  inconsistent.  to  (Anderson  an  Schrank,  exogenous variable. Thus,  risk  chosen  of  year  parameters  average  is measured in  is  many  varies  runs  wage  it  1984,  labour  researcher  make  labour  tThis is a c o m m o n practice in studies that adopt because it makes the results easy to interpret. +AII variable input prices are indexed in this way. *For  the  I  aggregate  Squires,  return  may  industrial of  This  price  for  1983,  upon the  bias which  earnings  as negative  be  a vessel,  implicit  wage  remuneration  remuneration  opportunity  the  a  value.  depends  quantities  salmon species into  must  1976).  aggregate  Hannesson  actual  catch  the  numbers.t  five  by  (Diewert  input  output,  index  sale  Results /  salmon catch*  wage,  1982,  the  price  every  by  obtain  cost  single  sample.* The  receipts  to  a  aggregate  price  aggregate  order  because  record  each  of  aggregate  output  in  fishing  and  an  which  observation  pounds  that  is necessary to  aggregate  total  is  and variable  Econometric Technique and  be  1977). for  the  average  Earnings are  five  restricted  important profit  100,000 pounds of salmon.  weekly obtained regional  framework  Econometric Technique and centres.  Since,  specific  region.  obtaining  then  order  to  rate  A  Divisia index  cost  earnings  are  in  the  region. The  the  cost,  but  spent  the  on  defined  weeks The  seasonal  repairs  average  minus weekly  order  is  assumed  maintenance  prior  The  weeks  quantity  68  to  a  difficulty  probability  season.  labour.  the  one  in  assigned  to  of  the  of  being average  earnings  are  generate  the  skipper is assumed to  cost  and  the  as  fished  is  reflect  by  expected  salmon fishing season.  vessel  should  weighted  region-specific and  of  each  wage  is  account for time  the  homeport,  vessel's number  opportunity  of  to  be  to  the  have  the  greater  in  beginning  ,  formula  number  fished  of  from  is determined  is used  to  labour  units  the by  sales  generate comes  the  aggregate  from  the  wage  survey  slips  data.  The  implicit  dividing the  total  expenditure  for  data  aggregate on  labour  both  and  types  the  index  number  of  by the  of  labour  aggregate  index.  prices are  eleven  of  gear  measure.  Fuel  fuel  Gear  from  Esso  expenditures  Canada for  are  divided  gasoline and  by  diesel products sold  the  relevant  fuel  traps,  etc.,  used  price to  in  find  the  input.  input  Unfortunately,  entirely  obtained  centres.  quantity  The  so weekly  each  cost for  weekly  wage  by  the  opportunity  probability  multiplied  indicates  true  unemployment  same  Fuel  The  This  opportunity  of  survey  employment,  employed. annual  the  Results /  consists  data is  exhausted  of  the  limitations taken in  one  to  be year.  nets,  preclude a For  lines,  inclusion  malleable each  of  capital  gear  type  electronic good a  whose  stock  (in  by  each  vessel.  equipment  in  this  services  are  not  quantity  terms)  is  Econometric Technique obtained  by  purchased unit  of  gear  adding  units  gear,  does  the  (over  no  not  existing  the  matter  1982 its  quantity, season)  age,  deteriorate  of  provides  because  the  as  of  a  given  a  1  January type.  constant  service  flow  is  1982,  It  flow  and  is  of  Results I  to  the  assumed  maintained  newly  that  services. That  69  each  is,  the  through  annual  modified  version  repairs.  A  rental  of  the  cost  of  standard  modification nominal  Jorgenson  interest as  plus  The  1%.  The  the  rate  the  one  A  gear  average  on  (over loan  is added  index  is  The  implicit  aggregate  index  gear  by the  aggregate  price.  With  regard  to  Net  tonnage  It  has  been  indexed  so  Fisheries  and  fixed  is taken  from  collected that  the  or  in  year) of  quantity  the  from  taken  in  as  each both  quantity  the  (Schworm  1977).  The  types  boats.  rates  and  on  the  usually  and  by  data  business  Bank  of  It  is  loans  Canada  charged  the  prime  rental  price  data.  preserve  the at  net the  unit  dividing  come  Fisheries and  sample  personnel  The  gear.t  of to  1963).  from  are  a  (Jorgenson  all gear  monthly  obtained  factors,  way  regulate loan  is  using  Department a  measure  for  the  and  is  using  maintenance  16.81%  restricted  to  of  gear  because fishermen  observation  Oceans tries  tPersonal communication Vancouver.  same  constructed  such  first  be  the  of  price and  equipment  of  type  repairs  the  rate  each  services  of  loans for  price  the  capital  cost  percent  percent  for  is assumed to  business  plus one  Divisia  is calculated  includes  calculated  Review.  gear  its  has  from  total  value  of  various sources.  Oceans license records. confidential  a value  tonnage Gulf  the  and  and  of the  Fraser  nature. 1.00.  It  is  Although  vessel Credit  length Union,  Econometric it  seems  more  the  values  ton.  This  of  appropriate the  facilitates  The  survey  also  the  number  of  desired  by  vessel  types.  fishing  days.  be  restricted  The  stock  season.  has  net  licences  are  transition  information  may In  declare  tonnnage usually  between  within  By including  Rather,  the  in  this  expressed  research.  in  the  work  done  number  of  fishing  is  at  a  terms in  This  of  is  because  dollars 5  chapter  70  Results /  per  to  net  that  in  the  of  the  output  proportion to  to  of as  is  area  two  fixed  because closed  also  of  to  has  forces,  variable  by it  externalities is  stock the  Fisheries  the  This  encountered  supplied the  vessel  nature  to  demand  construct  Department calculated  stock*  the  the  all  which  way  the or  over  the  fishing  It  level  fishing  control  the  days.  vessel  is assumed is  less  fishery  open  finds  than  is  its  that  managed.  only  to  maximum  that  certain  number  of  fishing  days  to  fixed  within  a  season.  this  intention  determinant  per  these  the  on  an  addition,  Between  or  days  vessel-owner.  abundance  crowdingt  used  the  fishing  the  regulator  on  fishing  use  and  6.  chapter  The  to  Technique  relative  by of  is not upon  observe for the fish  stock and  each  the the  firm. that  the  variable  Oceans. in  and  catch  come each  each  measure  fishing  from  each of  area  the  impact  is  an  is  is  important its  so  weighted  impact  small  reasonable.  publications stock  of  technology.  examine  vessel  fixity  several  vessel  to  the  firm's  abundance further  of  fishing  assumed  to  stock  assumption  For  also  individual  inputs, The  is  intention  whether  variable  abundance  vessel  Data  of  encountered by  the  in  the is  number  tThis is defined as occuring when too many vessels on a ground may cause damage to equipment and vessels. *This is defined as a reduction in the stock of fish that causes per unit harvesting costs to rise and is typically a long-run concern.  Econometric Technique and of  weeks  the  abundance,  vessel  so it  section  quadratic, The  nonlinear  that of  area.  the  This  five  is  a  single  measure  of  71  salmon  species.  TECHNIQUE  has  two  restricted  linear  in  is an aggregate  B. ECONOMETRIC This  fished  Results /  case,  parts  profit  which  case, which  which  correspond  function does  with  not  to  and  impose  imposes convexity,  the  estimation  of  the  without  convexity  in  prices  convexity,  is  discussed  normalized,  first.  imposed. Then  the  is presented.  1. Linear Case The  estimating  profit  equations  function  equation variable three  (5.2) input  fixed  single  with to  Output  is  labour  to  be  the  stock  vessel,  Z ,  and  numeraire  for  the  (5.2)  of the  price  output  convenience this  as the  they  condition  fish  3  and  the  catch and  by  by  of  and  input  demands  is made.  are set equal to zero  In  as  symmetry  addition,  as previously  Z .  certain  3  The  the  output  numeraire  the  inputs,  and  variable  is  good. (5.3)  in  prices  imposed,  taken of  adopted  The and  in  the as  equations (5.4).  although  appear  the  inputs  are  tonnage  price  in  equations.  factors  net  in  discussed.  to  three  given  that  respect  demand  are  parameters  terms  correspond to  fixed  the  restricted  the  variable  that  . The  Z ^,  The  with  input  X,  vessel,  stock  with  fish  variable  t t  days,  adding  three  services, X . a  by  equations  vessel,  the  expressed  output,  three per  quadratic,  differentiating  one  gear  fishing  normalized, formed  estimating  encountered of  the  scale,  the  four  and  X ,  number  supply are  are  to  (5.1),  For  salmon  fuel,  2  the  prices.  equation  from  returns  equation  case there  services, X ,  2  in  output  supply  are  of  those  factors  defined  obtained  non-constant  and  output  are  a  (5.1)  For test and  Econometric  (5.3,  i,  -i  =  «'  +  +  "  "  4 )  X  i  |_. a  5-*2 !-2 j l b  (  j l  Z  Z  0, J ! b . Z . / Z , J  ( 5  a.z.  .»  ?  ?= 1  =  3  J  Z  ^  Z  54  « i  +  +  £  0 X  /  Z  (  PjP  +  5-i  '  )/Pf  k  ,j j  C  Z  Jbofl./z,  +  c,  J  £4  j  +  )  u  Technique and Results / 72  ^ k ^ / ^  U  b  j i  (  z  3b.Z./Z,  ] — Z  J  j  z  +  i  )  /  ^  z  ibo/3.  J  5=i ij j c  +  /Z,  z  +  c.  1  1  for  There  are  restrictions three  for  types  requires  28  of  independent  parameters  in  (5.3)  and  cross-price  symmetry  and  cross-equation  parameter  restrictions  are  given  parameters  describes  parameters  restrictions  in (5.3)  to  equal  on parameters  in all four  equations  in  (5.5),  (5.4)  equality (5.6),  corresponding parameters  across the equations  once are  the  necessary  imposed. The  and (5.7). in (5.4).  in (5.4). Type  i = 2,3,4  The first  The second  three  restricts  to be equal.  (5.5)  a..  : X,  a.,  : - X . l  =  X,  b  ik  a.. : - X .  =  1  ik  for i = 2,3,4 and k = 2,3,4  l  (5.6)  ik  'o  =  a.. : - X . ik  0  : ~ X  k  i  for i = 2,3,4  for i = 2,3,4  and k = 2,3,4  for all  i*k  Econometric Technique and  Results /  73  (5.7)  b.  X  b .. : - X .  =  J  J  b. jl  Prior  to  error  structure  estimation  distributed  for  zero  an  from  the  and  the  procedure  is the in  (5.3)  (5.4)  are  restrictions imposed.  For  gillnet-troll,  seine,  above,  however,  of  gillnet  the  other that  than  the  labour  is  estimated fixed  with  factors  and  the  system of  sample.  For this  skipper. The a  fixed  one (stock  input  variable of  fish,  troll  are  not  to  Errors  an  exact  equations for  in  as  the  rest for  of  this  output, net  the  of  80  vessels are type  two  tonnage,  of  variable fishing  terms  be  error  the  unrelated  of  the  as  deviations  error  with  structure  Thus,  estimation  the  appropriate  estimated  vessels report  true  regressions. The  account for  man  across  observations. Since  terms  are  The  normally  fashion, the  system  one  are  correlated  assumed  linear  to  vessel.  equation.  representation  equations  equations is modified out  a  1 = 2,3  each  across  seemingly  estimated  19  a  to  may  the  Given  and  error  correlated  1980).  samples  fleet  1 = 2,3  appended  interpret  technique  across-equation  the  the  '  i = 2,3,4, j = 2,3  variance.  be  (White  and  is assumed that  are  to  into  Zellner  and  It  possible  values  enter  iterative  they  taken is  for  positive  but  is it  parameters  equations  and  i = 2,3,4  terms  following.  means  profit-maximizing  that  four  is the  function,  -X.  disturbance  quadratic  profit  b. jl  observation,  normalized,  restricted  =  additive  adopted  with  equations the  X  for  1  the  one  as  shown  peculiarities  crew  member  operations.  It  the  sample  gillnet  inputs  (fuel  and  days,  and  crew  gear) size,  appears  and  is  four  including  Econometric Technique and Results / 74 Table  5.1:--Eigenvalues  Sample  from  linear  estimation:  four  vessel types  Eigenvalues  9.21E-02  Seine  -1.12E-01  -7.33E-01  Gillnet -non-crs -crs  6.06E-02 9.37E-02  -5.99E-04 -7.82E-04  Troll  1.31E-01  4.36E-01  6.83E-04  Gillnet-Troll  7.17E-03  9.64E-02  -5.16E-02  Econometric  Technique and  Results /  75  skipper).  All  samples  are  Convergence for  all but  of  equal  returns  to  re-estimated  scale  is  matrix  is positive  more  of  locally  and  the  in Table  Only  one  to  eigenvalues  sample, in  other  The  that  prices. three  involves  using the  demand  and  of  form  any  requires  60  iterations.  A  of  non-constant discussed  only  the  in  to  scale  used  if  and  is  for  the  row  A  are  global  then  for  the  in  matrix  in are  A  they  of  estimated in  obtain  the  c o m p o s e d of  eigenvalues are,  calculated  is  convexity  are  is  by  constant  the  of  then  is accepted. prices  the  sample  used to  the  If  prices  convexity A  are  of  this  acceptance  non-negative.  convexity  negative,  point  this  verify  performed  hypothesis  At  case.  iterations  to  is  so  check  17  test  scale  column of  to  scale  to  sample,  matrix  and  is sufficient  they  eigenvalues  of  first  it  gillnet  check  to  The  imposed.  to  elements  Thus,  see  the  9  statistical  returns  earlier.  from  to  If  the  A  one  or  rejected and  the  are  both shown  5.1.  convexity the  after  Because the  semidefinite  globally.  obtained  are  is singular.  matrix  matrix  of  returns  is  returns  matrix  non-constant  estimates  accepted  matrix.  the  parameters  estimates  the  (N-1)  the  A  for  assumption  constant  the  of  the by  this zero  Parameter  zeroes,  sample; it  to  of  eigenvalues  (N-1)  of  estimated  parameter  seine  with  parameters prices.  the  the  appropriateness setting  first  No  further  samples  are  estimation  supply  troll  for  the  prevents  nonlinear the  vessel, troll  with  technique  equations  nonlinearity  the  re-estimated  reparameterization  output of  corresponding to  sample  global  discussed in  Zellner  a  accepts  imposed. the  The  unrelated  local)  However,  that makes  parameters.  seemingly  (and  is required.  convexity  earlier  few  global  This input  presence  regressions  Econometric Technique and Table  5.2:--Eigenvalues  Sample  from  nonlinear  estimation:  three  Results /  vessel types  Eigenvalues  Seine  1.98E-01  4.09E-04  Gillnet -non-crs -crs  6.50E-02 9.50E-02  4.45E-05 5.48E-05  Gillnet-Troll -non-crs -crs  1.31E-02 2.70E-02  1.05E-01 1.36E-01  1.97E-04  6.43E-06 1.87E-05  76  Econometric Technique and technique  from  being  used.  Instead  the  new  equations  Results /  require  nonlinear  do  accept  77  estimation  techniques.  A  discussion  found returns  in  the  Appendix  to  method  of  scale,  of  3,  results  shown  technology nonlinear  the  estimation all  the  parameter  the  the  elasticities these  tests  in  for  with  for  relevant  uses  results  along  and  presentation, are  linear  this  analyses of  samples  are  for  tests In  is  performed  three  symmetry  next  detail.  nonlinear  discussion for  other  the  troll  nonlinear  Following  system  seine,  and  the  sample  and  gillnet,  Nonlinear Case  The  (5.8)  new  nonlinear  X  equations  -i(  I  are  a  given  +  through  Z./PJ) * ( e ? P i  +2e e«P P« 1  in (5.8)  2  +  (ei+ 3  5  2  (5.11).  e i  e P P 2  2  3  e|)Pi  2(e e„ + e e ) P P « 2  +  3  +  (eg + e| +  e|) P j )  + +  (5.9)  < £ " "jZj  + +  /Pi)*(e^P  2  +  e,e P 2  3  +  this their  harvest  gillnet-troll.  2.  is  constant  the  about  samples,  convexity and  section  in  the  estimates  the  the  the  not  for  given  on  Finally,  parameter  estimates  of  interest.  chapter.  linear  samples that  e^P,)  the and  Econometric Technique  (5.10)  -X  =  3  M  f=i  (  +  03 £  =  ^  parameters  (eg +  used  routine.  After  sample,  convergence  the  new  are  are given  is  a  and  is  errors,  In order  to check that  new  j  z  i  z  of  )  /  Z  i  +  for the  are used  nonlinear  j l  b  the  (  Z  j  Z  l  0  z  j +  3  +  2  )  a  /  Z  ^  The  is  80  maximum  c  3  e e )P 3  5  values  starting  than  3  for the of  +  c«  and  (5.4).  depending is  fairly  different  These  must  be  likelihood  achieved  attempt  one are  the  stringent,  ie.,  estimates  estimates and  their  2.  three  parameters  upon  from  in Appendix  first  j  Davidson-Fletcher-Powell  parameter  For the  Z  A maximum  the  1.0E-05  are given  values  (5.3)  4 j  in (5.8)-(5.11)  criterion  has been  are tried.  C  and 200  nonlinear  statistics,  in  technique.  algorithm  more  U  +  equations  convergence  no  as starting  +  2  4  estimation  between  The  iteration.  (e e«  i bo0 /Z,  3. The set of  iterations,  parameters  3 j  c  b /3 /Z,  parameters  parameters  3  e!)P„ )  particular  a global  ?= i  +  to  can be  previous  i  +  achieved.  )  5  b.Z./Z,  along with summary  estimation the  the  values  standard  For  the  values  (  using a nonlinear  from  linear  related  number  coefficient  3  5= 2  in Appendix  obtained  starting  3  J  e§ +  5-2  as a system  procedure  2  j i  b  J  + 0, £ _  estimated  (e e„+e e )P«  =  +  relationships  +  3  2  ( S " a j Z j /P, ) * ( e , e « P +  'e'  2  b.Z./Z,  3  j  The  /Pi)*(e,e P  ^ 3 - 5 = 2 54  +  -x,  j  z  (el+ei)P  +  (5.11)  j  a  and Results / 78  different values  sets of  from  that  are still  used.  Next,  the  linear. starting  Econometric Technique Table  5.3:--Testing  for  constant  returns  to  scale: four  and  vessel  Results /  types  Sample  LLF(R)  LLF(U)  -2LQG(n)  xi (0 = 0.010)  Decision  Seine  -124.398  -95.612  57.573  18.475  Reject  Gillnet  -50.453  -46.319  8.268  18.475  Accept  Troll  -460.418  -447.365  26.106  18.475  Reject  Gillnet-Troll  -536.565  -526.621  19.890  18.475  Reject  V  a  l  u  e  79  Note: The null hypothesis of constant returns to scale cannot be rejected if the calculated value of -2LOG(y) is less than the critical value. The number of degrees of freedom used to determine the critical value of x is given by the number of restrictions. For each sample this number is 7. The log-likelihood values for the troll sample are obtained from linear estimation. Those for the rest of the samples come from nonlinear estimation. For a different level of confidence, ie., where a is 0.005, the critical value of x is 20.278. In this instance the hypothesis of constant returns to scale cannot be rejected by the gillnet-troll sample. 2  2  values  of  for  parameters.  4  all  digits,  Once the  one  are  basic  estimates  in  eigenvalues  have  prices in  5.2  in  in  However,  is always  it  are  specified  prices  testing  for  imposed  in  monotonicity  condition.  This  all  non-negative,  be  test.  The  the all  troll  other input  without The their  hand,  and the  demands, constant  gillnet-troll values  are  input  seine  is  returns sample  sample  way,  accept  been  the  the  checked  is  done  this  in  ten  same  to  by  condition, A  are  used  at  least  to  make  to  sure  that  verifying  whether  as shown  by  the  Incidentally,  by  matrix.t  prices  unable  estimated by  is also  imposed.  accept  the  calculated  latter  all  and  gillnet  exception  for  each  non-positive.  satisfy  of one  equations  examining  this  has  has  three  observations  satisfy  The  observation with  should  signs  of  observation.  requirement  gear.  scale,  the  However,  samples  to  close to  This  symmetry  have  are  is  reparameterized  verified  samples  the  values  values  80  Many  hypothesis.  subsequently.  gillnet-troll with  starting  Results /  results.  each  new  prices,  the  of  parameter  samples  this  demands  and  Finally,  correctly.  symmetry,  convexity  supply and  All the  in  with  output  final  obtained  for  and  parameters.  consistency in the  is accepted.  Table  convexity  all  case the  been  researchers,  Along  each  ensuring  equations  imposing  In  for  thereby  the  convexity  used  Econometric Technique  this for  it  positive  positive  gear  former  output  the  predicted  a  should statistical  observations.  sample, a  the  is not  all  for  gillnet with  The  satisfy  On  supply  and  with  and  both gear  demands.  demand. However,  zero.  tit is noted that this table shows two sets of results for the gillnet-troll fleet. This is because the hypothesis of constant returns to scale cannot be rejected using the nonlinear estimates, although it is rejected in the linear case.  Econometric Table  5.4:-Goodness  of fit: four  Technique  vessel R  and Results /  types  Sample  Equation  Seine  Output  0.3503  Labour  0.3681  Fuel Gear  0.1695 0.2210  -non-crs  Output Fuel Gear  0.2289 0.1645 0.1568  -crs  Output Fuel Gear  0.2172 0.1438 0.1134  ;  Gillnet  Troll  Output Labour Fuel Gear  •;.  0.2477 0.3961 0.3814 0.0084  Gillnet-Troll -non-crs  Output Labour Fuel Gear  0.1853 0.3171 0.1979 0.0572  -crs  Output Labour Fuel Gear  0.2140 0.2535 0.1057 0.0568  Note: The R values for the troll sample are those derived from, the linear estimation technique. Since the other samples are estimated using a nonlinear technique the R values are calculated as the squared correlation between the predicted and the actual values. 2  2  81  Econometric Technique and In  all,  five  nonlinear  samples.  Numbers  two  estimation  The  first  and  three  returns.  Numbers  without  constant  performed  by  equations scale  in  statistic  and  and  cases.  to  a  to  equal from  the  as  of  number rejected.  of  3  of  5.3  test.  Each  sample  ie.,  without  form,  with  mentioned  the  gillnet-troll  variable  in  all  gillnet  it  at  a  sample  —  the  the the to  null  with  the  critical  test  in  of  number value, of  it  0.010%.  For  relevant  at  is  as a system  of  returns  to  imposed the  and the  on  following  c .t  A  test  unrestricted  and  u  one  results.  level  are  case.  This  freedom  equal  to  of  which  The  of  completeness,  parameters  restricted  constant  scale decisively, whereas  accepts  for  and  scale  that  3  the  degrees  hypothesis  relevant  to  scale  c ,  2  constant  LOC(U)],  function  the  c ,  scale.  (5.12),  samples  than  to  for  with  constant  requires  functions  -2[LOG(R) -  random  imposed;  sample  likelihood  likelihood  returns  c,,  3  as in equation  is estimated  this  b ,  2  again  returns  hypothesis of  to  without  sample,  82  estimates  returns  and  constant  constant  earlier  the  returns  the  b ,  0  with  gillnet-troll  ratio  logs of  then  both  for  b ,  presents  constant  the  parameter  non-constant  sample,  to  zero,  of  Chi-square  restrictions,  rejecting  the  log  with  test  Chi-square is greater  Table  hypothesis The  a  the  obtain  The  is calculated  restrictions  calculated  tFor  is  to  scale.  restricted  set  used  gillnet  pertain  form,  As  It  LOG(R)  number  c .  the  -2LOG(M)=  distributed  while  for  estimates.  is formed  where  it.  seine  five  (5.12)  the  sample  unrestricted  be  restricted  the  are  returns  an  parameter  parameters  four  are  using a likelihood  imposed,  the  is  techniques  Results /  depends  upon  gillnet  b ,  test  b , 2  for  b , 3  to  sample  significance the  0  is  returns  seine the  restrictions  sample (a  =  the  troll  b , 4  c,,  the 7.  scale  rejects  is  If the is the  accepts 0.005%), sample  c , 2  and  Econometric Table  5.5:--A comparison  of the  linear  Technique  and nonlinear  and Results / 83  log-likelihood  functions  Sample  Likelihood function (Linear)  Likelihood function (Nonlinear)  Seine  -81.449  -95.612  -45.858 -49.790  -46.319 -50.337  -516.184 -528.890  -526.621 -536.702  Gillnet -non-crs -crs Gillnet-Troll -non-crs -crs  Econometric Technique and using the  the  linear  estimation  results  is included  constant  returns  to scale.  hypothesis of  Before  examining  samples  it  For  troll  the  is  the  characteristics of  necessary sample,  In  particular,  goodness  of  fit.  are  not  calculating then a  fit  the  data  the  these  worst  variable  is also  and  to  functions  and  the  other  5.4.  are  an  quite  this  factor  be of  may actual  actual  show,  for  39.61% The  samples is that  has characteristics which  on  each  techniques  R  obtained  The  by It  to  2  is  yield  goodness that  the  variation  and  variation.  For  the  the  input  data.  the  example,  of  four  the  quantities  of  the  quantities.  measure.  24.77%  rejects  evaluate  be  2  acceptable. all  to  nonlinear  and  fit  statistics  used  and  explains  explains  equations  R -type  They  sample  equation  examine  log-likelihood  linear  troll  measures  predicted  generates  technology for  measure  quantities  also  84  demand of  equation  gear services.  make  it  similar  to  factors.  used in the  estimation.  the  Table  the  is that  vessel types  nonlinear  for  in  means  sample  summary  can  comparable  of  This  estimated provide  by  predicted  correlation  table.  harvest  values  2  results consistently across  fixed  instructive  a  errors  demand  possible explanation  both  It  equation  R  estimated  between  the  the  techniques  However,  presented  labour  cross-sectional  A  are  output  obtains  samples  the  estimated well  calculated  standard  Squaring  estimated  that  the  the  statistics  estimated  the  covariance  by  correlation.  of  For  how  estimation  generated.  the  divided  discuss  linear  equation.  values  to  the  in  Results /  the  effect  fishery. This may obtained  Strictly  from  speaking  nonlinear.  of be  the the  However,  imposing price done  linear  it  is  by comparing the estimation  models  convexity  are  not  possible  to  with  on  values  those  comparable, see  the  whether  of  from one  four the the being  imposing  Econometric Technique and convexity The  is an  larger  reflect  (negative)  the  parameters  fact  convexity  not  differ  in  constant scale be  in  each  is  values,  has case.  not  an  values  obtained  been If  relevant  from  imposed,  the  In  in Table  nonlinear the  values  one.  found  the  although  likelihood  unreasonable  are  most  estimation,  same  are  not  number  too  cases  5.5.  of  different,  the  values  do  and  troll  the  fleet  with  RESULTS  that  follows  compares  non-constant  for  to  with  with  A  the  techniques. The  returns  scale.  gillnet  presented.  samples,  restriction  The  85  much.  returns  and  a  restriction  discussion  fleets  to  that  ECONOMETRIC  The  restriction.  log-likelihood  is estimated  the  C.  unreasonable  Results /  The  for  scale  case,  to  estimates  non-constant  brief  discussion  exception  troll  results  sample  of  for  the  is estimated  and  do  their  troll  seine, for  gillnet-troll  returns of  the  not  by standard  the  with differ  differences  sample,  gillnet-troll, gillnet  constant much  follows  are  from the  estimated  linear  returns the  ones  analysis.  using  to  All  nonlinear  techniques.  1. Own- and Cross-Price Elasticities of Supply and Demand The  estimated  used  to  parameters  calculate  demand.  As  restricted  profit  to  quantity.  from  equations  output-variablet  discussed with  in  Chapter  respect  Appendix  4  to  are  in  contrast  to  4  an  derives  tThese elasticities have both a elasticities obtained directly from constant. They cost function.  own  (5.3)  and  and  cross  they  output these  are or  (5.4)  price  defined input  elasticities  substitution a restricted  or  effect profit  output-constant  and  elasticities as  price for  (5.8)  the  times the  and an function  elasticities  first the  (5.11) can  be  of  supply  or  derivative  of  ratio  normalized, output d o not  obtained  of  price  quadratic,  effect, since hold output  directly  from  a  Econometric Table 5.6:--Nonlinear  Quantity/  estimates of  output-variable ownseine  Technique and Results /  and cross-price elasticity  Output  Labour  Fuel  Gear  Output  0.290 (0.246)  -0.144T (0.089)  -0.288 (0.274)  0.142T (0.092)  Labour  0.050T (0.031)  -0.025 (0.021)  -0.050T (0.029)  0.024t (0.014)  Price  Fuel  Gear  0.112  -0.055T  -0.111  (0.106)  (0.032)  (0.123)  0.055 (0.044)  -0.025T (0.016)  0.013T (0.007)  0.025 (0.020)  -0.012T (0.008)  Note: Asymptotic standard errors are in parentheses and the symbol "t" signifies that the estimated elasticity is significantly different from zero at a = 0.10.  Econometric Technique and restricted  profit  calculated  at  the  the  elasticities  different  from  gillnet-troll  The  the  and  of  are  end  of  where  It  had  the  samples.+  In  zero  at  Table  a  of  90%  and  troll  significance  elasticity  for  fleets  level.  Not  are  elasticities.  general, found  as many  the  to  are  5.6,  different not  higher  may  fish. fleet.  from  Table  5.8,  show  that  an  response  increase  order Table  after 5.9,  zero,  is  in  the and  but  able  the  gillnet  it  is  price  that  supply  species,  the  Thus,  anticipated  sample,  it  Furthermore,  in response to  Tables  to  They  are  majority  of  be  significantly  significant  gillnet  for  the  troll  fleet  choose  special  using  not  is  more  the  least  able  to  ie.,  bait  able or  controlled mobile  target  a  5.9.  vessel has  the  1%  increase  supplied  by  are  a  5.7.  The  they  are  0.153  least  in  troll  those  Table  is the  fishing  also  this  through  response  fleets,  small,  by  is  fleet  5.6  ie.,  quantity  troll  It  is  0.480,  the  regulator.  fleet  it  at  very  surprising since the  priced  spectrum,  in  from  Hence,  intervention  given  elicits  gillnet-troll,  fleet.  is  output  descending  are  estimates  troll  salmon  In  results  ie.,  been  the  significant  significantly  salmon-fishing effectively  of  gillnet,  0.480%.  the it  each  seine,  landed  little  preferred,  these  the  salmon-fishing  relatively  display  for  most  0.098. These the  5.9  of  set  of  seine,  two  to  values  elasticities  price  vessel  5.6  mean  complete  largest  Tables  87  fleet.  Own-price  the  function.  Results /  of  latter and  regulated  of  areas  and  times  with  to  target  the  more  the  other  hooks. by  regulations  component productive  At  of  areas  about  the  entire  or  move  variation.  the  response from  the  seine  vessels would  be  greater  tAsymptotic standard errors are generated from the formula for the variance of a random variable comprised by either adding or multiplying several random variables that are not independent (Kmenta 1977, Judge et al. 1982).  Econometric Technique Table  5.7:-Nonlinear  estimates  of output-variable  and Results /  own- and cross-price elasticities:  gillnet(crs) Quantity/ Price  Output  Fuel  Gear  Output  0.098T (0.064)  -0.126t (0.072)  0.028t (0.011)  Fuel  0.524T (0.298)  -0.672T (0.333)  0.148T (0.062)  Gear  -0.054T (0.022)  0.069t (0.029)  -0.015t (0.010)  Note: Asymptotic standard errors are in parentheses and the symbol " t " signifies that the estimated elasticity is significantly different from zero at a = 0.10.  Econometric Technique and since  they  However,  have  the  fishing  salmon-fishing variation  largest  times  fleet.  and  scale areas  Although  across species and  of  operation  are  these  rigidly  vessels  areas, they  are  and  the  controlled  have  the  prevented  most for  powerful  this  ability  to  from  taking  for  labour  Results /  89  engines.  segment respond  of to  advantage  the price  of  their  size.  A  comparison  significant along unit.  only  with Thus,  it  number  of  Turning  the  seine  zero  labour  fleet,  in  in  that the  exhibits  the  troll  On  is best able  significant  elasticity,  eg.,  large  own-price  elasticity  for  is  an  much  to  area fuel  important cruising  significant hypothesis  and  elasticities, that  moderate  elasticity  This  sample,  may  or  other  hand,  Attempts  to  size, an  for be  from  ie.,  this  reveals  that  it  -0.371.  This  fleet,  industrialized labour  caused  by  significantly  an  insufficient  variation  estimates  are  in  often  possibility reveal  is  production  is not  insufficient  imprecise verify  to  of  demand  respond to  -1.368.  This  output.  It  of  down  ie.,  fishermen  the the  -0.677 are  troll coast.  and very  for  price  is  to  fuel,  to  be  no  that  and from  These  sensitive  to  results  fuel  given  the  caused obvious  largest  fleet  is  operation gillnet  argue In  in  favour three  very fuel  requires  vessels  the  and  relatively  areas. As well,  the  prices.  reinforced  the  troll  many  and  is  has the  the  since  gillnet-troll  -0.672.  notion  expected  technology, Both  the  changes. It  indicates  prices since it travels  component up  of  characteristics of  fleet.  elasticities  most  responsive  demand  own-price  this  data.  of  among the regressors.  own-price  fleet  the  the  and the  seine  for  the  elasticity  sample  the  prices.  multicollinearity  to  troll  observations  multicollinearity  signs of  own-price  is surprising that  from  calculated  the  for  the  different  by  of  of  have the fleets  Econometric Technique and Results / 90 Table  5.8:--Linear  Quantity/  estimates of  output-variable o w n - and cross-price elasticities  Output  Labour  Fuel  Gear  0.480T (0.088)  -0.112T (0.029)  -0.357T (0.090)  -0.011  Labour  0.427T (0.111)  -0.371t (0.072)  -0.065 (0.103)  0.009 (0.031)  Fuel  1.464T (0.369)  -0.070 (0.112)  -1.368t (0,430)  -0.025 (0.039)  Gear  0.015 (0.025)  0.003 (0.011)  -0.009 (0.014)  -0.010 (0.019)  Price  Output  (0.018)  Note: Asymptotic standard errors are in parentheses and the symbol " t " signifies that the estimated elasticity is significantly different from zero at a = 0.10.  Econometric Technique and mentioned again,  fuel  the  expenditures  seine  response  significantly  different  the  of  impact  show  that  Estimates higher  is  of  or  lower for  increased fuel  The  last  change of  of  on  a  to  of  small;  fleet's  include  as  a be  upon  fisherman  of  elasticity  respond.  variable of  In  used  to  costs.  -0.111.  behaviour.  dissipate fishery  effects  turn,  rents  in  results  fisherman.  the  In  not  prices or  the  evaluate  is  these  for  91  Once  It  in fuel  general,  decision variable  fishing  to  total  a lack of variation  to  may  prices  an  reflect  fuel  elasticities  the  eg.,  ability  of  this  the  has  form  of  costs.  the  own-price  price  of  elasticities  gear.  describes  For each sample  elasticities. This suggests that  and  significantly  component  This may  the  price  ability  large  very  (eg.subsidized)  the  in the  all the  variable  fuel  is  zero.  important  own  implications  from  controls  it  are  Results /  fixed  characteristics.  different  from  zero,  gear  Only  but  it  response  is the  gillnet  responses  and are  of  gear  smallest and  is a complex  the  the  the  factor seine  very  usage  to  a  least significant  that  exhibits  elasticities  small,  ie.,  both  are  not  -0.015  and  have  two  -0.012.  Cross-price  elasticities  components, input  a  demand  output-constant following way  "»  <5  pure  obtained  substitution  elasticities input (Sakai  "il= 'Ik"-  directly  (e)  demand  from  effect in  the  and  Tables  elasticities  an  5.6 (v)  in  restricted output  profit effect.  through  5.9  Tables  5.10  function The  are  .«'tt-u>  '«u  related  through  1974):  «» i . k - 2 . 3 , 4 .  output-variable  5.13  to in  the the  Econometric Technique Table  5.9:--Nonlinear  estimates  of  and Results / 92  output-variable owiv- and cross-price elasticities: gillnet-troll(non-crs)  Quantity/ Price  Output  Labour  Fuel  Gear  Output  0.153T (0.108)  0.005 (0.045)  -0.160T (0.082)  (0.008)  0.060 (0.107)  -0.001 (0.007)  -0.677T (0.277)  (0.025)  Labour  Fuel  Gear  -0.015 (0.128)  -0.044 (0.076) 0.078  0.590T (0.301)  (0.140)  -0.0002  -0.00006  (0.0008)  (0.0003)  0.0003 (0.0007)  0.002  0.009  -0.000004 (0.00002)  Note: Asymptotic standard errors are in parentheses and the symbol " t " signifies that the estimated elasticity is significantly different from zero at a = 0 . 1 0 .  Econometric Technique and In 6  (5.13)  ik  '  profit £  v ^  S  is the  6  o  u  t  function,  D kl  '  ^  S  e  P  u  t  "  v  e  a  n  a  '  D  own-price  supply elasticity.  From  signs  the  the  relationships  positive, the  this  inputs  indicated of  are  intensity, of  Beginning  with  found  fuel  price  from  to  be  On  gillnet  found leads  to  a  with  sample  different options  species for  fuel  0.148%  may choose to  directly  input  The  of  are  and  of  the  other  elasticities has and  altering  gear.  increase  travel to of  only  in  more  salmon. the  input  estimated  output  it  For if  and  the  or  ability  of  the  and  is  the  find  out  the  converse  substitution  k  S  e  if  and  restricted  possible to  example,  k  input  Finally,  is  and  is  sign  true,  fisherman  to  is  then  complementarity  Used in conjunction with the  elasticities,  Although very  hand,  the  i  93  is  elasticities  subvert  the  dissipate resource rent.  output-variable  -0.05.  inputs  output.  demand  substitutes;  elasticity.  indicate  k  inputs.  degree  the  from  between  of  variable  inputs  variable  in  the  seine  complements with a cross-price elasticity  the  between  of  restrictions and  the  substitutes,  the  elasticities  changes of  zero.  The  that  magnitude  input  between  pairs  complements.  these  derived  cross-price elasticities  between  by the  are  the  implies  intentions  be  of  between  cross-price elasticity  elasticity  n c e  elasticity  elasticity  e  is is the "P  c r o s s  output-constant  Results /  labour  for two For the  the  value  is  gear  and  fuel  and  and  former  mix.  pair  inputs  example,  a  1%  demanded.  observers However,  significantly and  a  both  in  gear  the  cases,  use more  believe  the  gillnetter  results  from  this  to  different found  from  price  to  zero.  relationship  the  and  fuel  respect  are  different  in one  the  and  significantly  substitute  increase In  labour  labour with  this  areas or remain Many  of  small,  variable  fuel  sample  of  is  gear  vessel-owner nets to  to  catch  have  sample  few  exhibit  Econometric Technique and Table  5.10:--Nonlinear  estimates  of  output-constant  price  Results /  elasticities: seine  Price/Quantity  Labour  Fuel  Gear  Labour  -0.127E-12 (0.791E-07)  -0.018 (0.019)  0.035T (0.024)  Fuel  0.039 (0.073)  -0.84E-13 (0.575E-07)  0.117 (0.117)  Gear  0.018T (0.010)  0.027T (0.019)  -0.428E-14 (0.696E-08)  Note: Asymptotic standard errors are in parentheses and the symbol "t" signifies that the estimated elasticity is significantly different from zero at a = 0 . 1 0 .  94  Econometric Technique and the  largest  Looking  values for  at  cross-price individual  the  troll  pairs  substitutes.  of  gear  leads to  is  whether  to  But  seine  vessel the  gear.  As mentioned  coast  with  technology for  the  fuel  substitutes, other  the  opposite  and  gear  playing  and  gear  troll  other  the  sample, As  0.009,  are  to  lines,  hand,  it  to  the  the  proportion  of  the  time spent  switching  time  spent back  use labour  using and  fuel  troll  forth  The of  and  fuel  equipment - which  the  fuel  and  down  the  harvesting  results  elasticities  is  gear  found  are  much  fleet. be  that  knowledge  obtains  significantly  smaller.  In  are  Unlike  fish  of  troll may  -  set  to  to  particular, each  be  Insofar  found  and  the the  and  For this  choice  for  between  cruising up  is  price  in  elasticities  are  reason  the  the  relationships.  of  appear  demanded. The  labour/gear  the  in  of  and  specialized  and  increase  similar  elasticity  suggested by  the  seems that  fleet,  alone  "capital"-intensive  vessel. A  examination  gear  relationship  the  labour/fuel  complements.  1%  cross-price  gillnet-troll  those  requires  the  and  output-variable  or  consists of  complements. of  a  the  An  labour  signs  of  of  zero.  complementary  side  gillnet  concerned,  be  On  the  the  of  complementary  none  the  The  operation  obvious ie.,  quantity  etc.  none  eg.,  95  four samples.  labour  labour-intensive  a  to  that  small,  suggest  troll  and  in  at  pairs  found  more  that from  reveals  in the  pairs  are  different  is very  winches,  out  relationships  are  vessel  earlier  zero.  input  elasticity  across the  is observed  elasticities  vessel obtains  although,  the  gillnet  troll  and  from  the  fuel/gear  gillnet-troll  different  input  lines,  the  lines  it  significantly  the  troll  and  results  a 0.009% increase make  more  labour/fuel  are  of variable  be  of  cross-price elasticities  sample's  elasticities  to  form  the  Results /  as  have labour  gear  type,  labour  skills.  substitutes. This might  reflect  which  versus  is fuel-intensive  is labour-intensive.  Econometric Table  5.11:--Nonlinear  estimates  of output-constant  Technique and Results / 96  price  elasticities:  gillnet(crs)  Price/Quantity  Fuel  Gear  Fuel  -0.591E-11 (0.866E-06)  0.820t (0.374  Gear  0.084t (0.037)  •-0.276E-11 (0.405E-06)  Note: Asymptotic standard errors are in parentheses and the symbol "t" signifies that the estimated elasticity is significantly different from zero at a = 0 . 1 0 .  Econometric Technique and In  conclusion,  it  substitutability a very the  terms  of  the  with  one  which  are  are  often their  developed  ways  of  controls  gillnet-troll  to  arose  the  and  uses  fleets  troll  have  amongst  Earlier  gear.  variable  in  The  number  elasticities, this  between  gear  this  less  of  taking an  the  areas.  On  regulated on  can and  chapter  a The are  latter  that  is  means  few in  of  the  fleets.  vessels.  two  species to  suggest and  fuel  that are  substitution quite  large  made  than  between in  Tables  their  change  possibilities and  of  have  around  the  the  gillnet-troll is  out  develop  and  closed to sea  regulations.  These  substitution  output-variable 5.10  through  output-variable  sample. The output-constant  troll  fleets  area  the  the  period  troll  an  not  of  the  the  fact,  significant elasticities does exception  a run comes  getting  In  in  same  days. Then,  hand,  is  years  the  a short  When  needed  There few  on  moves further  and  less  captain.  presented larger  the  these  other  area  the  past  first  vessel merely  of  In  97  increasingly regulated  the  not  fleets.  salmon. W h e n  the  much  gillnet  allotment  a  gillnet  have  are  somewhat  of  avoid  distinction  fish  as  have  vessels compete  seems  inputs  restrictions  it  and  become  entire  It  fleets  dichotomy.  have  area.  least  seine  this  permission to  and  way  the  same species of  variable  controlled  elasticities  with  sample  In  gillnet-troll  These two  combination gillnet-troll  elasticities.  these  for  inputs still under control  the  output-constant general,  the  been  at  the  because of  gillnetter,  do  the  of  days  been  than  species.  given  capable  fishing  and  gillnetters,  for  chances  have  mainly  and  substituting  on  fleets  and and  usually  troll  explanation  seiners  another  the inputs  fishing areas, times,  given  fleet  variable  the  are  strict  that  interesting  ie.,  gillnetters  seiners, time,  and  fleets,  grounds in  between  simple  net  appears  Results /  nor  between  significant when  do  the  labour output  the  5.13.  and In  counterparts. signs of  the  elasticities for  and  fuel,  and  is held constant.  Econometric Table  5.12:-Linear  estimates  of output-constant  Technique and Results /  price  elasticities:  troll  Price/Quantity  Labour  Fuel  Gear  Labour  -0.217T (0.077)  0.035 (0.068)  0.101T (0.061)  Fuel  1.017T (0.441)  -0.281T (0.092)  1.062T (0.378)  0.004  -0.008 (0.013)  -0.010 (0.018)  Gear  (0.011)  Note: Asymptotic standard errors are in parentheses and the symbol " t " signifies that the estimated elasticity is significantly different from zero at a = 0.10.  Econometric Technique This  suggests  great  deal  other  that  of  the  troll  variable  fleets,  the  fleet  input  exhibits  a  substitutability  conclusions  derived  and  fish  harvest  technology  when  output  is  from  the  held  Results /  that  permits  constant.  output-variable  99  For  a the  elasticities  are  unchanged.  It  is  instructive  previous  ones.  fisheries,  the  (1985). profit  which  he  has  those -1.1485  a  fuel 1%  values are  He  variable  a  0.272%  the  variation. on  to  substitution  his  second  the  well,  price larger  In  than  Squires the  of  a  in the  one  the  of  supply  are  from  -0.8663  for  uses  years  studied tonnage.  variable  single-output  1%  a  of  labour  research,  of  data,  larger  for  than  capital  in  the  to  reduction. but  Squires does are  price  demanded  the  thereby  Hence, there  years  complementary  increase  0.2743%  this  by  of  fuel,  complementary  demand  a  restricted  two  and  fishery  (labour,  of  to  by  two  of  evidence  obtained  or  in  quantity  lead  translog  from  England  scallop  inputs  example,  would  possibilities between  that  range  sea a  those New  variable  shows  For  fishery  vessels  level  the  employs  three  with  different  and  elasticities  they  reduction  those  new  price  inputs.  he  elasticities  fishery  capital  addition,  entry of  study,  this  of  stock  study  study two  fishery,  price  this  1987b)  outputs,  eg.,  in  to  1987a,  the  own  research,  Furthermore,  regulations  For  The  the to  for  positive  between  different.  exploit  finds  outputs.  somewhat  price  variable  As  in  (1984,  over three variable  labour.  increase  obtained  multi-species  this  lead  are  in  for  would  very  more  is a  between  for  relationships  former  data.  results  a similar framework  fishery  a dummy  calculated  the  trawl  defined  and  relationships  of  otter  Since the  capital)  compare  Squires uses  function  and  to  not  and  These  fisheries  picking  up  have  any  no  incentives  a  normalized  inputs.  fishery,  Squires  adopts  Econometric Table  5.13:--Nonlinear  estimates  of  output-constant  price  Technique and elasticities:  Results /  100  gillnet-troll(non-crs)  Price/Quantity  Labour  Fuel  Gear  Labour  -0.035T (0.065)  0.048 (0.091)  -0.0008 (0.009)  Fuel  0.555T (0.264)  -0.048 (0.092)  0.499T (0.232)  Gear  -0.40E-4 (0.0002)  0.0002 (0.0006)  -0.123E-05 (0.139E-04)  Note: Asymptotic standard errors are in parentheses and the symbol "t" signifies that the estimated elasticity is significantly different from zero at a = 0.10.  Econometric Technique quadratic scallop  functional fishery  are  obtained  by this  and  fuel,  for  demand  large,  can  he  of  cross-price  It  is  the  it  inputs  supplied  degree  the to  by  provides greater  to  the  the  is  intensity  input  unity,  less  the  than  the  input  one,  the  and are  of  to  for  capital and  of  this  price  the  same  order  sea those  is -0.242  the  labour  from  zero  convexity,  fishery,  capital  101  the  than  different  and  relationships The  an  use.  said input  of to is  first  input  The  changes  quality is  For  on  smaller  labour of  produce  of  uses.  data  elasticity  condition  Results /  he  and of  nor  provides  energy.  The  magnitude  as  and  of  British Columbia salmon fishery.  the  price  elasticity  significantly  the  he  elasticities.  demand  about the  paper the  of  used  form  is  of  much  supply  former accept  year  are  price  output  capital  characterize  when  relative  which  than  in  types  input  not  one  They  own  the the  between  cited  the  for  but  using  (1985).  functional  two  knowledge  but  signs  Squires does  further  changes  according  Squires  in this thesis for  through  intensively  The  with  elasticities  obtained  For example,  substitutability  generated  in  incorrect,  -0.956.  possible  zero,  are  impose  evidence  those  research.  -0.001.  ie.,  Results  reported  elasticity  and  form.t  and  the  inputs  elasticity  indicates  altered.  the to  An  This  Inputs  gives  the If  output  suggests can  be  price  how ranked  about  the  increases.  This  firm,  eg.,  the  value  is  input  has  inferior  each  how  information  output  superior.  normal.  output  output.  second  when  be  is  between  if  the  value  greater a  is  than  negative  value.  The  elasticities  through  5.9.  necessary  For  +Although  this  functional  forms  all  has  to  vessel the  are very  describe types  same  fuel  name  different.  these is as  the the  relationships input form  are  used  most  chosen  for  given  in  Tables  intensively, this  thesis,  5.6  followed the  two  Econometric Technique and by  labour  supplied  and  intensity  The  results  of  use  for  can  the  for  the  says  if  the  only  are  troll  that,  price  be  above  hand, is inferior  is normal  This  than  described  superior,  other  gear.  increases more  the  either  then  as of  ranked  fleet,  or  the in  fleets,  but  sign  in  oi  input  the  normal,  in all samples, with the  seine and troll  price  another  if  mirrored  the  fuel  decreases,  were  of  the  to  other  exception  inferior  for  of the  of  output  is  Fuel  Gear,  troll  Thus,  negative.  inputs.  samples. the  102  decrease.  elasticity  classification all  Results /  on  is the  sample. Labour  gillnet-troll  fleet.  2. Elasticities of Intensity In  this  inputs  section I investigate  the  and  factors  intensity  profit  interpreted to  elasticity one.  The  have  restricted  (Diewert  restricted  leads  the  in a  function  the  x%  1974).  indicates degrees  implications  The are  following  change a  importance  given  the  for  these the  In  order  to  behaviour  of  be. each  understand the  participant  constrain  output  to per  the  and  success  a  one  lack  increase  of  effects must  of his  participant  by  4.  a  of  the  positive  by  the  limited  elasticities  level  of  the  variable  magnitudes  entry  of  program  to  restricted  a  of  quadratic, are  input.  elasticity,  variable  elasticities  normalized,  These  the  the  A  be  factor  negative  complementary the  that  elasticities, uses  input  rent dissipation.  of first  property own  from  demanded  given  the  non-normalized  increase in the  relationships,  fishermen,  Recognizing that  1%  prevent  the  Appendix  relationship  controls per vessel in order to  relationships between  derived  in  quantity  substitute  of  A  the  analyzing  formulae  way.  in  by  of  the  input  restriction  program  ask what  the  regulator's  rights  the  fish  creates  regulator  hopes  output,  prohibiting  in the  the  use  of  a  key  upon  objective  the might  incentives to  input  for  effectively beyond  a  Econometric Technique and Results / 103 Table  5.14:—Nonlinear  estimates  of elasticities of intensity:  seine  Quantity/ Fixed Factor  Stock of Fish  Net  Fishing  Tonnage  Days  Output  -0.767t (0.520)  0.067 (0.162)  0.483t (0.210)  Labour  0.114t (0.070)  -0.010  0.004  (0.029)  (0.051)  0.114 (0.582)  0.336t (0.180)  0.167 (0.237)  -1.526t (0.890)  -0.425t (0.251)  0.406 (0.336)  Fuel  Gear  Note: Asymptotic standard errors are in parentheses and the symbol "t" signifies that the estimated elasticity is significantly different from zero at a = 0.10.  Econometric Technique and specified an  level.  effective  input  Experience shows that  means  restriction,  control;  in  the  this may  fisherman  increases  is  a  secondary This  variable  inputs.  to  restricted  the  costs if  in the  the  path  This to  fisherman  is  occurs the  begin  inputs  Oceans  has put  control  the  that  as  are  what  is  the  induces  an  variable  input  may  increase,  as  well.  costs  taking  operate is skewed  where  and  there  Leontief fixed  an  of  the  upper  actions of  inputs is  on  a given  of  inputs  the  the  that  the input.  that  harvesting  the  use  of  that  are  a  costs.  factor  is  complementary  direct  complements  higher  output  manner.  that  is  restricted  of  his  is  the  level  under  restricted  higher  to  an  means  view  leads  of  harvesting  would  Thus,  be  less  the  expansion  input  is  prevented.  substitution  elasticity  effect.  In  of  other  intensity words,  with respect  the  technology  type.  by analyzing those  input, the  fishermen. Tables  face  input controls.  a zero  elasticities  bound  to  too,  through  output  proportions  tonnage  This,  use of  exhibit  no  inputs  the  understood  for  in  unconstrained  dissipation  these net  an  by the  rent  all variable  and  in  well  lead  increase  of  could  so  In  many  for  104  per vessel is not  typical  substitutes  use  of  set  are  The  and  the  the  There  not  of  the  substitutes  place  use  vessel.  over  restriction.  can also take  turn,  discussion  variable  inputs  restriction  per  output.  way,  input,  the  his  this  case  when  fixed  the  in  restriction  the  However,  input  re-optimizes  increase  occurs  fisherman  one  is truly of  I  In  catch  merely  of  effect  sense that  for the  There  use  effect.  this,  a  circumvent  the  effect  and  can  to  indirect  secondary  increased  he  use  direct or  imposing  fisherman  way,  fisherman  This  of  imposing an  Results /  since  use  5.14  of  the this  through  obtained  Department input 5.17  of  between  the  Fisheries  and  per  vessel in  present  all the  order  to  elasticities  Econometric Technique and Results / 105 Table Quantity/ Fixed Factor  5.15:—Nonlinear  estimates of  elasticities of  intensity: gillnet(crs)  Stock  Net  Fishing  of Fish  Tonnage  Days  Output  0.052 (0.141)  0.105 (0.176)  0.535T (0.098)  0.190 (0.231)  Fuel  -0.257T (0.157)  0.144 (0.215)  0.578T (0.126)  0.734T (0.279)  0.225 (0.230)  0.018 (0.234)  0.226T (0.144)  0.965T (0.301)  Gear  Labour  Note: Asymptotic standard errors are in parentheses and the symbol "t" signifies that the estimated elasticity is significantly different from zero at a = 0.10.  Econometric Technique and of  intensity  seine is  fleet  not  net  the  ie.,  that  rent  use  of  whereas,  fuel,  use  to  best  able  to  is  for  form  rent of  finding,  since  expand  only  areas,  of  the toward  rent  5.14.  of  fuel  and for  vessel  fuel.  gillnetter  in an attempt to  use  has of  an  that  zero. This with  effect  the fairly  suggests  toward the  the  indirect  increase in the gear  strength of  by  values are  hand,  since  number  the  this  gear  On  and  the  other  intensively. of  the  observers  more  gillnet  positive  quite  the  increase its  a  convinced  for  segment  Most  relative  from  substitute  other of  the  complement  elasticity  the  However,  have  and  fleet.  this  On  used  and  of  the  channels  seiners  fuel  are  elasticities. that  are  use  it  the  may  vessels  British Columbia salmon fishery.  tonnage  uses fuel  a  106  inputs  The direct  direction  the  are  are  this  is  -0.425.  labour.  upon  intensity  both  gear  vessel-owners  is in the  the  Fuel  gear,  when  to  and  significantly different  complements.  of  fuel  substitutes. The  and  observers  Since  the  gear  appears  Most  much  occurs  labour  type  dissipation by  too  are  depends  effect  of  labour  are  result  zero.  type  are  Table  of  elasticities  direct  that  input,  fleet  inputs  rent.  between  this  this  vessel  the  no  and  that  is 0.336 and that for  dissipate the  from  relationship  the  this  dissipate  different  scope  net  I observe  intensity  amount  these  the  contrast,  output  gear  increased use  since  Nonetheless,  of  labour  by  increased  the  samples.  the  dissipation  of  there  for  that for fuel  substitutes,  In  four  elasticities  case  an  effect  the  have  tonnage,  large,  of  for  Results /  of  the  scale  fuel  it  output.  are  not  significantly  indicates  a  tonnage,  Table  5.15.  hand,  order  to  It  fleet,  fishery of  travels  in  appears  salmon  smallest as  fleet  that but  would  operation, to  a  complementary  increase  there it  greater  is little  should  agree and  Thus,  take  with can  this really  number  of  Econometric Technique Table  5.16:--Linear  estimates  of elasticities:  and Results / 107  troll  Quantity/ Fixed Factor  Stock of Fish  Net Tonnage  Fishing  Output  0.278T (0.085)  0.525T (0.199)  0.623T (0.162)  Labour  0.247t (0.072)  -0.354T (0.194)  0.022 (0.139)  Fuel  0.101 (0.091)  0.744t (0.242)  0.246 (0.175)  Gear  0.136 (0.668)  -1.222 (1.569)  0.323 (1.290)  Days  Note: Asymptotic standard errors are in parentheses and the symbol "t" signifies that the estimated elasticity is significantly different from zero at a = 0.10.  Econometric Turning  next  elasticities opposite -0.354  to  intensity  sign,  Table  for  labour  ie.,  encourages  fuel  usage,  since  to  be  variable  inputs  dissipating  behaviour.  the  complements and  significantly  gear,  Table  cross-price they this  are  I  to  elasticities  type on  net  look of  dissipating a  are  small  both  Furthermore,  the  no  direct  evidence  that  labour  not  have  significantly many  ways  of  that  is  not  use  among  range  and  by  net  the  three  elasticity  from  0.452  effect. and  of  Furthermore,  gear  different  In  labour  are  from  dissipating  rent  in  of  fleet of  fact,  all  it  of  are  all very to  large  1.608  for  although  It  the  inputs,  appears  the  is  rent  inputs  complementary zero.  the  troll use  variable  for  effect  amount  the  are  is  board  offenders  values  is a  gear  direct  The  tonnage.  worst  all  for  increased  increasing  of  fuel  on  gear.  the  elasticity  The  gear  and  of  whereas  zero.  induces an  rent  an  108  significant  are  elasticity  and  labour  the  suggest  from  have  ie.,  the  Results /  they  tonnage,  labour  that  to  large,  addition,  more  and  although  net  different  They  there  show  does  vessels  zero.  for  resource  found  fairly  In  to  on  fleet  from  are  effect  restriction  troll  Thus,  elasticities  vessel  want  5.17.  of  indirect  tonnage.  different  extremely  restriction  that  net  use  complement  against  the  the  are  tonnage,  significantly  a of  net  0.744.  an  gillnet-troll  to  of  is  is  capable  to  labour  is a substitute  value not  and  elasticities  it  toward  fuel  accepted  for  that  there  commonly  Results  These  but  substitution  fuel  respect  elasticity  -1.222,  addition,  three  with 5.16.  an  In  appears  fleet,  indicates  with  large,  vessel.  troll  of  complement very  the  Technique  face  that of  a  tonnage.  next  intensity  at  the  indicate  restricted  factor,  complementary  fishing  days.  relationships  For the between  seine  fleet,  the  fishing  days  and  Econometric Technique and Results / 109 Table  5.17:--Nonlinear  estimates  of elasticities of intensity:  gillnet-troll(non-crs)  Quantity/ Fixed Factor  Stock Fish  Net Tonnage  Fishing Days  Output  0.098 (0.183)  1.167T (0.384)  0.247T (0.123)  Labour  -0.016 (0.077)  0.452T (0.170)  0.277T (0.065)  Fuel  0.003 (0.157)  0.571t (0.356)  0.507t (0.129)  Gear  -0.872T (0.476)  1.608 (1.253)  -0.115T (0.381)  Note: Asymptotic standard errors are in parentheses and the symbol "t" : that the estimated elasticity is significantly different from zero at a = 0.10.  Econometric the  three  variable  restricting per  the  vessel,  the  light  of  In  potential  rent  true  for  fishing  days  0.226  (gear).  by  the  fishing  elasticity these  of  the  results  Table  also  5.16.  for  have  the  labour  and  different fishing the  from days,  use  labour,  of  is  ability they  to may  and  of  5.17.  gear,  instead  for truly  restrictions  and  Table  with this  somewhat  Although  days  zero  along  However, days  fishing  the  fleet there The  on  fishing  days  switch  gear Thus,  types, it  is some for  imposed the  appears  a  upon  is  fuel  the  very  been  able  to  the  are  have  not  and  to  prevent  fish.  This is  samples, variable  but  large  0.578  with  and used  number  significantly a  with  (fuel) inputs  the  prevented  by  output  complements  values,  relationships  than  with  gear  of  different  great  deal  of  for  both  elasticities to  be  the  between  significantly  a substitute  for  is  shown  by  an  increase  in  indirect  effect  is  an  increase  in  since  as to  these  inputs  whether  combination the  obtained  relationship  appears  effect  The  gillnet-trollers  those  complementary  days,  doubt a  and  elasticity  to  gear,  as if there  access  results  days. of  total  110  Furthermore,  restrict  days  has  gillnet  subsitution  use  to  Results /  fishing days.  fishing  fishing  able to  and  5.14.  DFO  large,  magnitude,  direct  need  of  exhibits  medium  of  are  different  and  increased  binding.  fish.  it  fuel  The  and  appears  number  is  gear  significant  seine  regulator  gillnet-troll  samples.  Both  elasticities  The  has  that  seiners'  5.15.  Table  respect  complementary  dissipation by controlling the  fleet  with  the  and  effect,  regulator  appears  the  rent  three  it  large  These  again,  the  controlling  fairly  direct  output  results  have  vessels  no  days,  fleet, Table  gillnet  Once  other  is  the  Like  zero.  of  there  by  and  days,  so  dissipation  troll  fishing from  number  since  positive.  also  inputs,  Technique  the  boat  is some  extend  arose  the  potential  complements.  constraint  single-operation  also  are  in  for  fishing  response  gillnetters. number  on  of  to  In  their  days  that  rent dissipation by  Econometric Table  5.18:-Nonlinear  estimates  of output-variable  Technique and Results /  o w n - and cross-price elasticities:  gillnet(non-crs) Quantity/ Price  Output  Fuel  Gear  Output  0.075 (0.061)  -0.099T (0.069)  0.025T (0.011)  Fuel  0.413T (0.289)  -0.550T (0.326)  0.137T (0.059)  Gear  -0.048T (0.021)  0.064T (0.028)  -0.016T (0.010)  Note: Asymptotic standard errors are in parentheses and the symbol " t " signifies that the estimated elasticity is significantly different from zero at a = 0.10.  111  Econometric Technique this  segment  For  much  of  of  the  the  concentrated  upon  appears  that  it  vessel.  However,  segments suggest  of  salmon  two  fleet,  there  in  is  to  area  I  area  scheme  conclude  by  the  stock  for  assessing  Columbia. its  success  of  more  The is  negative  and  stock  of  This  are  indicate 5.14.  is not.  all the  One  112  Oceans  has  that,  very  large,  as  well  fish  leads  to  a  causes  the  cost  other  of  in  as  of  level  harvesting  troll  set  of  which  is  the  the  this  It  type  of  of  the  other  trailers.  My  results  by  these  behaviour  certain  between  areas.  two  might In  be  fact,  a  fishery.  the  variable  elasticities so  inputs is  popular  stock  regulator  grows,  significantly  being  their  seiners.  of  to  fish.  prevent  and  important in  British  However, the  use  less  gear  catch.  size  the  the  to  increase  by  behaviour  the  this  Program  ability  hand,  for  intensity  are  smaller of  access  the  actions  controlling  restrict  stock  elasticities  the  of  take the  as the  On  dissipating  artificially  necessary to  Both  and  Enhancement  the  dissipation  gillnet-trollers  contained  upon  rent  and  operators,  the  implemented  to  Fisheries  ignored  rent  would  of  largest  much  means  elasticities  attempts  the  but  for  been  critically  than  has  information  program  Table fuel  inputs.  Salmonid  depends  for  the  the  results  used,  that  has recently  of  preventing  which  The  inputs  seine  licensing  fish.  The  in  latter.  Department  behaviour  scope  discussing the  of  the  particular,  still  especially the  two  the  regulator  components, introduce  decades  succeeded  the  Results /  fleet.  controlling  has  the  that  last  and  elasticity  significant. of a  output given  more  labour  and  different  from  zero,  between  stock  and  This and catch  suggests to to  that  the  use  rise.  One  whereas output  is  increasing of  more  possible  Econometric Technique and Results / 113 Table  5.19:--Nonlinear  estimates  of output-variable  own- and cross-price elasticities:  gillnet-troll(crs) Quantity/ Price  Output  Labour  Fuel  Gear  Output  0.191T (0.117)  -0.011 (0.049)  -0.184t (0.087)  (0.008)  0.030 (0.137)  -0.057  0.027  (0.073)  (0.118)  0.001 (0.009)  0.678T (0.319)  0.035 (0.155)  -0.725T (0.296)  (0.025)  -0.0004 (0.0008)  0.00004  0.0004  (0.0003)  (0.0007)  Labour  Fuel  Gear  0.004  0.012  -0.000008 (0.00003)  Note: Asymptotic standard errors are in parentheses and the symbol " t " signifies that the estimated elasticity is significantly different from zero at a = 0.10.  Econometric Technique explanation Access  of  to  certain  is permitted. a  given  the  stock  Hence,  the  at  catch  vessel  area for  further  study  For  gillnet  fleet  the a  but  substitute  harvesting inputs,  For  the  the  troll eg.,  0.247%.  Neither  stock  per  a  effective  1% the  unit  an  stock  is  also  a great one of  the  increase  increase  in  demand  1976).  However,  I  this  the  from  stock  stock  between  that fleet.  This  vessels,  on and  existence  repeated  might  be  this  for  This  of  the  finding  a  fruitful  5.15.  has a  output order  know  and  the  On  the  negative  increases to  the  stock  other  sign, as  assess  relative  fish  hand,  indicating  the  the  is  stock  impact  costs of  of  upon  the  two  output.  size  the  Output  the  it  Thus, in to  gear  Table  that  results nor  vessels  included  conditions.  problem  fishing  fishery.  zero,  in  not  is not  different  of  the  114  conditions. seine  more  have  This result  externality  in  change  5.16.  indicating  4.  under  need  changes, Table  to  reflect  extent.  fuel  regard  may  observed  in  number  elasticity  is significant,  would  a large  which  negative  intensity  for  thereby  with  to  of  in  the  stock  different  and It  magnitude  stock size size,  elasticity  fuel  not  fleet  services,  as the  the  days  fish,  fish  the  be  Results /  regulated  of  Chapter  they of  may  highly  of  abundance  rent dissipation  relationship.  costs  and  but  under  number  there  Lee in  fish  the  the  The  and  significantly  fish increases, but  by  time,  developed  of  between  seiners  larger  investigation  not  elasticity  The  types,  that  positive,  one  (Huang  suggests  the  any  model  an  that  per vessel.  externality  three  is  is controlled  ground.  possibility in the other  result  areas  fishing  smaller  a  this  and  leads  in  an  is very  would  a  increase  demand  Salmonid  to  for  greater in gear  also  labour  be  the  labour of  appreciably  increases  Program case  of  demanded  changes  responsive to  Enhancement  use  in  the  might  be  insofar  as  the  Econometric Technique and Table  5.20:--Nonlinear  estimates  of  output-constant  price  elasticities:  Results /  115  gillnet(non-crs)  Price/Quantity  Fuel  Gear  Fuel  -0.457E-12 (0.272E-06)  0.686t (0.368)  Gear  0.080t (0.036)  -0.214E-12 (0.127E-06)  Note: Asymptotic standard errors are in parentheses and the symbol "t" signifies that the estimated elasticity is significantly different from zero at a = 0.10.  Econometric gillnet-troll a  fleet  decrease  fuel  in  demands  responsive. the but  a  the  seems  of  fish  increase  output  the  program,  the  be  this  of  the  of  is  any  of  size  stock  size  5.17.  leads  Labour  output  is  to and  somewhat reduced  pairwise  comparisons  are  suggestive,  Enhancement  Program  could  made  be  possible by  doing  having  catch  116  be  of  the  but  Results /  would  catch  require as  of  in  and  Table  changes,  harvesting  capable  as well  increase 0.872%,  size  given  of  the  not  would  program,  stock  Salmonid  value  this  1%  increased. These  costs  model  a  demanded  total  or the  sample,  the  cost  of  the  since  administering by  that  hand,  to  gear  when  the  analysis  so  other  that  were  complete  in  of  unchanged  simulation,  the  quantity  are  It  stock  is concerned. For this  Technique  a  full  costs  a  full  compared  with  the  a greater  stock.  On  analysis  on  costs  of  cost-benefit  knowledge  opportunity  requires  if  about of  the  the  resources  used  it.  One  final  gillnet  set  fleet  labour  to  relationship elasticities  fleet returns made returns  and  input,  surprise  Before  of  to of to  describe  Table find  with are  ending with  elasticities  the  5.15. that  the  intensity  amount  fuel of  returns  scale.  for  variable scale  factor case  the  small  scale  gear  labour  used  from  more  have on  and  vessel  cross-price elasticities, has  discussed.  They  variable  inputs  the of  mention  scale  gillnet  be  the a  board  gillnet  pertain and  the  operation,  very  strong  the  vessel.  to  it  the fixed  is  no  complementary As  well,  these  the  gillnet  zero.  brief  to  to  between  and  a very  non-constant Results  the  different  section,  remain  relationships  Given  both  significantly  this  of  significant  is the  do with  given  to  results  gillnet-troll not the  elasticities,  differ  fleet  when  exception Tables  for  with  a  comparison  that  5.18  constant  the  is  constant  (output-variable)  Econometric Technique and Results / 117 Table  5.21:--Nonlinear  estimates  of output-constant  price  elasticities:  gillnet-troll(crs)  Price/Quantity  Labour  Fuel  Gear  Labour  -0.056 (0.067)  0.028 (0.106)  0.003 (0.018)  Fuel  Gear  0.689T (0.328)  -0.071 (0.088)  0.50E-4  0.0004  (0.0003)  (0.0008)  0.666T (0.286) -0.133E-06 (0.486E-05)  Note: Asymptotic standard errors are in parentheses and the symbol "t" signifies that the estimated elasticity is significantly different from zero at a = 0.10.  Econometric Technique and and  5.20  elasticity respect the  (output-constant). becomes  to  the  stock  case,  the  (output-variable) not  significant  and  significant,  to  change  between  but  indicate  Table  and  Table signs,  variable number  5.21  ones.  a  regard  insignificant,  elasticities  scale  In  5.22. but  factors of  the  elasticities  of  intensity  The  elasticities  of  output  are are  elasticity  the  significant.  slightly  higher  results  of  gear  labour  relationship,  although  not  the  and  the  the  gear  and  with  For  in  does  Labour and  between  elasticity  complementary  not  significant  (output-constant).  The  whereas  to  change,  to  insignificantly  fuel/stock inputs  constant  with fleet  returns  to  Tables  5.19  substitutes,  tonnage  respect  118  gillnet-troll  become  net  Results /  becomes  stock  but  larger  changes  different  from  sign zero,  5.23.  3. Returns to Scale  Since  some  calculate by  samples  the  degree  evaluating  the  (5.14)  The  R  sample  sample  that  of  factor.  factors,  T  It  scale  (Z^  =  S  of  of  hypothesis  returns  for  of  returns  them  is  actual profit  expression  is found  returns  scale. If  the to  restricted  fixed with  computed  with  O T T ( P , Z ) / 9 Z .  predicted  the  restricted  along  to  of  the  to  (Laitinen  scale 1980).  it  is  This  interesting may  be  to  found  following expression.  mean  means  derivative  reject  by  using  estimated be  greater  less than  one,  the  are  to  this  .  )  is  used  sample  one,  the  T T ( P , Z ) )  /  used  a fixed  parameters. than  Z  profit  factors  respect  ) *  If  in  in  the  factor  means the sample  the  denominator  numerator.  is the of  the  number is said  indicates decreasing returns  The  shadow prices  first  price and  calculated to  and  have  to scale.  by  of  fixed this  increasing  Econometric Table  5.22:-Nonlinear  estimates  Technique and Results / 119  of elasticities of intensity:  gillnet(non-crs)  Quantity/ Fixed Factor  Stock of Fish  Net  Fishing  Tonnage  Days  Output  -0.059 (0.166)  -0.038 (0.199)  0.438T (0.111)  -0.100  -0.197 (0.193)  0.240 (0.247)  0.699T (0.151)  0.949T (0.355)  0.703 (0.748)  0.049 (0.264)  0.338T (0.154)  1.128T (0.445)  Fuel  Gear  Labour  (0.295)  Note: Asymptotic standard errors are in parentheses and the symbol " t " signifies that the estimated elasticity is significantly different from zero at a = 0.10.  Econometric Technique It  should  called  noted  returns  literature.  to  of  in the  levels  The  expression  the  seine,  Since further seine troll  measure and  For  fixed  change  (5.14) is used to and  need  of  returns  necessarily  called  in  manner  notion  not  appropriately  the  local  restricted  at  to  scale  their  returns  profit  described  a  used  optimal  to  for  above  size  120 and  in  the  levels,  the  (Laitinen  proportionate  1980). change  be  troll  calculate  samples  accepts  the  calculated.  samples,  Appendix  2  the  using  degree the  hypothesis Nonlinear linear  for  nonlinear  local  appropriate  of  parameter  returns  to  parameter  constant  parameter  whereas the  of  returns  to  size  for  estimates. scale,  no  estimates  are  used Tor  the  estimates  are  used  for  the  for  the  estimates  and  Appendix  3  ones.  the  2.0390,  seine and  scale.  sample  for  That  the is,  a  of  profits  counter  to  accepted  alone few  has  of  the  of  fishing  the  effect  in  salmon areas of  a  1%  of  untapped  boats  the  troll,  increase  a  are  in  Results /  factors.  sample  See  the  factors  percentage  gillnet-troll  sample.  linear  to  gillnet  typical  is more  gillnet-troll,  the  not  fixed  all  in  calculated  the  the of  measure  is  returns  measures  the  scale  Because  measure This  that  and  value 1.3497.  wisdom  of  all  first  the  expression  the  in  At  in  economies  the  Only  increase  0.2860%.  few  of  seine of  fishery  scale  and  days.  However,  the  fleet is highly  regulated,  both  and  times.  regulated  These  results  diseconomies of  fixed  this  which could  terms  suggest  scale.  for  exhibits factors  leads  might  suggests  that  the  entire  is very of  the  gillnet-troll,  decreasing  finding  take  explanation in  0.2860;  sample  the  glance  is  only  appear the catch  simple.  is  observed,  to  an  to  run  seine  fleet  with  only  This  vessel capacity  that what  returns  and in  segment choice fact,  is  Econometric Technique and Results / Table  5.23:--Nonlinear  estimates  of elasticities  of intensity:  gillnet-troll(crs)  Quantity/ Fixed Factor  Stock of Fish  Net  Fishing  Tonnage  Days  Output  0.031 (0.179)  0.753t (0.218)  0.238t (0.119)  Labour  0.028 (0.077)  0.734t (0.098)  0.240t (0.066)  0.014 (0.166)  0.620t (0.207)  0.403t (0.133)  -0.830t (0.523)  1.910t (0.623)  -0.091 (0.364)  Fuel  Gear  Note: Asymptotic standard errors are in parentheses and the symbol "t" signifies that the estimated elasticity is significantly different from zero at a = 0 . 1 0 .  121  Econometric Technique On  the  size. of  other  This  the  is not  entire  benefits means  the  faster  to  trips  of  at  one.  sample.  such  constant  is  abundance  of  for  the  constant  although  estimates  parameters to  scale  is is  no  of  apparent  by  (1984,  New  England for  estimated the  the  upon  towards  data-based  results  significantly  relies  biased  Squires  scale  are  different  certain  evidence  of  this  researchers  1987a),  calculates  two  as  0.4513,  fixed  factor  Trawl  years  of  whereas and  As  are a  fishery, his for  modeled  the  vessel is  to  scale  0.010  should  Since the  being  close  by  this  test  for  insignificant,  hypothesis.  One  earlier,  an  is  level.  be  obtained  zero.  indicated  and  the  cause  of  analysis  of  phenomenon.  other  Otter  of  easier  the  (5.14)  parameters  acceptance  multicollinearity.  from  thereby  vessels  at  parameter  in  periods,  returns  rejected  it  capacity  gillnet-troll  imprecise  sets  is  size  the  reveals  returns  to  gillnet-troll  that  vessel  means  lies  data  to  the  also  explanation  the  returns  abundance  hypothesis  significance,  longer  in  precision  multi-species  of  stock  for  to  regulated  means  Greater  122  returns  least  operation  abundance.  grounds  returns  the  troll  is the  expression  many  thesis.  level  stock  it  evaluated  of  this  that  the  are valid for  of  since  Results /  increasing  the  sample  two  Greater  degree  of  fishing  arguments  given  nature  have  is that  lack  Only  the  fleets  troll fleet,  greater  port.  large  0.005  returns  gillnet-troll  to  the  the  a  on  same  a  for  gillnet-troll  expectation  The Not  and  As well,  stay  back  The  the  a priori  troll  vessel and  can  disturbing  accepted  fleet.  larger  catchability.  somewhat  The  a  the  the  a surprising result  trailer  finding  both  salmon  from  minimizing  The  hand,  and  comparable returns and  study. 1981, by  it  to  finds  For is  means  to scale  the  0.3889. a  In  obtained  measure  evidence  1980  of  those  of  dummy  the  decreasing  degree his  for  for  of  scale  model  stock  variable  for  Econometric 1981.  In  obtains  a a  measures  D. The  later  study  calculated are  results  indicate  substituting  toward  tonnage  way,  seine  troll  fleet  England  returns  may  inputs,  against  restrictions  have  to  a net  appears  two  days  given  because of  a  rent  sea  scale  scallop  equal  fishery  to  5.92.  Squires  123  (1985)  Obviously,  these  the  variable  inputs  in  to  control  a  great  for  rent  dissipation  restriction. have  the  deal  other  on  hand,  The  more  fleet the  catch of  gillnet  through  the  entry  moderately  substitution  appears  face of  of  the  potential  the  limited  been  employed  the  use  fishing control  of  days it  to  number  behaviour.  greater  absolute  three  the  restrictions  The  seine  has  capable  a  per  and  vessel  vessel.  resource  In  this  rent.  The  gillnet-troll  use  of  of  fleets  more  variable tonnage  program  with  net  successful  for  two  of  the  catch salmon.  dissipating  harvest.  the  On  to  technology  particular,  dissipate  appears  of  fishing  In  attempts  tonnage  a  all  may  restriction  means  of  that  used to  types  that  preventing fishing  use  scope  vessel  salmon  believed.  likewise.  little  vessel types  the  the  do  per  the  previously  vessel-owners  to  the  of  that  restriction  appear  Of  value  New  Results /  CONCLUSIONS  than  four  the  and  truly fishery-specific.  possibilities  net  of  Technique  For  control  of  fishing  example,  variable  gives them  an  inputs.  restriction  behaviour  is to  days  increase  This  also stop  is  raises  popular fishing  in  the  most in  fishery, effective  at  number  of  the  the with  activity.  it  costs the  of  taking  regulators  VI. MEASURING FISHERY RENT DISSIPATION  This  chapter  Although the  presents  in  the  of  the  types.  Second,  profit  sum  may  to  quantities.  A  investigated  of  means  seminal  from  obtain  predictions  the  In  I  Case  obtained  Substituting for  II)  of  rent  where  profit  of  increasing  net  tonnage  are  found  variable  quantity  choices.  the and  Rent  Third,  calculated  estimated  output  levels  of  of  and the  the  the  fishery  levels variable  four  vessel  economically  is defined  optimal the  efficient  in  1982  as total  the  in  for  124  to  the  role III).  the  for the  the  actual  levels  of  is  revenue  rent  entails  obtained  variable this  tonnage  substitutability  is  the  of  new  associated  the  from  to  doubling  equations.  Then,  restricted  permits  derived  This  tonnage  the  attributable  estimated  data  net  the  input  the  of in  of  possibilities.  solve using  I)  amount  parameters  dissipation  (Case  terms  to  for  tonnage  rent  substitution used  of  (Case  exercise  price  or  profit-maximizing  of  regulator.  the  the  of  rent  extent  another  for  level  associated  the  of  knowledge  actual  (1969),  prices  each  rent.  costs.  estimate  optimal  the  the  performing values  the the  reveals by  from  for  fishery  Pontecorvo  given  optimal  static  fixed  be  the  of  the  with  actual  and  an  along  for  and  uses  profit-maximizing  total variable  4,  it  This is done  vessel,  Chapter  5,  measurement  Crutchfield  First,  Chapter  per  in  by  aspects.  describes  of  empirical  work  profit  imposed by  the  each vessel-owner.  comparison  parameter  arbitrary  sum  solve  (Case  restrictions  by  for  novel  to  vessel.  as shown  researcher  of  each  function.  exercise  factors,  as the  vessel  the  information  for  minus the  of  equations  controlled  calculated  method  several  demand  This  choices  per  has  restricted  quantities  the  spirit  procedure  supply/input  a  This  optimal  is  an  levels  profit-maximizing  from  this  scenario  Measuring can  be  compared  to  that  amount  of  rent dissipation  Fourth,  in  each  required  to  minimum  and  estimate  No the  take  of  by the  1976).  on  It  the  ignores  A. THE  the  done  not  harvest  of  that  deadweight  resource.  ground. itself  vessels also  gear  and  for  in  a  called  rent  a  of  of  the  of  4  Scott  it  the  find  through  forms  attributable  The refers  (Huang  of to and  vessel caused  second to  is  the  other  called  possible  vessels.  As well,  estimated  an  1985).  further  per  the  vessels  to  externality  by  of  occurs  both  effects.  and  that  catch  vessel  these  and  125  fishermen.  between  used  area.  since  one  the  number  two  stock  in  of  be  rent  are  fishing  Chapter  dissipation  FISHERY  the  gear-fouling,  measurement  can  They is  indicates  difference  Furthermore,  particular  in  The  reduction  equipment  described  the  OF  the  as  first  difference  minimum  loss  Dissipation /  activities  fished  ignored. The  Rent  loss (Munro  fish  technology,  CALCULATION  vessels  are  the  catch.  of  other  aspects of  for  intertemporal  manifests  allow  solve  the  the  The  input-substituting  estimate  dissipation  the  second.  salmon  redundancy  externality, to  do  these  of  the  to  1982  number  fishing  usually  presence  restrictions of  rent  congestion  damage  to  depletion  period)  possible  actual  actual  made  excessive  the  is  the  the  is  overcrowding Lee  it  in  attributable to  seasonal fleet  attempt  (within  case  generated  Fishery  in  the  Data model  Chapter  5,  problem.  RESOURCE  RENT  1. Theoretical Measures of Fishery Rent  The  basis  fishery.  for  The  the  first  notion  is the  of  fishery  rent  self-reproducing  comes  nature  of  from the  two fish  features population;  specific the  to  the  second is  Measuring that  the  catch.  minimum  For  maximum  a  instructive  of  to  a harvest  present  as the  4.  equation  the  difference  now  associated the  sustainable  a  possible with  a  standing yield  understand  and  the  than  and  in  model  describes  the  growth  the  rent  is  cost  is used instead  described  logistic  functional  of  net  market  the  as  the  (Cordon  1954).  For  the  1955).  into  context  fishery.- This  natural  of  defined  chapter  the  value  simply  (Scott  this  function  the  natural  net  the  F(X(t)) -  net stock  growth  begins  rate  of  To  this  is  (6.1),  as  is used.  it  is  with the  a  fish  appended  the  of  of  is  fish  adopted  stock  growth  is  for  described,  rate and the  in  discussed  equation  harvest  rate,  fishery  as  in  (6.2),  (6.1).  h(t)  sustainable  growth  effort  notion  form  of  define  the  fishery  revenue  growth  =  zero  less  126  g(E(t),X(t))  net  to  is  Dissipation /  function.  =  x(t)  reduce  that  between  (6.2)  is  work  Cobb-Douglas  Then,  maximum  Cordon-Schaefer  F(X(t)). Typically,  the  fish  calculation  the  the  the  sustainable  value  h(t)  Chapter  the  between  (6.1)  To  case  rate production  Generally,  catching  putting  differential  population,  It  of  case a present  means  simple  static  difference  dynamic  As  the  cost  Fishery Rent  rate  fish.  of  This  the  yield  from  stock.  describes  the  That the  is,  harvesting  relationship  the  catch  does  between  not the  used.  sustainable  resource  rent,  prices  and  costs  must  be  Measuring appended landed  to  fish and  represents effort  marginal  measures  its  price  product  resource  biological  a constant  the  (constant) the  the  of  rent  the  unit  is found  uses  sustainable requires  the  with  entrants  are  is  maximized.  open  common  dissipated.  One  may  re-express  two  types  sustainable of  the  revenue  sustainable the  optimal  level  sustainable of  the  is  stock.  In  the  contrast,  there rent  unit  of  as  the  effort  a  is  maximum  fish  given  by  sustainable  two  functions  no  driven  cost  open  effort  this  put  fish  clear  authors  costs are  now  stock  the  there  new of rent  are  compare a  function  falls.  Maximum  maximum  difference  function. access  as  resource  that  is  upon  comprised  These  the  there  zero  returns  makes  the  when  to  the  where  of  controls  where  namely,  fishery  amount  normal  of  total  the  are is  that  level  the  of  is defined  the  for  of  is  Total  before;  price  price  access  levels.  as and  of  1985).  defined curve  The  Scott  the  cost  between  Open  manner  as  the  the  equilibrium  and  market  fishing  state  above  increase  revenue  fish  (Munro  a  constant  127  effort.  and  the  associated biomass  they rent  in  of  Dissipation /  revenue  distance  resource  by  and  effort.  effort.  bionomic  model  of  a  the  of  compares  resource  fishery  so-called  the  ie.,  resource  between  the  dissipation to  of  Sustainable  Gordon's  rent  biomass,  to  cost  optimal  He  level  property  used.  is the  is entirely  of  access  total  total cost  the  fish,  sustainable  maximum  rent  effort  This  the  of  amount  describe  attracted  rent.  the  as the  unit  The  both  Furthermore,  Then,  yield.  and  a  cost.  cost times simply  of  to  the  of  social  assumes  effort.  model  the  for  amount  fishery  this  benefit  revenue  resource  competition  social  Cordon  cost of  sustainable  describing sustainable  Gordon  unit  marginal  times  model.  Fishery Rent  This  case  of  defines  the  zero  rent  Measuring obtains  at  access term  a  lower  competitors this  Class  I  occurs  the  form  biomass effort  at  drive  Class of  when  stock  rent  the  its  I  the  at  the  Type  of  levelt,  and  behave  in this fashion by the  form  may of  continue  static  considerations  and  1970,  II  Type  total  does not  the  allowable  presence of equal  of  total  level.  harvest or  I  in  refer  when  this  revenues. t  I  open Clark as  the  Problem  maintain  the  amount  of  excessive number  of  They  In  this  Property to  123  and  control the an  harvest.  to  order  cannot  because  Munro  Common  fishery rents.  to  occurs  problem.  dissipation occurs  for  until  the  are  the  The  (harvest  for  Instead  present value  describes  represent  Following  1976).  objective.  the  not  developed  Clark  control variable  this situation  does  important.  the  solution  maximizes in the  are  maximize  optimal  rise  model  techniques  Smith  is to  to  optimal  Dissipation /  are  encouraged  manner call  this  total the  to  harvest Class  II  rent dissipation.  Cordon's  control  compete  the  either  its  Property  Class  restricts  Rent  overexploitation  below  Common  but  vessels  costs  stock  dissipation. The  fishery.  fishermen  Economic  fish  government  optimal  directed  level.  Fishery Rent  of  the  the  suggestions  analysis of the  time  of  flow  path  In  discount rate is set to  the  maximizing of  of  monopoly exploiter rate).  complete  order  to  of  Scott  fishery  static  rents the  picture  stock  Class  goal  optimal  1970, the  a period  achieves this simulate  rent  variable  intertemporal  (1955),  (Plourde  fishery  over  if  of  Quirk  objective time.  (biomass)  The that  through changes  I rent  dissipation in  infinity.  tThis is called a total allowable catch policy; it is used to regulate the total harvest of the British Columbia commercial salmon fishery. tMunro and Scott mention that rent dissipation may also result from crowding externalities or through the processing sector. In the former instance competing vessels disrupt each other's harvesting efforts. In the second the fishing season may be shortened as the harvest is taken ever more quickly by a greater number of vessels than optimal. This means that processing plants operate at full capacity only for the duration of the fishing season, then lie idle for the rest of the year.  Measuring In order  to  necessary 1979). of  address the Class  to  adopt  The two  a  state  2-state,  optimal  biomass level  of rent  to  complex.  Class  if the fleet size  model  be the  the assumption II  Dissipation / 129  dissipation in a dynamic  variable  are taken  Under  becomes analytically  form  2-control  variables  vessels in the fleet.  solution  II  Fishery Rent  of  (Clark,  biomass  setting  Clarke,  level  non-malleable  and  Munro  and the  capital*  rent dissipation may still  it is  number  the  optimal  occur at the  is too large.  2. Empirical Measures of Fishery Rent The  empirical  common (1975) of of  measurement  property  problem  and Gardner  of  (1980)  provide  management.*  comparison  with  reproduction function Loose  the  function  is estimated.  ones  for two  Their  fleet  vessel types  present  profit-maximization.  Loose  the  The  solution  set  to  of research.  value  estimates  in  using  are  presented  this  thesis.  historical  This is specified at the level  change.  For  results  obtained  technological value  present  attributable  level  and adjusts  modeling  includes  fishery the  each  Next,  However,  his measure  is  completed  an  estimate  by  of  I  type  both  a  of  a  harvest  effort  Loose flow  of  a  biological production  gillnet  vessel by  repeats  by an index the  of  a system  purpose  the latter  adopting  optimal  under  case  of the individual  by Gardner.  Class  of the intertemporal  for  In  data.  the  For example,  in the British Columbia salmon  is estimated  and at the aggregate  calculation  dissipation  is not a new area  rent that could be earned optimal  rent  criterion  escapement  the of of  and the  tNon-malleable capital implies the existence of fixed costs that cannot be salvaged by a shifting of the resources used to another activity. *However, G o r d o n considers only the Fraser River sockeye fishery and allows two types of vessels to fish, whereas Loose examines only the Skeena River gillnet fishery which harvests two species of salmon. In neither case d o the authors attempt to generate estimates for the industry as a whole.  Measuring optimal  amount  scenarios.  The  fleet  a  on  of  fishing  first  allows  weekly  basis  follow  an  annual  Loose  simulates  hiring  the  interest  the  net  dollars.  For  Case  the (Case  comparable optimal  he  calculates  the  For the  first  case, the  optimal  1975;  of  this  for fleet  Gardner vessel the  the  second,  the  types  to  take  increase  in  profits  These  life-cycle cost  15%  of  the  one.  combination  optimal  the  represent  salmon. of  He of  fishery  23.6  of  less.  Loose  fishery  to  series  to  44.8  hire  for  less than he  the  each  a 6%  in  optimal  actual  does  not  to  rates  rate  constant  $54.4  the  necessary  interest  I and  and  two  monopolist  different  million  $31.9  boats  However,  of  130  compares  the  For Case  are  Dissipation /  days).  constrains  fishery.  is 52%  His  vessel  finds vessel  types  that types,  estimated  to  be  between  0.51  represents  an  from  studies  of  is  19%-44% also  harvest  In rate.  of  calculate  of  1975  million.  number  cost spatial  to  take  the  2.2  boats  the  cost  of  1.23  profits  over  the  to  ascertain  catch,  earn  rents  with  million  type in  3.5%  from  actual  of  combination  ranges  him  optimal  the  rate  the  in fishery  to  in  permits  measure  38%-208%  least  dollars  already  and  relevance  1951  of  that a  the  uses a discount  in  needed  but  This  several  rents)  fishermen  increase.  of  He  methodology  to  increase  and  increases  rent  are  a  numbers  catch.  resource  There  the  escapement  optimal  (or  number  combination  optimal  of  number  is  second  Using  number  the  Rent  redundancy.  solves for  million.  it  the  from  the  vessel of  2).  value varies  as  owner  while  (Case  value  addition,  in  1),  present  present  (modelled  monopoly  policy  net  II  effort  Fishery  combination II  rent  1951  rent over  measurement  finds  to  2.55  four  year  the  least  than  the  sub-optimal  would  permit  dissipation.  current the  and  rather the  of  dollars.  It  is This  salmon cycle.  of  rent  dissipation  Measuring associated  with  1969,  Huppert  most  closely  are  1969) the  related  regulators  that  Starting  from  unit and  in  In  to  order  procedure. required  year rates  in  is  harvest  the  landed  a  chosen  such  that  the  those  period  excessive  harvest  remaining  years  the  price  will simply  for  the  of  calculate  the  catch.  that  inputs, would  from  inputs  First,  as being  used  tThis assumption means that the surplus (Copes and C o o k 1984).  are  price  times  represent base,  indexed  need  * J . A. Crutchfield and G . Pontecorvo. The Irrational Conservation. Baltimore: The Johns Future, 1969. p.m.  the  cases  by  of  the  individual  follow  a five total of  the  actual  catch.  Second,  a  of  fishing  effort,  and  required  that  the  fishery.  the  not  base  year,  calculate  the  the  the  For  value  base  They  prevented  each  thereby  the  harvest  inputs.  war  step costs  revenues  arguing  in  rent".*  minimum  minimum  the  fishing  gross  at to  both  has resulted  to  implicit  authors  less  In  from  the  the  directed  authors  the  Pontecorvo  optimally  costs  British  recovered  fisheries  are three  the  independent  in  or  calculate  distribution  their  is  reduction  revenues  been  two  latter  and  fisheries.  both  as explicit  they  in  determined  in  Bay fishery  total  landed  the  "any  dissipation  131  Pontecorvo  first  the  have  catch  entry  The  thesis;  salmon is  the  accrue  Bristol  Sound  and  (Crutchfield  could  catch  that,  argue  1942-1943  effort  annual  this  work  that  Puget  they  given as  rent  that free  they  year  total  in  1979).  rent  seminal  Dissipation /  (Crutchfield  Wilen  with  assumption  rent  each  choose  Washington  and  developed  The  resource  the  aggregate  approximate  of  problem  Pearse  concerned  fishery.  that  essence  1979;  are  salmon  the  property  methodology  they  calculate In  to  the  dissipation  the  1977,  Bay and  assume  rent  common  amount  and  complete  fishery  the  Bristol  authors  costs.t  to  because  estimates  II  Fraser  commercial  Alaska  the  Type  1982,  included  Columbia  the  Fishery Rent  of  creating  of  the an  consumer  Pacific Salmon Fisheries: _A_ Study in_ Hopkins Press for Resources for the  Measuring index  of  fleet  efficiency.  yield  per  unit  of  years  1934-1959,  annual true  harvests  amount base  of  is  projected  this the  net  As  an  yield  difference  at  step  used  the  is  profits  from  alternative per  provides  boat an  and  the  year  the  of  the  fourth  per  day  may the  that for  of  the  annual  for  each  all  factors  two  minimum  rent  gross earnings  of  arisen  efficiency.  Since  the  revenues  amount  of  dissipated  the  in the  step be  two  the  used.  minimum  scenarios: the  authors Dividing  number  this  of  boats  are  paid  actual the  obtained  by  an  as  by the  the  to  the and  given,  comparing efficient.  estimate  into  required  and  limited  taken  and  their  by  fleet  rent  the  recorded  the  been  that  yield  is  the  fleet  actual  suggest  over  the are  132  maximum  as indicated  potential  the  of  scenarios,  number  had  the  relationship  have  calculating  fishery  of  actual  of  estimate  yield-effort  assumed  measure  would  to  estimate  a  is  an  needed  computed  level  the  inputs  are  that  to  of  costs  between  equivalent  constant  it  Finally,  highest  a  Dissipation /  provides  Fourth,  each  earnings  also  quantity  Total in  year  assuming  minimum  costs.  gross  operated  Third,  requirements.  the  base  calculated.  inputs  year  taking  effort. the  opportunity  The  Fishery Rent  of  the  total  catch  the  entire  from  1.850  land  catch.  Estimates million The  of  the  amount  (1934-1939)  relative  amounts  1959  period.  Data  for  fishery.  the In  Puget  particular,  to  of  3.608 of  million  redundant  Sound it  dissipated  is  (in  gear  are  not  not  possible  rent  are  1959) range  as well for  substantial in  from  constant 33%  developed the  to  and 1951 83%  as those  authors  to  range  American over  for  the  the  designate  a  dollars. 1934  to  Bristol  Bay  base  year  Measuring period.  This  fishery  rent.  along  the  dollars  authors  claim  fishing  with  times  of  reduce  net  one  in  estimate  the  at  million  as  given  potential  of a  then  net  in  entry  methodology and  State  for  the  herring  roe  vessel program  fishery  of  could  the  form  fishery and  are  and  1979.  The  catch  extent.  of  (Huppert  latter  data  from  the  net  fisheries are  5  vessel  1982).  is  used in their  of and  claim and  7  fishery  is  fishery It  to  is set  1960-1965.*  This  per  boat.  revenue inferred  tThe gears are the drift, gill, and seine and the data are generated W. Royce, D. Bevan, J. Crutchfield, C . Paulick, and R. Fletcher Limitation in Northern Washington Waters", University of Washington Fisheries, new series, vol 2, no 1, 1963. ^Recall that only  They  dissipation  Pontecorvo. Total per  gear  salmon  rent  The  amount  between  period  seasonal quotas  by Crutchfield  1958.  Columbia fishery.  the  data  calculated.  use of  the  fishing  cost  in  true  reach  net  cost savings in  million  from  British  II  gear  Columbia  data  and  and  the  runs,  major  price  potential  133  potential  salmon  landings  greater  British  used  potential  a  in  three  governing the  catches for  Class  upon  3.771  to  use  of  the  underestimate  the  and  for  the  or  costs  that  prices and  with  types  1955  the  simulation  quantity  regulations  from  claim  basis of  California  limited  the  the  Using actual  the  fact  economic yield  dealing  the  1978  benefits  Washington  on the  paper  for  may  loss  effect  gear  in  harvesting  the  the  million  measure  studies  gear. in  three  would  to  follows  the  of  similar  by  of  Dissipation /  computer  the  of  because a relaxation  authors  managed  estimate  reductions  2.639  likely  a  to  utilization  amount  figures  The  examination  to  attempt use  area  in the  to  dollars.  second  and  in each  million  The  Pontecorvo  authors  these  annual flow  $15.0  ambitious  alternate  amount that  rent  that the  the  reduction  current  potential  and  reductions  available  a 50%  less  efficency  permits  arbitrary  rents  With  physical  This  days of  a  Crutchfield  with  gears.t  necessitates  Fishery Rent  is  fishery  an is  Huppert is from  taken the  in a study by "Salmon Gear Publications in  calculations.  Measuring 1976  and  those  1977  years.  earnings  catch  An  per  statistics,  estimate  vessel  in  of  since the minimum  1979,  for  enforced.  Therefore,  the  author  that total  revenues  equal  total  economic increase  rent) of  figures  100%  are  regulations, positive  for  the  the  gear  and  rent  types that  and  are  vessel  as the  individual to  disregard single,  vessel  These  for  include  basis of  the the  the  role  homogeneous  of  vessel  The  increase  for  type.*  the  of  a  of  an  constant  restrictions  substition,  the  and  addition,  of  by a  a  prices  and  season The  argues  Furthermore,  he  the  minimum  vessel.  and  Pontecorvo  technically  efficient  model  on  input  dissipated  These  change.  effort,  rent  an  12%.  unit  maintained  1978,  of  than  the  (or  reorganization  costs.  per  profit  Huppert  behavioural per  for of  Crutchfield  explicit  and  and  not  so-called  catch  is dissipated  fleet.  more  average not  gear  does  for  is  dollars  because  use  taken  choice  lack  In  types  the  potential  existing  harvesting  to  in  134  largest  program  increase  seasonal quotas  approach  of  an  size  the as  that year  the  gear  lower  of  arbitrary  input  that  are  entry  million  1979,  incentive  in the  gear  3.15  underestimated  existence  the  of  costs.  in  no  assumption  effects  for  reducing the  comparison, the  the  rent  at  Dissipation /  obtained  all  among  result  is  limited  assumption  likely  has  shortcomings  fisherman,  incorporate  most  figures  the  dollars  by  effort  vessel  year  estimated  the  probably  because of  several  Huppert.  is  this  million  is achieved  would  necessary inputs  is  distribution  rent  each  in  per  per  suggests that  fishery  under  catch  cost  opportunity  0.661  estimated  projected  suggests  There  and  resource  that  the  catch  Fishery Rent  the  the  failure  choicet,  assumption through  of  of  a a  crowding  tHowever, the authors note that gear and season restrictions may contribute to higher harvesting costs, thereby lowering potential rent (Smith 1969, Crutchfield 1979). * N o t only is inframarginal rent taken to be zero (Copes and C o o k 1984), but differences among vessels and/or gear types are ignored.  Measuring externalities is not in  thesis.  turning  fishery  rent,  This  two  to it  the  been  a  by  Fraser  issue  of  order  to  capital  and  its  growth  is characterized  Fraser  compares  dissipation since  the  average  real  has taken  annual of rate  growth  of  These  studies  suffer  from  importantly,  the  prices  increasing  and  means authors  that do  capital  the  one the  they  capital  Wilen  value  Over  the  period 3.3%,  Thus, they  an  overly  the not  roles  In  Scott  135 1985)  proposed  rent  analysis  therefore,  by  dissipation  that  played  addition,  the  to  do  fleet's  1969  rent  season,  dissipation. to  a  35% rent  capital  costs have  increased  has  they  argue  decreased  limitation  implicit  they  salmon  the  1977  to  they  the  rent dissipation  the  of  They  that  compared  between  (1979).  commercial  with  However,  other  earlier,  suggesting  license  by  calculate  by  capital  simplistic  Wilen  value  1969  to  mentioned  complete  from  of as  real  concludes  of  thesis  Columbia  their  agree  this  and  the  sugest that  distinguish  costs.  and  papers  Pearse  program.  the  in  calculate  He  limitation  be  by  costs  resource.  to  and  methodology  rent  three  British  begin and,  and  of  used  other  of  costs 4.4%.  This  in  license  rate  at  technology.  access  Pearse  the  in  They  increase  the and  time.  open  program.  revenue  methodology  issue  place.  captal  the  (Munro  in the  analysis  Dissipation /  a fishery.  this  of  of  for  1979)  value  growth  the of  by  deficiencies  complete  dissipation  over  49%  imposition  inception growth  a  these  discuss  (1977,  rent  processing companies  more  to  examine  which  the  of  conducted  worthwhile  In  in  a  by  discussion of  fishery.  increase  or  many  provides  is  studies  consider  grounds  I address  has heretofore  Before  ie.,  fishing  measured.  this  than  on  Fishery Rent  is  effects not  of  the  claim  the  rate  of  incomplete.  of  are  the  since  average  model inputs  that  the  harvest  ignored.  More  increasing  capital  address  the  issue  of  Measuring rent  dissipation attributable  B. METHODOLOGY  Total  fishery  calculated net of  supply  input  the to  use  desired  dissipation.  the  To  of  do  this  this  I  current  tFollowing this section of a ton is obtained.  a return  both  the  depend upon rent  a  vessel, cost  that  I  where  to  profit  associated with  calculate two  as  value  each  is  a  fixed  revenue  variable  is the  measure  factors,  the  solution  of  when  ton, to  set  of  ie.,  output  fixed  factors,  parameters  I also want  a  the  actual  how  the  the  level  I find  one,  appropriate  actual  obtain  an  fisherman  is free  to  of the  long-run  the  to  restrictions  optimal  net  the  fishing I  case is based upon the  tonnage  the  from  quantities,  levels of  vessel.  obtained  one  for  discussion  the  actual  for this  for  of  the  the  the  since  solve  price  and  associated with this  tonnage, first  of  levels of  that could be  input  this  is  costs  by  restricted  Substituting  includes  used  market  fixed  and  tonnage  must  per  rent  rent  net  profit  resource  the  of  of  RENT  the  However,  rent  amount  136  fish stock.*  I call the  net  FISHERY  including the  profit-maximizing  potential  Given the of  the  of  OF  sum  cost,  Thus,  estimates  fishery.  levels  the  fishermen  tonnage.  the  of  problem  total  vessel.t the  ESTIMATES  as  demands. They  net  estimate  quantity  minus  to  solve for  restricted  vessel.  the  obtain  rent  his  OBTAIN  fishing days and the  and  including actual  of  Dissipation /  fleet redundancy.  measured  revenue  to  first  is  profit  of  order  must  or  as  net  number  In  rent  tonnage the  TO  to  Fishery Rent  may net  tonnage  currently  profit the  cause  rent per  optimal  maximization corresponding  market  rental  price  *lt is difficult to separate the returns to these two factors, since returns to fishing days occur because of the existence of the fish stock. So, in some sense, the total return is attributable to the fish resource.  Measuring profit-maximizing revenue the  per vessel.  total  the  levels  fixed  optimal  restricted  of  Rent  cost.  and inputs  are found,  is calculated as before,  The details  amounts  input,  output  of  the  net tonnage,  of  the  variable  are given  Fishery Rent  steps  along  ie., estimated followed  quantities  and  to  Dissipation / 137  with  cost and  seasonal profit  obtain  the  total  minus  for each  optimal  level  vessel of  the  know  the  next.  1. Determining the Optimal Levels of Variable Quantities In  order  to  optimal input  quantity  quantities  obtained 5,  from  optimal each  type.  the  prices  coincides  (5.3)-(5.4) If  sample  They  an  for the mean  rent  per vessel,  efficient  the  true  the socially and  optimal  vessel as the one that  catches  and the  optimal  Predictions for these  quantities  can be  linear  and equations  of . a  Pontecorvo  vessel-owner  estimation and the  mean  static,  and  has the greatest  of  obtains  of Chapter  (5.8)-(5.11) for  fixed a  factors  solution  profit-maximization  costs,  then  is in contrast  Huppert,  equations  decisions for the mean  private,  opportunity o n e . This  levels  researcher  supply allocation  social  is necessary to  demand  equations*,  result  it  supply and input  prices  and output  are the  reflect  with  the  output  the estimated  demand  Crutchfield  efficient  that  the estimated  into  input  output  of  used to produce the output.  nonlinear.  substituted  estimates  of  ie., equations  the  by  obtain  which  the  to  historical  catch.  to the  vessel of  exercise.  private  the  Profit  If  solution  the approach,  determines  are  used  technically maximization  requires technical efficiency, but the converse is not true.  When  the  predicted  quantities  are multiplied  by sample  mean  prices,  estimates  of  tNonlinear parameter estimates are found in Appendix 2 and are used for the seine, gillnet, and gillnet-troll samples. Linear estimates used for the troll sample are found in Appendix 3.  Measuring variable  (or  between total  seasonal)  seasonal  fixed  rental  cost  (flow)  price  of  the  four  different  the  sample  shows, order  In  order  for  the  equations. per  and  the  into  the  mean  the do of  account  mean  demand  is  minus  positive  given net  by  tonnage.  fixed  it  possible  rent.  If  In  vessel-specific rents.  cost.  all  exhibit  order  to  Within output  levels  obtain  and  of  of  the  the  may  total  to  it  is  as  earn  factors  into  scale. Thus,  in  rent  for  the  obtain  above  that  the  each output  price  rent,  sample,  fixed  per  ie.,  ton  seasonal  same while I  the  estimated Total  the  an  rents.  substituting  as before, earn  is a 5  (flow)  negative  it  Predicted  by  necessarily  of  described  obtained  rental  each  chapter  assumed  inputs.  an  then  sum these  procedure  market  of vessels in  is necessary to  per vessel is defined  vessels  to  of  gives  for  as described earlier.  market  not  the  rent  returns  the  fixed  estimate  profit  number  138  difference  and  However,  sample  calculated  vessels d o  some  a  An  identical,  then  each vessel are  product  the  in vessels, the  for  Total  vessel.  sample and  costs are  Rent  of  it  the  variable  vessel.  sample,  as  tonnage  from  constant  Dissipation /  inputs.  vessels are  mean  rent per  slightly.  Thus,  that  all  not  for  net  product  the  total  cost  mean  the  vessel  variable  mean  fixed  of  prices  the  the  vessel.  vessel-specific  total is  to  mean  on  rent  quantities  and  the  the  differences  Revenues and variable vessel  by  each vessel in the  is modified  prices  of this  is equal  per  sample  input  Furthermore, earn  rent of  product  earned  an estimate  a vessel's own  profit  rent  for  expenditure  Subtracting  know  vessel  mean  ton.  rent  to  take  faces  the  vessel types  the  supply and  cost  the  generate  to  by  obtained the  vessel types  four  of  are and  resource  and  mean  sample  per  statistic  to  vessel  the  the  estimate  revenue  is given  estimate  sufficient  profit  Fishery Rent  sum  rent. others over  Measuring Since of  it  is  also  of  interest  each vessel type,  within sample the  rent  the  entire  rent  per  per  of  sample  vessel  is  are  per  sample  used to mean  one  extra  determined  from  number  of  vessels.  divided  by  the  optimal  catch  of  vessels  needed  number  levels  for  divided obtain of  each  into an  supposed  Once  type,  to  catch  supplied of  in  used,  catch. the  The  number  estimate  the  survey  data  a random  sample,  result  harvest from this  it  is  between  the  rent  variable  sum  and total  over  calculated  fixed.  in  the  the  is  matter  Estimated  fleet  fleet  revenue  four  vessel types  manner  and  described  is done  both  for  rent  obtained  those  that  used  the  using  to  obtain  optimal  output  the  minimum  necessary  for  vessel  is  used,  vessel  the for  then  gives  other  entire by  total  an  hand,  the  multiplied  the  is  if  the  output can  be  sample  size  to  of  on  the  sample entire  each vessel is  assumption.  mean  of  the  rent  per  vessel  type  is given  by  fleet  cost.  Total  industry  rent  above  is the  costs  per  fleet.  actual,  static  per  or  total  total rent  fleet  sample  construct  the  of  sample  representative information  catch  estimate  This assumes that the  obtain  total of  the  solve  using the  to  type,  published  is a reasonable  either  each  use  technology I  to  fleet  can  output  which  This  entire  one  On  then  the  139  equation,  mean  of  for  the  Recalling  vessels required.  distribution,  simple  for  identical  to  fishery.  Dissipation /  vessels of  industry.  representative  sum  vessels is known, a  the  rent  of  and  are  1982  the  of  the  supply  single  the  to  required.  of  total  a sample  steps  by  a  of  sample  output  of  difference  The  be  are  a  is  number  both  merely  of  step  total  data  total  Since the to  the  entire  the  used  population.  If  vessel  estimate  vessels  actual  in  initial  the  on  amount  rent for  vessel  information  the  the  extrapolate  vessels. The  but  the  know  as o p p o s e d to  results  obtained  to  Fishery Rent  (one  its  vessel the is  period)  Measuring rent  associated with  This  rent  tonnage  is  obtained  by  per  vessel,  the  profit-maximizing a partial  It  is  that  variable. constitute  that  would  If  the a  the be  static  Kulatilaka  I  perform  this  discussion program bound  in  on  may  be  a  able  an  source  The  of  smaller  the  restricted  factor.  amount  of  than In net  this  be  one  is  can  Case  factors,  ie.,  the  stock  least  one  factor  for  of  net  fish.  fixed  I.  The  is called  like  of  if  the  choices  Christensen  optimal  factors all  1979).  (1979)  and  the  optimal  for  the  for  were inputs  Using  most  a  recently  levels  net  Columbia  per  vessel  by  to  prevent fish.  fisherman. a  variable  rents  used per  the  are  In  That  change  by  Recall  British  more  to  tonnage.  the  used  generated  were  and  factor,  use more  fishery  prices,  from  of  the  from  the  prices.  catch the  differ  optimizing  solve  presumably  to  they  way,  tonnage  this  the  Christensen  tonnage  would  would  140  I call  and  factors  (Brown  regulator  net  tonnage,  1982. fixed  market  the  restricted  the  intention  then  rental  one  as they  at  fixed  current  and  market  the  in  the  days,  the  solution  1987),  that  of  holding  of  the  Brown  for  levels  by  equal,  inefficiency  correct net  profits  at  increased ability  respond  and  optimal  3  control  use.  to  to  using the  exercise  to  its  leading  current  fishery  fishing  levels  (1985,  Chapter  tries  and  be  their  of  equilibrium  employed  the  Dissipation /  and Christensen 1979).  are  by  in  given  obtained  (Brown  levels  developed  factors at  number  actual  methodology  fixed  the  obtained  two  full  by  using  solution set  static equilibrium  possible  levels  conditions prevailing  Fishery Rent  in  this  use  an  entry upper  from  increasing  input  restriction  is, vessel-owners may market  prices.  inputs. Thus,  lower  vessel.  imposing  tonnage fact,  limited  of than  the  costs  correct  they  might  Instead are  of  higher  amount be  not  if  of the  Measuring Once  the  each  sample  supply of  optimal  and  these  net  and  for  input  as  rents  could be  In  Case  doing  number  described  has  been  vessel in are  quantities.  calculated  called  each  demand  variable  that  tonnage  used to  Within  earlier  obtained  the  calculated*,  obtain  estimated  and  potential  use of  for  predictions for  rents  called  by the  both  sample, the  sample  and  Fishery Rent  the  Dissipation /  the  equations  the  new  extrapolated rent,  optimal  mean  vessel for  they  levels  rents  refer  in  output  optimal  industry  since  141  to  are the  tonnage  per vessel. This is  factors,  stock  of  for  their  II.  this of  simulation,  fishing  days,  I  keep  the  other  at  their  actual  two  levels.  fixed I  do  not  solve  fish  and  optimal  levels.*  The in  optimal Case  input  In  or  I.  The  potential  rent of  difference  Case  measures  II the  inefficiencies induced by tonnage  an  ability another  effort of  to  the  isolate  the  amount  vessel-owners  simulation  called  Case  to III.  of  is compared to amount  of  the  estimate  dissipated  rent  of  actual  attributable  rent to  restrictions.  rent dissipation that  exploit This  input is  done  may  substitution in  an  be  attributed  ad  the  I  perform  hoc  manner.  possibilities  admittedly  to  +The next section contains a detailed discussion of how this is done. *The optimal level of the fish stock cannot be determined within the static framework used in this thesis. Rather, the operative assumption is that the regulator chooses the stock according to his own criteria. However, allowing the stock to change would be an interesting exercise that could be used to evaluate the impact of the Salmonid Enhancement Program upon catches and input usage. In reality, the actual number of fishing days may not be optimal, as this input is also regulated (for the entire fleet) to prevent overfishing of the total allowable catch. It is not clear what would happen to this input should the size of the fleet be reduced. In part, this uncertainty is due to the role played by nature in determining the maximum number of possible fishing days.  Measuring The  coefficients  means  that  Appendix  the  per  function.  The  input  I,  sample  of  II,  and  and  the  level  calculations of  vessel be  types  conducted.  vessel that  type.  III  are  rent to  is  that  vessel.  and  of  optimal  entire  annual  industry.  types.  The  total  As  These  an  associated  of  that  output,  the  the  the  it  is  optimal  of  the  four  vessel  type  is  estimates  net  tonnage.  is  from  done  vessels  in  turn  vessel  taken  to  types be  an  for are  of  sample.  each  for  industry  maintained  catch  among  following by 5  hypothesis, using  the  required  to  each  of  exercise a  single  are  used;  but  it is  predicted take the  computed. of  vessel  the  landed  estimate  the  II.  Chapter  Then,  of  each  total  the  is a maintained  number is  of  that  catch  both  assumption  distribution  supply  vessels within a  is undertaken  salmon  substitution  using  I and  fleet  one  net profit  output  in  entire  suggested  parameter  vessels  the  relaxes  the  entire  minimum  of  It  substitution optimal  new  in  rent  restricted  rent for  the  This  upon  the  before  142  equations  of  the  rent in Cases  to  IV.  for  the  as  value.  effects  for  of  the  the  degree  predict  simulation  This  each  the  both  determined. each  to  (see  solve  distribution  cases take  the  input  uses  with  Case  to  constructed  to  final  alternative,  assumed  costs  is  obtain  One  greater  Dissipation /  absolute  the  parameters  turn  in  size  simulate a  extrapolating  This is called cases.  is  in  entire  to  by  vessel  catch  new  Rent  the  to  necessary  the  used  undertaken  degree  each  is  doubled  absolute  with  Case is compared  the  given. It  is  are  in  only  It  with  obtained  alone.  actual  levels  rent  this  double  characterized  per  type  i,k = 2,3,4)  meant  For each vessel type  is, the  assumed  and  observed.  levels  previous as  is  tonnage  each  hence,  the  k  associated  rent for  and  all  actually  optimal  type  in  =  technology  demand  Finally, the  i  exercise  vessel  vessel  Cases  a  than  tonnage  mean  This  of  possibilities  (for  cross-price elasticities  4).  dissipation  and  a., ik  Fishery Rent  the  the  vessel  The  total  potential  Measuring rent which salmon. more  The  rent  catch,  It  fishey could earn  objective  of  by following  than  it  this  well,  it  strategic  the  vessel  that  possibility of  assumed that  the  the  one  is to  only  section, I discuss  and  the  vessel were  permitted  fish  development  the  of  to  continue  to  to  take  earn  the  entire  fish.  technology  any new  to  fishery would  one vessel type  basic harvesting  does  not  change.  In  vessel types is ignored. As act  competitively.  Thus,  no  is allowed.  the  work  of  143  vessel types  vessel owners  next  type  Dissipation /  observe whether  allow  multiple  the  or collusive behaviour  data  only  exercise  does by permitting  the  is  if  a scheme to  is assumed throughout  particular,  In  the  Fishery Rent  method  required  to  used to generate  obtain a  the  optimal  market  rental  tonnage price  per  of  net  tonnage.  2. Calculating the Optimal Net Tonnage The  solution  to  the  maximal  amount  the  amount  restricted  the  of  profit  a  profit of  restricted  restricted  or  input,  minus expenditures  (6.3)  T —' — it (p,w ; z ) =  In  equation  this  maximization  m  is  problem  seasonal profit. total  R — —• it ( p , w ; z ) -  m«z  rental  price  If,  here  as  assumed  that  for  maximum  the  the  net  tonnage,  other total  two profit  it  the  may  4  determines  firm be  can  vary  defined  as  input:  2  of  the  fixed  factor,  z , 2  where  z  2  is  It  is  R is  restricted in  chapter  profit  T defined  in  however,  long-run  fixed  unit  on  or  the  the  discussed  (6.3)  total  profit  factors it  is  and  remain  it at  necessary  is their to  restricted actual  first  profit.  levels. To solve  obtain  the  optimal  Measuring amount is  of  given  the  by  tonnage  Equation  (6.4)  is  It  that  the  states  the  level  implicit (6.4) ,  of  may be  given solved  (6.6)  shadow fixed  for  (6.6).  z* = - ( z i=2  Long  (6.7)  run  .  1=1  price  of  is  a  of  condition with  the  optimal  optimal  the  fixed  - m  2  envelope  factor  is  (Diewert  profit-maximizing  quadratic,  L  for  respect to  net  tonnage  demand  amount  of  =0  theorem  equal  1974). for  net  to  (Samuelson  the  Equation  the  net  tonnage,  market (6.4)  1954). price  defines  tonnage  input.  if an  Thus  z^:  4  the  restricted  profit  function, the  translog  case,  this  specific form  expression  of  is  linear  and  zf  into  (6.3).  (6.5) may  is be  form.  1  /(*> L * P V )  K=2  22  a  i  0.P. +2.  application  factor  the  Unlike  in closed  ( I  order  144  h(p,m,w;z)  normalized,  in  first  R — — = 97r (p,w ; z ) / 9 z  2  an  solved for  z* =  the  merely  the  function  (6.5)  The  Dissipation /  (6.4)  T —• — 97r ( p , w ; z ) / 9 z  (6.4)  For  input.  Fishery Rent  (  i=  P  k  .((b  A 2 3  L  -[m + l / 2 .  L  2  / *» P  z,)/z +b /z ) 1  a  l  C _ P. ] i2 l  profit  is found  by substituting  the  optimal  level of  7r (p,m,w; z) = ir (p,m,w; z f (p,m, w;z);  z ) - m * z * (p,m, 2  w;z)  Measuring  I  turn  next  to  the  market  Ideally,  stripped-down types  The  of  the  survey  dollars.  should reflect  Unfortunately,  unit  rental  a suitable  the  this  price  are  current  estimate over  the  net  market  opportunity  information  rental of  not  available  is  that  price  cost  salmon fishery.  derived  high  gillnet  sample,  10  gillnet-troll  sample  The  vessels  in  the  addition  those  average  that are  price  expected  life  of  (out  of  the  a  a  145  tonnage.  constructed  for  As an  provide  for  newly  the  vessel  alternative,  reasonable  per  vessels  is  of  his  vessel,  including  of  the  values  for  older  it  21) the is  less  two  range  unit  obtained  The  flow  from as  rental  this  seine  a  the  such  net  to  for  estimate  price  m  2  if  each  sample, and  11  similar  must is  current  is  second  newly  fixed  input  were  sample (out  (out  of  obtained  for  they  10  each  onboard  1982  given  the  in  asks  any  tonnage  ton  sample it  obtained  vessel in  well-equipped  better-equipped.  and  net  in  and  variable  per  sample,  obtained  and  of  vessels  the  troll  of  unit  in  of  for  stock  refers  included  number of  per  because  2  estimate  newer  stock  The  for  price  market  cmval  84)  Thus,  asset.  value  market  (out  of  low  price a  the  Vessels are  is 2  sample.  market  purchase  this  1979-1981. price  to  current  call  information  market , value  the  tonnage.  period  the  of  the  vessels. I  model,  calculate  the  expenditure  responses refer  high  averaging  my  which  for The  A  during  The  obtaining  British Columbia commercial  from  constructed  the  of  Dissipation /  price.  equipment.  in  price  vessel.  vessel-owner  by  problem  used in the  measures this  the  Fishery Rent  built  used  to  of  80)  for  60)  for  the  fashion,  but  uses  all  vessels  are  used  in  estimate  of  the  for  the  is an be  adjusted  calculated  by  applying  a  Measuring straight stock  line  depreciation  price, c m v a l  m =  annual  (1977) in tonnage  in  rate  is  set  of  5  tons  at  (for  smaller  nominal  rate  of  interest  is  the  Bank  Canada  Review  (February,  average  This  yields in  method  available  is  data.  1982  not The  nature  of  the  reflect  different  of  most  small  radar,  sonar,  etc)  some  portion  of  of  across rent  the  true  opportunity  are  certainly  the  necessary. rental  not  unit  tonnage  this  as  low type  prices calculated for the  it  the  the  it  levels of  (in  a  of  net  per  fleet.  the  rate  is  average  make the  is  7.14%).  obtained of  the  the  best  possibly  market  form  from  monthly  of  per  electronic  the  the ton  fishery  rental  capacity  in the  potential into  error  is  may  equipment,  in  that  onboard  that  units.  most  may  fishery. This is  minimum  probably  ton  prices  problem  marketable  since some  the  believe  calculated of  of  unrepresentative  values  of  use  excessive investment  divisible  tonnage  Jenkins  Canada bonds.  from  of  by  a gross registered  figure  simple  of  second  approximation  gillnet  a  observers  true,  were  suggested  vessels with  reported  is  A  for  rate  seems to  form  cost of  if  as  the  this  the  This  Many  underestimated.  case for  Therefore,  that  is  14.25%.  (aside  that  dissipation takes  overestimate  treats  to  be  but  types.  extent  methodology  (r)  recommended  investment  vessel  the  rents  rate  vessels the  Government  is  capital  To  that  interest  This  1983)  problem  sizes)  equipment.  means  to  problems,  serious  sample  levels  taken  long term  without  4%.  Canada Review  The  of  nominal  in (6.8):  Economic Council of excess  a  146  2  depreciation  a  and  Dissipation /  c m v a l ( r + 6)  2  The  (6)  as indicated  2  (6.8)  rate  Fishery Rent  size  this  This is  is  likely  serious  for  Measuring It  might  also  be  biased.  be  reviewed.  feasible.  be  As  argued  a  check  Since  However,  Classified  and  estimates.  actual  of  the  West  The  of  computed  selling  prices  Coast  are  the  vessel  is seldom  may  be  to  fish.  license the  license  reflects, value  a  to  fish  should be rather  Advertisements per  ton  Classified These  period  calculated.  In  sections, I use are  value  $4,000 They  are  What  remains computed  the  net the  is  cannot  The  asking  has  asking  to  for  estimate prices  of  by  fishing  average  an  1981  estimates  ton  a  of are  selling this  be  value value  not  in  the  such as  the  listed  with  these  asking  prices  rather  than  Furthermore,  of  in  the  age  the  value  licensed  positive  the  the  for  include  of  price. of  the  participants,  market  value.  This  fishery  rents.  This  anticipated  of  is  problems  number  of  could  strategy  often  accounted  a  may  two  may  acquire  and  prices  magazines,  high.  price  through  1982  correct the  of  the  per  staff  other  $5,000  are  vessel  ton of  vessel,  analyzed selling  market  as it  Fisheries  and  per  ton  net  at  market  bracketed  by  the  value the  end of  of the  high  represents  asking  of  found  a  prices in  the  a fishing license.  Oceans  Canada.  An  (for  the  seine  vessel)  from  the  vessel  asking  the  1981  vessel  and  and  prices  price  vessels is subtracted  prevailing the  realistic  147  cost.  license  values  to  market  the  the  too  limited  present the  order  monitored  of  per  price.  the  the  since  thus  the  from  that,  trade  least  and  a social opportunity  over  values  estimated and  are  out  at  be  expected  things,  netted  than  be  are  may  fishery  vessel  confidential,  fisheries  Dissipation /  not  fishing vessels are  and  is  are  actual  usually  There  prices  given  the  may  other  the  problem.  Because  among  private  listed,  further  are  problem  values  figures,  Sun  Fisherman.  uncontrollable  survey  commercial  Vancouver  prices  There  reported  the  transactions offered  the  asking prices for  sections  Fisherman  that  Fishery Rent  low  fishing  alone.  I  estimated  season.  find  that  average  Measuring Table  6.1:--Estimated  market  rental  prices  and shadow  Fishery prices  Rent  Dissipation  per net ton: four  types Sample  High  Seine  Price  Low Price  Shadow  5958.72  2651.26  6414.31  Gillnet  1905.02  1587.40  1350.34  Troll  3731.10  2050.35  3401.74  Gillnet-Troll  2325.67  1781.38  22494.80  Price  Notes: The method by which these figures are calculated figures in the table are measured in 1982 current  is discussed dollars.  in the text. All  /  148  vessel  Measuring current  The  values calculated from  low and high  given of  market  in Table  the optimal  shadow  Chapter the  profit  the  net tonnage for  net  estimated the  optimal  net  tonnage  tonnage, whereas  RENT  section fishery  harvest  level.  vessel  The  rents.  However,  actual  amount  of rent  generated,  if there  associated with within  variable,  the  are  seine mean  by  a greater  estimates  them  into  differentiating  the  (4.12) in  (4.12) the means of  reported  and troll  to the  in  Table  fleets  vessel  in a larger  factors, 6.1  may be  has  along  too  and  at the great  a  tonnage.  DISSIPATION  The first  cases  of  presents  245  results  vessels  used  obtained  from  in Chapter  I call the rents  are presented.  no tonnage degree  results  obtain  of the fixed  gillnet  sample are  see equation  The first  are  restrictions. The third  of variable extrapolated  input to  generates  to  calculation  estimate  estimates  rent  total  the  in this way  that  of the  could be  finds the amount  substitutability. generate  5  the  generated  in 1982. The second shows the potential  were  sample  obtained  vessel should invest  sample  Three  are  results  in the  to  O n e may compare  by substituting  technologies for the four vessel types. sample  section  of the quantities  values.  RENT  for the  within  these  values  the gillnet-troll  parts.  latter  is obtained  representative  has two  rent  solution  AND  type.  respect to the tonnage  parameter  that  of  with  The  per net ton for each  in the next  vessel  Dissipation / 149  data.  prices  are used  for each  and the mean  suggest  This  the rental  tonnage.  function  prices  C. FISHERY  of  These values  4. A numerical  actual  with  6.1.t  values  restricted  estimates  the survey  Fishery Rent  of rent  In the second part industry  rents.  Four  tUnfortunately, only one year of data is available for the construction of these prices. Therefore, it is not known whether these price estimates are those that would prevail under normal operating conditions. Additional surveys over time would provide a means of verification.  Measuring cases  are  done  for  simulated. the  The  entire  three  fishery.  It  evaluates  fishing fleet c o m p o s e d entirely  1.  Within  Rent  Sample  for  the  difference  in  results  Any  inherent  in the  rents  using in  all  in  Table  sum  of  stated  minus  Case  in  Table  the  (obtained  are  the  earlier,  I:  Actual  6.2,  mean  high  vessel rent  earns  amount  of  current  to  of  potential  a  fourth  rent  individual  rent  per  that  available  can  only  from  a  be  salmon  of  present  using  the  the  within  mean  vessel  total  data  calculated  is  of  entire  used  to  sample  the  aggregation  Table  by  the  seasonal  profit  rents.  (obtained Thus,  number  Table  within  Tables  type.  the In  bias  the  6.3  vessel  rent.  of  vessel in a  distribution.  per  multiplied  each  calculate  and  rent  estimate  as  type  the  sample  an  for  vessel)  within  vessel gives is  of  mean  total  the  and  6.3,  sample of  of  the  the rent.  vessel  costs.  Rent  actual of  rent  each  is equal  scenario.  negative  vessel  a sample  illustrative  obtain  each  the  5  the  to  in  as representative  the  sample  1982  the  price  equal rent  the  for  vessels,  1982  6.2  in  vessels. The the  Table  vessel  is  average  Appendix  its total fixed  a.  an  in  6.2  rents  of  mean  A5.10  vessels)  observations  As  use  through  the  and  150  a single vessel type.  both  sample.  The  of  above  Dissipation /  Rent  is calculated  A5.1  mentioned  Fishery Rent  rent  Canadian  sample,  sample, to  At  lowest  per  is  obtained  greatest  $919,000 for -$238,400  rents.  dollars  (low  Using  generated and  the  the  by  for low  price high  by  this  fleet  the  data  used  using  the  seine  price  to to  rent  fleet,  scenario and  scenario), net  the  the  tonnage  troll price  $1,530,200. calculate  All  them  calculated with  for  only  21  -$741,000  for  fleet,  with  increases rents are  84 the  are  in  given  in  Measuring Table  6,2:--Total within sample rents (using  Fishery Rent Dissipation / 151  mean vessel): all vessel types,  Vessel TyjJe  # of Vessels  Case  Case  Case  Seine High Price Low Price  21 21  -741.0 919.0  1,499.9 3,012.2  969.9 2,474.0  Gillnet High Price Low Price  80 80  -279.7 -128.0  520.0 484.4  423.1 393.6  Troll High Price Low Price  84 84  -1,530.2 -238.4  -3,005.2 -117.6  -58,478.1 -5,392.8  Gillnet-Troll High Price Low Price  60 60  282.0 510.0  782.8 1,027.7  578.1 849.1  Total High Price Low Price  245 245  -2,268.9 1,062.6  -202.5 4,406.7  -56,507.0 -1,676.1  Notes: Troll results are sensitive to price changes, so the high price estimate for tonnage is used for both price scenarios. All rents are expressed in thousands of 1982 dollars. The rents per sample are calculated as the product of the rent of the mean vessel (of each type) and the number of observations in the sample.  all cases  Measuring tables price  A5.1  and  scenario  scenario).  A5.2  exhibits  This  the  within  vessel  rent  sample,  In  with  the  low  Total  sample. Since  of  This  degree  of  the the  seems  vessels  for  within  variation  a in  the  low  price  scenario for  For  the  same  price  positive  gillnet  to  gillnet-troll observed  vessels to  be  of  do.  earning  in  the  from  those  the largest  to  calculate  particularly  true  for  the  heterogeneous,  associated  other  At  rents,  Overall, positive  the  59  8  low  vessels  rents.  with (out  and  is  21)  of  the  6.3,  the  above.  This  sample.  The  with  negative  rents  a  at rent  for  both  leads  to  an  representative  of  the  gillnet-troll  vessels.  troll  observe  For  example,  entire  only and  samples.  to  somewhat  scale,  84)  (or,  estimated  second  vessels earn  the of  a  rent,  possible  exhibit  of  (out  (out  is not troll  of  end 30  sample  it  price  scenario.  individual  vessel types  whereas  of  becomes  only  Table  within  vessels  price  in  high  scenario  discussed  245  low  the  price  comes  mean  the  for  sample  in the  seine fleet,  low  amount  the  the  vessels, the  as  vessels  Thus,  rent  245  low  calculated,  rent.  are  152  seine  of  -$572,000  rents.  positive  The  vessel  scenario,  negative  vessels earn  to  the  Dissipation /  of  is  of  Rent  -$2,268,900  vessel  slightly  earns  sample  (or,  sample  sample  sample  the  of  the  be  per  the  scenario.  amount  entire  homogeneity  mean  to  $1,062,600  vessels,  is equal  using  overestimation  60  to  differ  of  price  rent  scenarios and  general,  lack  For the  in  estimates  the  5.  $4,337  each  gillnet-troll  price  to  for  reflects  $56,100.  out  scenario).  difference  of  equal  price  rent  for  rent  high  sample  $252,800  Appendix  averages  -$9,261 in the  When  of  Fishery  the in  positive  rents.  different  rates  4  out  of  80  17  (out  of  60)  245)  are  sample  of  Measuring Table  6.3:--Total within sample  Vessel  rents (using  Fishery Rent  all vessels): all vessel types,  # of Vessels  Case  Case  Case III  High Price Low Price  21 21  -1,603.5 56.1  17.8 1,532.3  -373.0 1,132.3  Gillnet High Price Low Price  80 80  -803.1 -648.1  484.7 462.0  440.0 413.9  High Price Low Price  84 84  -1,524.0 -232.8  -10,617.5 -1,956.3  -14,331.9 -5,653.0  Gillnet-Troll High Price Low Price  60 60  22.7  65.8 312.6  -122.7 148.6  Total High Price Low Price  245 245  -3,907.9 -572.0  -10,049.2  -14,387.6 -3,958.2  Tyjje Seine  Troll  252.8  Dissipation / 153  350.6  Notes: Troll results are sensitive to price changes, so the high price estimate for tonnage is used for both price scenarios. All rents are expressed in thousands of 1982 dollars. The rents per sample are calculated as the sum of the rent of each vessel in the sample.  all cases  Measuring b.  Case  II:  Optimal  As discussed the  of  net  the  current  net  tonnage  the  four  price  vessel  per  are  types. in  to  an  estimate  averaged  whether  the  average  optimal  6.1  tons  net  gillnet-troll  the  1.2  distribution indicative  the of  (high  the  price  vessel  lack  of  154  The  is  of  the  optimal  than (for of  On  the  troll  used)  discrepancy in  to  actual  the  of  price  in  other  hand,  both  should net  troll  fleet.  size,  It  that  the  its  net  This is  sets  appears  the  ie.,  the  (when two  each  obtain  increase  tons  these  with  that  to  each  tonnage  scenario).  used  of  rental  in  indicates  reduced  61  two  associated  is  each  net  ie.,  when  average  vessel  be  between  the  according  mean  actual,  high  vessel  or  the  for  values  vessels  also  includes  amount  the  the  that  vessel for  calculated  tonnage  should  homogeneity  is  rent,  the  per  of vessels.  21.3  the  tonnage  fishery  amount  shows  sample  distribution  ie.,  6.4  tonnage  net  scenario).  alone  used).t  to  inputs  optimal  smaller  vessel  larger,  net  of  optimal  Table  the  the  potential  set  attributes  of  actual  23.9  a  tonnage  entire  be  or  gillnet  be  vessels is of  from  vessel  The  mean  and  should  reduced mean  the  ton.  the  Then,  over  vessel  vessels should  (when  vessel.  optimal  value.  to  net  obtain  upon  chooses the  average  First,  and  be  optimal  ways.  is found  should  over  net  two  mean  seine  one  optimal  the  of  of  the  The  impact  re-optimize  price  vessel and  used  the  Each vessel-owner  with  tonnage  is  to  Dissipation /  Vessel  case examines  rental  and  optimally-sized  tons  Per  allowed  market  comparison  true  is  vessel  associated  this  tonnage.  scenarios  sample  A  earlier,  vessel-owner  amount  Tonnage  Fishery Rent  from  troll  and  22  net  to the  entire  of  results  that  the  t A n example of the heterogeneity of the troll results is found when one compares the lowest net tonnage to the highest. The former is 6 and the latter is 250. Obviously, the troll sample results must be treated carefully given the extreme sensitivity of the optimal tonnage calculations to slight variations in the initial conditions.  Measuring Table  6.4:--Sample  mean  net  tonnage  and  vessel: Vessel  predicted  Fishery Rent  optimal  mean  Dissipation / net  tonnage  155  per  all cases  Case  Case  Case  Actual  Optimal  23.9 23.9  21.3 21.5  21.3 21.5  21.2 21.4  21.2 21.4  Gillnet High Price Low Price  6.1 6.1  1.2 1.7  2.2 2.7  1.3 1.7  2.2  Troll High Price Low Price  9.2 9.2  22.0 22.0  61.0 61.0  58.0 58.0  61.2 61.2  Gillnet-Troll High Price Low Price  7.0 7.0  7.5 7.5  7.5 7.5  8.3 8.3  8.3 8.3  lY££ Seine High Price Low Price  1  Optimal  2  Optimal  1  Optimal'  2.6  3  Notes: This is tonnage This is solution Troll tonnage 1  2  3  calculated by using data on the mean vessel to solve for the optimal net for that mean vessel. calculated as the mean of the optimal net tonnage per vessel, when a for each vessel's optimal net tonnage is found. results are sensitive to price changes, so the high price estimate for net is used for both price scenarios.  optimal vessel  net  tonnage  should increase it  Conditions  in  discussion most to  for  in  In  are  of  capacity,  close to my  tonnage  vessel for  evolved  two  vessel  boats  that  types.  and  ground.  either  so  are  have  The  above. open is  In  two  waters.  therefore  at  a  fleets  boats  now  tonnages  built  for  of  this  type  are  and  probably  owners  these  vessels would  days  tonnage  is a  hold  capacity  it  may  reduced.  is  be  grounds  their  catches  catch  fleet  to that  not  the  average.  and  useful  that  the  net  fishery  by  these  the  packer  the  fishing  processing  plants.  to  the  a  used to  access  measure  argued  fishing  the  rivers  Furthermore,  having  are  and  Since net  without  different  fishes off  flexibility  fishing  fleets  the  leave  latest  These  gillnet vessels new  boats  are  speed.  fleet  the  gillnet  Recall  of  Oceans reveal  troll  has  results.  mouths  off-load  the  gillnet-troll  the  the  the  than  fish in very  fleet  be  net  the  premium  at  the  156  7.5.  and  Hence,  by  simply  Fisheries and  gillnet-troll of  boats  sit  deliver  net  operate  could  then  vessel types  Vessels  two  to  available  Dissipation /  Finally,  these  seine  of  gillnetter.  boats  smaller  particular,  a  7.0  for  additional  another  bowpickers and are  other  that  down  at  the  usually  put  officals  substantially  called  or  to  that  processing plants.  a  fishing  large.  number  fleets  seiner  extremely  explanation  the  say  packer  packer  Discussions with  of  Fishery Rent  slightly, ie., from  indicates  these  these  is  an  findings  The  ready  The  which  shore and  for  has  tonnage  in terms  characteristic per  trailers  suggest  addition,  therefore, hold  5  regulated  stock.  net  fishery  Chapter  heavily  the  the  some  Measuring  to  profit  often  the at  west  sea for  represents  respond from  circumstances than  to  coast of  those described  Vancouver  several weeks. a  profitable  unanticipated  additional capacity.  Hold  Island  capacity  investment.  area  in  openings  The and  Measuring Table  6.5:--1982 salmon  catch  and landed  Fishery Rent  value,  Landed Value  Seine Gillnet Troll Gillnet-Troll  33644 16037 23345 21009  51793.5 28137.7 43911.8 41090.9  Total  94035  164933.9  Type  Fleet  /  157  by vessel type  Aggregate Catch of Salmon (000's pounds)  Vessel  Dissipation  (000's  dollars)  Notes: The value of the catch is expressed in 1982 current dollars. The catch and landed value are for five species: chinook, c o h o , sockeye, pink and chum. Source: Government of Canada, Fisheries and Oceans Canada (Pacific Region), British Columbia Catch Statistics 1982 by Area and Type of Gear.  Measuring Finally,  a  piece  of  calculating  the  vessels  of  recent  reveals  that  existing and  A  net  gillnet  that  less  obtains  the  the  Case  the the  It  is  not  generate  a  (out  used,  A5.6  of  In  high  is  true  the  case  their  are  for  results  price  of  vessels  in  the  the  I  only  net  tonnage  the  average  vessels  158  reasonable.  include  than  new  Dissipation /  are  average  larger  21)  do  the  price total as  note  in  price the  is  to  price  (using  be  sample as  5 give  scenario  be  to  entering  all  In  those figures in  the  and  the seine  as  $350,600, the  all  price  high  when  information  of  seine  high  vessels  used to  the  for  all  are  calculate  rent  gillnet  seine  sample (using sample  scenario 245  (using  vessels  scenario.  when used.  the  mean  Tables  A5.3  these  rents,  sample  are For  rents.  across vessels in  positive  is  sample  troll  price  rent  this  the  troll  to  This  $3,012,200  $4,406,700,  vessels earn In  price  the  inframarginal  scenario.  The  again,  rents  as all  5).  the  The  rent.  that  is either  low  for  sample  for  similar  again.)  given  Once  Overall  negative  is  it  both  pattern  6.3  within  (Chapter  the  a  and  expected,  vessels).  -$1,956,300.  rent  the  scale  For  calculated  reveals  6.2  scenario, ie.,  rent.  distribution  high  Tables  and  returns  II,  vessels,  overstate  scenario  the  of  Case  to  low  to  for  (Consult  resource  low  rents  tends  constant  in  Appendix  low  results.  positive  and  to  sample  $1,532,300  low  scenario  are  I  is calculated  the  interesting  sample.  that  examination  sample  of  rent or  through  the  distribution  vessel  gillnet  highest  former  entire  mean  hypothesis  for  within  in  vessel)  vessels  An  opposite  the  all vessels) rent  the  the  potential  mean  positive  for  gillnet-troll  for  for  the  does  and  and  using  accepts  the  troll  of  observed  true  prices  suggests  Rent  fleets.  vessel  obtained  tonnage  whereas  comparison  mean  evidence  construction.  new  fleet,  casual  Fishery  17  whereas (20)  each 14 earn  Measuring positive the  rents  latter  return  vessel.  scenario,  gillnet-troll price  The  the  low  because the  per  price  in  fixed  Only  out  a  have  which  rent  that  rents  not  just  vessels  of  single  positive  between  is  84  troll  vessel  price  in  scenario).  a larger  vessels  does  rents  could a  estimates).  be  An  that  the  in  the  the  positive  high  low  Rents  are  vessel size  show  price  price  market  the  rent  in  rent, ie.,  correct  amount  of  net  shows  the  largest  restrictions.  On  the  vessels  actually  chosen  amount  costs.  This  attributable  to  rental  other  the  tonnage  of  in  when  causes total  An  by  scenario.  in  the  in  (14  159  higher  lower  rents  scenario  the  fleet,  to  net  the  low  Finally,  in  the  the  tonnage.  23 high  a  generated  for  the  this  sample.  tonnage  the  price  an  even  of  the  across  the  fleet,  use  The  tonnage using  all  optimally  much  this to  would  of by  incurring  calculations  all  low  adoption  sample  part,  inputs,  using  that  removed.  In  all  uses the  the  troll  thereby  is  per vessel were  gillnet  in  is  hypothesis  differentials  the  relaxation  dramaticallyt,  optimal  by  to  by  indicates  rent  by  restriction  for  tonnage (This  extent  over  obtained  vessel  the  the  The  optimize  if the  of  calculated  fall  to  followed  from  indicates  estimates  mean be  tonnage  increases  of  net  examination  the  sensitivity  of  II  restrictions.  able  rent  could  rent  I and  $922,600,  for  rents  rent  were  the  prices  seine  hand,  tonnage  the  of  $3,344,100,  increase  decrease of  use  the  increase  tonnage.  that  experience  Cases  calculations  increase  types  in  vessel-owners  could  greater  vessel  if  rents  examination  rent  given  Using  through  larger  subset.  for  total sample  dissipated  reveals  optimal  be  (high  Dissipation /  scenario).  difference  fixed  scenario  costs associated with  4  whereas  vessels  price  Fishery Rent  higher  result variations  may in  tThis is disturbing in light of the shadow value obtained for this sample and presented in Table 6.1. This gives another warning that the troll results are to regarded with some scepticism.  Measuring the  c.  market  Case  This  III:  case  variable ability  inputs of  the  An  of  Increase  upon  the  demands.  Tables  associated  costs for  sample  rent  larger  (Case  loss  the  and  II.  able  245  rent of  loss  of  of  rent  than  to  input  troll fleet  substitution  hypothesis leads  exercise  160  alone.  the  (in  to  possibilities  is that  rent  admittedly predicted  Appendix  an  The  In  present  the  the  order  estimated  supply  the  in  arbitrary exercise. output  5)  among  increase  dissipation.  is undertaken.  is an  the  of  type  net  is  vessel and  by  scenario) fishery  gain  in  tonnage,  potential of  for  the  rent  rent ie.,  resource  dicussion in  the  to  values Optimal  and  input  quantities  latter  could  and  to  be  rent.  Two  5 of  rent  important vessel  types, They  harvest  in are  the from  scenario),  is  a  through  means  price  falls  price  earned  within  using  rent  This  245  low  by  low  achieved  activities. the  III,  in  or  of  Total  and  that  $4,308,800.  difference an  high  vessel  (Case  be  sample  increased.  show  the  substituting  Chapter  to  entire  the  mean  equal  that  the  are  both  -$3,958,200  appears  input  for  using  to  for  possibilities  negative  Estimates  substitution  advantage  of  substitution  potential  dissipate  troll vessels. Recall the  each  calculated  price  amount  take  A5.10  vessels.  a  may  inputs  with  vessels is  low  Thus,  in  rent The  following  input  II,  correct  fishermen most  all  distribution  constituting  of  for  increase  doubled. This  rent for  when  whether  $350,600  fishery  through  the  Dissipation /  this case.  fishery  decreases  an  along  for  Rent  Possibilities  substitute  are  A5.7  vessels  entire  to  recalculated,  expected,  of  hypothesis, the  are  scenarios,  Substitution  potential  coefficients  a  This is observed  impact  fisherman  this  ton.  in  the  tonnages  As  a net  examines  investigate of  price  Fishery  much  the  in by  Cases  technology.  seine It  I  which  particular, the  use  are and  predicts  Measuring Table  6.6:--Actual  number (using  of vessels and estimated mean  Vessel  Case La  lY££  Actual  Seine High Price Low Price  Fishery  minimum  vessel): all vessel types,  Rent  number  Dissipation / 1 of vessels  all cases  Case L b Min #  Case II Min #  Case 11 Min #  Case  539 539  357 357  359 358  359 359  1002 1002  Gillnet High Price Low Price  1331 1331  1136 1136  1196 1197  1157 1157  7012 7017  Troll High Price Low Price  1638 1638  1057 1057  623 623  390 390  2511 2511  Gillnet-Troll High Price Low Price  1020 1020  974 974  876 876  883 883  3920 3920  Total High Price Low Price  4528 4528  3524 3524  3054 3054  2789 2789  N.A. N.A.  #  Note: Troll results are sensitive to price changes, so the tonnage is used for both price scenarios.  high  price  Min  estimate for net  IV #  Measuring this  very  finding.  substitution more  than  resource  The  vessels  whereas gillnet  all  than  This  of  still  earn  case,  quantities  are  used,  vessels of  of  is to  among  a  be  much  greater  expected  the  (18  same  scenario  not  somewhat  in  out  vessels  of  21  earn  different  in  degree  of  input  that  they  also dissipate  shows  that  quite  the  negative  from  smaller per  required  actual  vessel  in  each  vessels  in a sample.  both  sample  within  industry  to  catch,  low  price  rents.  those  a  few  scenario),  Results  obtained  for  in  the  Case  II,  vessel.  the and  of  sample  rent  calculations  For  the  up  predicted  each  data  actual  to  predicted  case  in Table  and  number  obtain  output  Cases  1982  quantity  minimum  scaled  the  each  the  in  the  for  rent.  take  both  Once  appropriately using  obtained  conjunction with  are  done  the  total  per  is  it  rents  are  results  when  vessel types.  This  are  the  competing vessel  rent  the  vessels  rents  presents  estimates  distribution  types,  positive  vessels in  generate  of  two  vessels exhibit  162  Rent  fourth  number  two  inframarginal  that the  section a  other  gillnet-troll  2. Industry  these  Dissipation /  rent.  troll  and  other  as  the  distribution  seine  Since  Fishery Rent  an  and  quantities  of  II,  and  are  6.5,  to  Table  vessels is  estimate input for  of  well  the  to  supply  minimum  6.5  shows  the  among  the  four  determined,  rents  total  quantities the  output  find  terms,  111, as  extrapolated  predicted  catch. value  I,  entire  industry  from  the  rent. mean  distribution  of  Measuring Table  6.7:--Estimated  actual  Fishery Rent  and optimal fleet net tonnage vessel types,  (using  Dissipation / 163  mean  vessel): all  all cases  Vessel  Case La  Ty£e  Actual  Case Lb Optimal  Case II Optimal  Case III Optimal  Case IV Optimal  Seine High Price Low Price  12882.1 12882.1  8532.3 8532.3  7646.7 7697.0  7610.8 7682.6  21342.6 21543.0  Gillnet High Price Low Price  8119.1 8119.1  6929.6 6929.6  1435.2  1504.1  8414.4  2034.9  1966.9  11928.9  High Price Low Price  15069.6 15069.6  9724.4 9724.4  13706.0 13706.0  22620.0  55242.0 55242.0  Gillnet-troll High Price Low Price  7140.0 7140.0  6818.0 6818.0  6570.0 6570.0  7328.9 7328.9  29400.0 29400.0  Total High Price Low Price  43210.8 43210.8  32004.3 32004.3  29357.9 30007.9  39063.8 39598.4  N.A. N.A.  Troll  Note: Troll results are sensitive to price changes, so the the high tonnage is used for both price scenarios.  22620.0  price  estimate  of net  Measuring a.  Case /: Actual  Table  6.6  1982  Rent  the  actual  shows  estimated  minimum  number,  possible  to  distinguish  number  of  vessels  first  for  the  associated  a  not  two  that  in  smaller  extent  phenomenon.  this  including the is used  and Table  tonnage, of  lost  rents is  number  Table  obtained  by  smaller is  distribution  of  those  Table  mean is  net  made  net  to  do  net  (mean  results of  of  the  are  the  may  of  in  the net  The  most  (all  to  the  the  total  There  is  fleet, is  so  information  it  be  number  comparable  as of  many  the  the  ways,  mean vessel of  excess  finally,  used  current must  of  the  net  value  difference  in  of vessels,  than  when  results  for  these  a the  results  as necessary.  tonnage  calculated  actual  recent  no  fleet  between  noted,  solves  through  the  only  discrepancies  net  l.b  distribution  Thus,  actual  rent  in  level  now  the  vessels). The the  the  is  estimate  amount  industry  vessel is used are  the  gives an expressed  (all  rents.  detail;  Case  calculates  vessels); and  6.13  It  uses the  shows this when  6.12  Table  I.a  164  with  cases.  dissipated  l.b  be  along  rent.  then  be  as o p p o s e d to  in  tonnage  the  Case  and  and  6.6  all  industry  may  sample  salmon  per vessel and  I.  also  I.a  extrapolated  mean  tonnage  total  and  vessel,  presented  Case  Dissipation /  1982,  using all vessels); the  Table  within  for  vessels  in Cases  and  are  cases.  tons.  for  in  but  calculate  rent  same  mean  all  so,  to  fishing  I,  redundancy  vessel)  for  tonnage  43,210.8  Fleet  estimates  fleet  situations  rent  vessel)  when  gives  of  order  when  Case  Thus,  does the  using the  obtained  6.12  amount  6.8  for  excess vessels (Table  (mean  vessels  salmon-fishing  In  6.7  Table  comparison  and  6.11  rent,  much  of  vessels  number  fleet.  a comparison of  of  1982  required  redundancy and of  only  possible  fished  minimum  with  number  Fishery Rent  by on  estimated product  vessels. The  estimate  comes  the the  for of  entire actual  Case  the  sample  estimated from  I.a.  total  Sinclair  Measuring Table  6.8:--Estimated  total fishery  rent (using  mean  Fishery Rent  Dissipation /  vessel): all vessel types,  165  all cases  Case l.b Min #  Case II Min #  Case III Min #  Case IV Min #  -45,543 -2,935  -12,676 15,544  -7,527 .  -8,127  17,673  17,215  -634 69436  -11,832 -9,253  -5,976 -3,775  5,870 4,944  7,114 6,492  34,375 28,968  -58,277  -22,030  -33,086  -5,775  -25,019 -2,035  -65,838 -27,819  -112,893 -20,256  2,670 6,579  4,403  11,328 14,904  8,406 12,395  31,750 47,751  -112,982  -36,279  -38,695  14,129  -15,348 35,486  -58,445 8,283  N.A. N.A.  Vessel Type  Case I.a Actual #  Seine High Price Low Price Gillnet High Price Low Price  1  2  2  2  2  Troll High Price Low Price Gillnet-troll High Price Low Price Total High Price Low Price  8,135  Notes: Rent is calculated using the actual number of vessels given in Table 6.6. Rent is calculated using the minimum required number of vessels given in Table 6.6. All entries are measured in thousands of 1982 current Canadian dollars. 1  2  Measuring (1978).  He  reports  population the  of  estimate  Table  shows  according  to  commercial  to  appears  that  earned mean  in the  of  the  a  calculations  done  earns  current  seine  with  all  zero  troll  suggest 245  only the  I  are  for  left  vessels the  used,  estimates  that  $0.8  for  166  a  the  fleet  fleet,  million  well,  $2.9  so  of  positive  sample.  of  resource  positive to  the  average  when  per  degree  the  (Table  of  predicted mean  vessel,  and  as the  worst  42.8  negative  rents  In  The  rents  by  this  the case  discrepancy  heterogeneity output  are  however,  obtained  rents.  The  rents  Recall,  6.8).  vessel  hence,  from  inframarginal  Rents  fleet  1982  gillnet-troll  negative  million.  the  scenario).  generates  45.5  in  the  price  that,  Columbia  ranges  only  substantial  and  the  British  rents  (low  it  noteworthy  rents  contrast,  since  As  in  fishery  gillnet-troll  the  than  In  is the  negative  presence  attributable find  of  It  I.a,  negative  fleet,  the  presence  likely  rent  per  among vessel is  is  used.  This,  of  total  rents  for  this  there  are  First,  and  salmon-fishing fleet.  rent  explanations  the  to  between  vessels  entire  equal  eg.,  sample.  47,300,  have  cases.  Case  dollars.  fleet,  the  for  amount  million.  most  the  the  $58.2  different  of  vessels  all  aggregate  to  of  1977  300  for  Canadian  rents  results  20%  this  in  as a whole,  $33.0  is  reduces  Although several  in  when  portion  rents  total  in  Dissipation /  reasonable.  fishery  scenarios show  results  course,  appears  sample  are  vessels  smaller  about  fishery  the  some  vessel  these  1977  associated  within  price  Since  rent  from  to  by  vessels.  enjoy  is  from  the  tonnage  (1982)  to  rent  attributable  net  fishery  million  ranging  both  the  For the  lowest  fleet  estimated  salmon  117.1  fleet  5084  total  I present  6.13  season.  a  Fishery Rent  might  for  the  be  expected  appearance  of  negative  possible outcome,  rents  in  aggregate.  Measuring Table  6.9:--Estimated  fishery  rent  per  Fishery Rent  vessel (using  mean  Dissipation /  1  vessel): all cases  Vessel Tyjje  Case La Actual #'  Case l.b Min #  Case II Min #  Case III Min #  Case IV Min #  Seine High Price Low Price  -84.5 -5.4  -35.5  -21.0 49.4  -22.6  -0.6  43.5  48.0  69.3  Gillnet High Price Low Price  -8.9 -7.0  -5.3 -3.3  4.9 4.1  6.1 5.6  4.9 4.1  High Price Low Price  -35.6 -20.2  -20.8 -5.5  -40.2 -3.3  -168.8 -71.3  -45.0 -8.1  Gillnet-troll High Price Low Price  2.6 6.5  4.5 8.4  12.9 17.0  9.5 14.0  8.1 12.2  Average High Price Low Price  -31.6 -6.5  -14.3 10.8  -9.8 16.8  -44.0 -0.9  N.A. N.A.  2  2  2  2  Troll  Notes: Rent is calculated using the actual number of vessels given in Table 6.6. Rent is calculated using the minimum required number of vessels given in 6.6. This is a simple average of the rents of the four vessel types. All entries are measured in thousands of 1982 current Canadian dollars. 1  2  3  Table  Measuring perhaps  most  too  high.t  and  its  rental  lead  to  the  important,  Since  that would  set  I.a  this  vessel  the  actual  high  value  close per  to  positive  The of  price).  ton  and  the  contain  the  to value  interest  rate that  of  rates  of  a  to  for  a  cost*  (m ).  This  2  $2423.42.  This  actual  high  for  low  the  This  and  of  troll  gillnet-troll  6.1.  the  the  is  is  the  vessel's  price. price  because  the  to  may the price  zero.  For the 40%  The and  break-even  vessel is less than  and  rental  equal  gillnet-troll  For  seine of  the  break-even 28%  of  value  the  be  tonnage  determine  represents  the  hand,  to  168  may  net  vessel in each sample.  of  other  total  interesting  is $447.72 (24%  vessel, be  of  low  the  is  very  actual  prices  sample  earns  high price scenarios.  for  current  there  charged year  discussion  m  are  2  market  equipment  'capital-stuffing'  the  ton  of  actual  vessel,  value  is  tonnage  product  the  I use suggests a 25  tSee Appendix I previous seasons.  and  is  it  Dissipation /  net  each vessel type  mean  ton  high values given  the be  net  for  the  proportion  net  6.6)  by  of  Table  the  a  prices for  91%  that  in  in both  6.1  the  stripped-down  considered from  On  whereas  reasons for  prices  fleet  given  rents  the  Table  gillnet  zero,  net  in  of  for the a  given  Therefore,  Table  of  rental  substantial  price  (in  value  a  rents.  using data  break-even  low  be  rental rent  market  vessel are  negative  industry  price  per  may  the  is done  for the  actual  of  for  estimated  costs  they  finding  value  Case  fixed  price,  break-even  the  Fishery Rent  and  nature is  the  against  of  the  values  In  electronics.  matter  of  total.  lifetime 1982  addition  used  (Crutchfield  the  average  several.  For  the  obtain  the  rental  These  items  are  often  Rettig  appropriate  example,  the  1984).  season  as  Apart  depreciation depreciation  for vessels in excess of fishing  value  to  1979,  the  to  5 gross  compared  to  tSee Appendix 5 for the calculations of total cost per vessel type. They show the importance of total fixed costs in determining total cost. The proportion of total fixed cost to total cost varies across the samples, with the highest proportion found for the seine sample.  Table  6.10:--Estimated fishery  Vessel  Case  IY££  Actual  Seine High Price Low Price  I.a  rent per  Measuring  Fishery Rent  ton  mean  (using  Dissipation /  1  vessel): all cases  Case l.b Min #  Case II Min #  Case III Min #  Case IV Min #  -3.5 -0.2  -1.5 1.8  -1.0 2.3  -1.1 2.2  -0.03 3.2  Gillnet High Price Low Price  -1.5 -1.1  -0.9 -0.5  4.1 2.4  4.7 3.3  4.1 2.4  Troll High Price Low Price  -3.9 -2.2  -2.3 -0.6  -1.8 -0.1  -2.9 -1.2  -2.0 -0.4  Gillnet-troll High Price Low Price  0.4 0.9  0.6 1.2  1.7 2.3  1.1 1.7  1.1 1.6  Average High Price Low Price  -2.1 -0.7  -1.0 0.5  0.8 1.7  0.5 1.5  N.A. N.A.  #  1  2  2  2  2  3  Notes: Rent is calculated using the actual number of vessels given in Table 6.6. Rent is calculated using the minimum required number of vessels given in 6.6. T h i s is a simple average of the rents of the four vessel types. All entries are measured in thousands of 1982 current Canadian dollars. 1  2  3  Table  Measuring tons the  and  17  years  for  fleet  are  built  of  hulled  concerns  the  rental  This  by  of of  cost  of of  of  the  then  the  longer  newest  vessels  expected  170  introduced  lifetime  than  into  wooden  other  for  fishery  rate  same  fishing  may  is  often  in  the  social  true  in  this  immediately  that take  If,  a  is  an  that  of  the  of  On  the  in  for  the  form  of  time  underestimate  interest gear.  Fishermen amount  of  opportunity estimated  other the  fishery  hand, elapsed is  only  employment  between  the  since  the  time.  social  only  lag  and  Thus, the  labour.  another  gear  increased the  calculated  up  of  life  difficult  unemployment  I calculate  true  communities.  costs  however,  costs that  the  through  remote  costs  depreciation  through  argued  thesis  assumes  the  understate  going  is  to  assumed  depreciation it  season.  labour  on  especially  This  fishermen  of  lines  is zero,  to  it  is possible that  unrecorded  tax  evasion  However,  problem  incentives  the  the  applicable  based  when  weeks.  hand,  to  phenomenon. serious  is  be  estimates  computed  the  also  true  at  jobs  is  social costs  labour.  attributable catches  gear  overstate  labour  that  fishery  the  may  of  may  life  labour  and  end  above  the  fishing  substantial,  On  a  have  service  true  Along  labour  frictional  of  and  endogenizing  fishery  number  the  aluminum  unit  maintained  maintenance.  the  per  especially  respond  price  However,  expressed  price  The is  cost  vessels.  Dissipation /  boats.  The  rates.  smaller  Fishery Rent  for  purposes. as  the  encourage  catches.  suggested  the  That No in  revenue is,  data  fishermen are  Appendix  British  Columbia  complete  reporting.  estimates  salmon  this  low.  deliberately  available I  are  on  does  fishery  the not  because  This  may  understate extent appear it  has  their  of to  be  this be  a  built-in  Measuring Table  6.11:—Actual  number (using  of vessels and estimated  Fishery  minimum  all vessels): all vessel types,  Rent  Dissipation /  number  of vessels  all cases  Vessel Tyjje  Case La Actual #  Case l.b Min #  Case II Min #  Case II Min #  Case IV Min #  Seine High Price Low Price  539 539  356 356  229 227  256 254  640 634  Gillnet High Price Low Price  1331 1331  1096 1096  1153 1153  1201 1201  6774  High Price Low Price  1638 1638  1056 1056  302 302  370 370  1221 1221  Gillnet-Troll High Price Low Price  1020 1020  942 942  1002  1002  1002  1002  4500 4500  Total High Price Low Price  4528 4528  3450 3450  2686 2684  2829 2827  N.A. N.A.  6560  Troll  Note: Troll results are sensitive to price changes, so the tonnage is used for both price scenarios.  high  price  estimate for net  171  Measuring There  are  two  more  data-based.  The  first  reasons may  for  be  due  chosen  is suboptimal  because the  smaller  landed  of  may  have  some  biologically  A  may  to  comparison  rent  and  from  (Table  reducing  only  seine  fleet,  troll  fleets  would  Table  number  of  from  the  235;  troll,  (or  vessels  582;  and  industry  is 1078.  This  without  a reduction  associated (1982)  with  calls  for  for by  rent  in  the  l.a).  this  fleet  the  entire  actual  For 78.  the  to  the  The  is be  the  fleet  rent.  The to  (high  fleet of  The  to  be  Fleet  of  of  scenario). l.b.  For  seine  and  determine  the  (Case  l.b)  183;  gill,  vessels  in  the  reduced  by  24%  is  excess net  11715.4  total  vessels.  number  be  in  Case The  to  redundant  amount  fishery  $55,255,000  difference  vessels could  The  in  possible  the  gain  price  rents  required  income  redundancy  be  number  calculated halved.  upon  at  a given period.  the  shown  of  in the  of  harvest.  in  form  scenario).  number  number  stock  price  seine  a  the  (low  minimum  implies  preserve  positive  is  level  regulators  earn  it  harvest  the  of  $79,393,000  vessel)  the  1982  redundancy fleet  or  is  by a reduction  subtracting  that  fishing  fleets  mean  gillnet-troll, means  vessels  not  Second,  costs  fishery  172  are  high. This  rents  extent  that  the  some  impose static  the  $15,602,000  the  (Case  actions  potential  scenario  to  most  6.6  number  of  to  achieve  negative  of  gillnet-troll  equal  gain the  excess actual  are  to  is,  is too  need  Dissipation /  rents  That  fishermen.  the  reveals  loss  price  and  or  l.b  the  as  these  low  number  low  they  of  error.  the  desire  of  and  upon  seine  6.11  Both  l.a  the  the  the  the  From  impact  the  negative  escapement  to  such  or  generation  Cases  in  revenue  level,  of  regulatory  permitted  or  fishery.  the  of its  6.13)  However,  the  finding  to  objectives,  critical  within  lead  problem  fish  non-economic  distribution and  value  the  Fishery Rent  or  Rationalization  37%.  tonnage Pearse  Committee  Measuring Table  6,12:--Estimated  actual  and optimal fleet vessel types,  Vessel  Fishery  net tonnage  Rent  (using  Dissipation / 1  all vessels): all  all cases  lY£e  Case I.a Actual  Case l.b Optimal  Case II Optimal  Case III Optimal  Case IV Optimal  Seine High Price Low Price  12882.1 12882.1  8518.7 8518.7  4917.1 4914.6  5475.2 5464.7  13743.9 13736.5  Gillnet High Price Low Price  8119.1 8119.1  6685.6 6685.6  2494.1 3019.7  2607.0 3168.0  14670.0 17719.7  High Price Low Price  15069.6 15069.6  9656.3 9656.3  18511.9 18511.9  22633.2 22633.2  74716.2 74716.2  Gillnet-troll High Price Low Price  7140.0  6634.8 6634.8  7595.2 7595.2  8330.0  34110.0  7140.0  8330.0  34110.0  43210.8 43210.8  31495.4 31495.4  33518.3 34041.4  39045.4  N.A. N.A.  Troll  Total High Price Low Price  39595.9  Notes: Troll results are sensitive to price changes, so the the high tonnage is used for both price scenarios.  price  estimate of net  Measuring (1982) my  suggests that  findings,  fleet to  With the  the  1985).+  of  The  no  tonnage  is  associated of  of  the  cut  to  and  of  of  redundant  400  vessels, which  the  combined  superfluous  costs per  the  deadweight  flow  the  deadweight  $26.0  million;  using  the  low  this  235  are  fleet  costs  are  loss  scenario  for  and  total amount  has  $1.3 the $25.7 of  surplus  $2.7  surplus vessels are  each it  is very  gillnet  and  174  close  and  to  gillnet-troll  $19.8  million  (high  entire million negative  fleet  is  for  the  fishery  for  the  by  the  For  million  the  price)  and  estimated low.  The in  of  to  be  former  Case  l.a,  the  fishing vessel cost  amount  of  is  surplus  the at low  million.  price  costs  deadweight  low  price  scenarios).  vessels  million  (low  million  represents and  $11.6  seine  the  and  $49.9  surplus  fleet,  redundant $1.0  Scott by  capital  and  troll  (high  and  price scenarios.  high  the  estimate  multiplied  entire  both  the  number  rent  is  loss is estimated  and  $10.9  smallest  its  multiplied  million.  the  (Munro  loss associated with  vessels  and  possible to  loss  sample  then  price,  $2.2  now  is assumed that  loss. This is done  price  has  If  price  tonnage  fleet  in  fishery,  tonnage  is  deadweight  vessels  vessel type.  of  the  vessels, it  redundancy  high  with  deadweight price  be  vessels,  fleet  outside  the  gillnet-troll  tonnage  fleet  1467  seasonal  Thus,  equals  gillnet  The  number  value  the  costs  the  capital  nonsalvageable.t-  The  to  number  non-salvageable  vessels  troll  of  amount  Using  seine  Dissipation /  2208.  estimates  has  the  Fishery Rent  the  and  their  price).  The  for  about  the one  latter about  high half 60%.  tObviously, this is an estimate that applies to the 1982 fishing season. A larger fish stock would probably require more vessels. So, this does not claim to be the final word on the optimal size of the salmon fishing fleet. An answer to this question would require a longer term analysis of the fishery. t-This would be the case if the vessel could not be used in any other production process such as pleasure boating or recreational charters.  Measuring Table  6.13:--Estimated fishery  Vessel Type  Case I.a Actual #  rents  (using  Fishery  Rent  Dissipation / 1  all vessels): all vessel types,  all cases  Case l.b Min #  Case II Min #  Case III Min #  Case IV Min #  -45,522 -2,926  -12,570 15,602  14,846 31,001  -5,221 15,097  28,735 73,090  -10,228 -7,650  -3,454 -1,331  5,051 4,670  4,641 4,217  29,186 27,198  -58,195  -21,908  -40,861  -65,941  -177,382  -33,017  -5,678  -9,547  -27,559  -50,830  High Price Low Price  -3,107 804  273 3,884  1,104 5,263  -2,197 2,367  -14,650 4,030  Total High Price Low Price  -117,052 -42,789  -37,659 12,477  -19,860 31,387  -68,718 -5,878  N.A. N.A.  1  2  2  2  2  Seine High Price Low Price Gillnet High Price Low Price Troll High Low  Price Price  Gillnet-troll  Notes: Rent is calculated using the actual number of vessels given in Table 6.11. Rent is calculated using the minimum required number of vessels given in Table 6.11. All entries in the Table are measured in thousands of 1982 dollars. 1  2  Measuring An  interesting  difference an  in  earlier  amount case,  of  it  manner.  low  price  two  and  other  For  variation fleets,  rents  electronic  by the  the  For Case  alone.  gillnet-troll  rents  that  is possible to  cases.  little  actual  the  in  ie.,  is a true  this  troll  low  may  rent  fleet,  million  and  of  contributes  the in  on  is given  price  of  the  price  between  $3.9  is  million.  measure  of  this  an is  rents  in  indeed  the  As  the  if  the  total  and  in  and  difference  amount  the of  the  expected  gillnet  p h e n o m e n o n , then the  high  million. for  the  dissipated in  million  However,  to  excessive  $42.6  found  the  is suggested in  rent  to  176  analysis of  of  $25.9  is  "capital-stuffing"  large  the  amounts  rents  If  amount  difference  an  adoption  vessels.  the  differential  by  Dissipation /  scenarios. It  newer  idea  the  high  l.a  reflect  difference  and  measure  equipment  different  some  as the  l.a  Case  equipment  obtain  $2.6  in  difference  This is caculated  fleet  these  obtained  electronic  this  very  rents  discussion  then  seine  comparison of  Fishery Rent  in  use of  dissipated  rent.  b.  Case  II:  Optimal  Optimal  quantites  tonnage  per  number ie.,  of  2686  (Table  6.11).  within  take using  the the  vessel  rather  (Table  variation  and is  than  6.6) In  sample  in  1982 entire  seine  vessel  place  of  take the  1982  6.11).  not  much  different  earlier,  Results for particular,  catch,  distribution  as of  359  are  the  (Table  as noted  In  each  in  to  Vessel  3450  rents.  results.  for  used  are  fact,  Per  rent  vessels required  vessel  the  Tonnage  the  compared vessels,  the  results  from  In  when this  case,  lower  obtained  those  the  and  by  obtained  seine  vessels to  229  of  samples mean  when  presence  of  all  the  using  minimum  the all  that  show  vessels  vessels for  greatest  required  are  l.b,  mean  found  the  are  vessels  net  in Case  using  size  larger  optimal  than  is less discrepancy than  troll  seine  actual.  catch is much  The  there  calculated  used.  to By  substantially  Measuring Table  6.14:-Estimated  fishery  rent  Fishery Rent  per vessel (using  Dissipation /  177  all vessels): all cases  Case l.b Min # '  Case II Min #  Case III Min #  Case IV Min #  -84.5 -5.4  -35.3 43.8  64.8 136.6  -20.4 59.4  44.9 115.3  -7.7 -5.7  -3.2 -1.2  4.3 4.1  3.9 3.5  4.3 4.1  High Price Low Price  -35.5 -20.2  -20.7 -5.4  -135.3 -31.6  -178.2 -74.5  -145.3 -41.6  Gillnet-troll High Price Low Price  -3.0 0.8  0.3 4.1  1.1 5.3  -2.2 2.4  -3.3  Average High Price Low Price  -25.9 -9.4  -10.9 3.6  -7.4 11.7  -24.3 -2.1  N.A. N.A.  Vessel  Case  Type  Actual  Seine High Price Low Price Gillnet High Price Low Price  I.a #  1  2  2  2  Troll  0.9  Notes: Rent is calculated using the actual number of vessels given in Table 6.11. Rent is calculated using the minimum required number of vessels given in 6.11. This is a simple average of the rents of the four vessel types. All entries are measured in thousands of 1982 current Canadian dollars. 1  2  3  Table  Measuring increases fleet,  the  average  where  302  number  of  sample,  since the  of  the  The  of  in  (Table is  across  $15,399,000 gain  of  fleet  could  low  price  other from be  Case  net  tonnage  for  fleet  by  using  to  (when  costs  are  since in  the  its  different 6.8).  the  Case  II  as  6.13)  mean  rent  $3,740,000.  the  optimal  obtained  averaging  is 61.2,  Given the  higher  when  mean  net  proportion  to  obtained  this  all  an  high  vessels  tonnage increase  over  means  is  is  when the  the  degree  compared  Table  6.8).  fleet,  The  $3,869,000  (Table  fleet  increases  rent  gillnet both  On  when  two  a  using all  6.13).  these  by  to  $1,379,000,  calculations done  the  going  results  may  values obtained  when  the  when  all  used.  Since  the  the  entire  optimal  net  vessels are  of  vessels have  market  rental  prices of  used  than  However, tonnage.  mean  distribution number  net  tonnage  note  as  a large  are  sizes  rents.  to  that  58. in  the  discrepancy in  tonnage  seine  larger  indicated  6.13),  gillnet-troll  troll  The  net  that  by  the  the  could increase its rents  Table  to  troll  the  optimal  gain  vessel alone,  the  equal  vessel  the  of  the  for  the  lowering  use  for  178  Obviously,  hand,  interesting  according to  o p p o s e d to  tonnage.  mean  true  higher  other  seine fleet  and  hand,  from  vessels,  using the  lose  by  all  much  the  is  also  Dissipation /  needed.  thereby  It  the  is  the  through  (Table  using  one  would  each vessel,  much  very  (Table  examining  net  not  On  is  are  Rent  per vessel,  possible  scenario,  $6,001,000  tonnage,  greater  increase  price  by  larger.  This  size)  calculations.  costs  $21,357,000  vessel. mean  samples. For example,  troll  used,  much  used,  is  It  (of  vessel is  6.13).  $2,100,000  l.b  explained  mean  per  per  623  rent  rent  scenarios. O n  hand,  is  the  gain  the  vessel  the  industry  used,  (low  only  vessels,  versus  output  total  vessel  gain  output  vessels increase fixed  $18,910,000 mean  vessels  vessels affects  troll  gain  predicted  Fishery Rent  when  a  a net  the  predicted As  of  mean  output  result,  the  ton,  a  fixed  vessel  is  does  not  rent  per  Measuring vessel  must  fall.  This  phenomenon  to  the  rent  calculations  million  for  this  fleet  According $14.9 when  all vessels are  Overall; rent, in  it  is clear  ie.,  conjuction  total so  landed  far  1982  total  been  of  further  c.  a  able  the  of  fishery  price  could if  minimum  fish  rent  minimum  using the  low  in  mean  the  gillnet-troll  vessel,  scenario,  in  1982  could be  size.  generate  the  optimal  number Of  redundancy contributes fishery  manifested  rent  compared  results.  is as  to  179  high  $5.3  as  million  of  the  most  A  relaxation  of  in  Substitution  net  tonnage  forms  the  $30,312,000  substantial  vessels.  two  to  a  loss  larger  tonnage  This of in  than  amount  of  resource  per vessel were  represents  rent  19%  used  of  the  dissipation considered  potential  fishery  rent.  the  actual,  if  the  restrictions  would  increase  Static  fleet  had  rent  a  $18,910,000.  Case  The  the  the  value  fleet  done  as $31,387,000,  with  also  Dissipation /  used.  that  as much  in  is  Fishery Rent  ///: An priori  to  Tables  Increase  expectation  exploit 6.8  a  (using  falls when  this  greater mean  is the  input  substitution)  clear  that  to  potential  case. Case  rent,  Case  and  -$5,878,000  indicates concern  that to  total  the  III  obtained  rent  regulator  of  and  6.13  rents  rents  rent  input  falls who  Case by  III.  the  to  degree  in  the  the  II of  input  Thus,  generate  input a  the  he  total  rents  not.  As  industry  rent  degree  substitution),  be  The  low  it  substitution  to is  resource  of is  price  $31,387,000  latter  substantial  is  (actual  case.  is calculated to of  vessel-owner is  when  former  comparison  $37,265,000.  wishes  than  comparing Case  higher  A  when  all vessels) show,  by using all vessels,  for  reduced  substitution,  (double  are  is  (using  For example,  fishery  total  industry  degree  vessel)  scenario II  is that  Possibilites  for  the  former  of  serious  rent  from  Measuring Table Vessel  6.15:~Estimated fishery Case La Actual #  Type  1  rent  per ton  Fishery Rent  (using  Dissipation /  1  all vessls): all cases  Case l.b Min #  Case II Min #  Case III Min #  Case IV Min #  2  2  2  2  Seine High Price Low Price  -3.5 -0.2  -1.5 1.8  3.0 6.3  -1.0 2.8  2.1  Gillnet High Price Low Price  -1.3 -0.9  -0.5 -0.2  2.0 1.5  1.8 1.3  1.5 1.5  High Price Low Price  -3.9 -2.2  -2.3 -0.6  -2.2 -0.5  -2.9 -1.2  -2.4 -0.7  Gillnet-troll High Price Low Price  0.4 0.1  0.04 0.6  0.1 0.7  -0.3 0.3  -0.4 0.1  -2.7 -1.0  -1.2 0.4  -0.6 0.9  -1.8 -0.1  N.A. N.A.  5.3  Troll  Average High Price Low Price 3  Notes: Rent is calculated using the actual number of vessels given in Table 6.11. Rent is calculated using the minimum required number of vessels given in 6.11. T h i s is a simple average of the rents of the four vessel types. All entries are measured in thousands of 1982 current Canadian dollars. 1  2  3  Table  Measuring the  fishery.  It  serious than  A  is  that of  comparison  of  worst  offenders  Using  either  or  from  all  of  this  become  mean price  of  of  these  is  is very  two  of  the  Once  a  of  Thus,  the  large  Rent  for  from  reduction  the  two  does  the  rent  former,  $2,896,000  of  (mean  the  fleet  the  form  redundancy  is large The  higher in ie.,  Case  enough  to  exhibit  elasticities  181 more  much  does  little  in  II, II  and  substitution alter  the  activities.  II  falls  by  industry  rents  the  entire  when  Case  not  the  mean vessel  make  Case  does  to  of  price scenario. The  fleet,  $15,904,000 fleets  of  low  from  one  the  in the  rents  is  from  rent  seine  rent  fleet  than  to quite  fall  (gillnet-troll). This is because the not  and  input-substituting  either  potential vessel)  other  troll  of  obtained  the  much  that  the  scenarios.  earns  of  Dissipation /  restrictions.+  that  that  total  price  that  reveals  ie.,  $25,784,000  vessel types doubling  type  observed  both  used.  $458,000.  Therefore,  is  component  $453,000 (gillnet) and of  it  in  as  tonnage  calculations,  vessels is used,  scenario) ie.,  net  vessel  vessels) or  fleet's  problem  dissipation that takes  rent  vessels,  vessel  latter,  per  rent  negative  distribution  a  inefficient  of  (all  serious  rent  set  $18,012,000 size  as  Fishery Rent  Case  III  small  the  the (low  for  by much, harvest  in  when  the  merely  technology  first  optimizing  instance. decisions  vessel-owner.  again  comparison using the  the is  entire  gillnet  made  fleet  between  distribution  shows rents  the  least  generated  by  discrepancy using  the  in mean  results vessel  when and  a by  of vessels.  tThe rents calculated in Case ill are done for the optimal net tonnage associated with the greater degree of input substitution, so the difference in rents is attributable solely to an increase in input substitution possibilities.  Measuring d.  Case  The  IV:  final  Single case  tonnage/input the  the  configuration  calculate entire  from  the  1982  rents  catch  alone.  present  Tables  6.7  and  6.12  type.  Thus,  the  figures  They  show that,  could  catch  rent  (using  the all  approximately in  industry  to  take  increased Case  The  IV  high  scenario the  640  show  largest  seine  the  II  the  of  the  Take the  the  four catch  permitting  each  of  for  fleet  becomes  each  optimal  samples.  total  half  the  of  the of In  the  the  6.6  across  the  vessel  Now  relax  vessel  four  fleets  total  view  cost.  For the  of  my  current  be  $73.1  the  total  1982  IV  total fleet  about low  net  types. to  take  fishery  rent  fleet  (using  all  fishery  rents  ($29.2  million)  this  fleet  seine. This is due  also due  to  the  fact  for  each  totals  for  vessel  Case  seine  scenario, total  million. landed  the  This  However,  seine total  fleet  seine  IV. fleet  fishery  represents  catch. The  60%.  the  needed  increase in  order  must  tonnage  be in  tonnage.  gillnet  fact,  vessels  fishery, the  price  that  tonnage,  fleet  the  is approximately suggest  of  tonnage  are  to  results  of  number  net  6.15,  expert's  Case  terms  total  through  estimated  to  minimum  associated  least  harvest, In  and  each  of  of  gross value  Case  that  at  is  vessels.  does  for  rent  tables,  harvest  amount  fleet  The  estimates  all  1982  scenario.  than  in  from  is about  price  of  entire  to  results  second  44%  the  II  experiment.  distribution  show  vessels)  rents  Case  keeping with the  total  182  harvesting.  6.11  in  following  associated with  and  and  6.6  the  the  Dissipation /  Harvesting  from  regarding  single vessel type  Tables  Type  performs  assumption  Then,  Vessel  Fisher)' Rent  vessels,  produces to that  the the  by  more higher seine  Table  6.13)  generates  the  using 6774  vessels in  the  rent fixed  in costs  sample  the  high  price  associated with  exhibits  decreasing  Measuring returns 5).  to  The  price  scale, whereas  gillnet-troll  case).  vessel  is  scenario  be  of  is not  the  high value  do  so  the  cannery.  the  range  Many  larger,  ie.,  $47.8  million  rents of  In  and  wholesale  fact,  catch  -$50.8  are to  the  or frozen  low  valued  mean price  highlight  mean  the  vessel  however,  that this  when  low  low  it  million. O n c e  believe  best  fresh  other  the  the  the  the  to  consistent,  fishery  the  the  since  in  183  (Chapter  in  when  serves  -$177.4  functions  for  of  vessels,  fleet  it  coho)  merely  scale  million  sample  observers of  efficient.  ($4.0  this  troll  from  rents  for  in  the  largest  to  results  distribution for  rents. They  fish (chinook  at  the  difference  Results  least  third  returns  Dissipation /  may  always  again  this  segment  of  selectively  harvesting  market.  does  not  destined  for  It  species  CONCLUSIONS  Tables of  is the  the  accepts constant  is much  entire  unexpected.  fleet  D.  the  fleet  to  rent  The  using  the  well  produces  fishery  6.8).  negative  gillnet  according  representative.  produces result  total  (Table  importance not  fleet  However,  used,  the  Fishery Rent  6.9-6.1 Q and  the  cases,  individual very  (using  Cases  I  vessel earns  large  already  6.14-6.15  and  through a  small  negative.  discussed  in  measure  6.10  and  the  6.15.  the  license to  Tables  not  be  sold  marginal  it  Strictly  independently.  the  rents  Tables  amount  of  tables  6.6-6.8  be  (using  An  informal  and  of  merely the  market  rent,  total  summary  unit to  of  the  estimates  net  that,  industry  statistics  vessel)  is attached for  per  show  observe the  one  license  6.14  mean  to  compared  speaking the  vessel and  negative  is interesting  may  per  6.9  are  shadow value  These values fish.  IV.  These  all vessels). However,  they  show  and  rents  to  for  each  although  each  rent of  per  may  the  Tables  restricted of  ton  net  results  6.11-6.13 ton since  input,  Tables  the  market  the  vessel and  licenses has grown  up  be  price  since  of  may the  Measuring inception net  of  the  tonnage.  and  gives  gillnet, ton  troll,  lower ton  seine  not  as  prices  following  and  of  than  program  Fisheries and  the  price  license  a  for  price year  this  fact,  the  the  $5,000 the  but  of  to  the  for  the  years  of  in  per  $4,000.  other  unit  a lag. Thus, expectations  ton,  while  prices  For  example,  seems are  licensed  Licenses  vessels, $4,000. it  184  informal  These  season.  1977-1979  of  an  season.  $3,000  1982  Dissipation /  one  sales  1982  averages  of  per  these  the  $2,700  fleet  and  boom  with  end  start  expressed  monitors  average  seine  at  is  as  for  the  values  Canada  fleets  prevailing  license  reflect  data  license  those  good  Oceans  gillnet-troll  a  with  Fishery Rent  for  the  the  per  are  much  the  Since  that  way  per  1982  the  is  tonnage  changed slowly  in  the  fishery.  The to  British -$42.8  estimate is  a  and  Columbia million  of  the  1982.  amount  substantial Scott  in  associated with  used  to  the  1982  This  represents  vessels,  less  net  optimal  tonnage  were  million,  bringing  the  rent  inefficient  tonnage  total  to  rent  be  a  seasonal fleet of  the  it  per  used,  to  tonnage.  the of  restrictions.  the  $25.7  the  minimum  rent  brought  industry  rents  would  million Input  is  a  19%  measure  substitution  represents  about  loss  increase the  allows  a  23%  of  the  that  it  (Munro  of  vessels were  use  ie.,  $12.5  of  fewer  If,  in  an  additional  addition,  landed  deleterious  further  An  non-salvageable  the  total  the  60%.  positive,  by  inputs.  of  of  equal  million.  shows  or  number  become  of  rents  is $164.9  million,  about  variable  or  earning  amount  could  fewer  million  catch  excess  If  fishery  ie.,  be  deadweight  and  $31.4  dissipated. This  of  to  the  $55,266,000  total  $18.9  rent,  measures  vessel,  to  is found  redundancy  negative  only  gain  total  fishery  total landed value  catch,  tonnage  equal  salmon  excess fleet  million.  of  of  However,  costs  loss  The  proportion  1985)  take  commercial  $37.3  gross  the $18.9  value.  The  effect  of  million  in  value  of  the  Measuring 1982 to  catch.  If  generate  could troll  also  positive,  inefficient  distribution  $41.7  British of  million.  an  This  fleet  inefficient  amount  of  inefficient an  thesis  distribution  implicit  dissipation  to  fishery is capable  as  of  of  the  ability  generating.  as that  total  to  cases four  in  185  potential  gillnet-troll  rents,  fleets  contrast,  examined  in the  vessel types  of  the  current  resource  tonnage  the  thesis.  contributes  among  user  generating  rent  vessel  the  reduce  input types.  a  each the  although of  the  potential  great  value in,  of at  substitution, The  government's  groups,  However,  landed  a  is dissipated  restrictions,  through  substantially  has the  and  capable of  static  competing trade-off.  the  is  44%  catch  fleet  gillnet  fishery  Dissipation /  fishery.  fishery  dissipated  among  seine  of  the  the  inefficent  the  be  for  among  lost to  much  efficiency/equity  have  rents  salmon  redundancy,  appears  catch  rent  the  million. The amounts  catch  demonstrates  distribution  rent  $73.1  postive of  possibly  is permitted,  smaller,  commercial  rent,  ways:  generate  in potential  Columbia  fishery  four  reflects  million  rents,  but  the  least,  rent  produce  fishery  to  $164.9  and  largest  is unable  further  deal  the  fleet  Thus,  The  single vessel harvesting  Fishery Rent  greatest  use this  other rent  of  an  probably forms  of  that  the  VII. In  this  input in  thesis  I  demand  from  the  by  of  net  the  levels  issues  This  are  fully.  The  is  calculated  and  compared  this  is  of  me  to  shadow to  determined.  obtain  an  value  it of  the  A  permits one  market  comparison  estimate  of  of  the  the  harvest  collected  used to  the  price.  the  are  estimate  allows  the  of  operates  role  for  of  input  restricted In  inputs,  addition,  actual  cost  an  and  the  optimal  associated  with  inefficiency.  quadratic,  features prices.  to  input  another  of  methodology  evaluated  desirable  obtain input  optimal the  of  restricted use  This  in  this  it  gained tonnage translog  function  study. leads  acccordance  measures  levels,  to  profit  procedure  perform  advantage,  from  function.  and  be  which  derived  fishery  as  a  of  profit  that  data  way  demands  the  restricted  salmon  Micro-level  in  several  for  function.  within-season  a description  one  has  second  profit  permits  the firm  fruitful  normalized,  and  restricted  duality  a fishing  rent dissipation.  The  output  a  to  decisions of  describe  and  regulatory-induced  in  Appealing  to  substitution  enables  convexity  allocation  theory  input  is  to  level  of  quadratic,  tonnage,  optimal  supply  production  British Columbia commercial  approach  restrictions  output  means  1982  integration  micro-economic  environment.  normalized,  The  use  and  a regulated  technology  a  CONCLUSIONS AND DIRECTIONS FOR FUTURE RESEARCH  of  rent  with  is necessary to through is  use  linear  form.  It  First, to  under  of  it  to  allows  estimated  perform for  alternative  this  in  parameters.  is  nonlinear  This  and  form,  not  supply  and Since  the  functional is  well.  imposition  using  contrasts  does  very  principles.  senarios  well-behaved  functional  the  output  microeconomic  have  186  is found  It of  input it  is  predicted  estimates.  A  that  the  equation  with  the  equation  have  a  closed  form  Conclusions solution  (Brown  Estimation output  and  Christensen  proceeds  supply  in  equations  unrelated  regressions  convexity  in  the  equations  impose  equations  require  cross-price four  vessels.  In  factors  are  potential in  a  the  of  by  Crutchfield  vessel with  the  is also allowed the  This  of  assumption  of  and ie.,  The  greatly  187  do  of  intensity  to  (1969).  However, the  of  fishery  However,  it  vessel.  to  profit-maximizing and  Pontecorvo  of  troll  largest vessel  most  to  as  a  this fishery the  rent.  that  their the  adopted work  by  benchmark  economically output.  the  vessel,  fishery  to  out  of  largest  on  important  bear  examination  configuration  of  and  more  is similar  level  the  has  seem  this  for  fishing firm  improves  Furthermore,  and  fixed  second  rent  Own-  and  as the  an  new  variable  loss in potential  tonnage/input  Crutchfield  by  These  gillnet-troll  believed. The it  price  estimating  computed  between  to  the  The  technique. are  and  seemingly  accept  parameters.  elasticities  altered  not  gillnet,  is commonly point  or  undertaken.  seine,  demand  Zeller  estimation  calulated  estimates  choose its  that is  representative  by  Research /  input  iterative  the  observers  scenarios.  efficient  the  output-constant,  conclusion is not  Pontecorvo  of  nonlinear  likelihood  than  Many  obtain  made  Future  results suggest that the  inputs  contribute  an  estimation  elasticities the  set  samples  use  fishery,  alternative  economically of  the  behaviour.  used to  and  an  characteristics  to  those  maximum  the  linear  using  second  by  seine vessel.  under  methodology  a  general,  dissipating  The  establishing  in  In  a  output-variable  substitution  is also found  For  non-normalized  expectation.  obtained  troll,  both  First,  estimated  case,  active  is the  rent  are  nonlinear  computed.  priori  rents  a  addition,  for  stages.  convexity  types  operation  source  linear  Directions for  1979).  technique.  elasticities,  vessel  two  and  This  technically  efficient contrasts efficient  Conclusions output to  level  enter  the  manner. this  per  It  different  ways:  of  input  be  a valuable  may  their  other  a  share leave  model  questions  royalty  scheme  that  They  given  developed of  the have  are  as a starting  the  the  revenues  estimated  the  of  Future  this  tonnage  of  related in  to  our  to if  dissipating use  the  quota  catch.  behaviour.  least  trading  Less  cost is  Used  to  resource owner,  the  indicate  own  might  a  the  the  least  four  of  might system  inputs  efficient  tax,  Canadian public. O n are  sensitive  to  to  boats  incentives  royalty  of  evidence  quota  have a  are  system  a  more  with  this  distribution  hand,  quota  will  fishermen  reduce  one  combination  conjunction  that  in at  of  findings  Under  boats  prices  consistent  inefficient  allowed,  efficent in  itself  the  suggests that  and  188  economic incentives,  These  On  allows  understanding  restrictions,  fishery.  thesis  integrated  redundancy.  the  Research /  to this the  prices,  excessive amount  of  inputs  starting  a  further  and  related  harvest.  in  role  this of  presented for  thesis  provides  regulations  generated  point  an  fishery.  its  in  increase  technology  elasticities on  an  fleet  rent  Furthermore,  the  take  investigation  also  fisherman  could provide  to  given.  the  and  and  harvest  upon  quota  that  the  in  for  rent dissipation manifests  management  preventing  catch.  II  developed  is inherently  inefficient  for  greater  hand,  used  The  a  Class  Directions  fisherman  towards  types,  future in  the  step  tool  a given  scheme  so  is  take  sell  the  of  substitution, vessel  procedure  behaviour  that the  substitution  onus  harvest  input  for  making  important  among  significance  new  dissipation  is found  catch  the  rent  as an  process.  of  The  decision  Since  is seen  vessel.  and  interest  briefly, future  not  in  a  during only  research.  as  a  useful  fishery. the  Several  course of  a suitable  point  for  extensions the  ending  thesis to  this  research  are  thesis,  but  Conclusions Using  the  framework  distribution has  been  efficiency  enhancement  increase  in  input  the  harvesting  fleet.  evaluated.  The  being  increase  and  no  usefulness  effect  success  of  of  the  program  One  the  stated  income  Other  in  scenarios, which and  tool,  of  the  interest  the  is the  income  upon  If  costs  be  called  the  a  limited  Using  a  be  of  royalty  usually  incidence  distributional  of  this  are  be  this  policy  the  are  to  state  costs  can  be there  Going  further,  viability it  is  fishermen.  increase  curve  an  the  upon  of  a  of  the  incomes  it  supply  increase,  is to  Lorenz  means  output  predicated  question.  program  income  example,  this  harvesting  the  189  increased through  predict  found  upon  the  For  model  been  into  entry  tax.  stock of  evaluate  schemes.  total  standard  simulated,  a  fish  Research /  scenarios concerning the  costs.  such  Future  is possible to  possible to  compared with the  can  imposition  is  has  of  of  It  for  regulatory  program  fashion.  can be  it  context  policy  must  effects  objectives  equitable  distribution  days  Again  an  the  the  alternative  this  the  harvesting  In  factor.  of  in  examine  thesis,  alternative  (SEP).  fixed  The  to  incomes  a  of  responses under  possible of  of  this  Directions  Pacific Coast salmon  program  level  demand  in  effects  proposed that the  salmonid  and  and  developed  and  fishermen's  approach  the  new  old.  an  With policy  increase respect (Devoretz  and  efficiency  impacts  the  following.  What  of  in to  the  number  the  latter  and  and  these  of  fishing  management  S.chwindt  regulations  1985).  may  be  of  all  involves  the  examined.  Another three  fixed  solution net  interesting  of  tonnage  factors,  question when  a system of obtained  in  they three this  is  are  permitted  equations manner  in  could  to three be  vary  are  the  optimal  freely? The  unknowns. compared  to  levels  answer  The that  optimal already  amount  of  calculated  Conclusions in  the  the  thesis.  Of  model  known  employed  in  this  certainty.  In  reality,  with  fluctuate  from  in  fishery  the  Furthermore, estimate model for  number  the  size  interaction  research. The  of  the  implicit  to  recast  the  assuming the  by  existence of  multi-lived  inputs,  interesting  to  One  Future  between  the  Research /  net  190  tonnage  and  fishery,  of  of  the is  stock  of  assumed  to  or  that  days it  is may  two  or  the  input  of  also  input  upon  (Gates  1984).  with  be  bear  the  a  regulator's  Extending useful  direction  investigation.  it  formation. would This  be  the  This  for  necessary  might  prices  gear, only.  involve  decisions  and  It  is  Because  planning horizon. In  demand  allocation  may  perfectly  problem.  current  and  is  factors  expectations  three year,  fish  relevant  fluctuate.  extensions  of  other  would also  stock  imperfectly  correlated  multi-period  depend  optimal  only  a host  uncertainty  eg., two  is  are  uncertainty  these  available  known  processes of  dynamic  thesis  the  understood  thus,  price  nature  a finite,  the  fishing  different  a  not  and,  output  is  there  are  of  that  fact, other  would  be  from  the  obtained  dynamic cases.  effects  ability  of  as  compare  alternative,  the  effects  assuming  problem  As well,  stock  intertemporal  shortcoming  static and  effects  stock  allowed  the  the  assumes  the  which  of  of  incorporate  handled  the  is the  thesis  season.  environment  the  of to  season to  usually  of  interest,  Directions for  fishing days restrictions.  The  a  particular  and  of  which is to  allow  fishermen  regulators  endogenized  exploits  into  the  to  for  the  strategic  forming monitor  design of  fundamental  behaviour  coalitions the  optimal  uncertainty  could  actions regulatory  of  surrounding the  by  the  be  analyzed.  the  participants. Also,  fishing  schemes (Wilen  For the  vessels 1985).  operation example, imperfect could  be  Conclusions Another  extension  equipment data  set  in  Returning multiple  by  large  is currently  to  the  more an two  the  fisheries that  profitable  extended very  as  catch  an  be  model.  different  the into to  one  investigation  rent.  This  Future  of  would  the  Research /  role  require  of  a  191  electronic  much  better  a vessel-specific time series of  its five this  the  at  seine single  However,  and  research It  not  adding  and  in  many  the  roe  year.  vessels are  seiners. This requires  programs.  so  costs  an  role  fact,  Kirkiey  as those  gained  catch.  evaluation  some  could of  in  distinct  efficient  hypothesis  to  1987a;  herring  two  of  possible  participate  In  more  the  be  1984,  gillnetters,  the  is  might  in harvesting these  times  this  of  harvesting.  probably  herring  doing  license limitation  are  scope  salmon  area  components (Squires  seiners  different plus  of  output  especially  place  obvious  efficiency  economies of  salmon than  full  in particular,  aggregate  vessels,  take  the  available,  advantages  may  is a  resource  problem,  salmon  of  fisheries. There  of  determining  salmon  number  believe  in  lines  Directions for  needed.  static  However,  as their  be  the  outputs  keeping  these  dissipation  would  disaggregate 1986).  the  than  and output  along  and  the  both  species,  observers  and be  A  certainly tested  in  impacts  of  BIBLIOGRAPHY  Adasiak,  A.  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Cornell  "Production  Scallop  D.  Application  to  Economics  18(2)  Squires,  D.  Stanistreet,  England  (1987a):  Effort:  "Limited  139-152.  Canberra:  Atlantic edited  Surf by  Publishing  I.E.  Clams"  L.G. Inc,  and  411-417.  Rome:  in  the  National  Southwest  Structure  a  in  Multispecies  the  New  Oceanic  and  Fisheries  of  Trawl  Industry"  Fishery"  England  Sea  Atmospheric  Center,  Production  in  Specification, JEEM  Abalone edited  Government  McConnell  14(3)  and  1985.  Industries:  Rand  (1987b):  Fishery by  Internal  An  Journal  of  Structure  in  of  N.H.  Publishing  268-282.  Victoria" Sturgess  Services,  "Economic Analysis and  Economic  Anderson,  113-141.  Analysis Ann  for  Arbor,  Fisheries Michigan:  in  and  Policy T.F.  and  Meany,  1982.  the  Management  Management Ann  Arbor  of  Plans Science  1981.  V.J.  Management"  Management"  Management  K.  Regulation  Otter  Testing,  Australian  and  the  in  232-248.  Its  Entry  Fisheries  J. 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Resources: of  Fisheries  Vancouver:  British Columbia,  Some  1970.  Key  Problems  Management: Institute  of  A  Animal  208  Requiring Symposium Resource  APPENDIX 1 : DATA CONSTRUCTION This type due  of  largely  Therefore, this  to  Oceans  is  in  The  have  survey of  is  no  material.  The  made  There  is  the  available  by  providing  revenue  linking  these  of  each  data  includes  an  of  basic  and  two set.  output  data  data  quadratic,  restricted  description  of  data  of  the  is  a  profit  origin  major 1982.  Slips  file  It  is  choice  of  of  the  function.  The  vessel  level.  component  of  although  Fisheries  and  the  Program,  Planning  and  access  to  Statistics  survey  Branch  Department first  data has  important that  and been  four of  samples. variables  appendix  is a cross-sectional by  vessel.  data  set  by  of  this  work  is  the  confidential' nature  below.  This  Following used  concludes of  and  first  part  detail  Fisheries  the  preserves the  in  of  information  supplements  and subsequent transformations  209  fishery,  data,  has expenditure  An  types  this  the  significant  sources. The  described the  a  at  for  data.  which  information.  in  (Federal)  data  for  set  list  of  and  output  the  is  providing  sources in a manner  Each  analysis  the  Sales  source  in  attempted  information  base  Economics the  two  data  generous  been  price  Economists  use of  are  1982  and  single  one.  most  the  has never  suitable  Pacific Coast fishermen  second  the  a  been  been  Vancouver.  of  major  permitting  SOURCES  of  the  Branch have  A. DATA  Oceans,  expenditure  There  background  data  of  construction  Canada  instrumental  production study  lack  research.  Economics  The  level  the  the  thesis  other  micro  each  in  discussion  the  descriptions  a  normalized,  with variable.  a  detailed  /  210  of  the  1. The 1982 Survey of Pacific Coast Vessel Owners This  data  set  provides  individual  vessel owner  this type  of  micro  level.  described  The  data  Furthermore,  than  data  set  size  one  salmon  these  is 762  or  includes  tonnage,  used,  and  licenses  held.  In  set  consists  of  cost  fourth  detail  efforts  have  and  input of  to  data  the  level  British C o l u m b i a . * The  examine  never  at  been  fishing used  lack  of  at  the  behaviour  for  the  objectives  value,  and  of  case represents  vessel owner  three.*  fish.  each  type,  Tables of  This  Of  the  total  represents  A1.1  interest on  license  vessel's characteristics:  horsepower, through to  this  major  purchase,  estimated  of  one  who  may  cases  560  13.6%  of  the  1982.  information  year  A  other  on  engine  the  A  and  a maximum  in  type,  variables  the  to  hull  selected  replacement  cases.  information  for  to  data  without  presented  original  previous  fishing population  gross  data  cost  commercial fisheries  vessel up  with  salmon-licensed  The  the  detailed  in this thesis.  more  fished  in  first  has hampered  survey sample  own  the  current value.  age,  home  size,  port,  length,  gear  types  A1.4  descriptive  statistics  are  research.  Another  component  of  equipment market This  crew  purchases value,  component  such  net of  as  book the  the  value,  data  refers  vessel.  on  section the  in  the  number  data  and  set  value  provides of  gears  a  gear  inventory  purchased, sold,  for  1982.  destroyed,  tThe survey is not designed to elicit truthtelling from the participants, provide a means of cross-checking the answers. However, there is knowing what biases, if any, exist in the data. * O n l y 80 cases indicated ownership of more than one vessel.  It  provides  and  repaired.  nor does it no way of  / Fishing  activities  fishing  trips,  breakdown  the  of  Sales  the  survey and  side.  but  These  may  Fisheries from the  and  the  type  within the  is  the  output  what of  the  is  time  the  fished,  of  the of  above  information, is  the  value  number  of  money  bonuses  spent  proves it  to  does  contained  required  be  are  and  the  packer  Canada. either  date  record  generally  so-called  In  to  They  on  be  not  in  and  duration  of  Finally,  a  deliveries.  to  the  fuel,  an  have  the  case  vessel-owner,  and  is included.  excellent the  so-called  source  required Catch  prevailing  price  to  generate  supplied information periods.  fish stock  two each  by  vessel  This  is  the unit.  of  detail  input  on  Statistics  the  collected  the  every  packer fishing  must  catch, The  and  about  fill  catch  price  that  boats  a  with  varies  registered the  catch,  registered  and  the  a  receive  sales  by  to  are  grounds  out  along  variables the  which  along  by an  of  collect  slip  units  that of  species,  with  catches records  each  as  well  fish as  location.  vessel  used,  encountered  on  important  by  The  buyers  of  per  sale  processing companies boats.  the  location  the  wait  season and according to  possible  second  is  vessels.  and  number  Oceans Canada.  Oceans  transaction  fifth section, eg., the  1982  described  buyers  also  days  amount  information  vessel-owner  buyer.  It  This  the  including  quantity  Fisheries and  The  for  in  of  including the  Data  expenditure  by  number  Slip  Whereas  output  described  revenues,  expenditures,  2.  are  211  with  individual  from  this  associated  fishing biomass vessel.  set.  vessel-specific  grounds data,  data  to  are  The  price.  frequented  generate  first  an  and  is The at  estimate  / 212 B.  VESSEL  SELECTION  AND  sources  Given  the  basic  choice  of  which  a complete  set  data  DATA  vessels to of  TRANSFORMATION  two  tasks  include  data for  must  in the  be  performed.  analysis. The  The  first  second is the  involves  the  generation  of  each vessel.  1. Vessel Selection Three  different  troll  lines  one  of  some  gear  with  the  types  baited  three  vessels are  are  hooks.  and  are  used Most  to  harvest  salmon:  vessels participating  referred  to  as  seiners,  called combination vessels;  gillnet  seine in  nets,  the  fishery  gillnetters, and troll  gill  or  nets;  employ  trailers.  gears are  the  and only  However, dominant  combinations.  Since the to  gear  seiners, A  scale of used,  operations  four  gillnetters,  separate  production  are  the  the  mobile. for they  For gear  structure  biggest  next.  long  periods  come  each type  in to  gear  of  type  by  largest  tend  both  time  port  as well as the  exhibited  vessels  operate  developed. There  in  to  different  gear  that  congregate  at  seas,  unloading  is a  is uncertainty  crewsizes  open  before  the  a great  combination of  classification scheme  vessels with  Gillnet  Trailers  this  salmon fishing vessels varies  samples are  and trailers,  second reason for  the  of  on  move one  the  their  catch,  about  or  mouth  in  each  area are  Vancouver  Georgia  of  seiners  one and  of  gears.  uniformity  example,  from  coast of  for  and troll  the  For  swiftly river  west  sample  gillnet  types.  deal according  Strait  to less  Island, where  frequently.  the  (predominantly)  objective to  is  to  obtain  a  sample  fish salmon as a major  of  species.  vessels that  uses that  In  I do  particular,  not  want  to  reason  include is that  fisheries  in  a  multi-output jointness concentrate  systems.  the  same  the  inputs  is  the  the  is  license-holder  vessel.  catch  of  However,  must  one in  leasing arrangements  My  point  Owners.  Of  salmon  as  the a  of  actually  fished  When  the  hardship  762  major  number  permanant,  is the  in  non-Indian licensing  cases.  licenses  were  granted  to  The to  the  last  licensed 1982  to  (See  or  system  was  owners  holders  were  ten of  years  these  the  only  first issued only.  is  the but  the  not  do  the  of  of  168,  their  In  to  this.  A  licensed  I  catch  would of  informal  the and  licenses.  vessels  4528  are  licenses. made  for  licenses. These  extensions are  total  vessels  4112  temporary were  fished  the  vessels  temporary  numbers  is  licensing  1982  only  provisions  ensuing years  for  Pacific Coast Vessel  licensed  " B " or  test  salmon  the  herring  species.  special  a  person-specific.  salmon  the  so-called In  use  licenses, and  and  are  two  estimate  different  given  Survey  minor  the  season. Ideally, the  the  to  in  are  however,  adopted  licenses,  fishery  4638,  Of  Indian  do  tonnage  with  The  objective  permanantly-licensed  other  6).  to  1982  560  salmon  are  very  impossible  respect  in  Chapter  under  combined  without  fish  licenses; 358  for  with  surveyed  I  the  species.  to  my  Coast,  herring  is  is  dissipation  net  213  survey  outputs  Since  a vessel for  this  vessels included  vessels  roe  its  major  the  two  rent  West  and  be  cases  made  species, with  vessels  the  designate  many  to  as  solution the  operate  vessel  in  as  in  1987a).  the  vessel to  unrecorded  starting  and  technology  the  given  herring  on  salmon  possible  fisheries  issued  and  costs  One  1984  the  fishery  licenses  total  roe  fishery  that  salmon  herring  and  harvest  major  herring  the  (Squires the  the  both  way.  salmon  linking  whereas  However, like  apportion  factor  In  factors,  cannot  with  which  fish  predetermined  on  complicating  that  model  in  fishery,  I  vessels  /  rapidly  have  been  declining.  / They  are  specify  distinguished  the  length  After  dividing  have  caught  sample.  the  to  Instead,  roe  I  am  number  recent  review  and  Oceans,  the  number  landings,  for  1982  539  in  fleet,  my  and  1020  in  samples constitutes  percentage Otter of  is  of  Trawl  coverage  fleet  uses  than 2  of  with  to  licenses,  be  following 80;  troll,  of  active  salmon vessels,  of  Squires of  an  1331  in  combination the  active  (1984,  fleets.  21  60.  Department  those  that  fleet,  appears  study  of  the  vessels in  a  that  gillnet-troll,  1638 that  in  the  each  New  total  of  reported  This is a somewhat  His  on  It  those  per  the  gillnet  fleet.  1987a).  observations  the  ie.,  not  observations  and  economist at  do  perpetuity.  deleting of  84;  which  in  and  number  by  seine fleet,  held  categories  fishery  5-6%  years  four  the  "A"  meant  gillnet,  gillnet-troll  about  are  or  the  the  the  one  21;  of  salmon  they  left  Fisheries  troll  regular  vessels into  vessels a  the  tenure.  560  herring  Seine  According  of  from  214  of  greater England  population  776.  2. Data To  Generation  estimate  restricted variable  the  profit inputs:  input function  labour,  information  on  the  stock  relative  output  Since  tThe  the  price and  the  demand  fuel,  three of  are  justification  for  need and  fixed  price gear  or  fish available.*  quantity  data  I  equations  derived  and  To  information.  quantity  services. In  restricted  the  normalized,  information  addition,  it  is  for  estimate  the  output  must  input/output  including these variables is given  quadratic,  the  following  necessary to  inputs, vessel tonnage,  These data  cross-sectional, the  from  fishing  have  days and  supply equation  I  need  be vessel-specific.  prices  later  are  in this  either  region-  appendix.  or  / vessel-specific. fisheries  (Squires  particular, the  the  use  west  Regional  of  Vancouver  1984,  vast  have  1987a).  amount  regional  coast of  prices  of  prices.  Victoria.  used  Furthermore,  non-uniform Homeports  Vancouver Island  and  been  to  Seven  the  major  the  successfully geography  coastal area,  are  scattered  northern  area  regions,  with  River, Madeira  Park)  in  of  studies  British  is a sufficient across  of their  the  other  Columbia, justification  province  Prince Rupert major  of  215  from  and  centre(s)  for the  down are  in  to  listed  below. 1.  the  North  2.  the  Central  3.  East Georgia Strait  4.  West  5.  Lower Mainland  6.  Capital Area  7.  West  A  detailed  with  the  The  The  Island  services  (Powell  are  Nanaimo)  0 to  skipper  used per  data  Next,  Price  labour on  all  Ucleulet).  a  generated  and  discussion  of  subsequent the  output  transformations variable  is  begins  undertaken.  inputs are described.  Variable:  varies from are  of  inputs.  used  River,  (Victoria)  restricted  of  (Campbell  (Port Alberni,  variable  quantity  Klemtu)  (Vancouver)  description  Labour  Rupert)  Coast (Namu,  Georgia Strait  Finally, the  a.  Coast (Prince  input the  and  is obtained  vessel:  5 across the vessel.  Quantity  crew  entire  from and  sample.  the  Survey data. Two  skipper. It  The  number  of  is assumed that the  types crew  of  labour  members  services of  one  / The  fishing  industry  often  adopted  share  of  to  the  year  the  fishery..."*  and  the  particular,  this  unit  the  price  for  assumed  Earnings,  for  (Roy,  the  and  1987a)  notion  This  a first  labour)  crew vary a  adopted the  year  may is to  be find  vessel-owner  the  it  is  "wage"  employ  the  Hannesson  a  potential  approximation to  is  gets  from  variables  by  equal  1982,  system  presents  researchers  Tsoa  wage  average  weekly  earnings  category, Data regions the  are  the  Canada  collected  for  not rate  wage  1983,  in  Squires  to of  cost  Tsoa  (1982),  in  wages  to  construct  a  Columbia  in  for  of  in  Employment, Columbia  Columbia  relevant this  fishery  employees  British  British  the  suitability  all  72-002,  cities  calculate  commerical  for  catalogue  and  the  and  overtime)  five  already  used  discussion  Schrank,  British  (including  Statistics  method  Roy,  opportunity  for  mentioned  each vessel a brief  and  of  relevant  explaining  the  labour  exogenous  fisheries  The  the  to  is frequently  "...as  share  is,  independent  be  (of  a  1984).  adopts  to  cost  Schrank,  research  Hours.  returns  that  to  that  That  fluctuations.  that  most  (1984,  composite  Before  practice,  the  solution taken  in  crew.  so-called  argues  Squires  be  corresponding  (1981)  of  labour.  and  cost wage  Bj0rndal  work  to  industrial  average.  industry  1987a;  is  the  price  opportunity  In  industries  way  the  One  that  this  or  of  terms.  the  In  stock  labour  set  primary  remunerating  one  Hannesson  to  the  error  for  1977).  Following  is  That  manufacturing  1984  catch.t  is,  unreasonable outside  the  bias.  price  (Anderson  of  of  the  other  means  with  with  relevant  unlike  accordance  simultaneity  a  a  value  in  correlated  as  is  216  data  on  opportunity is given.  tAccording to one study of the British Columbia salmon fishery, the share varies by fleet and even by vessel (Cislason 1978). *R. Hannesson, O . Hansen, and S. A. Dale "A Frontier Production Function for the Norwegian C o d Fisheries" in Applied Operations Research jn_ Fisheries edited by K.B. Haley, 338-350. Plenum Press, 1981. p.338.  / There  are  two  employment wage two  matters  for  the  price  series should be  British  the  Department  (Hunter forms  of  uses  the  tries  to  Both  sources  average calculate  in  fleet  four  manufacturing  Taxation  Statistics,  which Taking  fishermen  of  a  by  the  that  evidence  report  and  on  as  his  includes  with  on  residual,  the  He  this  average  the  to  be  (1980)  on  from  incomes  most  popular  study,  Gardner  the  after finds  of  officials  the  of  regional  means  reveal  empirical  fishery.  of  Gardner  as  Gislason,  a  use  type  fisherman's  forestry In  the  and  discussions  industry.  in  alternative  that the  (1979)  a  labour  employed  noted  quotes  fisherman.  forest  to  be  Gislason  and  of  second is the  pieces of  latter  the  range  in  evidence  presents  am  British  Every year summary  able  in to  Columbia.  sector, Table  the  comes from  information  I  second matter A1.6  in  must  Two  choice  the  agriculture  for  capital  it  Oceans  returns  over  Division.  the  years)  manufacturing  The  identify  the  other  hand,  assuming that  weekly  they  wage  a  vary  in  the  industry.  second piece  the  the  types  Revenue,  Table  weekly on  matter  and  is  fishery;  research  wage  first  similar.  employment  weekly  the  fishery.  Fisheries  return  returns.  salmon  alternative  first  in  of  competitive all  is shown  Columbia  1971).  the  The  in  labour  first  to  used  regard  the  The  labour  With  case. The  over  consider.  data.  the  The  to  217  for  average  this  division  personal  Table  8  calculate Over  Revenue  publishes  income  or  8A  the  time  Canada, Department  or  statistics 9  average  this  a volume,  (the  table  weekly  closely  based  of  entitled  Tax  on  taxable  number  changes  income  follows  National  earned  incomes  in  by the  A1.5.  discussion weekly  concerns the earnings  for  use British  of  regional  Columbia  wage on  information.  average  and  In five  / regional which  centres would  evidence has  a  appear  homeport  Starting for  the  between  and  areas  1985  Given  the  average weekly  AWE  mentioned Series  the  of  show  mobility  made  in  this  upon  catalogue,  a  as  estimates  for  average  This  a  in  above.  For  the  respective  average  A comparison of  each  the  force.  for  This owner  his  the  Port  the  crew.  necessary  Alberni,  data  for  urban  are  1982  areas  earnings  1983  variation  his fishery study.  areas  weekly  of  vessel  market  publishes  1982  urban  generates  that  Nanaimo,  these  and  labour  for  Canada  deal  the  regional  Victoria,  whole.  great  thesis  the  Statistics  Vancouver,  Columbia  high  wage  to  unemployment reflect  cost wage  in  not  the  is  as  1983  applied  1982  differential  and  to  for the  to the  1984  the  I calculate  rates  in  1982  it  difficulty  of  for  vessel is taken  each  obtaining  is  necessary  alternative to  be  for  the  employment. the  expected  earnings. This is defined as:  EAWE is  data  reveals little variation.  relatively cost  lack  draws  areas:  B.C.  mentioned  opportunity  (A1.1)  1983  1982.  differentials  opportunity The  for  The  1987a) also assumes as relevant  urban  the  a  vessel and  obtain  B.C. average urban  his  British  To  1982.  assumption  March  for  for  suggest  the  following  and  differential  for  the  disaggregated.  5  to  Squires (1984,  with  Courtney,  the  presented  accords with  This is what  data  are  218  =  (1-U)*AWE  average  earlier,  D771624  Table  to  economic  regions  Columbia.  Basic  weekly 16.  Labour  (U)*AWUIB  earnings U  D771633, of  +  British Force  a  is  the  found  in  the  unemployment  monthly Columbia.  series  on  The  title  Characteristics  by  Statistics  rate  and  comes  unemployment of  this  Economic  Canada  data  Region  from  Cansim  in  different  rates series and  catalogue  is  British  Metropolitan  / Area. the  The  areas  two  metropolitan  determined to  the  insurance  for  as one  two  Report  on  the  Average averaged  earnings.  paid to  weekly  earnings  fished  comes from  weeks  from  beginning be  viewed  The  work  Squires  by  are  are  (1984,  the  cost wages  is  valid  Although,  a  the  opportunity  than  52  the  fishing  and  (A1.1) the  weeks. and  for  of  weeks  Information is determined  may  season if  miss  out  nothing  weekly  rate  to is  probabilities  unemployment  73-001,  Statistical  (quarterly).  The  from  weekly  payment  The  data  Table  12,  benefits  are  rate.  expected  costs the  give  They come  benefit  opportunity  then  Act  Type.  represent  number  This  average  relevant  to  weekly  the  salmon  salmon fishing season the each on  vessel  the  as the a  number elapsed  week  is caught,  fished;  but  or  in  of  weeks  number  two  the  all  of  at  the  figures  may  estimates.  opportunity and  Roy,  on the  is  used.  in addition  employment  catalogue  Insurance  cost wages  the  delivery.  assumption  fishery  by  last  the  1987a)  reflect  The  average  Canada  an average weekly  sales slip data  of  opportunity not  to  less  as reasonable  on  the  Month  980-990,  These rates  Unemployment  equation  multiplied  to  end  done  the  need  much  first  and  create  obtain  they  is  Statistics  Province,  and  Victoria.  rate.  AWL) IB the  the  by  year to  cases  from  of  Payments  To  and  960,  British Columbia fishermen are  These figures  season.  world.  comes  generated  fishing  Vancouver  unemployment  the  Operation  over the  data  areas,  of  and  Weekly  Economic Regions 950,  minus the  states  benefit  benefits  The  chosen are  219  the  cost wages  Schrank,  and  for  this  Tsoa  fishery  (1982).  differs  They  assumption that fishing is a full-time  for most  the  British  important  Columbia of  two  that  calculate  of  annual  occupation. This  commercial  major  from  fisheries  salmon on  the  fishery. West  / Coast,  the  five  November average 12.6;  (MacDonald  number  of  for trailers,  this  thesis  18  species  for  labour cost  employed  wage  number  The  of  weeks  exhibits  find  new  this  assumption  costs  alternative  for  reflect the  the  to  is quite  gillnet-trollers, statistics:  vessels number  generate  underestimate is  fishery  zero  a  Thus,  it  to  the  hand,  opportunity that  cost wages  in this thesis strikes the  So  discussion  in  the  the  different  off-season  Department  of  has  concerned  and  is  vessel  shows  that  for  fished,  wages  crew  members  of  season.  be for  for  used for gillnetters, view  the  opportunity  since  this  that  the  is  is  the  are  labour  assumed  to  the  extent  jobs,  the  opportunity  cost  of  used that  especially an  data  To  weeks  may  the  job.  between  made  12  early  gillnetters,  relevant  observers believe  choice  to  14;  cost  fishing time  This  March  assumption to the  opportunity  some  estimate  that  fishermen. to  An  account  labour true  used in  in  of  for  remote  opportunity  middle ground.  only  fashion, since many  repairing  a  number  cost.  the  the of  the  it  seiners,  Hence,  Thus,  true  increase  other  seems  of  the  season  in an alternative  unemployment,  amount  for  reasonable  opportunity  the  may  is a  work  the  weeks  weeks  underestimates  the  a slightly  of  fishing  late  (Gislason 1979). The  seasonal.  end  On  in  as  from  For seiners  18 15  It  only  1976  small.  the  fishing season.  the  the  at  the  far  of  could not  frictional  methodology  communities.  available  gillnet-trollers.  crew  used  are  study  following  immediately  has  for  salmon  only  jobs  wages  16  A  fished  and  the  on  should  assumption  market  15.8;  and  salmon  1982).  weeks  generates  trailers,  of  220  the of  maintaining  crew  them the  Fisheries and Oceans indicate  members.  are  vessel.  owners  Skippers who  Discussions  that 6 weeks  on  do  are  treated  spend  with average  time  officials are  at  spent  / on  maintenance  to  of  be  an  estimate  spend  on  such  attributed  to  plus  6  The  notion  that  wage  of  adjusts  those  use  full-time  ie.,  to  the  is not  for  average  over  that  figure  average  viewed  the  as  of  10%  is  taken  skippers also  number of  is  various  take  by  of  weeks  weeks  fished  clear  chosen for  of  the  accorded a higher  not  view.  Squires  20%.  Roy,  50%  for  higher  fishery specific.  also  average  skilled,  is  skippers face  are  since the  the  skippers and  that  crew  into  This  arbitrary  skills are  the  enter  this  an  independent  management  categories  and  earlier  not  approximation,  also  earnings.  managers  upwards  for  It  may  weekly  mentioned  fisheries  bad  members  skippers  earnings  a  independent  vessel-specific number  of  papers  wage  weekly  that  determined  crew  amount  their  weeks  number  maintenance.  from  Both  cost  that  this  used  weekly  unskilled,  for  the  earnings  part-time,  and  employees.  to  and  labour  obtain skipper)  procedure  equal  followed of  is  processing companies.  Indeed,  standard is set  crew.  average  order  (crew  differ  of  it  skippers should be  the  an  equal  choose the  by  costs,  are  are  processing companies. This  number  Therefore,  relevant  the  employed  skipper.  In  the  and Tsoa  Therefore,  I  of  by  repairs and  opportunity  opportunity  extra  skippers  than  the  Schrank,  of  whether  rate  the  skipper  weeks  determination question  for  activities.  the  more  vessels owned  221  for  an a  divisia  used  to  1.00  all  other  quantity  aggregate index  is  of  the  generated  to  create  the  first  vessel in  prices  and  for  the  determined  by  dividing  for  is  measure  appropriate  to  (Diewert  aggregates.  each fixed  wage  both  1978, The  types 1986).  unit  price  sample. This indexing inputs.  total  The  implicit  expenditure  on  of  labour  This of  is  a  labour  procedure is  aggregate labour  by  index the  / aggregate  b.  The  The  Fuel  index.  Variable:  Price  cross-sectional survey  well as  price  as  to  the  the  company. the  21  16  out  Quantity  gives  information  of  engine,  nature  of  vessel ownership,  The  breakdown  80  are  vessels are  vessels  are  eg.,  diesel  between  seine vessels four  gillnet-troll  and  type  of  222  owned  not  or  fuel  In  expenditures  addition,  independent  two  by  by  total  gas.  eg.,  these  owned  on  types  of  or  it  The  entire  by  ownership  processing companies.  independent.  troll  vessel,  provides  owned  processing companies,  per  is  In  a processing  the  sample  information  as  follows.  gillnet  whereas  as  14  is  Of  sample  out  of  60  independently  owned.  Regional Table sets for  fuel  A1.7. of  prices Esso  prices  clearance fishing  available:  applies  and  is  valued  exemption,  valued  at  1.1  All  with  vessels  independent  For  each  This  is  homeports  of  diesel  the  one  to  Esso  of  for  its  cents  involvement  engines  litre,  deliver  used  approximation, their  catches  and  two  per  the  able  as an for  other of  deep  diesel.  sea fishing  both  to  gas  and  take advantage  of  usually  available  the  fuel  Two used  Canadian fishing  purchases.  those  vessels  second.  is purchased.  back for  in  customs  a  diesel  of  come  The  family  Only  where  Fuel  by  The  exemption.  found  retailing.  exemptions.  1982.  Prices are  are  fuel  for  in  indicator  They  marine  litre  vessels  refuel.  in  types  first  to  Canada.  the  for  applies  for  are  and  used  cents  qualify  is  to  fuel  2.9 per  Petroleum  gasoline  diesel at  homeport  reasonable to  because  processing companies  vessel a  from  fishing purposes is subject  exemption  ship  obtained  is chosen  are  commercial  are  the  to  their  following  / centres:  Prince  Rupert,  Namu,  Vancouver/Steveston,  Nanaimo,  Fuel  once  prices  change  Therefore,  a  divided  price  by  the  vary  fuel  about  costs.  fuel  The  prices  of  vessel's own  fuel  c.  Variable:  The  The  Gear  gear  entirely that being is,  variable  used  variable  gear  provides  can  1982  season (the  season. electronic  in one each  the  Port  to  at  is  Hardy,  by  of  Since one  generate  Campbell  beginning  the  River,  variation  reflects  the  October  to  price.  expenditures  for  to  sum  fuel  October.  share  pre-October  aggregate  dividing  of  prior  shares  minus  an  The  deliveries  the  is likely that the by  the  calculated.  number  determined  and  one,  the  share.  The  Fuel  prices  transportation  on  fuel  by  the  are  not  lines,  etc.,  a  of old  Unfortunately, equipment  as  a  malleable  capital  component  It  season,  since well-defined  type units),  given in the  is appropriate  board  about  each gear  on  the  the  of  or  gear  as well data  measure  to  on  nets,  traps,  view  this  type  of  from  board  limitations,  used for this  services  the  onboard  as the  whose  are  markets  removed  gear  good  parts  vessel.  information  inventory  Quantity  year. The  easily taken  detailed  an  is  treated  within  gives  price  weighted  samples; it  Price  is  by  be  fuel  season,  deliveries.  summed  fuel  Park,  price.  exhausted  are  are  1982  as  of  are  over the  quantity  average  number  prices  20%  the  determined  total  post-September weighted  is  Madeira  Bamfield/Ucleulet, Tofino, and Kyuquot.  during  share-weighted  pre-October  Klemtu,  223  exist  a vessel.  each  the  loss  or  it  is  input.  for  used The  vessel.  vessel at addition not  equipment  In the of  gear.  That  survey  data  particular, start  gear  possible  as  to  it  of  the  over  the  include  / The  first  step  calculated  by  justified  by  of  gear  are  to  deteriorate  and  the  well,  There  in the  is,  and  or  however,  phenomenon; attributable  that  to  expenditures  the  gear,  in  particular  the  to  estimate  a  types.  In  asset  price  tThey  light  life  over  age  gear  of  of  units  of  each  assumed  their  an  period  given  the  important for  gear  that  both  is, gear  productive  off-season  is  of  the  of  the  depreciates  a unit  for  assure  nature  of  appear  This  gear  type.  This is  old  This  to  of  type.  units  ability.  part  each  and  are is  a  new  constant  the  fishing  is  units  assumed  because  not  repairs flow  of  operation,  pre-season preparations. As to  be  well  established,  a  to  of of  unit  be  gear an  of  dealt  with.  decays over  old  gear.  gear  unit.  Thus,  for  This  time.  of  between  a straight  over  time.  gear  unit  the  age  of  line  calculation assumed  each  of  of  the  depreciation the  true  suitable  constant For  is  the  flow 1982  not  As well, each  known,  gear  per  is  In  as  it  vessel  is assumed for  a  part,  price this is  maintenance  vessel and  is an endogenous p h e n o m e n o n . Given the  approximation  is  effect  expectancy  time  structure  relationship  include The  of  markets  shorter  a linear  step  is  assumption  price  taken  next  of  production. That  the  is, the  Therefore,  The  stock  number It  depreciation  price depreciation  be  the  magazines attest.t  depreciation. to  in  repair  a  decline  of  in  rental  trade  the  terms  reasonable  second-hand  classifieds  in  done  maintenance  of  assumptions.  time  are a  of  equivalently  over  is  generation  addition  following  treated  This  gear  the  a simple  maintenance  service. as  involves  224  data is  unit  limitation,  not and  possible its  price  convenience. It  is  price depreciation.  rental of  prices  services,  season,  the  for it  is  the  different  assumed  appropriate  Fisherman, Pacific Fishing and Westcoast Fisherman.  gear  that  method  the of  calculating standard guise, of  this  reflect  rental  Jorgenson  the  The  the  the  rental  (A1.2)  Pg  this equation  is  the  D,  current  gear  taken  maintenance for  this  has  the  =  or  +  D)  unit  other  to  be  constant  repair work  not  is work  privately  owned  personal  income tax  relevant and  to  calculate  the  unit  several  sources.  inventory  data  found  in  provides  detailed  different  gear  types gear  all  type.  the and follow  the  the  gear  1977)  1963).  current  In  (1982)  discount rate,  is chosen to  user or  the  and  gear  in  rental  be  and  the  type.  industry  1982  and  fisherman's are  rental The  of  the  its  purchase  usual price  parameters  that  following:  This  of  straight-line  Estimates  of  and  averages.  is vesselIt  and  the RM  is  for  seems that the  gear  each  purchase  rental  prices In  expenditures.  It  depreciation rates  are  corporate  most  of  I  tax  vessels are assume  and for  the  is  each vessel  available  addition,  rates, are  value  price calcuation.  gear type  owners.  depreciation  the  rate,  gear-specific. The basis  However,  the  Q  each vessel  depreciation  incorporated.  vessel  maintenance  R,  gear type.  specific to  since  affect  rates  is  a given  decision making,  not  current  Survey  cost of  discount rate,  are  does not  from  repair  of  owners  structure  include  (Schworm  Oorgenson  by Schworm (1977).  the  their  of  unit  done done  price  rate,  hand, the  originate  to  that  version  RM.  price  the  modified  225  structure.  +  On  is  according  tax  Pg represents the  equation  used to  a  services  components  Q*(R  structure  Data  use  capital  corporate  (1982)  type.  are  of  to  price for each type  In  and  is  economic depreciation  aspects of  gear  type  method  gear,  price  /  from  the  inventory  assumed but  obtained  that  the  that  the  they  vary  from  industry  / sources  and  provide  vary  between  from  33.3% to  and  traps.  33.3%  study  robustness  of  with  The  nominal  discussion many  been  average  of  the  In  interest  fishermen  usually  No  is  as clients,  calculated monthly  as the  rates  the  cases,  two  on  or more  February  gear  price.  A  divisia  price  to  index  rate  loans  33.3%  natural high  and for  (1980) way to  in  range  is  are handlines traps,  and Gislason test  depreciation  that  1%.  in  same  Fraser  for the  rates,  then,  the  estimates.  all  gear  for Credit  loan  Union,  rates  The  The prime  types. which  to fishermen rate  1982. The rates  are kept  quantity  over  is calculated  price  is obtained  by dividing the total value  and troll  to  rates  chosen  A has  have  is the  are obtained  from  1983. The rate is 16.8125%.  The aggregate  gillnet  the  the vessels  found  the  and  plus  information.  include  be  Gulf  price  tSources  is  these  by using the low rates.  types  gear  a  nets  gears  by Gardner  run with  the information  business  25%  used  seine  and troll  are  difference  the  prime  construction of an aggregate  rental  of  gill  provide  are first  assumed  elicited  Bank of Canada Review,  some  ranges  obtained  representative  For the  used o n board  rates  appreciable  rate  the  handlines  from  These  only the estimates  a  for  type.t  for  gear types  The programs  rates.  gear  whereas  rates  fishery.  results.  with  each  d o not differ  this  low  results report  33.3%,  depreciation  50%. They  to  rerun  and  for  50%. Two other  The  to  (1979)  20%  ranges  226  quantity  fishermen  index  on board  a vessel.  all gear types  using  the  of gear  the  by the price  and a marine  requires  and an associated  quantity  associated with  This  and unit  rental  aggregate  rental  index.  supply store.  / d.  The  Raw  Output  data  record  come  every  data  include  over  the  by  Variable:  sale the  of  book  prices  season. per  That  is,  that  is,  species the  the  bonus  type  and of  week.  No  given  species  to  as  are  effectively  raise  of  Statistics.  packer each  the  at  until the  to  the  increases  in  the  unit  per  fish  Prices  vary called  the  stated  end  of  species the  The  of  slips are  catches  made  They  boat.  type  fish.  sales  the  according  percentage  a  the  record  bonuses  or  catch  from  payments  Catch  landed  used  Prices taken  calculated  per  quantity  gear  as the  company  companies  progresses. are  known  processing  processing  are  rates  a  pound)  by  skippers  bonuses  slips, also  to  the  and  season  time,  sales  (per as  area,  That  Quantity  officially  well  by  and  1982  price  as  as the  At  The  unit  fish,  prices".  the  made  season,  type  "book  from  Price  227  caught.  book  prices  the  prices. obtained  per species.  The  bonus  rates  negotiations these  the  are  has  value  of  Pearse they a  available on  The  as the  landed  value  bonuses given  complains record  significant  over  portion  of  the  tPersonal  Communication  Economics  Branch, Department  are  the  survey  the side  all  from  types  and  individual the  These  given  catch  Table the  are  also  skippers.  Department  rates are  in  from  and  used  A1.8.  Total  Sales Slips data  to  Unfortunately,  of to  subject  Fisheries obtain  and  end  of  revenues plus the  are total  data.  usefulness sales.  sales  He  of  Catch  that  these  fishermen  wish  Fletcher,  Fisheries and  the  claims  because  Heather of  gear  Instead,  rates.t  rates  about  of  vessel.  1983  in the  and  companies  per  the  prices.  not  species  processing  unit  (1982)  do  not  across  information  season  calculated  be  between  rates  Oceans  vary  economist  Oceans  (Pacific  Statistics  data  unofficial to in  because  sales  might  underreport  their  the  Region),  Planning  and  Vancouver.  official  catches  Department  of  not  be  the  fisherman  way  too  in  number  for  to  their  license  e.  is  the  The  latter  and  Oceans.  by  The gear  be  per  price  Fixed  two are  with  why  that  it  paid,  be  paid  to  that  do  not  ie.,  the  best  first  has  to  are  unincorporated  the  do  based  for  might  interest  skippers,  landings  of  criticisms  in  benefits  report  employee  Pearse's  is  reasons. The  an  with  the  upon  the  as  two  of  well  years  as  have  tonnage  is  fishing  types. days.  restricted  from  Survey  is  the  In  per  vessel.  aggregate  into  the  The  species  total value  per vessel on license  also  also  a  fixed  days per  declare  addition,  Between within the  registry  has  restricted  data  by  the  factor  vessel to  vessel-owner. may  information  a  divisia  output  of  index  quantity  of  is  aggregate  obtained  by  sales plus bonuses.  Inputs  The  regulator  fishing  may  quantity  is obtained  tonnage  desired  benefits  reasons  suggests  for  vessels  gives information  Net  of  and  calculated  or  Survey  number  addition,  aggregate  The  gross  In  price  Restricted  vessel.  employee  and  discussion  provides  landings  worked  A  228  revoked.  price  dividing  The all  purposes.  Oceans  unemployment  members.  output  report  weeks  the  and  troublesome.  crew  Using  evasion  Fisheries  which of  tax  /  This  is  the files  on  kept  the  fixed  because  of  closed  to  nature  has  control  over  season.  forces,  the  It  is  the  all  fishing  fishing  level which the or  tonnage.  of  Fisheries  finds  a  each the  assume  the  is less than  that  to  is  only  number its  by  season  fishery  open  maximum vessel  net  days  within  reasonable  way  the  Department  of  fishing the  not  although  a some  area  two  number  vessel.  an  these  by the  government,  per be  gross tonnage,  managed. to  of  fishing  certain possible days  to  / The  third  season. that  fixed  It  is,  seems  a  choosing  areas  since  I  use  season.t adding and  from  certain  number  of  to  control he  the  available  on  the  of  the  stock  I  construct  escapement areas  (the  and  vessel within  a  the  vessel's point  of  fish  each  amount  of  control  fish.  is important  an  the  the  cannot It  of  available  number  species  the  degree  fish  species  by  as fixed  reduce  measure  some  try  encountered  this  abundance,  impact  together  a  can  an  each  stock  view  only  great to  fish to  have  For  for  of  serve  may  a  provides  vessel-owner  that it  is the  reasonable  nature  although  vessels  factor  input  in  of  fish  view;  Furthermore,  encountered  actions to  fishing  by  of  the  other  include  this  factor,  substitutability.  an  estimate  the  year.  229  area of  fish that  at  the  the  stock  spawn),  sports  catch  and  described  above  is  the  the  beginning after  the  of  the  fact  by  commercial  Native  catch,  food  fishery  catches.*  The  stock  number stock be  generated  of  values  done  weight,  not  stock  In  are  harvest the  the  order  manner  to  multiplied  because  underlying  For  fish.  in  catches  obtain  by are  the  management  of  purposes  of  the  weight  described  function  fish  estimate  average  usually  production  number,  an  in  of  measured total  fish  terms  of  should  be  thought  areas  have  been  in  weight  caught their of  in  terms of  fish,  1982.  weight. as  of  the these  This  Thus,  explaining  is the the  caught.  thirty  designated  by  DFO.  A  t A more complex method would generate weekly stock estimates by subtracting the previous week's catches from the beginning total stock. However, most fish pass through an area quickly, so that most fishing takes place within a short time (ESSA 1982). As well, total catch is generally a small proportion of the total stock. *They are important only for certain species and for specific areas.  management  area  1982,  commercial  both  Unfortuntely, not  reflect  reason  for  to  actually  fish  the  vessel  should  fish,  other  but  is  over  relative  also  relying  is  abundance This  is done  aggregated relative  These  stock  weighted  should  reflect  appropriate that the  into  area  a  in  the  may  escaping  River  to  small  proxy  season.  A  of  some  work  for  by  each  single  species.  area  the  added  aggregate stocks  a given  are area.  of  the  This  each  the  of  these  their  each  fish  number  catches.  available  individual  estimate  that  That  relative  by  prevail  for  area  weighting in  each  the  relative  number  that  sample  there  is a fair  the area.  patterns  vessel of  of  total  per  each vessel's fishing Thus,  Lane  the  measures  is,  prices  a measure by  to  vessel  abundance.  area  stock  fish  escapement  large  the  data  heading  abundance.  accomplished prices  fish  though  relative  stock  Finally,  by  some  of  species.  escapement that  basis of the  measure.  weighted Within  is  its  However,  for  relative  relative  together. stock  area's  The  and very  area. Thus, for that  fishermen.  the  absolute  the  estimate  may  amount  the  on  above  even  measure  not  Next,  index.  then  final  dividing  by  average  only  in this  quantity  per  the  suitable  not  small,  For  described  area.  areas, where  estimates. by  example,  that  230  obtained  collects  for  are  stock  time to  escapements  salmon,  area  are  manner  given  in  catches  have  data  means,  management  Fraser  compile  Oceans  of  other  to  the  any  as  created  vessel fished in  at  This  a subjective  aggregate  in  Fisheries and  upon  stocks are  use  counted  meant  measures  I  calculated  available  chooses a particular  relative  5  escapement  abundance  done  are  and  of  the  (1986) has recently  biomass.  data stocks  areas  variable  the  that  destination.  Hence,  owner  fisherman  are  a number  caught.  be  unit  salmon  spawning  River  stock  of  data  Department  the  Likewise,  The  of  the  through  is high.  the  area-specific  Fraser  migrate  basic catch  number  is that  the  are  the the  according  is the  /  the  weeks  degree  of  / variation  in  this  variable  as shown  by the  summary  statistics  in Tables  A1.1  231  through  A1.4.  C. IS A  1982  final  year  A  question  to  year,  considered items  are  landed  REPRESENTATIVE remains  the  to  1982  be  fishing  as represenatative  of  considered. These  are  catch,  including  its  item is an economy-wide  In  YEAR?  general,  the  1982  answered. season  Given variability  must  be  and  future  the  fish  biomass,  among  season  does  fishing for  the  the  gear  the  not  prices  appear  suitability  from  to  be  Three fishery-specific per  types.  interest  conditions  its  fishing seasons.  p h e n o m e n o n , namely,  fishing  examined  past  distribution  in  species,  The  and  fourth  and  the final  rate.  too  different  from  previous  years, t  With varies  regard widely  (sockeye which  to  and  has  (chinook)  the  stocks of  across  the  species.  coho);  one  exhibits  been and  1982  one  severely  salmon it Two an  depressed  stock has an  of  appears that the  five  unexpectedly in  the  unexpectedly  bad  stocks  large  previous year  availability are  return  years,  of of  the  average  (chum)  continues  biomass  One in  this  size stock, state  (pink).  tit was subject to a very brief strike in August by members of the United Fisherman and Allied Workers Union (UFAWU). Most observers d o not believe that the strike had a detrimental effect upon the fishery due to its short duration. This union, which includes processing workers as members, went on strike to complain about the. minimum landed prices offered to them by the processing companies. Every year bargaining takes place for minimum prices for the various species. In the 1970's actual prices were often the minimum negotiated prices, but this is no longer the case. Actual current day prices are typically much larger than the minimums.  / Real  prices  in  with  1975,  it  other  is  hand,  species  on  catch  of  each  gillnet,  constant  much  smaller from  lower  four of  of  more  the  somewhat pink  stocks  their  catch  in  less  years,  1978  is  of of  values. the  three  It  as  has  reflect  this  to  only.  On  the  their  1975  position  They the  chinook  the is  distribution  total  not  of  in  years,  seine  not catch  from  the are  and  sockeye,  the  less  of  pink  dollars  for  this  exception  of  the  landed  value  unusual  The  do  a  chum,  much  fleet.  but  a  pink  same  gillnet  seine,  and  the  the  the  chinook  much  that  coho  different  catch  suggested  the  years,  salmon  constant  with  of  seiners caught  and  too  coho,  value  are  previous  Troll-caught  previous  the  the  in  troll-caught  landed  sockeye,  detrimental  it  1977-1979.  the  been  Overall,  although  total  than relative  show that  for  Cillnetters  and  data  values  but  on  vessel types  Landed  years,  comparison  years.  than  years.  a  changed.*  the  species and  the  not  In  lower  However,  chum  years,  The  have  and  years,  1979.  chinook  to  for  earlier  same  and  particularly  appears  in  boom  chum.  per  salmon.  trends.  substantially  last few  sockeye  previous  larger  the  different  prices  higher.  For 1982,  previous  the  or  more  pink  four  than  dollars  of  are  catch  available  counterparts  exhibit  boom  constant  value  value  over  landed  value  coho  much  troll fleets.*  preceeding  especially,  two  the  and  prices  are  changed  dollar  than  lower  is  the  their  years  fleet  prices  of  species show  sockeye  chum  species are  and  larger  is  and  value  salmon  that  Chinook  the  the  found  prices has not  Data  differ  for  pink  counterparts.  the  1982  232  total  and  coho,  decline landed  in and  of  the  value  of  possibility.  tData on prices c o m e from a draft of the 1985 Commercial Salmon Fishery Season Update. This is written by members of the Regional Planning and Economics Branch of the Department of Fisheries and Oceans, Pacific Region. *This information is from the 1984 Commercial Fishing Guide, from "Review of the Financial Status of the Salmon Fishery" by the Department of Fisheries and Oceans, O c t o b e r , 1986.  Pacific Region and Heather Fletcher of  / The  catch  the  fishery,  species  distribution  at  gillnet-troll troll  ie.,  by  over  either  years. the  The  years  of  the  than  is  lower  than  otherwise.  large in  interest  normal  operate.  changes  in  rates  higher-than-normal  of  to  rental  larger  must  gillnetters.  have  been  troll  the do  claiming  vessels,  may  or  experts  enjoying  However,  statistics  either  economy  high  interest  possible  been  that  may  larger  hide  gillnet  increasing it  a  this  gear.  gillnet-only  have  of  most  be  true  that  portion  These  equipped  about  shares  also  fact,  made  of  since gears  the  catches may  vessels,  entire are  be  or  used  by  the  vessels.  impacts high  observations  have  experienced  Columbia commercial  payments  fishery  by  equipped  debt-servicing that  the  catch  as taken  Canadian  British  of  The  gillnet-troll  the  seiners  vessels  time.  troll-only  detrimental  few  expense  recorded  1982  and  combination  combination  In  trailers  the  catch  typically  by species reflects  233  the  prices  for  the  However,  salmon  borrowing  rates  not  have  calculated,  both  for  fishery. they  This do  rates.  pose  reflect  that  the  estimation  the  real  for  net in  are  the  preponderance  the of it is  may  be  might  be  under which  the  this  relatively  from  that  rates  tonnage,  robust  many  amounts  interest  conditions  whereas  problems  explain  and  rents  results  Therefore,  serious  might  means  gear  argued  large  high  for  exempted  have  added  Given these  rates  been  people  costs.  depreciation  rates  has  Some  1982  interest  fisherman's  the  interest  highest  fishery  costs.  preceeding  Furthermore,  not  the  year  in  the  face  of  small  variations  econometric  analysis,  of  negative  rents.  / Table  A1.1:--Vessel characteristics  and expenditures:  seine  Characteristic  Mean  St. Dev  Minimum  Maximum  Crew Size GRT NRT Length HP  5.1 35.1 23.9 56.5 214.5 25.8 32.0 1.11  0.44  4.0 14.0  8.6 81.9 18.3 15.8 0.27  9.9 44.8 n/a 4.0 12.0 1.00  6.0 123.0 83.7  Fuel Gear  27524.0 8480.7 20768.0  6581.5 4819.9 15183.0  15199.0 2800.0 6509.7  38214.0 22500.0 61059.0  Revenue  93579.0  43424.0  31231.0  173620.0  Age Days Fished Stock Index Expenditure Labour  22.8 15.4  234  86.0 365.0 56.0 79.0 1.83  Notes: Sources: The Survey Data and the Sales Slip Data. The number of observations is 21. Crewsize includes the skipper. GRT and NRT are gross and net registered tonnage. They are measured in imperial units. Length is measured in feet. HP is the horsepower of the vessel. Age represents the vessel's age in 1982. Stock index represents the index of stock abundance and is indexed with reference to the first observation set at 1.00. Revenue is the sum of the value of landed catch and bonuses. Gear expenses are calculated using low depreciation rates. Labour expenses are calculated as the opportunity cost wage bill. Expenditures and revenue are in constant 1982 dollars.  / Table  A1.2:-Vessel characteristics and expenditures:  gillnet  Characteristic  Mean  St. Dev  Minimum  Maximum  Crew Size CRT NRT Length HP Age Days Fished Stock Index  1.2 6.8 6.1 33.0 178.7 14.1  0.43 3.1  1.0 1.0 0.7  2.0 23.0 12.4 38.0 440.0 32.0  22.0 1.28  1.9 3.8 86.1 8.3 12.5 0.50  7520.3 1647.0 5978.5  2710.8 1146.8 4356.7  4084.4  Fuel Gear  200.0 601.4  17133.0 5750.0 19613.0  Revenue  17982.0  10220.0  5027.4  67199.0  Expenditure Labour  15.0 n/a 1.0 6.0 0.33  235  91.0 2.39  Notes: Sources: The Survey Data and the Sales Slip Data. The number of observations is 80. Crewsize includes the skipper. GRT and NRT are gross and net registered tonnage. They are measured in imperial units. Length is measured in feet. HP is the horsepower of the vessel. A g e represents the vessel's age in 1982. Stock index represents the index of stock abundance and is indexed with reference to the first observation set at 1.00. Revenue is the sum of the value of landed catch and bonuses. Gear expenses are calculated using low depreciation rates. Labour expenses are calculated as the opportunity cost wage bill. Expenditures and revenue are in constant 1982 dollars.  / Table  A1.3:--Vessel characteristics  and  expenditures: troll  Characteristic  Mean  St. Dev  Minimum  Maximum  Crew Size GRT NRT Length HP  1.9 11.2 9.1 39.4  0.60  1.0  3.0  6.5 2.4  3.0 2.8 27.0  60.0 17.7  n/a  Age Days Fished Stock Index  21.6 97.1  1.0 30.0 0.07  471.0 54.0 165.0 1.00  58.0  0.45  4.5 85.8 13.2 30.3 0.27  Expenditure Labour Fuel Gear  9773.6 3542.3 4624.7  3816.8 1975.6 5594.3  3352.1 950.0 5.2  21394.0 1000.0.0 32409.0  Revenue  42659.0  23254.0  10154.0  108630.0  130.6  236  Notes: Sources: The Survey Data and the Sales Slip Data. The number of observations is 84. Crewsize includes the skipper. GRT and NRT are gross and net registered tonnage. They are measured in imperial units. Length is measured in feet. HP is the horsepower of the vessel. Age represents the vessel's age in 1982. Stock index represents the index of stock abundance and is indexed with reference to the first observation set at 1.00. Revenue is the sum of the value of landed catch and bonuses. Gear expenses are calculated using low depreciation rates. Labour expenses are calculated as the opportunity cost wage bill. Expenditures and revenue are in constant 1982 dollars.  / Table  A1.4:--Vessel  characteristics and  expenditures:  gil Inet-troll  Characteristic  Mean  St. Dev  Minimum  Maximum  Crew Size GRT NRT Length HP  1.6 7.6 7.0 35.7  0.58 1.8 1.4  1.0 5.0 3.9 32.0 n/a  3.0 14.0  Age Days Fished Stock index Expenditure Labour  171.3 15.6 57.5 1.11  36.0 0.51  1.0 13.0 0.37  10.6 42.0 671.0 50.0 150.0 2.66  2.2 97.1 11.1  237  Fuel Gear  11447.0 3043.9 6803.6  4880.2 1981.8 5468.2  5428.2 800.0 36.8  30903.0 12000.0 22438.0  Revenue  32015.0  22413.0  10910.0  135900.0  Notes: Sources: The Survey Data and the Sales Slip Data. The number of observations is 60. Crewsize includes the skipper. GRT and NRT are gross and net registered tonnage. They are measured in imperial units. Length is measured in metric feet. HP is the horsepower of the vessel. Age represents the vessel's age in 1982. Stock index represents the index of stock abundance and is indexed with reference to the first observation set at 1.00. Revenue is the sum of the value of landed catch and bonuses. Gear expenses are calculated using low depreciation rates. Labour expenses are calculated as the opportunity cost wage bill. Expenditures and revenue are in constant 1982 dollars.  / Table  Year  1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983  Al.5:--Average  weekly  Fishermen  168.46 278.51 223.33 178.41 240.03 265.36 417.82 399.54 336.27 289.46 304.60 369.03  earnings,  British Columbia, current  Manufacturing  year  238  dollars  Employee  Forestry Operator  158.22 163.79 176.63 197.23 171.28 168.03 267.30 194.16 343.19 320.61 300.82 503.69  188.47 219.74 227.56 234.79 262.03 268.30 362.54 319.45 423.87 396.29 404.40 408.67  Notes Sources: Revenue Canada, Department of National Revenue Canada, Taxation Division, Taxation Statistics, 1974-1985 (Table 8, 8A or 9, depending upon the edition). Average annual wages are obtained by dividing total reported taxable income by the number of returns; weekly wages are obtained by dividing the average annual wages by 52 weeks.  / Table  A l . 6:--Average  Region  North Coast Central Coast East Georgia Strait West Georgia Strait Lower Mainland Capital Region West Island  weekly  earnings  and  unemployment  region  Unemployment  Average  Weekly  Earnings  (Current  1982  400.726 400.726 393.533 286.207 359.816 393.533 345.807 430.965  (B.C. average wage) (B.C. average wage) (Metro Vancouver wage) (Courtney wage rate) (Nanaimo wage rate) (Metro Vancouver wage) (Victoria wage rate) (Port Alberni wage rate)  $)  Notes: The average weekly unemployment insurance Sources: Statistics Canada 72-002 Employment, 16.  rate by  239  Rate  (%) 11.758 11.758 10.358 13.800 13.800 9.825 11.117 13.800  benefit is calculated to be $178.97. Earnings and Hours, 1983-1985, Table  C A N S I M , British Columbia Basic Labour Force Characteristics by Economic Region and Metropolitan Area, (D771624 to D771633). Statistics Canada 73-001 Average Weekly Payments by Province, Month and Type, 1982, (Table 12).  / Table  Region  A1.7:--Fuel  Gasoline (1982$  prices  Price ($/Litre) per litre)  by region  Diesel Price ($/Litre) (1982$ per litre)  North Coast -Prince Rupert  0.428  0.386  Central Coast -Namu -Klemtu  0.450 0.470  0.411 0.436  0.437  0.397  West Georgia Strait -Port Hardy -Campbell River  0.430 0.437  0.391 0.397  Lower Mainland -Vancouver -Steveston  0.410 0.410  0.371 0.371  Capital Region -Nanaimo  0.430  0.391  West Island -Bamfield -Ucleulet -Torino -Kyuquot  0.440 0.440 0.440 0.466  0.411 0.411 0.401 0.426  East Georgia -Madeira  Strait Park  240  Notes: Source: Esso Canada, Ltd. These prices are for the period O c t o b e r through December, 1982. Prior to O c t o b e r 1, 1982, prices are $0.015/litre less than those reported. Diesel prices include the $0.029/litre fishing exemption. Neither the gasoline nor the diesel prices include the $0.011/litre family fishing exemption.  / Table  A l ^--Representative  bonus  rates(%) by species and  Gear Species Chinook Sockeye Coho Pink Chum  Seine 11.4 13.5 10.8 13.4 13.0  Gillnet 8.2 12.2 9.4 11.7 10.8  gear  241  type  Type Troll 3.2 3.2 3.2 3.6 3.4  Notes: Source:The Department of Fisheries and Oceans, Pacific Region. These rates are representative of the 1983 rates paid to fishermen catch. Personnel at the Department of Fisheries and Oceans believe 1982 rates are not very different from these.  for their landed that the average  APPENDIX 2 : PARAMETER ESTIMATES - NONLINEAR CASE In  this  appendix  technique  are  the  parameter  presented  for  estimates  five  samples.  constant  returns  to  scale  constant  returns  to  scale,  and  the  constant  returns  to  scale.  The  single  functions  estimated  technique Testing  of  elasticities in  is  the  Appendix  nonlinear  the  results  obtained  case  are  of  imposed,  the  They  maximum is  also the  normalized,  the  nonlinear  seine  estimation  sample  without  both  with  and  without  gillnet-troll  sample,  both  with  and  without  in  parameter  are  a  sample,  output  likelihood given  using  gillnet  described in equations  using  the  obtained  supply  (5.8)  and  5,  values.  The  quadratic,  4.  242  through  details  chapter  and  restricted  (5.11)  may  along  three  be with  equations profit  input  in chapter  found a for  demand  in  chapter  discussion these  function,  are  5.  of  The 5. the  elasticities, given  in  / Table  A2.1:—Nonlinear  parameter  estimates:  seine  Variable Name  Coefficient Value  Standard Error  Variable Name  Coefficient Value  Standard Error  e  -0.13898T  0.06017  c  -1.6698T  0.72191  x  e  2  -0.27236+  0.15059  c  e  3  -0.10149E-05  0.30752  c  e  4  0.32342t  0.10552  c  e  5  0.66494E-06  0.23151  e  6  0.60085E-07  1  3  1.2204  1.9528  0.19913  0.66133  2 2  1.4732  1.3651  c  2 3  -2.4131 +  0.61377  0.12445  c  2  -2.4782  1.9881  0.18851  1.1531  -1.4136  2.0234  -2.9992t  0.94912  -1.0295  2.6248  1  2  1  b  2 2  3.4979  2.6956  c  3 1  b  2 3  -3.7283+  2.2831  c  3 2  b  3 3  -1.4241+  0.70353  c  3  3  *  3  b  0  -3.5805  3.0012  c  b  2  -0.41799  3.0397  c  4 1  13.7110+  7.7443  b  3  5.4111t  1.1033  c  4 2  19.7710+  10.8770  c  1 2  -0.01292  0.70759  c  4 3  -9.4196+  5.9794  c  1 2  1.6776  1.5384  c  4  -31.1710+  13.7130  LOG-LIKELIHOOD  Notes: The symbol t indicates from zero at a = 0.10.  that  the  FUNCTION  estimated  =  coefficient  243  -95.612  value  is significantly  different  / Table A2.2:--Nonlinear  parameter  estimates:  gillnet(crs)  Variable Name  Coefficient Value  Standard Error  Variable Name  Coefficient Value  Standard Error  e  -0.30848t  0.07642  c  1 3  0.24806t  0.05250  x  e  2  0.02347t  0.00768  c  1 4  0.27135  0.31932  e  3  0.24644E-06  0.01804  c  2 1  0.05437  0.07420  2 2  -0.09300  0.14759  -0.17623t  0.03784  b  2 2  0.34610t  0.25899  c  b  2 3  -0.05924t  0.05655  c  b  2 4  -0.25907  0.29721  c  2 4  -0.41892t  0.20449  b  3 3  -0.03166t  0.01712  c  3 1  0.01004  0.05840  b  3 4  0.00855  0.08770  c  3 2  0.01958  0.12812  b  4 4  0.28517  0.28500  c  3  3  -0.04878t  0.02873  c  x  l  0.10269  0.12499  c  3  4  -0.36074t  0.17667  c  1 2  0.19981  0.23837  LOG-LIKELIHOOD  Notes: The symbol t indicates from zero at a = 0.10.  that  the  estimated  2  3  =  coefficient  244  -50.3367  value  is significantly  different  / Table  Variable Name  e  A2.3:--Nonlinear  Coefficient  3  parameter  Value  Standard Error  -0.25528t  Coefficient Value  Standard Error  0.07556  0.17764+  0.26625  0.02188+  0.00704  0.20204+  0.05691  0.60436E-07  0.01799  0.18694  0.41075  2 2  -0.02156  0.40886  0.47888  0.47115  b  2 3  0.04651  0.07844  -0.01576  0.08914  b  2 4  -1.0575T  0.63005  0.04361  0.16310  b  3 3  0.08117t  0.02678  -0.18205T  0.03615  b 4  0.14710t  0.10497  -0.22369  0.26293  b, «  0.90405  1.0564  -0.04301  0.29480  b  0.89043  0.97200  -0.06439  0.07789  0  b  0.47506  0.59378  0.17657  0.15109  2  b  -0.31174t  0.15388  -0.6123+  0.03033  3  .0.45444  0.94111  -0.13477  0.24993  -0.06858  0.14927  -0.11300  0.26552  b  4  c, ,  LOG-LIKELIHOOD  Notes: The symbol t indicates from zero at a = 0.10. a  Variable Name  gillnet(non-crs)  b  3  3  estimates:  2 2— 2  — 3  e  i/'  ei  e ; 2  a, =el+e|; s  that  the  FUNCTION  estimated  =•  coefficient  245  -46.319  value  is  significantly  different  / Table  Variable Name  A2.4:--Nonlinear  parameter  estimates:  gillnet-troll(crs)  Coefficient  Standard  Variable  Coefficient  Value  Error  Name  Value  Standard Error  0.16337t  0.10405  -0.40717t  0.0.2300  -0.05490  0.24739  -0.95225E-03  0.19577  0.36502t  0.08334  -0.95825t  0.35617  -0.39102E-02  0.03313  -0.30314T  0.10273  -0.01254  0.02534  -0.10147  0.20390  -0.30223E-08  0.04324  -0.54612t  0.36021  -0.26218  0.38829  -0.41800t  0.11250  0.11032  0.16203  38.6840t  24.349  -0.35911E-02  0.05527  -93.9910t  30.672  0.21649  0.53457  2.5369  10.4550  2.4660t  0.72924  LOG-LIKELIHOOD  FUNCTION  =  246  -536.7018  Notes: The symbol t indicates from zero at a = 0.10!  a =e *e ; a,,-el+e§ a 4=(e *e +e *e ); a =ef.+e§+e . 2 4  3  1  4  2  4  3  2  4 4  s  that  the  estimated  coefficient  value  is  significantly  different  / Table A2.5:--Nonlinear  parameter  Variable  Coefficient  Name  Value  Standard Error  0.12799  estimates:  gillnet-troll(non-crs)  Variable  Coefficient  Name  Value  Standard Error  0.11095  0.45318+  0.23642  -0.12676  0.24470  -0.37025  1.4360  -0.29299+  0.12682  -0.03259  0.18662  0.59117E-02  0.02761  -1.5662+  0.56867  0.57212E-02  0.02876  -0.26009T  0.09589  0.14491 E-08  0.03954  0.79165  0.66303  -2.6812+  1.5572  -0.15556  0.19664  0.45804t  0.20406  -1.479+  0.59394  0.07340t  0.05269  -0.36415T  0.10388  b.  -3.4896T  1.9096  1.1607T  0.68181  b  3.0380t  1.6183  40.5510t  22.1390  -0.56747T  0.21560  -80.1440+  61.7270  0.27289  0.55843  3.2792+  10.9660  2.6970t  1.2666  -18.4010  68.5170  3  b,  LOG-LIKELIHOOD  Notes: The symbol t indicates from zero at a = 0.10.  that  the  FUNCTION  estimated  =  coefficient  247  -526.621  value  is  significantly  different  APPENDIX 3 : PARAMETER ESTIMATES, TESTS, AND RESULTS - LINEAR CASE This  appendix  the  seine,  described  gillnet,  in  (5.3)  nonlinear  require linear two  4  function  may  Chapter A3.5.  Each  estimates, scale  the fixed for  although Chapter  It  is  values  and  the  detail.  found  the  A  set  brief  specific  to  in the  imposed.  A  fleet  fleet  these  test  cannot  Table  troll,  A3.7 are  results  and  fleet  for  included and  the  the  for  is  the  be  Chapter  troll  elasticity  estimation to  this  normalized,  technique  is  5  given  concentrates  upon  since  between  elasticitiy  for  are  it  appendix  made  results  estimated  sample,  equations),  linear  set  quadratic,  does  not  discusses  the  results  measures  tables  gillnet-troll  fleets  are  of  the  given  restricted  with  and  of  returns  to  relevant those  elasticities  have  with  of  constant  x  of  values.  2  technique  numbered  both  possibility the  estimation  of  hypothesis  the  presents  the  has two,  the  reject  of  in  and  in  profit  4.  all  gillnet  discussion  the  given  fleets  equations  comparison  using  seine,  The  of  obtained  the  samples.  definitions  in Appendix  for  tests,  four  exception  nonlinear  forms  the  troll  5  the  a  estimates,  gillnet-troll  estimates  of  factors. the  the  whereas  gillnet  parameter  applicable. The  be  5 are  (with  some  and  parameter  and  Chapter  with  where  Chapter  to  in  linear  and (5.4). Whereas  estimation  cases,  The  in  results  results  the  troll,  detail  in equations the  presents  from  one  set  without scale  A3.1 of  to  parameter  the  other  fleets  for  derived  from  them  are  returns  and  scale  parameter  in  through  constant  is made  returns The  described  in  only the  estimates  completeness, discussed  in  5.  interesting with  their  to  compare nonlinear  the  linear  counterparts.  parameter A  248  estimates  complete  set  and of  equation-specific information,  R  2  including  / equation-specific A3.1 2,  through  tables  of  is  done  values.  by  5.5.  different  In  significant  linear  equations, much  in  R  at the  is the  furthest  from  5.1  Chapter  5  A  of  test  is  estimates  made and  are  to  level  seine  gillnet-troll  chapter scale The  A  5. There  and  the  output  It  is likely  are  regularity  of  larger and that  A  uses  a  maximum  a  goodness-of-fit  is similar to actual  number  equations  reflects  the  for  comparison of  seine  that  the  2  predicted  the  5 in  significantly  parameters  for  the  fact  are  the  calculated  R .  in Chapter  of  Furthermore,  linear  and  parameters  greater  those  the  measure  R  2  the  are  values  for  nonlinear  sample seine  eigenvalues  have  sample  in  Table  the  linear  this assertion.  the  given  cases.  in  This  accept  samples reject  than  estimation  linear  A  tables  appendix  case are found  cases.  this  convexity.  is it shown that  condition  the  labour  hypothesis Table  significance. However,  that without,  other  half  in  in  between  nonlinear  appendix given  that  correlation  this  case are  calcuate  demands  squared  somewhat  examine  results  nonlinear  confidence level.  accepting  a = 0.010% and  input  in  nonlinear  corresponding nonlinear  bears out  of  the  is found  necessary to  than  a 90%  values.  2  the  more  particular,  higher  is  the  goodness-of-fit for the  equation in  it  case  for  However,  supply and  calculating  zero  than  linear  estimates  therefore  general,  from  the  A2.5.  output  Estimates of  Table  each  through  the  for  Parameter  technique,  each  This  values,  2  A3.5.  A2.1  likelihood for  R  249  of  A3.6. at  for  samples  strongly  gillnet  symmetry  All  reject  a = 0.005% symmetry  contrasts both  cross-price symmetry  with  the  two  levels of  symmetry  at  the  is accepted in  the  nonlinear  samples, that with the  in  results  in  constant returns  to  significance specified.  the hypothesis.  called  monotonjcity  must  be  checked, although  verification  of  / its  acceptance  predicted  output  negative.  The  since the perform  The  However, total  of  and  the  results  80.  Similar  labour  this  fleet  fuel  both  results fuel  to  be  least  input in  for  to  the  to  seine  accept  to  be  demand  is  predicted  as  positive  ie.,  21.  Second,  some  distance  these  vessels  hand,  fuel  two  factors  This  has  it  most  from than  prices is  First,  vessels  most others  in  the  Vancouver  for  the  the  seine  an  input  unexpected  other  is  result,  samples do  returns  as negative  for  a  single  all  the  correct  3  out  of  60  to  for  scale  not  where  signs.  cases,  all observations.  observation  sample,  are  out  output  Once  observations.  once  again,  The  output  correct  for  all  of  a  supply  again,  The  and  understand  why that  as  all  their  lower a may  to than  positive be  labour  the  nonlinear  of  homeport. fuel  grounds.  elsewhere. fuel  generated  fact  that  and  gear  However,  explanations  number  more  the  the  observations.  Several  least  therefore  closer  generally  elasticities  has the  reflects  supply,  signs for  Vancouver  homeports  this  observations.  sample  grounds  are  predicted  that  is not surprising.  gillnet-troll  fleet;  register  with  possible to  ramifications  of  fishing  not  non-constant  convexity.  predicted  phenomenon.  is  that  requires  these.  all  this  this  demand  the  for  are  for  and  This  positive  demands  identical  likely  as  positive  and  fuel  Monotonicity  convexity. The  convexity,  and  obtain  as  accept  constant  test.  positive  condition.  to  reject  input  is different  is  one  the  gear  predicted  found  situation  demands  and  is  The  only  the  statistical is  this  supply as positive  predicts  a  observation  since they  for  it  are  with  accepts  is the  sample,  input  each  but  output  made  sample  fleet  as well,  predicts  be  for  troll  troll  gillnet  gear  cannot  250  observations, Vancouver  is  required  by  is On  the  Combining  demand  exist  other these  is  predicted.  using the  parameter  / estimates.  In  adversely with  In for  affected.  their  Of  in  sign  substantially magnitude and  elasticity  of  counter  Estimates studies and he  the  of  two  a  own-price  conditions  reflect, price  of  elasticity.  landed  prices  pinks to  in  or  the  supply  the  zero  is very  elasticity part,  quantity  fishery In  for  $2.50 for  the  the  the  5  merely itself British species  own-  elasticities  demand  does  the  gear  other  own  price  nonlinear  case,  both  labour  and  linear  fuel  case.  On  and  they  disturbing.  are  not  new  multi-output  to  (1985),  otter  trawl  labour  to  obtain  Columbia salmon  good  these  contribute  of  to  the  widely  fish are  not  the  generation  salmon from  $0.35  a for  per  in similar  These  may A  other  of  fishery,  available  addition,  estimates.  On  1987a)  positive. which  run  Squires  (1984,  be  own  results  In  to  positive  fisheries.  data  differ  hand, the  result.  parameter  problems.  commercial vary  the  large,  fishery  this  change  respect  These  of  obtains  for  are  significant.  studies  linear  elasticities  other  to  and  demand  exacerbates  the  the  not  with  elasticities  negative,  are  the  chinooks. However,  cross-price  for  cross-sectional nature  of  and  that  the  may  compared  seine sample.  the  the  is  and  only  large,  variation  sample  output  comparable  in the  of  each  of  has the  sea scallop fishery  observations in  from  England fisheries,  the  for  own-price  appendix  supply  New  of  However,  output  next  the  this  negative  finds  number  from  for  in  as such,  output  insufficient  A3.8  accepted theory;  single  may  Table  case  supply  the  results  estimates  particular,  different  output  to  In  discussed  elasticities  linear  sign.  significantly  case.  estimate  beginning with the  magnitude.  the  and  are  presents  own-price or  in  results  5.6  seine  the  elasticity  counterparts,  Table  nonlinear  estimates. either  5  the  These  nonlinear  Chapter the  particular,  251  offer small hand,  negative example,  pound  for  quantities.  / In  fact,  the  regulator  chinook  and  c o h o stocks, since these  to  a negative  A  comparison  linear  and  own-price  of  the  This  possibilities  between  The  5 are  linear  cases for  obtained  for  nonlinear  results  Finally, 5.10  as  do  not  estimates.  In  again, Chapter the  these 5.  fixed  reveals  variable to  output  have  the  the  factors  and  correct,  of  A3.12  of  to  large.  convexity  have  intensity, in this  encouraging  This  the  higher-priced  This may  for  the  for  that  sign  the  contribute  fleet and  of  in  the  order  of  substitution  results  discussed  in  in prices.  signs  labour  The  and  case  and  nonlinear  the  sign  fuel.  tables  and  changes  However,  the  compare  are  all  similar and  the  and in  analysis  the  when  are  to  linear  at  the  the  nonlinear  results.  the  between  the  from  change  support  in  values  between  hardly  seine  degree  appropriate  relationships  changed  the  expected,  is made  they  the  same  follows  appendix.  since  of  different  the  elasticities  for  the  implies  demand  comparison  be  it  of  of  ie., theoretically  significant  not  very  analysis  variables.  elasticities  a  access  demand  be  for  use  fuel  discussion of  need  the  input  when  are  Thus, the  for  inputs,  elasticities  particular, results  to  and  5 and Table  fleet's not  of  them  imposition  labour  change  seine  stocks are  the  own-price  regards  the  elasticity.  encouraging  the  the  the  in Chapter  signs  cases  invariant  of  control  supply  is very  elasticities  to  cross-price elasticities  nonlinear  magnitude.  Chapter  tries  252  nonlinear  size.  Once  discussed  in  variable  inputs  and  convexity  does  not  obtain.  Moving  on  to  a  comparison  of  the  linear  results  for  the  other  / samples, returns  much to  nonlinear  5.18, in  5.19,  5.  gillnet-troll,  of  all  5.22,  are  For  the these  linear  to  positive  for  the  linear  case,  desired  result.  general,  this  suggests that the  demand  for  changes,  in the  might not  be done  intensity factors,  A  specified for  between  the  of  is  values,  especially  and  made.  elasticity  stock  the  magnitudes  results  an  a  in particular,  discussion  nor  this  and only  of then the  In for  more  net  other  elasticity  it  set  the  fuel  output-stock  the  need  when  a  of  sign.  and  stock.  elasticity  to  be  is  brief.  comparison estimates  happens In  demand. This  the  short  individual  the  more  is  is  the  which  gear  run.  in  It  zero  the  5.1  sign  all responsive to  in  and  likely  ie., Table  from  5,  this  most  negative.  Chapter  obtain  in  price input  This  elasticities obviously  is of  fixed  vessel.  intensity. It  it  at  factor  factors  only  nonlinear  elasticities change  desirable  of  elasticities  is not  fixed  variable  tonnage  makes  5.13,  given  change  gear  The  5.11,  variation  the  scale, the  5.9,  to  constant  variation.  are  significantly different fleets  a  of  for  as suggested in  as  5.7,  elasticity  that  convexity  these  is  of  general,  between  for  price  is  is not  run. Thus,  much  intensity  case  little  estimates  lack  to  accepting convexity,  own  imposing  change  the  only  nonlinear  since  complete the  the  The  without  returns  very  tables  linear  to  and  constant  5,  the  come  with  show  Chapter  whereas  appropriately  study,  gillnet,  A3.13-A3.15.  gear  short  in  estimates  but  In  least  5.23,  the  the  elasticities  found  samples  the  of  and  linear  For  with and without  sets  and  from  at  found.  A3.9-A3.11  "close"  Chapter  is  estimates  tables  how  going  signs  parameter  appendix  in  and  5.17,  reflects  variation  scale, and the  magnitudes  5.15,  less  253  the  Only  of  significantly  short, the  obtain in  twice, linear  In  neither  linear  slightly  the  and  nonlinear  larger  elasticity  the  gillnet-troll  fleet  once  between  output  case they different  are  from  signs  both zero.  does and  negative In  the  / nonlinear obtained values result.  for  case for  they this  each  are  fleet  positive show  equation  are  and  significant.  the  least  number  the  lowest  of  all  Since  of  the  significant  sample,  this  parameter values is  not  and a  254  estimates the  R  2  surprising  / Table  A3.1:--Linear parameter estimates:  VARIABLE  ESTIMATE  Output  Equation  a a a a a  -0.01116t  0.04535  -0.12979t -0.05065t -0.69575t -0.09576t 0.05610  0.02805 0.01732  2 2  2 3  2 4  3 3  3 4  a  4 4  b  2 2  b  2 3  7.8018t -5.8896t  b b b b Cn  -0.79829t  3 3  -3.4013t -1.7465  0  2  3  Ci  R = 0.7961 LLF = -81.449 Labour a 2  2 2  a a b  2  3  2  4  2 2  b b bo b b  2 3 3 3  2  2 1  C  2  c c  2  2 3  R =0.8416 2  Note:  0.88513 0.53745 1.3256 0.57820 1.3857  ESTIMATE  Fuel  Equation  a a a  3 3  4  3  b b b b b b  c c  3  2  2 2  3 3  2  l  3 2  C33 c  R =0.2091 Gear 2  a4 a4  -0.05065t -0.0957610.05610  2  b b b b. b b  7.8018t -5.8896t -0.798291-3.40131-1.7465  2 2  0.04535 0.06390 0.01732 2.8185 1.9553 0.50318 2.2167 2.5932 0.88513 0.52118 1.2493 0.55973 1.3550  2 3  3 3  2  3  c  4 a  c c c R = 4 2  4 3  4  2  2.8185 1.9553 0.50318 2.2167  -1.8811t 0.44078 SEE=1.1617 Equation  3  4  -0.11164t 0.12979t -0.05065t 7.8018t -5.8896t -0.79829t -3.4013t -1.7465  7.8018t  4.5025t 0.45981 0.29436  3 3  0.06370 0.15418 0.06724  -3.4013t -1.7465  0  0.2280  4.5025t 13.166t 21.046t -8.9233t -30.280t SEE = 9.1659  SEE = 0.08367  The symbol  t  denotes  significance  at the level  ST. ERR.  0.12979t -0.69575t -0.095761-5.8896t -0.79829t  2 3  3  Equation  2.5519t -1.7211t -1.7144  2  0.15418 0.06724 0.04975 2.8185 1.9953 0.50318 2.2167 2.5932  VARIABLE  a *  4.5025t -0.29856  3  c  4.5025t -0.75789t 2.2684t -1.2064t 1.0942 SEE = 0.2037  ST. ERR.  seine  of a = 0.10  2.5932 0.88513 1.1755 2.0388 0.94328 2.3536  0.01732 0.06724 0.04975 2.8185 1.9553 0.50318 2.2167 2.5932 0.88513 8.2836 12.027 6.2620 14.872  255  / Table A3.2: --Linear  VARIABLE  ESTIMATE  Output  Equation  a a  0.09276T -0.8006E-02t -0.9605E-04  2  2  2 3  a 3 3  b b b b b b  0.35368T -0.06567T -0.25275  2 2  2 3 2 4  0.03112t 0.01367  3 3  3 4  Cn  0.27220 0.08367  Cia  0.19165  C  4 4  l 3  R =0.2258 LLF = -49.79 2  0.2528T 0.26866 SEE = 0.5800  parameter  ST. ERR.  0.03859 0.0026 0.00063 0.26311 0.04905 0.28983 0.01580 0.07829 0.26513 0.12261 0.22621 0.0539 0.30659  ESTIMATE  Fuel  Equation  2 2  a  2 3  b b b  2 2  2 3  2 4  b b  3 3  3 4  b4 4  C»i C  22  C 3 2  C 4 2  R =0.3001 Gear 3  2 3 3 3  b b  2 2  2 3  b b  2 4  3 3  b 4 3  b44  c i 3  c  3 2  C34 2  t  denotes signiciance  0.09276t -0.8006E-02+ 0.35368t  0.03112t 0.01367 0.27220 0.05652 -0.08279 -0.17322T -0.4205+ Equation  0.03859 0.0026 0.26311 0.04905 0.28983 0.01580 0.07829 0.26513 0.06901 0.13368 0.03506 0.1872 SEE = 0.2547  -0.06567t -0.25275  .  -0.8006E-02+ -0.9605E-04 0.35368+ -0.06567t -0.25275 0.03112t 0.01367 0.27220 0.01043 0.02802  -0.0466+ -0.3634t R =0.1401 SEE = 0.2049 at the level of a = 0.10 C33  The symbol  ST. ERR.  2  a  Note:  estimates: gillnet(crs)  VARIABLE  3  256  0.0026 0.0006 0.26111 0.04905 0.28983 0.01580 0.07829 0.26513 0.05679 0.12144 0.0288 0.1701  / Table  VARIABLE  ESTIMATE  Output  Equation  a  0.13337T 0.02285 -0.8553E-03  2 2  a a 3  2 3 2 4  0.43443T 0.21790E-02 0.68019E-03 -0.02060 -0.07768 -0.07855 0.12539E-02  3 3  a  3 4  a 4 4  b b  2 2  2 3  b  3 3  b b  2  b  3  0  0.10897E-03 0.15106  Cn  2.6153T  Cia  2.2514T 3.1010+  Cl3 Ci  R =0.2477 LLF = -447.37 Labour 2  a a  2 2 2 3  a 4 2  b  2 2  b b b b b  2 3  3 3  0  2  3  C i C 2  2  2  C 3 2  c R =0.3961 2  2  Note:  -1.4410T SEE = 1.655 Equation 0.1337+ 0.02285 -0.85529E-03 -0.02060 -0.07768 -0.07855 0.12539E-02 0.10897E-03 0.15106 -0.64257+ 0.40369 -0.17596 -1.6061 + SEE = 0.3850  The symbol  t  denotes  A3.3:-Linear  ST. ERR.  parameter  estimates:  257  troll  VARIABLE  ESTIMATE  Fuel  Equation  0.02577  a  0.02285  0.03634  0.03634 0.0029 0.13651 0.0034  a  0.13651 0.0034 0.10338  0.00128 0.10338 0.10280 0.19672 0.28867  b  0.43442T 0.2179E-02 -0.02060 -0.07768 -0.07855 0.12539E-2 0.10897E-02 0.15106 -0.56070T -0.91479T -0.73352T -0.64344t SEE = 0.4416 Equation  0.26129 0.33269 0.29133 0.45529  -0.85529E-03 0.217909E-02 0.68019E-03 -0.2060 -0.07768 -0.07855 0.12539E-02  0.00294 0.00340 0.00128 0.10338 0.10280 0.19672 0.28867  0.10897E-3 0.15106 -0.15098 1.0612 -0.32061 -1.6436 SEE = 2.7845  0.17349 0.19392 1.1481 1.1552 1.2458 1.5730  0.17349 0.19392 0.70872 0.72877 0.75726 0.97165  2  3  3 3  a 4 3  b b  2 2  2 3  3 3  b b  2  b  3  0  C31 C3  2  C3 3  c R =0.3814 Gear 3  2  a a  2  4  3  4  a 4 4  b 0.02577 0.03634 0.00294 0.10338 0.10280 0.19672 0.28867 0.17349 0.19392 0.22326 0.32139 0.25897 0.39391  significance  b b b b b  2 2  2 3  3 3  0  2  3  C41 C4 3  C4  R = 2  at the level  0.0084  of a = 0.10  ST. ERR.  0.10280 0.19672 0.28867 0.17349 0.19392  / Table A3.4: --Linear  VARIABLE  ESTIMATE  Output  Equation  a a a a a  2 2 2 3  2 4  3 4  b  2 2  b  2 3  b  3 3  b b b  0.02805 0.0067 0.04342 0.0074  -3.4504t 3.7671t  0  2  -0.61733T -0.05562  3  C  4.6402t 0.11122  x2  C l 3  Ci  R =0.4032 LLF = -516.18 Labour 2  2 2  3  2  0.03084  0.04515  Cn  a a a b b b b b b  0.01165  -0.05144t -4.1940t 0.58971  a*4  2 4  2 3  3 3  2  -0.61733t 0.02468  3  Cji 2 2  c  2 3  c R =0.3169 2  2  Note:  Equation 0.01165 -0.02086 0.62659E-02  -3.4504t 3.767Tt  0  c  -1.8207t SEE = 1.697  -4.1940t 0.58971t -0.04515  2 2  ST. ERR.  -0.02086 0.62659E-02 0.09146t -0.41309E-02  3  3  parameter  -0.9000t -0.28604t 0.06548 SEE = 0.3512  The symbol  t  denotes  0.01008 1.3625 0.17958 0.04731 1.6921 1.3957 0.18335 0.47116 1.2292 0.22481 1.3895  0.03084 0.02805 0.00665 1.3625 0.17958 0.04731 1.6921 1.3957 0.18335 0.16993 0.51974 0.09015 0.62701  significance  estimates:  gillnet-troll(non-crs)  VARIABLE  ESTIMATE  Fuel  Equation  a  3  -0.02086  3  2  0.09146t 0.4131E-02  3 3  a * b 3  -4.1940t 0.058971t .04515  2 2  b  b b b b c C  2 3  3 3  -3.4504t  0 :  2  3  3 1  2  3  c R =0.3709 Gear 3  2  a a a b b b b  0  b  2  b  3  c c  4 3  3 4  -0.85500T -0.36538t 0.45883  2 2  -4.T940I 0.04515  2 3  3 3  4 2  4  0.0563  at the level  ST. ERR.  0.0281 0.0434 0.0074 1.363 0.1796 0.0473 1.6921 1.3957 0.1834 0.17938 0.5363 0.09798 0.6442  SEE = 0.4013 Equation  0.5144t -0.2060  4 4  2  3.767lt -0.61733t -0.07268  0.62659E-02 -0.4131E-02  2 4  c R =  258  -3.4504t 3.7671t -0.61733t 40.7390t -79.895 3.3870 -18.964 SEE = 99.358  of a = 0.10  0.0067 0.0074 0.0101 0.1034 1.3625 0.0473 1.6921 1.3957 0.1834 25.770 64.185 11.508 73.354  / Table A3.5 :--Linear VARIABLE  ESTIMATE  Output  Equation  a  2 2  a  2 3  a  3 3  b b b  2 2 2 3  2 4  b  3 3  b 4 3  b * 4  b b b b c  0 2  3  4  2  2  0.06035T -0.609E-02t -0.45965E-05 0.02273 0.03954 -1.0393+ 0.08066t 0.14703t 0.76686 0.78726 0.44082 -0.30656+ -0.33665 -0.09031 0.17278  parameter  ST. ERR.  0.03346 0.0021 0.00052 0.35950 0.07586 0.54753 0.02595 0.09536 1.0226 0.92508 0.48656 0.14471 0.94009 0.14476 0.26524  estimates: gillnet(non-crs)  VARIABLE  ESTIMATE  Fuel  Equation  a  2 2  a  2  3  b b  2 2  2 3  b 4 2  b  3 3  b 4 3  b 4 4  b„ b 2  b b  3 4  C 1 2  C  2 2  C 3 2  Cl3 Cl'4  c R =0.2495 LLF = -45.86 x  2  0.2063+ 0.1871 0.48198 SEE = 0.5710  0.0585 0.3973 0.46245  C 4 2  c R =0.3178 Gear 2  2  3 3  3  b44 0  2 3  c i 3  3 2  -0.17876t -0.23590 -0.229E-03 SEE = 0.2514 Equation  0.08066t Q. 14703+ 0.76686 0.78726 0.44082 -0.30656t -0.07211 0.17700  -0.06111t -0.14744 -0.07943 C3 R =0.1872 SEE = 0.1992 at the level of a = 0.10 3 3  3 4  2  denotes significance  -0.30656+ -0.33665 -0.02055 0.04452  -1.0393+  2 2  b 4  t  0.14703t 0.76686 0.78726 0.44082  2 4  3 3  c c c  -1.0393t 0.08066+  2 3  2 3  a  b b b  0.06035+ -0.609E-02.T 0.02273 0.03954  -0.609E-02t -0.4596E-05 0.02273 0.03954  3  b b b b  Note: The symbol  259  ST. ERR.  0.03346 0.0021 0.35950 0.07586 0.54753 0.02595 0.09536 1.0226 0.92508 0.48656 0.14471 0.94009 0.08469 0.15895 0.03563 0.25311 0.0008  0.0021 0.0005 0.35950 0.07586 0.54753 0.02595 0.09536 1.0226 0.92508 0.48656 0.14471 0.07675 0.14566 0.03134 0.23637 0.25719  / Table Sample  A3.6:--Testing LLF(R)  for symmetry: LLF(U)  all samples (linear -2LOC(u)  x  2  260  estimates)  Value  Decision  (a = 0.010) Seine  -81.449  -75.230  12.438  11.345  Reject  Gillnet -non-crs  -45.858  -33.155  25.406  6.635  Reject  -CIS  -48.037  -35.948  24.178  6.635  Reject  Troll  -446.365  -436.577  19.576  11.345  Reject  Gillnet-Troll  -516.184  -510.262  11.844  11.345  Reject  Note: The null hypothesis of symmetry in cross price terms cannot be rejected if the calculated value of -2LOG(M) is less than the critical value. The number of degrees of freedom used to determine the critical value of x is given by the number of restrictions. For the gillnet case this number is 1, for all other cases this number is 3. It should also be noted that at a = 0.005, the critical value is x = 12.838. In this case symmetry is accepted in the seine and gillnet-troll cases. 2  2  Table Sample  A3.7:--Testing LLF(R)  for constant  returns  LLF(U)  to scale: all samples (linear  estimates)  -2LQG(M)  Decision  X  2  Value  (o=0.010) Seine  -106.085  -81.449  49.272  18.475  Reject  Gillnet  -49.790  -45.858  7.8646  18.475  Accept  Troll  -460.418  -447.365  26.106  18.475  Reject  Gillnet-Troll  -528.890  -516.184  25.412  18.475  Reject  Note: The null hypothesis of constant returns to scale cannot be rejected if the calculated value of -2LOG(M) is less than the critical value. The number of degrees of freedom used to determine the critical value of X number of is given by the restrictions. For each sample this number is 7. 2  / 261  Table A3.E1:--Linear estimates of  output-variable own- and cross-price elasticities:  Quantity/ Price  Output  Labour  Fuel  Gear  Output  -2.546+ (0.457)  0.0005 (0.171)  2.351 + (0.474)  0.195+ (0.076)  Labour  -0.0002 (0.060)  0.143+ (0.058)  -0.170+ (0.084)  0.028+ (0.009)  Fuel  -0.913+ (0.184)  -0.190+ (0.093)  1.044+ (0.231)  0.059+ (0.042)  Gear  -0.035t (0.014)  0.014+  0.027t (0.019)  -0.007+  (0.005)  Note: Asymptotic standard errors are in parentheses and the symbol the estimated elasticity is significantly different from zero at a = 0.10.  Table A3.9:—Linear estimates  of output-variable  (0.006)  "+"  signifies that  own- and cross-price elasticities: gillnet(crs)  Quantity/ Price  Output  Fuel  Gear  Output  0.077+ (0.058)  -0.118+ (0.060)  0.041 + (0.014)  Fuel  0.491 + (0.251)  -0.655+ (0.272)  0.163+ (0.052)  Gear  -0.079+ (0.028)  0.076+ (0.024)  0.003 (0.018)  Note: Asymptotic standard errors are in parentheses and the symbol the estimated elasticity is significantly different from zero at a = 0.10.  "+"  signifies  that  / Table  A3.10:--Linear  estimates  of  output-variable owngillnet-troll(non-crs)  and  cross-price  262  elasticities:  Quantity/ Price  Output  Labour  Fuel  Gear  Output  0.096 (0.111)  0.012 (0.046)  -0.134T (0.084)  0.026t (0.011)  -0.034  -0.031  0.077  -0.012  (0.129)  (0.083)  (0.104)  (0.013)  Fuel  0.494t (0.309)  0.101 (0.136)  -0.610t (0.290)  0.015 (0.026)  Gear  -0.028t (0.001)  -0.0005 (0.0005)  0.0004 (0.0008)  0.003t (0.0006)  Labour  Note: Asymptotic standard errors are in parentheses and the symbol the estimated elasticity is significantly different from zero at a = 0.10.  Table  A3.11:--Linear  estimates  of  output-variable gillnet(non-crs)  own-  and  "t"  signifies that  cross-price  Quantity/ Price  Output  Fuel  Gear  Output  0.051 (0.060)  -0.086t (0.062)  0.036t (0.014)  Fuel  0.360t (0.260)  -0.509t (0.282)  0.149t (0.052)  Gear  -0.070T (0.027)  0.070t (0.024)  0.0001 (0.017)  Note: Asymptotic standard errors are in parentheses and the symbol the estimated elasticity is significantly different from zero at a = 0.10.  "t"  signifies that  / 263 Table A3.12:-Linear  estimates of  elasticities  of  intensity: seine  Quantity/ Fixed Factor  Stock  Net  of  Tonnage  Days  Output  -0.536t (0.320)  0.021 (0.102)  0.548t (0.146)  Labour  0.130t (0.053)  -0.004 (0.023)  0.033 (0.037)  Fuel  0.069 (0.642)  0.351t (0.190)  0.272 (0.243)  Gear  -1.517t (0.958)  -0.427t (0.278)  0.423 (0.354)  Fish  Registered  Note: Asymptotic standard errors are in parentheses and the symbol the estimated elasticity is significantly different from zero at a = 0.10.  Table  A3.13:-Linear  estimates  of elasticities of  Fishing  "f"  signifies  intensity: gillnet(crs)  Quantity/ Fixed Factor  Stock of Fish  Net Registered Tonnage  Fishing  Output  0.036 (0.140)  0.101 (0.171)  0.545+ (0.104)  0.196 (0.225)  Fuel  -0.259t (0.157)  0.134 (0.202)  0.588+ (0.128)  0.732+ (0.263)  0.217  0.005 (0.230)  0.237+ (0.142)  0.962+ (0.293)  Gear  (0.236)  that  Labour  Days  Note: Asymptotic standard errors are in parentheses and the symbol the estimated elasticity is significantly different from zero at a = 0 . 1 0 .  "+"  signifies  that  / 264 Table  A3.14: -Linear  estimates of  elasticities  of intensity: gillnet-trollfnon-  Quantity/ Fixed Factor  Stock  Net  Fish  Tonnage  Days  Output  -0.028T (0.154)  1.622T (0.369)  0.086 (0.116)  Labour  -0.015t (0.075)  0.379+ (0.173)  0.274+ (0.062)  Fuel  -0.017 (0.152)  0.507+ (0.353)  0.469+ (0.123)  -0.875+ (0.554)  (1.303)  Gear  Registered  1.615  -0.119 (0.400)  Note: Asymptotic standard errors are in parentheses and the symbol the estimated elasticity is significantly different from zero at a = 0.10.  Table  A3.15:—Linear  estimates  of elasticities of  Fishing  "t"  signifies that  intensity: gillnet(non-crs)  Quantity/ Fixed Factor  Stock of Fish  Net Registered Tonnage  Fishing  Output  -0.074 (0.160)  -0.036 (0.197)  0.448T (0.114)  -0.077  -0.182 (0.186)  0.242 (0.235)  0.718t (0.149)  0.935T (0.368)  0.626  0.046 (0.261)  0.356T (0.162)  1.104T (0.428)  Fuel  Gear  (0.725)  Labour  Days  Note: Asymptotic standard errors are in parentheses and the symbol the estimated elasticity is significantly different from zero at a = 0.10.  (0.291)  "t"  signifies that  APPENDIX 4 This  appendix  supply  and  generate the  in  value  are  chapter  variable  linear  formulae  and  for  elasticities  of  the  shadow  from  the  normalized,  relationships  (5.1)  and  output fish  the  net  as the  The  as  and  the  factors  restricted  factor.  nonlinear e,,  the  included. function  given  for  price,  and  They  eiven  used  profit  are  are  the  to  defined case  presented  the  These  three  estimates  in  of  For completeness,  are  parameter  etc.,  formula  given.  normalizing  normalizing  using the  a.,  is  formulae  the  cross-price elasticities  As well,  restricted  quadratic,  (5.2).  and  tonnage  other  price  elasticities  between  two  own-  intensity.  of  the  with  the  value  the  of  the  stock of  obtain  for  for  equations  quantities,  To  the  formulae  using  with  case. the  elasticity  calculated  5  quantities,  the  estimate  shadow  four  use  demand  an  formulae  gives  ELASTICITY AND SHADOW VALUE FORMULAE  tables  fixed  for  one  of  the must  found  in  ik  Appendix gillnet-troll  2.  fleets  modifications system  of  These  to  elasticities  as  given  the  in  formulae  three variable  are  used  chapter are  quantities  to 5  obtain and  the  values  appendix  needed,  since  and four  fixed  its  3.  for  the  seine,  troll,  For  the  gillnet  parameters  are  estimated  quantities  as discussed  fleet  Elasticity of  Supply:  e  (A4.1)  =  (3 ir/3P ) 2  2  -(P^X,)  = OX,/BP,) .(P,/X,)  = [2*  i=2  k=2  265  l k  •(P.P /p3)] k  .(P,/X,)  slight  using  in chapter  S Own-Price  and  5.  a  / Output-Variable  Own-Price  Elasticities  Of  Input  Demand:  266  e. .  (A4.2)  0 7r/3 P.). 2  =  (P./X.)  2  (3X./3P.•(P./X.)  =  (  a  i i -  (  z  j = i j  Z j / P ^ J ^ P ^ X . )  a  for  i  =  2,3,4  c Output  Elasticity  With Respect  to  Input  Price:  e .  (A4.3)  =  (3 7r/3P 3P. ) 2  1  =  (3X,/3P.)•(P./X,)  -  -[((I.  a.Z.)/  P  2  ). Z  a. P  U  k  for  Input  Elasticity  With Respect  to  Output  Price:  k  MP./X,) i,k =  2,3,4  and i * k  e ^  (A4.4)  S e.,  = =  (3 TT/3P. 3P, ) 2  (3X./3P,)•(P,/X.)  =-[((!.  a.Z.)/  P )- I< 2  = 2  a  i  k  P  k  for  ].(P,/X.) i,k =  2,3,4  and i * k  / 267 Elasticities of Intensity Between Fixed and Variable Factors  (A4.5) 8 TT/3P 3Z  =(3X /3Z  2  1  1  1  =[(-(a  l / 2  P?).  -(^/2Z?).  ( Z  1  ( Z ^E  -(/3 / Z i )  +c  ) • (Z,/X, )  1  =  i  =  b  2  .(Z3  n  L  2  a.  U  j  l  Z  j  Z  l  P.P )  k  K  ) b o M ]  -(Z./X,)  b j Z j + 1/2 b / 3 . ) ]  .(Z,/X.)  b.Z. + l/2  (A4.6) 3 jr/9P.3Zi 1  =  2  1  +  c.  (3X./3Z, ) •(Z,/X. ) l l 1  -(/3./Z )  .(2»  2  = 1  1  = 2  0  for  i  = 2,3,4  (A4.7) a 7r/9P,  =  2  -  O x / 3 Z j ) •(Zj/X, ) r  [(-(a  P ).  ( E  2  i  /  2  + (/3,/Z ).(b 1  j j  Z  i  +b  j  -  j l  2  Z«  -  2  a.  Z +b.)  k  P.P ) k  +c. ].(Z /X )  1  j  for  j  1  l , j =  2,3 a n d  l * j  (A4.8) 3 TT/3P.3Z.  =  2  "  [ ( a  ( 3 X . / 3 Z .) • (Z ./X. )  j K=2 Z  *ifi./ZO'(b..Z.  a  i k  P  k  )  /  P  '  -b.^^b.) for  l , j =  +C..MZ./X.) 2,3  and i  = 2,3,4  Shadow  Prices  of  Fixed  Factors  (R,  and  R.):  (A4.9)  37r/3Z,  =  R,  ^ i=2  =  g=2 ik  2  a  [  +£  1  /  (b.Z./Z ) 2  = 2  +2  c  *  i=l  5=2  2  +  ( P  iV ^ P  ?=2  1/2S  bj^Z.Z^Z?) (a.P.bo/Z )] 2  = 2  .P. i=1 I  (A4.10)  3TT/3Z .  = R . D  3  ^ j i = 2 £=2 L  +  f>i  +  ?=i  a  i iij i p  c  p  [  a  ik  f=2  ( P  iV i P  )  w '> z  + (  V  Z i )  APPENDIX 5 : CALCULATIONS FOR CHAPTER 6 Table  A5.1:--Mean  predicted  quantities  and  expenditures  per  vessel  (using  mean  vessel),  all samples: Case I  Quantity  Seine  Gillnet  Troll  Gillnet-Troll  Y L F G  94350.1 5.6 1817.3 0.5  14113.8 I. 2375 586.1 II. 3  22095.8 3.9 2467.1 10.9  21573.7 1.6 1775.2 20.0  38172.9 142413.4 63365.1 180586.3 101538.0  10723.0 19306.7 17369.2 30029.7 28092.2  28246.5 34139.6 18760.7 62386.1 47007.2  21294.5 16372.7 12540.9 37667.2 33835.4  Costs TVC TFC-High -Low TC-High -Low  Notes: The quantity terms are defined as follows: Y is output (pounds of fish), L is labour (persons), F is fuel (gallons), and C is gear (nets, lines, etc.) For the gillnet fleet, labour is taken as a fixed fator. All cost figures are expressed in 1982 current Canadian dollars. Total Variable Costs (TVC) for the gillnet fleet include expenditures only on fuel and gear. Total Fixed Costs (TFC) for the gillnet fleet include the cost of labour. High refers to the high rental price of a net ton and low to the low rental price of a net ton. These notes refer to all tables in this appendix.  269  / Table  A5.2:-Mean  predicted  quantities and expenditures samples: Case I  per vessel (using  270  all vessels), all  Quantity  Seine  Gillnet  Troll  Gillnet-Troll  Y L F C  94373.1 5.6 1818.0 0.5  14642.0 1.2375 562.2 10.0  22107.9 3.9 2465.7 10.8  22301.0 1.5 1775.2 51.7  38170.0 142375.6 63348.3 180545.6 101518.3  9518.6 19306.7 17368.9 28824.9 26887.5  28214.3 34121.7 18750.9 62336.0 46965.2  26950.0 16381.0 12547.3 43331.0 39497.3  Costs TVC TFC-High -Low TC-High -Low  / Table  A5.3:--Mean  predicted quantities and expenditures per vessel and using all vessels), seine: Case II  Using mean Vessel  Using all Vessels Predicted with high price net tonnage  (using  mean  271 vessel  1  Predicted  Quantity  Predicted with high price net tonnage  Y L F C  93837.9 5.6 1760.8 0.5  93872.0 5.6  '  -Low TC-High -Low Note: Sample totals expenditures.  with  low  price  net  tonnage  Predicted with low price net tonnage  148223.7 4.8  1765.5 0.5  146908.4 4.8 2671.1 0.3  38316.3 126920.7  38305.5 -  33388.7 127951.3  33265.0  165237.0 -  57002.1 95307.6  161340.0 -  57407.5 90672.5  2677.0 0.3  Costs TVC TFC-High  1  are  divided  by  the  number  of  vessels  to  obtain  mean  quantities  and  /  Table  A5.4:-Mean  predicted  quantities  and  Using  and  expenditures  using all vessels), gillnet:  mean  per Case  vessel  (using  mean  vessel  II  Using all  Vessel  Quantity  Predicted with high price net tonnage  Predicted with low price net, tonnage  Vessels Predicted with high price net tonnage  Y  13411.4  F  476.3 9.1  13401.9 490.6 9.5  13882.6 481.9 8.6  13907.8 494.1  8590.1 10029.2 18619.3 -  8976.2 10400.5 19376.7  8230.3 11810.5 20040.7 -  8523.3 11847.9  C  272  1  Predicted with low price net tonnage  9.0  Costs TVC TFC-High -Low TC-High -Low Note: Sample totals expenditures. 1  are  divided  by  the  number  of  vessels  to  20371.2 obtain  mean  quantities  and  / Table  A5.5:-Mean  predicted quantities and expenditures per vessel and using all vessels), troll: Case II  Using  mean  Y L F C  mean  vessel  Using all  Vessel  Quantity  (using  273  Predicted with high price net tonnage  Predicted with low price net tonnage  Vessels Predicted with high price net tonnage  37452.6 3.8  37452.6 3.8  77005.4 4.2  77005.4 4.2  3973.7  3973.7  6.3  3.8  8310.6 54.6  8310.6 54.6  28746.3 81897.6  28746.3  51925.2 228406.9  51925.2  1  Predicted with low price net tonnage  Costs TVC TFC-High -Low TC-High -Low Notes: Sample totals expenditures. 1  45005.2  124660.8  110643.9  280332.1 73751.4  are  divided  by  the  number  176586.0 of  vessels  to  obtain  mean  quantities  and  / Table  A5.6:--Mean  predicted quantities and expenditures and using all vessels), gillnet-troll:  Using mean Vessel  per vessel Case II  (using  mean  Quantity  Predicted with high price net tonnage  Predicted with low price net tonnage  Using all Vessels Predicted with high price net tonnage  Y L F G  23990.6 1.6 1133.2 3.3  23990.6 1.6 1133.2 3.3  20920.3 2.2 1492.8 4.0  20901.7 2.2 1492.2 4.0  16533.1 17442.5 -  16533.1 13360.4  22278.3 17629.2 -  22265.3 13491.1  33975.6 -  29893.5  39907.5 -  35756.5  274 vessel  1  Predicted with low price net tonnage  Costs TVC TFC-High -Low TC-High -Low Note: Sample totals expenditures. 1  are  divided  by  the  number  of  vessels  to  obtain  mean  quantities  and  / Table  A5.7:--Mean  predicted quantities and expenditures per vessel and using all vessels), seine: Case III  Using mean Vessel  (using  mean  Quantity  Predicted with high price net tonnage  Predicted with low price net tonnage  Using all Vessels Predicted with high price net tonnage  Y L F C  99687.5 5.7 1766.0 0.5  99724.9 5.7 1770.5 0.5  131267.1 5.1 2863.4 0.3  132501.8 5.0 2868.7 0.3  TVC TFC-High -Low  38797.2 128112.5  38787.7  35404.1 127277.4  35297.2  TC-High -Low Note:  166909.7  275 vessel  1  Predicted with low price net tonnage  Costs  Sample totals expenditures. 1  57532.3  57066.5 162681.5  96319.5 are  divided  by  the  number  92363.8 of  vessels  to  obtain  mean  quantities  and  / Table  A5.8:--Mean  predicted and  Using  quantities  and  expenditures  using all vessels), gillnet:  mean  per Case  vessel  (using  mean  276 vessel  III  Using all  Vessel  Quantity  Predicted with high price net tonnage  Predicted with low price net tonnage  Vessels Predicted with high price net tonnage  Predicted with low price net tonnage  Y F C  13860.8 443.5 8.4  13859.5 455.0 8.8  13340.9 604.0 7.9  619.0 8.2  8008.4 10162.5 18170.9  8323.6 10384.6 -  7756.2 11824.4 19580.6  -  18708.2  -  1  13355.3  Costs TVC TFC-High -Low TC-High -Low Note: Sample totals expenditures. 1  .  are  divided  by  the  number  of  vessels  8057.2 11876.7 19933.9  to  obtain  mean  quantities  and  / Table  A5.9:--Mean  predicted quantities and expenditures per vessel and using all vessels), troll: Case III  Using  mean  (using  mean  277 vessel  Using all  Vessel  Quantity  Predicted with high price net tonnage  Predicted with low price net tonnage  Vessels Predicted with high price net tonnage  Y L F C  59877.9 6.7 10352.2 42.2  59877.9 6.7 10352.2 42.2  63333.4 6.6 10758.0 54.3  63333.4 6.6 10758.0 54.3  65006.0 216403.8 281409.8 -  65006.0 118920.3 183926.3  68738.0 228482.8 297220.8 -  63738.0  1  Predicted with low price net tonnage  Costs TVC TFC-High -Low TC-High -Low Notes: Sample totals expenditures. 1  are  divided  by  the  number  of  vessels  to  obtain  124634.7 193110.7 mean  quantities  and  / Table  A5.10:—Mean  predicted quantities and expenditures per vessel and using all vessels), gillnet-troll: Case III  Using mean Vessel  (using  mean  278 vessel  Using all Vessels Predicted with high price net tonnage  Predicted with low price net tonnage  20980.9 2.3 1863.2 4.3  23851.0  1  Quantity  Predicted with high price net tonnage  Predicted with low price net tonnage  Y L F G  23801.5 1.6 1476.8 3.6  23801.5 1.6 1476.8 3.6  20997.8 2.3 1864.1 4.3  17713.0 19303.1 37016.0 -  17713.0 14785.5 32498.4  23865.8 19335.5 43201.3 -  Costs TVC TFC-High -Low TC-High -Low Note: Sample totals expenditures. 1  are  divided  by  the  number  of  vessels  to  14795.6 38646.6 obtain  mean  quantities  and  

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