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. "Alaska's Board Anderson, Canada 36(7) F.J. Natural Resources Fisheries" L.G. 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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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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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Title | Input substitution and rent dissipation in a limited entry fishery : a case study of the British Columbia commercial salmon fishery |
Creator |
Dupont, Diane Pearl |
Publisher | University of British Columbia |
Date Issued | 1988 |
Description | Entry-limiting regulations imposed on common property fisheries have been suspected of encouraging fishermen to substitute unregulated for regulated inputs. This imposes a cost upon society in the form of a reduced amount of resource rent generated by the fishery. Almost no research has been done to provide quantitative estimates of substitution possibilities and the associated degree of rent dissipation. The thesis provides the first estimates of the harvest technology for the British Columbia commercial salmon fishery, one of the first fisheries in North America to experiment with limited entry controls. Estimates of cross-price elasticities of input demand and of elasticities of intensity are given. These elasticities exhibit a greater degree of input substitutability than has heretofore been assumed in the theoretical literature. Two of the four vessel types used in the fishery are observed to be responsible for most of the resource rent dissipation. Potential rent for 1982 is shown to be $73.1 million. This represents 44% of the total value of the landed catch. Actual rent for the 1982 season is estimated to be -$42.8 million. A model of a fishing firm subject to input restrictions is developed in the thesis. The empirical model uses a flexible functional form proposed by Diewert and Ostensoe (1987). The major advantage of the normalized, quadratic, restricted profit function over the translog is its ability to distinguish differing degrees of input substitution between pairs of inputs, while imposing convexity in prices upon the functional estimates. The function is estimated for one output, three variable inputs, and three restricted inputs. Four samples are used which correspond to the vessel types that fish salmon. This allows rent to be calculated for the entire fleet, as well as for each of the components. The study of the salmon fishery is completed by addressing the important issue of rent dissipation. The actual amount of rent is established by using the predicted input demands of each vessel to calculate total fleet costs for the number of vessels that fished in 1982. This is compared to the potential rent that would be generated by an efficient fleet. To determine the characteristics of the efficient fleet, the optimal amount of (the restricted) net tonnage for each vessel is determined. Predicted output levels for each vessel are then used to calculate the minimum number of vessels required to take the 1982 harvest. This is done for each of the four vessel types. This exercise is repeated for two alternative scenarios, including the assumption of a greater degree of substitutability per vessel than actually found and a change in the distribution of catch among the vessel types. A comparison of rents generated in each scenario with an estimate of the actual rent from the 1982 fishery suggests that input-substituting activities of the fishermen may cause a substantial amount of rent dissipation. In addition, fleet redundancy and an inefficient catch distribution are found to contribute to the problem. The thesis concludes with a discussion of the implications for effective fisheries management. In particular, the findings of the research endorse the (Pearse) Royal Commission on Pacific Fisheries Policy (1982) recommendation of a fleet reduction scheme to be used in conjunction with a royalty tax on catch. On the other hand, evidence of input substitutability suggests that a vessel quota restriction might be successful in preventing some rent from being dissipated. |
Subject |
Fisheries -- British Columbia |
Genre |
Thesis/Dissertation |
Type |
Text |
Language | eng |
Date Available | 2010-09-24 |
Provider | Vancouver : University of British Columbia Library |
Rights | For non-commercial purposes only, such as research, private study and education. Additional conditions apply, see Terms of Use https://open.library.ubc.ca/terms_of_use. |
DOI | 10.14288/1.0097962 |
URI | http://hdl.handle.net/2429/28665 |
Degree |
Doctor of Philosophy - PhD |
Program |
Economics |
Affiliation |
Arts, Faculty of Vancouver School of Economics |
Degree Grantor | University of British Columbia |
Campus |
UBCV |
Scholarly Level | Graduate |
Aggregated Source Repository | DSpace |
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