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Western Greenhouse Growers’ Co-operative Association : a cost-benefit analysis of marketing regulation… Woo, Wendy 1995

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WESTERN GREENHOUSE GROWERS' CO-OPERATIVE ASSOCIATION A COST-BENEFIT ANALYSIS OF MARKETING REGULATIONS AND CO-OPERATIVE STRUCTURE by WENDY WOO B . S c ,  The. U n i v e r s i t y  o f B r i t i s h Columbia, 1993  A THESIS SUBMITTED IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER  OF SCIENCE in  THE FACULTY OF GRADUATE STUDIES (Department o f A g r i c u l t u r a l Economics) We accept t h i s t h e s i s as conforming t o the r e q u i r e d standard  THE UNIVERSITY OF BRITISH COLUMBIA  October 1995 © Wendy Woo,  1995  In  presenting  degree freely  at  thesis  in  partial  fulfilment  the University  of  British  Columbia,  available  copying  of  department publication  this  for reference  this or  thesis by  of this  and study.  for scholarly  his  or  thesis  her  of  I agree  I further  purposes  gain  agree  requirements that that  shall  It  is  Department  of  r  i  OJ / ^Cf  The University of British Columbia Vancouver, Canada  Date  DE-6 (2/88)  nc*.  )L / /<91S~  I  not be allowed  ^00/10/^(^5  make  it  permission for extensive by the head  understood  permission.  for an advanced  the Library shall  may b e granted  representatives.  for financial  the  that  without  of my  copying  or  my written  11 ABSTRACT  Western Greenhouse Growers' Co-operative s e l l s approximately this  study,  we  organization greenhouse  tomato  competitive  a  growers.  issue  This  of  need  to a  private  issue  arised  production,  t o expand  firm  In order  production.  the f a c i l i t i e s  at t h e  is  a  organization. receives  "problem" Under  one vote  with the  the  present  co-operative  regardless  the  of  t o be I f the  co-operative  Unfortunately,  structure  system,  o f patronage.  In  f o r B.C.  as a r e s u l t  must i n c r e a s e t o handle the a d d i t i o n a l products. there  i n BC.  incorporating  f a c i n g the c o - o p e r a t i v e .  the growers  expand  the  co-operative  pressures  competitive, growers  96.5% o f the greenhouse vegetables analyzed  from  A s s o c i a t i o n (WGGCA)  Also,  of  the  each  member  some  growers  want t o expand p r o d u c t i o n but they do not want t o unless they are guaranteed a reasonable  return.  Hence, one p o s s i b l e s o l u t i o n i s  t o i n c o r p o r a t e WGGCA from a c o - o p e r a t i v e t o a p r i v a t e f i r m . We c o n s t r u c t e d a market model f o r B.C. Hothouse tomatoes f o r this  study.  curves.  Our market  model  a cost-of-production  estimated  tomatoes  and demand  and the demand  The supply f u n c t i o n i s estimated  schedule  u s i n g econometrics.  B.C. Hothouse results  o f supply  The supply curve r e p r e s e n t s the producers  curve r e p r e s e n t s the consumers. using  consists  and the demand  We have presented  i n Chapter  4 and we  function i s  the r e s u l t s f o r  have presented  the  f o r B.C. Hothouse cucumbers and B.C. Hothouse peppers i n  Appendices C and D.  Then, impacts  we b u i l d  t o estimate  o f marketing  regulations,  (B.C.)  and  Marketing hypothesized at  a model  Act,  economic  the N a t u r a l  Products  co-operative  t h a t WGGCA operates  present.  under  t h e welfare  into  a private  We  under a m o n o p o l i s t i c environment  I f t h e members o f WGGCA decide  organization  structure.  firm,  we  t o incorporate the  hypothesized  that  some  members o f the o r g a n i z a t i o n w i l l d i v e r g e and s e l l the products on their  own.  operate  In t h i s  under  monopolistic competitive From producers  case,  perfect situation  B.C. greenhouse  competition. as our base  tomato  Therefore, scenario  growers we  will  used t h e  and t h e p e r f e c t  s i t u a t i o n as our a l t e r n a t i v e s c e n a r i o . our study,  gain,  we  found  t h e consumers  that  B.C. greenhouse  l o s e , and the s o c i e t y gains  the m o n o p o l i s t i c s c e n a r i o as opposed t o the competitive  tomato under  scenario.  Hence,  WGGCA should remain as a c o - o p e r a t i v e because t h e members  gain.  WGGCA should  remain as a c o - o p e r a t i v e  a l l o c a t i o n s i n order t o be c o m p e t i t i v e .  and i n c r e a s e quota  iv  TABLE OF CONTENTS Abstract  i i  Table o f Contents  iv  L i s t o f Tables List  v i i  o f Diagrams  ix  Acknowledgements  x  1.0  INTRODUCTION  1  1.1  Problem Statement  3  1.2  O b j e c t i v e s o f the Study  4  1.3  Methodology  4  1.4  O r g a n i z a t i o n o f the Study  6  2. 0  3.0  BACKGROUND TO THE INDUSTRY AND WGGCA  8  2.1  H i s t o r y o f t h e B.C. Greenhouse Vegetable Industry  2.2  Present Status o f WGGCA  2.3  Economic I m p l i c a t i o n s o f Co-operative S t r u c t u r e  .. 8 11  ....  17  MARKETING REGULATIONS AND THEIR IMPLICATIONS  25  3.1  The N a t u r a l Products Marketing  25  3.2  The B r i t i s h Columbia Vegetable Marketing Commission  (BC) Act  26 4.0  MODEL, DATA, AND RESULTS 4.1  Market Model f o r B.C. Hothouse Tomatoes 4.1.1  4.1.2 4.1.3 4.1.4 4.1.5 4.1.6  The Demand Model i n B.C. 4.1.1.1 Short-Run E q u i l i b r i u m Under M o n o p o l i s t i c Competition 4.1.1.2 Long-Run E q u i l i b r i u m Under M o n o p o l i s t i c Competition 4.1.1.3 The S i t u a t i o n f o r B.C. Hothouse Tomato Growers The Demand Model i n the Rest o f Canada The Demand Model i n U n i t e d States Aggregate Demand f o r B.C. Hothouse Tomatoes The Supply Model f o r B.C. Hothouse Tomatoes The P r i n c i p l e O b j e c t i v e o f WGGCA  31 32 32 33 35 36 38 40 . 41 . 42 43  4.1.7 4.2  4.2.2 4.2.3 4.2.4  4.3.2 4.3.3 5.0  50  Demand E s t i m a t i o n Procedure f o r B.C. Hothouse Tomatoes 50 Demand E s t i m a t i o n Data f o r BC Hothouse Tomatoes 57 A D i s c u s s i o n o f the Demand V a r i a b l e s 58 Demand E s t i m a t i o n R e s u l t f o r BC Hothouse Tomatoes 60 4.2.5.1 B r i t i s h Columbia 63 4.2.5.2 The P r a i r i e Regions of Canada 66 4.2.5.3 E a s t e r n Canada 69 4.2.5.4 Washington 74 4.2.5.5 Oregon 75 4.2.5.6 C a l i f o r n i a 77 4.2.5.7 Other P a r t s o f United States 78 4.2.5.8 Comparing R e s u l t s Across Regions .. 80 4.2.4.9 WGGCA's A b i l i t y t o P r i c e Discriminate 82  E s t i m a t i o n o f t h e P r o d u c t i o n Model 4.3.1  V  . 45  E s t i m a t i o n of the Demand Model 4.2.1  4.3  The Market Model f o r B.C. Hothouse Tomatoes  83  Cost o f Production E s t i m a t i o n f o r B.C. Hothouse Tomatoes Cost o f Production E s t i m a t i o n Data f o r B.C. Hothouse Tomatoes Cost o f P r o d u c t i o n E s t i m a t i o n Procedures and R e s u l t s  83 84 84  MEASURING THE BENEFITS AND COSTS OF MARKETING REGULATIONS AND CO-OPERATIVE STRUCTURE FOR B.C. GREENHOUSE TOMATOES 89 5.1  Graphical I l l u s t r a t i o n Impacts  5.2  S i m u l a t i o n Model Used t o Measure the Economic Impacts 5.2.1  5.2.2 5.2.3 5.2.4  o f the Economic  Welfare  89 Welfare  94  Determination of the Demand Functions, the Inverse Demand Functions, the Inverse Demand Functions F a c i n g the Co-operative, and the M a r g i n a l Revenue Functions 95 Determination o f the Competitive E q u i l i b r i u m S o l u t i o n s and the Optimal Solutions 99 Determination of the Economic Welfare Measures 105 The P o s s i b i l i t i e s o f Remaining As a S i n g l e - S e l l i n g Desk A f t e r P r i v a t i z a t i o n .... 107  vi 5.3 Conclusions BIBLIOGRAPHY  and Recommendations  108 112  APPENDIX A:  Data Tables  118  APPENDIX B:  Variable Construction  140  APPENDIX C:  Demand E s t i m a t i o n R e s u l t s f o r B.C. Hothouse Cucumbers and B.C. Hothouse Peppers  143  C o s t - o f - P r o d u c t i o n R e s u l t s f o r B.C. Greenhouse Cucumbers and B.C. Greenhouse Peppers  151  APPENDIX D:  V l l  L i s t o f Tables Table 2.1: Table Table Table Table Table Table Table Table Table Table Table Table Table Table Table  Table Table Table Table Table Table  Table Table Table Table  Greenhouse P r o d u c t i o n Q u a n t i t i e s and Values f o r B r i t i s h Columbia 12 2.2: Advantages and Disadvantages of Co-operatives ... 20 4.1: Durbin-Watson S t a t i s t i c s f o r Demand Equations Using OLS 62 4.2: Lagrange M u l t i p l i e r Test S t a t i s t i c s f o r 2SLS .... 63 4.3: Demand E s t i m a t i o n R e s u l t s f o r B.C. Hothouse Tomatoes - B.C 66 4.4: Demand E s t i m a t i o n R e s u l t s f o r B.C. Hothouse Tomatoes - P r a i r i e Region of Canada 69 4.5: Demand E s t i m a t i o n R e s u l t s f o r B.C. Hothouse Tomatoes - E a s t e r n Canada 74 4.6: Demand E s t i m a t i o n R e s u l t s f o r B.C. Hothouse Tomatoes - Washington 75 4.7: Demand E s t i m a t i o n R e s u l t s f o r B.C. Hothouse Tomatoes - Oregon 76 4.8: Demand E s t i m a t i o n R e s u l t s f o r B.C. Hothouse Tomatoes - C a l i f o r n i a ' 78 4.9: Demand E s t i m a t i o n R e s u l t s f o r B.C. Hothouse Tomatoes - Other P a r t s of U n i t e d S t a t e s 79 4.10: Cost o f P r o d u c t i o n f o r Greenhouse Tomatoes i n B.C., 1993 85 4.11: C a p i t a l Cost Schedule 87 4.12: Rate o f D e p r e c i a t i o n f o r C a p i t a l A s s e t s 88 4.13: T o t a l Costs o f Producing B.C. Greenhouse Tomatoes 88 5.1: R e s u l t s from the Determination o f the Demand F u n c t i o n s , the Inverse Demand Functions, the Inverse Demand Functions F a c i n g the Co-operative and the M a r g i n a l Revenue Functions 98 5.2: A Comparison of the Three Scenarios 104 5.3: R e s u l t s from the S i m u l a t i o n Model 106 5.4: Simulated R e s u l t s i n Terms o f Nominal 1994$ and Thousand Cases i n Each Market Each Month 10 6 5.5: Welfare R e s u l t s In Terms o f Nominal 1994 $ 107 A l : Monthly Estimates o f P o p u l a t i o n f o r Canada, and S e l e c t e d Provinces (in thousands) 119 A2: Monthly Estimates of Resident P o p u l a t i o n f o r the U n i t e d S t a t e s and S e l e c t e d S t a t e s , D i v i s i o n s and Regions ( i n thousands, i n c l u d i n g armed f o r c e s r e s i d i n g i n each State) 120 A3: Monthly Wages and S a l a r i e s f o r Canada and S e l e c t e d P r o v i n c e s , raw. ( M i l l i o n s o f d o l l a r s ) 123 A4: T o t a l P e r s o n a l Income f o r U n i t e d S t a t e s , S e l e c t e d Regions and States ( M i l l i o n s o f d o l l a r s , s e a s o n a l l y a d j u s t e d at annual rates) 125 A5: Consumer P r i c e Index o f A l l - i t e m s , Food, and Fresh Vegetables i n Canada and S e l e c t e d P r o v i n c e s , 1986=100 127 A6: Consumer P r i c e Index f o r A l l - U r b a n Consumers  Table A7: Table CI: Table C2: Table C3: Table C4: Table C5: Table C6: Table C7: Table C8: Table C9: Table CIO: Table C l l : Table C12: Table C13: Table C14: Table D l : Table D2:  (CPI-U) i n U n i t e d S t a t e s : Consumer P r i c e Index of A l l - i t e m s , Food, and F r u i t s and Vegetables, 1982-84=100, by r e g i o n Canada-U.S. Exchange Rates Demand E s t i m a t i o n R e s u l t s f o r B.C. Hothouse Cucumbers - B r i t i s h Columbia Demand E s t i m a t i o n R e s u l t s f o r B.C. Hothouse Cucumbers - P r a i r i e Regions of Canada Demand E s t i m a t i o n R e s u l t s f o r B.C. Hothouse Cucumbers - E a s t e r n Canada Demand E s t i m a t i o n R e s u l t s f o r B.C. Hothouse Cucumbers - Washington Demand E s t i m a t i o n R e s u l t s f o r B.C. Hothouse Cucumbers - Oregon Demand E s t i m a t i o n R e s u l t s f o r B.C. Hothouse Cucumbers - C a l i f o r n i a Demand E s t i m a t i o n R e s u l t s f o r B.C. Hothouse Cucumbers - Other P a r t s o f U n i t e d States Demand E s t i m a t i o n R e s u l t s f o r B.C. Hothouse Peppers - B r i t i s h Columbia Demand E s t i m a t i o n R e s u l t s f o r B.C. Hothouse Peppers - P r a i r i e Regions of Canada Demand E s t i m a t i o n R e s u l t s f o r B.C. Hothouse Peppers - E a s t e r n Canada Demand E s t i m a t i o n R e s u l t s f o r B.C. Hothouse Peppers - Washington Demand E s t i m a t i o n R e s u l t s f o r B.C. Hothouse Peppers - Oregon Demand E s t i m a t i o n R e s u l t s f o r B.C. Hothouse Peppers - C a l i f o r n i a Demand E s t i m a t i o n R e s u l t s f o r B.C. Hothouse Peppers - Other P a r t s of U n i t e d S t a t e s Cost o f P r o d u c t i o n f o r Greenhouse Cucumbers i n B.C., 1993 Cost o f P r o d u c t i o n f o r Greenhouse Peppers i n B.C., 1993  viii 133 139 143 144 144 145 145 146 14 6 147 147 148 148 149 149 150 151 152  L i s t o f Diagrams Diagram 2.1:  ix  Sales Q u a n t i t i e s and Values of BC Greenhouse Tomatoes 13 Diagram 2.2: Sales Q u a n t i t i e s and Values of BC Greenhouse Cucumbers 14 Diagram 2.3: Sales Q u a n t i t i e s and Values of BC Sweet Peppers 15 Diagram 2.4: Sales Q u a n t i t i e s and Values o f BC Greenhouse Lettuce 16 Diagram 4.1: M o n o p o l i s t i c Competition i n the Short-Run .... 34 Diagram 4.2: M o n o p o l i s t i c Competition i n the Long-Run 36 Diagram 4.3: The S i t u a t i o n f o r B.C. Hothouse Tomatoes 37 Diagram 4.4: Aggregate Demand f o r B.C. Hothouse Tomatoes .. 41 Diagram 4.5: Aggregate Supply o f B.C. Hothouse Tomatoes ... 43 Diagram 4.6: Market Model f o r B.C. Hothouse Tomatoes 46 Diagram 4.7: R e s u l t s from I n c r e a s i n g Production i n the Industry 47 Diagram 4.8: The Consequences o f Ignoring S i m u l t a n e i t y .... 53 Diagram 4.9: P r i c e and P r o d u c t i o n o f Greenhouse Tomatoes in Alberta 68 Diagram 4.10: P r i c e and P r o d u c t i o n o f Greenhouse Tomatoes i n Ontario 72 Diagram 4.11: P r i c e and P r o d u c t i o n o f Greenhouse Tomatoes i n Quebec 73 Diagram 5.1: The Market Model f o r B.C. Hothouse Tomatoes .. 93 Diagram 5.2: A Market Model Using L i n e a r F u n c t i o n a l Form .. 102 Diagram 5.3: A L i n e a r Demand Curve with E l a s t i c i t y at Mean o f -1 and a Slope o f -1 103  X  Acknowledgements I would l i k e t o thank t h e members o f my t h e s i s committee: Mary Bohman, John S c h i l d r o t h , and James Vercammen f o r t h e i r sound advice and h e l p f u l comments. S p e c i a l thanks goes t o Mary Bohman, f o r t h e numerous hours that she spent d i s c u s s i n g v a r i o u s aspects of my t h e s i s with me. Her guidance, i n s i g h t s and encouragement throughout t h e l a s t two years o f my graduate program w i l l not be forgotten. I would a l s o l i k e t o thank the members o f Western Greenhouse Growers' Co-operative A s s o c i a t i o n , e s p e c i a l l y Howard Kosaka and David R y a l l f o r e x p l a i n i n g t o me what i s going on i n the i n d u s t r y and how greenhouse operations i n B.C. f u n c t i o n . Furthermore, I would l i k e t o thank Glenn Wong, P r e s i d e n t and C h i e f E x e c u t i v e O f f i c e r o f WGGCA, Danley Yip, V i c e P r e s i d e n t o f Finance and Administration o f WGGCA, and B r i a n Mauza, Product Development o f f i c e r f o r a l l t h e i n f o r m a t i o n that they have p r o v i d e d me. Without them, t h i s t h e s i s would not have grown t o the extent t h a t i t i s now. I would a l s o l i k e t o thank the members o f the B.C. M i n i s t r y o f A g r i c u l t u r e , F i s h e r i e s , and Food, Jim A l c o t t , P.Ag., H o r t i c u l t u r e Marketing Specialist, Lome Owen, P.Ag., Farm Management Specialist, and Jim Portree, P.Ag., Provincial Greenhouse Vegetable Industry S p e c i a l i s t f o r sharing t h e i r knowledge about the greenhouse v e g e t a b l e i n d u s t r y i n B.C. with me and p r o v i d i n g me with v a l u a b l e i n f o r m a t i o n . I would a l s o l i k e t o take t h i s opportunity t o thank Kathy Shynkaryk, Retha Gertsmar, and Donna C u r t i s f o r t h e i r support and encouragement i n the department. F i n a l l y , I would l i k e t o thank my f a m i l y and f r i e n d s f o r being t h e r e when I needed them. I am very f o r t u n a t e t o have them i n my life.  1.0  1  INTRODUCTION  The  greenhouse  grown v e r y from 1994,  vegetable  rapidly.  $29,102,000  I n terms o f t o t a l  an i n c r e a s e  o f 64.65%  i n five  from  $24,275,015  i n BC.  a marketing  1  o f $47,917,338 i n Western  Greenhouse  The s a l e s v a l u e s  i n 1990 t o $46,327,426  i n c r e a s e o f 90.84% i n 5 y e a r s . As  years. "  i t increased  A s s o c i a t i o n (WGGCA) s e l l s a p p r o x i m a t e l y 96.5%  t h e greenhouse vegetables  increased  Columbia has  sales value,  i n 1990 t o a p r o j e c t e d v a l u e  Growers' C o - o p e r a t i v e of  industry" i n B r i t i s h  f o r WGGCA  i n 1994, a n  3  co-operative,  t h e members own WGGCA.  member o f WGGCA h a s a v o i c e i n t h e o p e r a t i o n o f t h e b u s i n e s s . addition,  they  pool  resources  together  Every In  f o rprofessional expertise,  r e s e a r c h and development, a d v e r t i s i n g and marketing,  and c a p i t a l t o  m a i n t a i n and expand f a c i l i t i e s a t t h e c o - o p e r a t i v e . In t h e c h a n g i n g market environment, w i t h i n c r e a s i n g c o m p e t i t i o n f r o m M e x i c o , U n i t e d S t a t e s , a n d o t h e r p a r t s o f Canada, t h e g r o w e r s h a v e t o be m a r k e t r e s p o n s i v e . organization large  growers  i s questioned want  The p r e s e n t  structural  f o r various reasons.  t o expand p r o d u c t i o n  i n order  form o f t h e  F o r example, t h e t o become more  P r o d u c t i o n o f V e g e t a b l e C r o p s T o g e t h e r W i t h An E s t i m a t e o f Farm V a l u e f o r B r i t i s h C o l u m b i a 1990 a n d A n n u a l H o r t i c u l t u r a l S t a t i s t i c s 1992. P r o v i n c e o f B r i t i s h C o l u m b i a . Ministry of A g r i c u l t u r e , F i s h e r i e s a n d Food. N a h a n n i H o r t i c u l t u r a l S e r v i c e s . The Greenhouse V e g e t a b l e I n d u s t r y i n B r i t i s h C o l u m b i a : An I n d u s t r y P r o f i l e & S t r a t e g i c P l a n f o r I n d u s t r y Development. BCMAFF: May, 1993. Source: Western Greenhouse Growers' Association  Co-operative  competitive. operative  I f production  need t o r a i s e  because t h e f a c i l i t y  increases,  capital  t h e members  t o handle  the additional  a t WGGCA h a s r e a c h e d  There a r e a p p r o x i m a t e l y  of the  2  co-  products  i t s maximum c a p a c i t y .  50 g r o w e r members i n WGGCA a n d f i v e o r s i x  o f them own l a r g e o p e r a t i o n s ; 10% o f t h e g r o w e r members p r o d u c e 80% of t h e product. BC,  each  According  t o t h e Co-operative  co-op member r e c e i v e s one v o t e  t h a t i s t h e member's s h a r e upon p r o d u c t  put through  have a r i s e d a s a r e s u l t  Association Act of  regardless o f patronage,  o f the co-operative's earnings  the co-operative. o f t h e changing  i s based  Two m a j o r i s s u e s t h a t  market p l a c e a r e t h e i s s u e  o f one-member-one-vote a n d t h e i s s u e o f f i n a n c i n g t h e new f a c i l i t y a t WGGCA. Some members o f t h e c o - o p e r a t i v e have c o n s i d e r e d o f e x p a n d i n g the  operation but there  With  a r e many  others  who a r e o p p o s e d t o i t .  t h e one-member-one-vote s y s t e m i n p l a c e ,  some members o f t h e  c o - o p e r a t i v e f e e l t h a t i t i s u n f a i r b e c a u s e t h e y h a v e more invested  i n t h e co-operative than  more v o t i n g r i g h t s .  Also,  should  have  some members o f t h e c o - o p e r a t i v e  have  t h e c a p i t a l t o expand t h e f a c i l i t y unless  they  operative the  realize  a t WGGCA b u t t h e y do n o t want t o  a reasonable  return.  With  structure of the organization, the profit  co-operative  dividend.  of  a r e guaranteed  o t h e r s ; hence, t h e y  i s returned  Furthermore,  any c a p i t a l  the co-operative  capital  t o t h e members  t h e members  cannot  generated  coby  v i a t h e patronage  sell  g a i n s i n t h e a s s e t base they  the  these  shares t o  represent  structure of the organization.  because  Hence, t h e  growers must stay i n p r o d u c t i o n they have i n v e s t e d i n the  1.1  3  i n order t o r e a l i z e the r e t u r n t h a t  co-operative.  Problem Statement  Presently, organization  WGGCA  i s considering  from a c o - o p e r a t i v e  incorporating  to a private  r e s o l v e the two i s s u e s mentioned above. firm,  of  firm.  the  This  will  By s w i t c h i n g t o a p r i v a t e  t h e members o f t h e o r g a n i z a t i o n w i l l  vote a c c o r d i n g  amount i n v e s t e d and r e c e i v e a d i v i d e n d based on the  t o the  shares h e l d .  Furthermore, the i n v e s t o r s can s e l l t h e i r shares t o someone e l s e i f they need t o l i q u i d a t e t h e i r investments. I f WGGCA switches  t o a p r i v a t e f i r m , i t might l o s e i t s s i n g l e  s e l l i n g desk s t a t u s which many producers i n the as one o f the major b e n e f i t s o f c o - o p e r a t i v e  industry  consider  structure.  t o s e c t i o n 12 o f the Co-operative A s s o c i a t i o n Act,  According  i t states  that  "Every a s s o c i a t i o n , which as one o f i t s o b j e c t s a c t s as an agency designated object object,  by a marketing board,  a l l the capacity and p r o v i d e d  has s i n c e  and powers necessary  that  i t i s carrying  e x e r c i s i n g the powers on a c o - o p e r a t i v e of  this  study  t h e adoption  out  the  out t h e o b j e c t and  basis."  i s t o determine t h e b e n e f i t s  t o carry  of the  Hence, the purpose  and c o s t s  s e l l i n g desk under the N a t u r a l Products Marketing  of single  (BC) A c t versus  the p o s s i b i l i t y o f e n t r y by other f i r m s as may happen w i t h p r i v a t e i n c o r p o r a t i o n , f o r the WGGCA.  Which a l t e r n a t i v e i s b e t t e r f o r an  organization competitive  1.2  that  i s  export-oriented  and  facing  4 increasing  p r e s s u r e s from t h e g l o b a l market?  O b j e c t i v e s o f t h e Study  The  main o b j e c t i v e o f t h i s  study i s t o formulate and e s t i m a t e  a model t o determine t h e b e n e f i t s and c o s t s under t h e N a t u r a l  Products Marketing  of single selling  desk  (BC) A c t v e r s u s p r i v a t i z a t i o n  f o r t h e WGGCA. The  sub-objectives  o f t h i s study are as f o l l o w s :  1)  To d e s c r i b e  2)  To d i s c u s s how t h e N a t u r a l a f f e c t s t h e WGGCA.  3)  To d e t e r m i n e t h e economic i m p a c t s o f c o - o p e r a t i v e on t h e WGGCA.  4)  To draw i m p l i c a t i o n s a n d c o n c l u s i o n s on t h e i s s u e o f s i n g l e s e l l i n g d e s k a n d c o - o p e r a t i v e p o l i c i e s f o r members o f WGGCA, i t s consumers, and s o c i e t y .  1.3  t h e BC g r e e n h o u s e v e g e t a b l e  industry.  Products Marketing  (B.C.) A c t principles  Methodology  In British  order  t o understand  Columbia,  entails a historical  B.C.  greenhouse  vegetable  of the industry,  relationship  with  vegetable  a b r i e f overview o f t h e industry  This  structure  t h e greenhouse  description industry,  industry i n  i s provided.  o f t h e development an o u t l i n e  of  the  o f t h e present  a n d a d e s c r i p t i o n o f t h e WGGCA a n d i t s  t h e BCVMC.  Also,  the sales  performance  greenhouse i n d u s t r y i n B r i t i s h Columbia i s analyzed.  of the  The  economic  implications of co-operative  government r e g u l a t i o n a r e d e v e l o p e d . is  o n government  vegetable  regulations  The f o c u s o f t h i s d i s c u s s i o n  as they  i n d u s t r y a n d on a g r i c u l t u r a l  apply  t o t h e greenhouse  marketing  co-operatives.  The members o f a c o - o p e r a t i v e g a i n b y p o o l i n g o f r e s o u r c e s towards  a  common  operative equipment for  pool  goal.  F o r example,  resources  together  f o r p o s t - h a r v e s t i n g which  an i n d i v i d u a l  grower.  i t s products  is  Marketing  of  these  issues  literature  will  reviews  t h e members  t o purchase would  be  This  coand  expensive  regulation that  (B.C.) A c t .  and p e r s o n a l  machinery  under a s i n g l e  be p r o v i d e d .  together  of the  otherwise  The government  WGGCA t h e r i g h t t o s e l l t h e N a t u r a l Products  5 and  principles  gives  selling  agency  Hence, an a n a l y s i s  i s achieved  interviews with  through  experts  in  the  field. Finally, and  costs  a model w i l l  o f marketing  be d e v e l o p e d  t o determine  the benefits  r e g u l a t i o n s and c o - o p e r a t i v e  policies  as  t h e y a p p l y t o W e s t e r n Greenhouse G r o w e r s ' C o - o p e r a t i v e A s s o c i a t i o n . A partial and  e q u i l i b r i u m model w i l l  demand  o f greenhouse  more t h a n t o m a t o e s . made b y WGGCA.  be u s e d t o d e t e r m i n e  tomatoes  i n BC.  Tomatoes a c c o u n t e d  The c o - o p e r a t i v e  f o r 35% o f t h e t o t a l  We c a l c u l a t e d t h e w e l f a r e i m p a c t s  tomatoes f o r i l l u s t r a t i o n purposes.  t h e supply does sales  f o r B.C. H o t h o u s e  The o t h e r p r o d u c t s  t h a t WGGCA  s e l l s a r e peppers,  cucumbers, a n d b u t t e r l e t t u c e .  sells  d o m e s t i c a l l y and i t exports a l l o f i t s p r o d u c t s  to  i t s products  other  Furthermore,  regions  of  i t faces  Canada  and U n i t e d  competition  from  local  The c o - o p e r a t i v e  States, field  as  well.  products and  imports be  i ntheBritish  estimated  function  using  will  be  the  will  greenhouse  using  econometrics.  be e s t i m a t e d  f o r t h e base  scenario w i l l  monopolistic  be s i m u l a t e d .  situation  growers  The s u p p l y  a c o s t - o f - p r o d u c t i o n schedule estimated  e q u i l i b r i u m model counterfactual  Columbia market.  with  i n Districts  no  6 will  function  a n d t h e demand This  partial  s c e n a r i o and t h e  The b a s e  competition  scenario i s  amongst  B.C.  I and I I and t h e c o u n t e r f a c t u a l  s c e n a r i o i s t h e c o m p e t i t i v e s i t u a t i o n w i t h c o m p e t i t i o n amongst B.C. greenhouse growers i n D i s t r i c t s e f f e c t s such a s producer  I a n d I I . By c o m p a r i n g t h e w e l f a r e  s u r p l u s , consumer  s u r p l u s , and dead-weight  l o s s between t h e s e t w o s c e n a r i o s , we c a n d e t e r m i n e costs  of single-selling  desk  on WGGCA,  s o c i e t y i n w h i c h WGGCA o p e r a t e s i n .  t h e b e n e f i t s and  i t s consumers,  and  the  From t h e r e s u l t s o f t h e m o d e l ,  c o n c l u s i o n s a n d i m p l i c a t i o n s w i l l b e drawn.  1.4  Organization  Chapter vegetable  of the  2 p r o v i d e s a h i s t o r i c a l account  industry  conditions,  Study  outlining  a n d government  how  o f t h e B.C. g r e e n h o u s e  production  r e g u l a t i o n s have  methods,  changed  over  market time.  W e s t e r n Greenhouse G r o w e r s ' C o - o p e r a t i v e A s s o c i a t i o n (WGGCA) i s t h e most i m p o r t a n t it  sells  agency i n t h e greenhouse v e g e t a b l e  approximately  i n d u s t r y because  96.5% o f t h e g r e e n h o u s e v e g e t a b l e s  i n BC, t h e I n t e r i o r V e g e t a b l e  M a r k e t i n g Agency C o - o p e r a t i v e  produced handles  3.0%  and t h e northern  Therefore,  chapter  region  two  o f BC h a n d l e s  focuses  on  WGGCA  less  than  and  the  i m p l i c a t i o n s o f i t o p e r a t i n g as a c o - o p e r a t i v e . principles examine  their  estimation tomatoes. methods  o f government economic  o f supply  regulations implications.  a n d demand  equations  Econometric estimation techniques  a r e used  t o determine  the costs  s e l l i n g desk u n d e r t h e N a t u r a l P r o d u c t s privatization welfare  Chapter  f o r t h e WGGCA.  effects  Conclusions  of  single  Chapter selling  4  3,  i n order  the to  discusses the  f o r B.C.  greenhouse  and c o s t - o f - p r o d u c t i o n and b e n e f i t s  Marketing  of single  (B.C.) A c t v e r s u s  5 i s a discussion desk  7 4  economic  I n chapter  a r e analyzed  0.5%.  versus  of  the  privatization.  and p o l i c y i m p l i c a t i o n s which a r i s e from t h e r e s u l t s o f  t h i s s t u d y w i l l b e d i s c u s s e d i n C h a p t e r 5, a s w e l l .  Nahanni H o r t i c u l t u r a l S e r v i c e s . The Greenhouse V e g e t a b l e Industry i n B r i t i s h Columbia: An I n d u s t r y P r o f i l e & S t r a t e g i c P l a n f o r I n d u s t r y Development. BCMAFF: May, 1993.  2.0  8  BACKGROUND TO THE INDUSTRY AND WGGCA  In  this  chapter,  industry w i l l deal  a profile  be p r o v i d e d .  The f i r s t  with  t h e past  history  greenhouse  vegetable  industry.  will  o f t h e B.C. g r e e n h o u s e part  of this  and t h e current  chapter  state  The s e c o n d p a r t  and d i r e c t o r s o f co-operatives  will  o f t h e B.C.  of this  d e s c r i b e t h e economic i m p l i c a t i o n s o f c o - o p e r a t i v e  managers  vegetable  consider  chapter  issues that  relevant  t o the  s u s t a i n a b i l i t y and growth o f t h e i r o r g a n i z a t i o n .  The t h i r d p a r t o f  this  issues  chapter  will  describe  t h e co-operative  that  are  r e l e v a n t t o WGGCA.  2.1  H i s t o r y o f t h e B.C. Greenhouse Vegetable  The existed terms  greenhouse  f o r many y e a r s of  tomatoes,  frames  construction continually The the 5  early  and  the first which  was  growers 1950's  planted  wax p a p e r replaced  increased.  i n British  structure.  greenhouse  were  with  industry  Columbia has  a n d i t h a s gone t h r o u g h d r a s t i c  production  introduced  wooden  vegetable  Industry  In  vegetable  as a f i l l - i n covering.  by  glass  changes i n  1927, t h e crop. crop  Japanese  They  grew  f o rberries, i n  Gradually, structures  this  and  type o f  production  5  formed  Haney  to assist  Greenhouse  Growers'  p r o d u c e r s t o market  Association i n  their  products.  T h i s s e c t i o n i s b a s e d on BC Greenhouse V e g e t a b l e I n d u s t r y : A P r o f i l e , an u n d e r g r a d u a t e e s s a y c o m p l e t e d i n May 1988 b y D a v i d Van D e r G u l i k a t UBC i n A g r i c u l t u r a l E c o n o m i c s .  9 T h i s name was l a t e r changed t o The Maple Ridge Greenhouse Growers' Co-operative. time  At that time,  driving  their  the growers were  too much  t r u c k s around t o negotiate the best p r i c e f o r  t h e i r produce.  Furthermore,  time  and e f f o r t  t o develop  time  were l o c a t e d at Oppenheimer  growers  spending  got together  the wholesalers d i d not spend enough their  products.  The brokers  and Malkin  Avenue.  and formed Western  operative A s s o c i a t i o n (WGGCA) on October  at that  Hence, the  Greenhouse  Growers' Co-  19, 1973. The  organizers  of WGGCA at that time wanted t o develop one name and e v e n t u a l l y one l a b e l f o r t h e i r products. WGGCA requested the P r o v i n c i a l Government of the day t o form a marketing control  o r g a n i z a t i o n i n order t o gain supply  o f the i n d u s t r y and t o stop  Their request was approved jurisdiction  price-cutting  competition.  i n 1973 and they were brought  o f the B.C. Coast  Vegetable  Marketing  under the  Board.  In the  opinions o f most greenhouse vegetable growers, t h i s i s one o f t h e i r major t u r n i n g p o i n t s because the co-operative could now s e l l i t s products  under  a  single-selling  maximum returns f o r them.  desk  which  At that time,  ostensibly  these  provides  products  include  greenhouse tomatoes and greenhouse cucumbers. Major changes and growth t o the industry continued.  The co-  operative introduced c e n t r a l grading i n 1983-84 crop year.  Also, a  method t o shrink wrap the cucumbers t o keep them f r e s h f o r a longer period  o f time  was developed  and t h i s  has r e s u l t e d  i n increased  s a l e s of cucumbers. Research systems,  new  and  technology  heating  systems,  transfers cropping  introduced systems,  hydroponic computerized  climate  control,  cultivars, technical  integrated  pest  management  and the d i v e r s i f i c a t i o n o f crops. innovations have been  Netherlands.  researched  10 hybrid  programs,  The majority o f the and developed  Many BC growers go t o the Netherlands  new t e c h n o l o g i e s and they b r i n g them back t o BC.  in  the  t o l e a r n the  Hence, most o f  the machinery and b u i l d i n g equipment f o r greenhouse production and processing improved  are from  the Netherlands.  By adopting  t o new and  t e c h n o l o g i c a l methods and by o b t a i n i n g a higher l e v e l o f  education among the growers, p r o d u c t i v i t y has increased. The quality  development grading  o f the industry  standards,  was a c c e l e r a t e d by  increased per c a p i t a  consumption o f  greenhouse vegetables  and aggressive marketing  and  In 1992, WGGCA introduced a q u a l i t y  export markets.  6  s t a f f t o monitor product  standards.  high  both  f o r domestic control  They make recommendations f o r  improvement as regards t o grading, s h e l f - l i f e , and v a r i e t i e s . a l s o check the products on appearance and cracks. that  the q u a l i t y  control  technicians  They  The g u i d e l i n e s  aim f o r are n u t r i t i o n ,  firmness, and f l a v o u r . The marketing s t a f f at WGGCA has created a branded product f o r t h e i r produce.  The new B.C. Hothouse logo used  t o i d e n t i f y B.C.  Hothouse grown tomatoes, Long E n g l i s h cucumbers, sweet b e l l and  butter  commercials, tomato,  lettuce  newspaper i n s e r t s ,  pepper,  operative.  are everywhere:  cucumber,  Furthermore,  supermarket  and b u t t e r they  transit  promote  Interviews with people i n the i n d u s t r y .  ads, t e l e v i s i o n  displays,  lettuce  peppers  and on every  sold  the export  by the of  co-  their  commodities creating  by p a r t i c i p a t i n g  a branded  commodity product. competitor four  product,  i n international WGGCA i s moving  have  away  shows.  from  being  11 By a  That i s , i t i s t r y i n g t o switch from a p e r f e c t  t o a m o n o p o l i s t i c competitor.  will  trade  a  more  complete  Section one o f chapter  description  o f monopolistic  competition.  2.2  Present Status o f WGGCA  Table  2.1 presents  the greenhouse vegetable  values f o r B r i t i s h Columbia from 1968 t o 1994. show the trends o f these products.  productions and  Diagrams 2.1 t o 2.4  From these diagrams, we can see  that the s a l e s volume and s a l e s value o f BC greenhouse tomatoes, BC greenhouse rather  cucumbers,  rapidly  greenhouse  and BC  i n the l a s t  lettuce  greenhouse  t e n years.  has decreased  peppers  have  expanded  The s a l e s volume  since i t s i n t r o d u c t i o n  s a l e s value tends t o increase over the years.  Overall,  o f BC  but  the  the s a l e s  volume and s a l e s value o f the BC greenhouse vegetable i n d u s t r y have i n c r e a s e d d r a s t i c a l l y i n the l a s t ten years.  TABLE 2.1: GREENHOUSE PRODUCTION QUANTITIES AND VALUES FOR BRITISH COLUMBIA TOMATOES TOTAL SALES Year Quantity '000 l b 1968 1969 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994*  3113 3288 3487 3928 4542 4584 3705 5068 5508 5934 5718 5644 5212 3940 6102 7100 46 8575 10679 13339 12137 14547 17586 17827 19756 20201 23207  Value $'000 912 1095 937 1227 1557 1687 1454 2225 2272 2644 2840 2776 3191 2396 3357 4113 32 4781 8015 10204 10273 8800 11959 15361 13675 13518 17480  CUCUMBERS TOTAL SALES  SWEET PEPPERS TOTAL SALES  LETTUCE TOTAL SALES  Quantity Value Quantity Value Quantity Value '000 l b $'000 '000 l b $'000 '000 l b $'000 2181 521 2452 602 2837 672 3418 835 3596 945 3962 994 4384 1129 6072 1598 5079 1292 5746 1625 6175 2405 6810 2665 10623 4689 6096 3165 6237 3108 9546 4432 4 1 11495 5011 11195 5684 11141 6352 11118 6632 12960 5500 13795 8324 13003 8145 15949 8562 15949 9875 19416 10095  0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 687 955 1890 3306 4678 6093 7879 15634 16560  0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1004 1563 3682 4900 7719 10359 12644 17522 18302  n/a n/a n/a n/a n/a n/a h/a n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a 2400 1524 1524 1500 1500 1562 1920 2040  n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a 1323 1527 1200 1100 1450 1615 2076 2040  *The values f o r 1994 are the p r e d i c t e d values. Source: BCMAFF. Production o f Vegetable Crops Together With An Estimate of Farm Values. V i c t o r i a , BC: 1968 through 1986. Continues by Annual S t a t i s t i c s , 1988. Continues by H o r t i c u l t u r a l S t a t i s t i c s , 1989 and 1990. Continues by Annual H o r t i c u l t u r a l S t a t i s t i c s , 1991 and 1992. Continues by The Greenhouse Vegetable Industry i n B r i t i s h Columbia: An Industry P r o f i l e & S t r a t e g i c Plan f o r Industry Development, 1993.  Quantity in Thousand Pounds  o  r  o  o o o  t  » o  . o o  a o  i o o  O o  o  o o o  -  »  r  -  -  o o  o  o  »  o o  ^  -  >  o  Value in Thousand Dollars  ua  -•-Valu  CD  D  o  c o  -  -  o  o  »  o  o  .  o  o o  » o  o  .  < o  /  >  J  ua  CD  -•-Valu  D  ><  Quantity in Thousand Pounds  Quantity in T h o u s a n d P o u n d s  The cherry  tomatoes,  lettuce, the  greenhouse vegetable growers produce long  coloured b e l l  exception  English  cucumbers,  peppers,  o f peppers  beefsteak  European  and eggplants.  and eggplants,  17 tomatoes,  butter  head  At present,  with  a l l commonly  grown  greenhouse vegetable commodities are regulated products and r e q u i r e a quota t o be marketed. to  be reviewed  only  be s o l d  I t takes one year f o r a quota  and approved. through  Regulated greenhouse vegetables can  designated  agencies  Greenhouse Growers' Co-operative A s s o c i a t i o n WGGCA  i s responsible  distributing,  f o r grading,  and conducting  vegetables that  i t sells.  application  research  such  as the Western  (WGGCA). packaging,  promoting,  and development  for  I t has one packing p l a n t and warehouse  and the members o f WGGCA own the land, b u i l d i n g , and f a c i l i t y . plant  i s about  they  10 years  o l d and i s s t i l l  are c o n s t a n t l y upgrading  warehouse i s at f u l l options:  buying  capacity.  another  the  their  very  efficient  equipment.  or b u i l d i n g  because  P r e s e n t l y , the  WGGCA i s c u r r e n t l y  facility  The  l o o k i n g at two  a larger  facility  from s c r a t c h .  2.3  Economic Implications of Co-operative Structure  Marketing  co-operatives are common i n a g r i c u l t u r e .  Farmers  form marketing co-operatives t o improve t h e i r well-being.  The main  reason can  that  obtain  distributing  farmers  form  economies their  marketing  of  scale  products.  co-operatives i s because i n processing,  Another  reason  why  marketing farmers  they and form  marketing  18 squeezed  co-operatives i s because they do not want to be  by o l i g o p o l i s t s such as farm equipment manufacturers manufacturers  and  by  o l i g o p s o n i s t s such  r e t a i l food s t o r e s .  as  By forming a marketing  and  fertilizer  wholesalers  and  large  co-operative, they have  c o u n t e r v a i l i n g market power. From S u r v i v a l authors  (Charles  Strategies for Agricultural E.  French,  et  a l . , 1980)  Co-operatives,  compiled  a  list  the of  advantages and disadvantages  of a g r i c u l t u r a l co-operatives based on  interviews  and  with  managers  operatives  i n United  are l i s t e d  i n Table  States.  of  These advantages and  i s that  et a l , one  co-  disadvantages  of the major advantages of a  i t s members have a v o i c e  that the co-operative promotes because they own operative.  agricultural  2.2.  According to French, co-operative  directors  Furthermore,  the members of the  i n the  activities  and c o n t r o l the coco-operative w i l l  l o y a l to the co-operative as long as the managers can provide necessary Also,  services,  s u p p l i e s , or marketing  a co-operative can  at competitive  work together with  other co-operatives t o market member products. advantages disadvantages  are  traded  off  with  be the  levels.  i t s members and  with  The above mentioned  disadvantages.  The  of a co-operative are that i t cannot acquire  major capital  by o f f e r i n g v o t i n g stocks and i t i s d i f f i c u l t to r e t a i n c a p i t a l f o r future  investment  bottom  lines  purposes because members want to maximize  each year.  Other disadvantages  their  of a g r i c u l t u r a l  co-  operatives i n c l u d e mandatory handling of a l l t h e i r members' product even i f i t means a higher operating cost per unit such as having to  pay  f o r overtime  t o handle  additional  products;  keeping  19 detailed  records of t r a n s a c t i o n s done by each patron so that net margins can be a l l o c a t e d c o r r e c t l y farm d i r e c t o r s  and tax laws can be complied with;  t o take r i s k  because  farm  directors  conservative and are not w i l l i n g t o take r i s k that  getting  are sometimes i s involved i n  maintaining a p r o g r e s s i v e operation, and keeping members of the cooperatives more informed i s a c o s t l y s e r v i c e , e s p e c i a l l y f o r large co-operatives. Some of these French, they  advantages  et a l , mention  and disadvantages  are a p p l i c a b l e  are not are a p p l i c a b l e  that  Charles E.  t o some co-operatives but  t o a l l co-operatives.  For example,  Ocean Spray has been very s u c c e s s f u l marketing i t s products.  Ocean  Spray  other  i s a successful  co-operative and i t markets products  than a g r i c u l t u r a l r e l a t e d products.  20 TABLE 2.2:  ADVANTAGES AND DISADVANTAGES OF CO-OPERATIVES  Advantages o f C o - o p e r a t i v e s i n Comparison w i t h Noncooperatives 1. A c c e s s t o t h e Banks f o r C o - o p e r a t i v e s . 2. A v a i l a b i l i t y o f s p e c i a l income t a x s t a t u s . 3. Use o f p a t r o n a g e r e f u n d s - c o - o p e r a t i v e s o f t e n r e t u r n more d o l l a r s t o t h e i r f a r m e r owners. 4. G r o w e r s ' l o y a l t y i n m a r k e t i n g c o - o p e r a t i v e s - t h e g r o w e r s ' f a m i l i a r i t y w i t h t h e d e s i r e d q u a l i t y o f product t o be produced. 5. G r e a t e r w o r k i n g r e l a t i o n s h i p among c o - o p e r a t i v e members, a n d the sanction t o act together. 6. More open t o farmer-members' needs. 7. L o c a l a n d r e g i o n a l c o - o p e r a t i v e s a r e l o c a t e d s o t h a t l o g i s t i c a l l y they provide b e t t e r s e r v i c e s . 8. C o - o p e r a t i v e s d e a l d i r e c t l y w i t h members; a n o n c o o p e r a t i v e o r g a n i z a t i o n may b e a s m a l l p a r t o f some v e r y l a r g e c o n g l o m e r a t e whose h e a d q u a r t e r s a n d t o p management a r e unknown t o f a r m e r s . 9. C o - o p e r a t i v e s h a v e p r o v e d t h a t t h e y do n o t d e s e r t t h e i r f a r m members d u r i n g t i m e s o f s h o r t a g e s . 10. Members r e c e i v e more e q u i t a b l e t r e a t m e n t . 11. C o - o p e r a t i v e s a r e more c o n c e r n e d about d e v e l o p i n g p e o p l e . D i s a d v a n t a g e s o f C o - o p e r a t i v e s Over N o n - c o - o p e r a t i v e s 1. Cannot a c q u i r e c a p i t a l by o f f e r i n g v o t i n g s t o c k . 2. Some c o m m e r c i a l b a n k e r s h e s i t a t e t o l o a n t o c o - o p e r a t i v e s b e c a u s e o f b a n k e r s ' l a c k o f knowledge about c o - o p e r a t i v e s . 3. I n some c a s e s , c o - o p e r a t i v e s l a c k u n i t y o r u n i f o r m i t y . 4. P l a n n i n g l o n g - t e r m i n v e s t m e n t s i s d i f f i c u l t b e c a u s e g r o w e r s demand t h a t t h e i r r e t u r n s be good e v e r y y e a r . 5. N o t a s m a r k e t o r i e n t e d a n d l a c k r e s e a r c h a n d d e v e l o p m e n t t o keep o u t l e t s open f o r f a r m e r s . 6. The o n e - p e r s o n - o n e - v o t e limitation. 7. Some f a r m e r s e x p e c t t h e c o - o p e r a t i v e t o o f f e r more s e r v i c e s a t b e t t e r p r i c e s t h a n anyone e l s e . 8. L i m i t e d f i n a n c i a l i n c e n t i v e s f o r managers. 9. L i m i t e d r e t u r n s on e q u i t y . 10. L i m i t e d t o the marketing o f a g r i c u l t u r e - r e l a t e d products. Source: Survival Strategies f o r A g r i c u l t u r a l Co-operatives. C h a r l e s E. F r e n c h , e t a l , pp75-78. Similarly, encountered operative regulations has  t h e managers  some  and d i r e c t o r s  o f t h e advantages  structure  mentioned  monopolistic  competitive  and disadvantages  above.  i m p o s e d on t h e i n d u s t r y  a t t h e WGGCA  This  as w e l l .  power  in  i s related  have  of coto the  F o r example, WGGCA  the  distribution  of  21  greenhouse products i n t h e Lower Mainland-Fraser V a l l e y r e g i o n and on Vancouver I s l a n d .  M o n o p o l i s t i c c o m p e t i t i o n i m p l i e s t h a t WGGCA  competes  by s e l l i n g  slightly  from other vegetable products.  advertising discretion  and marketing  will  vegetable  such Alberta,  products  as C a l i f o r n i a ,  losing  Florida,  WGGCA  Mexico,  O n t a r i o , Spain and H o l l a n d .  elasticity.  operatively  Hence,  r a t h e r than  by marketing  individually,  differ through  has  some  i t s e n t i r e market t o local  Lowering  induce a d d i t i o n a l s a l e s but the net b e n e f i t w i l l  demand  which  This i s achieved  not r e g u l a t i o n .  i n r a i s i n g p r i c e s without  competitors producers,  greenhouse  growers'  field prices  depend upon products c o -  t h e i n d u s t r y has i n c r e a s e d  i t s market power a g a i n s t i t s c o m p e t i t o r s . However, t h e producers have t o i n v e s t monetary funds i n order to pay  achieve m o n o p o l i s t i c c o m p e t i t i v e power.  f o r a d v e r t i s i n g and marketing expenditures i n order t o develop  a brand name. to  That i s , they have t o  Although i t i s expensive t o a d v e r t i s e t h e i r  product  t h e mass media, many c o - o p e r a t i v e o r g a n i z a t i o n s such as S u n k i s t  and Ocean Spray have been s u c c e s s f u l i n a c h i e v i n g brand names. Other advantages o f s i n g l e - s e l l i n g desk a r e uniform and q u a l i t y standards.  When the growers s h i p the products t o t h e  co-operative, the q u a l i t y growers'  packaging  control staff  goods a t t h e same time.  s o r t s and grades  a l l the  This prevents i n d i v i d u a l growers  from p r o d u c i n g v e g e t a b l e s t h a t do not meet t h e standards o f c e r t a i n grade, grades.  size,  and c o l o r .  That i s , t h e growers p o o l a c c o r d i n g t o  T h i s i s not a normal p r a c t i c e o f c o - o p e r a t i v e s .  why WGGCA i s s u c c e s s f u l .  There i s no p o o l i n g across  That i s grades.  Therefore, superior Also,  products  by  consumers  having  a  to  lower  central  a r e guaranteed  up  loyalty  a r e awarded a h i g h e r r e t u r n f o r p r o d u c i n g  than  because consumers w i l l pick  22  t h e producers  quality  products  packaging  and v i c e  and q u a l i t y  consistent products.  know what t h e y  "B.C. H o t h o u s e "  This  a r e buying  products.  This  standards, i s important  every  time  encourages  a n d e l i m i n a t e s f r e e r i d i n g among p r o d u c e r s  versa.  they  consumer  who do n o t s h i p  WGGCA. Furthermore,  there  i s cost  efficiency  d e v e l o p m e n t b e c a u s e a l l t h e members p o o l t h e i r t o w a r d s a common g o a l . for  i n research resources  and c a p i t a l t o m a i n t a i n a n d expand f a c i l i t i e s One p o s s i b l e d i s a d v a n t a g e  from  Free  taking  riding  together  These b e n e f i t s i n c l u d e p o o l i n g o f r e s o u r c e s  p r o f e s s i o n a l e x p e r t i s e , r e s e a r c h and development,  riding.  and  a costly  at the co-operative.  of co-operative  i s common a n d o c c u r s a c t i o n such  advertising,  structure i s free-  when a g r o w e r  as b e i n g  a member  refrains  of the  co-  o p e r a t i v e b e c a u s e he/she knows t h a t someone e l s e w i l l u n d e r t a k e i t . Initially, spending  WGGCA  was  formed  growers  have  growers  By f o r m i n g a m a r k e t i n g  more b a r g a i n i n g  Prices  f o r greenhouse products  today.  Free-riders benefit  result  greenhouse  were  t o o much t i m e d r i v i n g t h e i r t r u c k s a r o u n d t o n e g o t i a t e t h e  best p r i c e f o r t h e i r produce. the  because  power  with  are largely from  large  wholesalers.  s e t i n t h e marketplace  the increases  o f co-operative a c t i o n but they  co-operative,  i n prices  do n o t have t o comply  the  rules  not  have t o p a y f o r t h e a d m i n i s t r a t i o n c o s t  as a with  a n d r e g u l a t i o n s s e t o u t b y t h e c o - o p e r a t i v e a n d t h e y do of being  a member o f  the co-operative. to  prevent  The N a t u r a l P r o d u c t s  f r e e r i d i n g by growers.  Chapter 3 provides  d e s c r i p t i o n o f the N a t u r a l Products Another  example  bootlegging.  that  Bootlegging  Marketing  ties  occurs  23 (B.C.) A c t c l a i m s  Marketing  (B.C.) A c t .  closely when  a detailed  to  free-riding  t h e members  i s  of theco-  o p e r a t i v e can o b t a i n higher p r i c e s elsewhere.  When t h e y  higher  t o the co-operative  prices  because  elsewhere,  t h e co-operative  t h e i r products for  they  will  charges  t o -WGGCA.  not ship  t h e growers  can obtain  a fee f o r shipping  Presently, bootlegging  i s not a problem  WGGCA. Another p o s s i b l e disadvantage  member-one-vote different  system.  s i z e members.  co-operative recognition  than  This  i s especially  a  i s t h e one-  problem  with  Some members i n v e s t more i n e q u i t y i n t h e  others  regardless  of the co-operative  b u t each  of their  member  investment  receives  t h e same  i n the co-operative.  A l s o , t h e c o s t o f p r o v i d i n g i n f o r m a t i o n t o members i s h i g h w i t h t h e one-member-one-vote s y s t e m . what p r i c e s t h e y  are receiving for their  week t o week b a s i s paid three  F o r example, some g r o w e r s want t o know  because  weeks a f t e r  they  crops.  They c h e c k on a  a r e concerned.  The members a r e  shipping t h e i r products  t o WGGCA.  w a n t i n g t o know what p r i c e s t h e y  will  know why t h e r e  between t h e p r i c e s t h a t  receiving some  and the p r i c e that r e t a i l e r s  producers  therefore,  i s a huge s p r e a d  do  not  understand  t h e y want t o know why t h e y  peppers and t h e s t o r e i s s e l l i n g  Besides  r e c e i v e , t h e g r o w e r s want t o  areselling. margins  they a r e  F o r example,  and  added-value;  r e c e i v e $1.00 f o r a p o u n d o f  $2.88 p e r pound.  As a r e s u l t o f  24  the  co-operative  structure  everyone i s t r e a t e d capital  invested  equally  o f t h e greenhouse regardless  i n the co-operative.  vegetable  o f p a t r o n a g e and amount o f This  i s why some members o f  the  co-operative  w a n t e d t o change t h e o r g a n i z a t i o n a l  the  organization  from a co-operative  switching  structure  t o an i n v e s t o r owned f i r m .  t o an i n v e s t o r owned f i r m , t h e members c a n v o t e  t o t h e amount  invested.  industry,  of By  according  3.0  25  MARKETING REGULATIONS AND THEIR IMPLICATIONS  This chapter w i l l provide a b r i e f d e s c r i p t i o n o f the marketing board t h a t r e g u l a t e s t h e v e g e t a b l e i n d u s t r y i n B r i t i s h Columbia and i t s i m p l i c a t i o n s f o r t h e greenhouse v e g e t a b l e  3.1  The Natural Products Marketing (BC) Act  As  discussed i n section  3 o f chapter  when t h e g r o w e r s know t h a t t h e y operative. by  industry.  2, f r e e - r i d i n g  do n o t have t o b e l o n g  t o the co-  I n order t o prevent f r e e - r i d i n g o f co-operative a c t i o n s  n o n - p a r t i c i p a t e s , t h e members  government  of  WGGCA  f o r regulations i n the industry  According  t o some  greenhouse  Mainland,  t h e most i m p o r t a n t  Products  Marketing  Vegetable  Scheme.  f o r WGGCA t o s e l l a single-selling Furthermore, regulation  vegetable  the B r i t i s h  have  pushed  the  since i t s formation.  7  producers  i n t h e Lower  government r e g u l a t i o n  i s the Natural  (BC) A c t .  This  Act establishes  t h e B.C.  The B.C. V e g e t a b l e  Scheme p r o v i d e s t h e powers  d o m e s t i c a l l y produced  greenhouse v e g e t a b l e s under  desk. t h i s A c t provides f o r t h e promotion,  of theproduction, transportation,  marketing o f natural products i n the Province.  7.  occurs  Columbia  M a r k e t i n g Board  c o n t r o l and  packing, storage and I talso  establishes  (BCMB) a n d s t a t e s i t s p o w e r s .  F o r more i n f o r m a t i o n , s e e Mary Bohman's w o r k i n g p a p e r on B r i t i s h Columbia M a r k e t i n g R e g u l a t i o n s and C o o p e r a t i v e s . T h i s i s a v a i l a b l e a t t h e Department o f A g r i c u l t u r a l Economics at t h e U n i v e r s i t y o f B r i t i s h Columbia.  At  present,  BCMB s u p e r v i s e s  commissions. Marketing  WGGCA i s u n d e r  8  Commission,  26 commodity b o a r d s a n d  12 a g r i c u l t u r a l  t h e s u p e r v i s i o n o f B.C.  one o f t h e t w e l v e  agricultural  Vegetable commodity  b o a r d s a n d c o m m i s s i o n s t h a t BCMB s u p e r v i s e s . WGGCA i s r e s p o n s i b l e f o r greenhouse produce such in  t h e Lower  Island.  of a l l regulated  a s t o m a t o e s , cucumbers, a n d b u t t e r  Mainland-Fraser  Besides  the distribution  Valley  distributing  district  a n d on  and marketing  such  as c o l o u r e d b e l l  Vancouver  t h e above  mentioned v e g e t a b l e s , i t a l s o d i s t r i b u t e s and markets greenhouse v e g e t a b l e s  lettuce  three  non-regulated  peppers and eggplants  on a c o n t r a c t u a l b a s i s .  3.2  The B r i t i s h Columbia Vegetable Marketing Commission  Before  1980, t h e r e were two m a r k e t i n g  the v e g e t a b l e i n d u s t r y i n B r i t i s h Columbia: Marketing Board price  cutting  and t h e Coast competition  Vegetable  between  e s t a b l i s h m e n t o f a s i n g l e - s e l l i n g agency.  Commission. would  help  production availability  The v e g e t a b l e t o maximize i n naturally  that  regulated  theInterior  Vegetable  M a r k e t i n g Board.  these  b o a r d s amalgamated t o f o r m t h e B r i t i s h  boards  two b o a r d s  Columbia Vegetable that  returns,  advantageous  l e dt othe  On J u l y 1, 1980, t h e two  i n d u s t r y hoped  producer  However,  o f p r o v i n c e wide market i n f o r m a t i o n .  8.  Ibid.  9.  T h i s i n f o r m a t i o n i s p r o v i d e d b y BCVMC.  a single  encourage  areas,  Marketing agency  vegetable  and i n c r e a s e t h e 9  The  Commission  Marketing Under  (B.C.)  the  Vegetable and  Act  Natural  marketing  Act,  e s t a b l i s h e d under  to  administer  Products  the  the  in  Vegetable  the  the  has  an  market  Lower M a i n l a n d - F r a s e r  Valley  Island  Islands  Interior  the  Gulf  inspection on  a  markets,  p r o v i n c e t o which  BCVMC  as  into  Apart  designated  eight  a l l d o m e s t i c a l l y produced  and To  (B.C.)  monitor  the  The  B.C.  districts:  the  I, the  I I , and  from  control  Columbia.  basis.  District  B.C.  storage  to  three  District  III.  the  Marketing  staff  regular  r e g i o n as  r e g i o n as D i s t r i c t  municipal  and  packing,  Natural Products  place  Scheme.  t h e power t o p r o m o t e ,  Scheme d i v i d e s t h e p r o v i n c e  and  Act  i n the Province of B r i t i s h  r e g u l a t i o n s of  Commission  activities  (B.C.)  27 Products  Natural  Vegetable  production, transportation,  of vegetables  the  the  B.C.  Marketing  Scheme, t h e C o m m i s s i o n has  regulate the  enforce  was  Vancouver  the  Southern  roadside stands agencies  within  and the  regulated products  are  sold. Presently, vegetables  there  that  are  are  sixteen  under  the  fresh  control  of  and  eleven  processed  the  Commission.  C o m m i s s i o n does n o t r e g u l a t e p r o d u c t s u n l e s s r e q u e s t e d by percent  of  deregulate  a r e t h e two  commercial are  producers.  products.  Association  All  the  and  Furthermore,  Western  Interior  Greenhouse  Vegetable  the  60 t o 7 0  Commission  Growers'  Marketing  The  can  Co-operative  Agency  Co-operative  a g e n c i e s t h a t h a n d l e g r e e n h o u s e v e g e t a b l e s i n BC.  growers growers  registered  must can  with  register vote.  the  with  the  Commission  Commercial growers  Commission  in  any  one  are of  but  only  growers the  who  three  districts  specified  a n d who d u r i n g  months h a d r e g u l a t e d p r o d u c t s that  of at least  h a s b e e n grown on t h e f a r m  agency o f t h e C o m m i s s i o n .  t h e immediately  the  growers  within  The c o m m e r c i a l  their  28 12  a g r o s s v a l u e o f $5,000  and marketed  e i g h t members t o s e r v e on t h e BCVMC.  preceding  from  i t through  growers e l e c t  an  a total of  These members a r e e l e c t e d b y  districts.  The g r e e n h o u s e  vegetable  i n d u s t r y h a s one r e p r e s e n t a t i v e on t h e C o m m i s s i o n . Besides maintains and  l i c e n s i n g and r e g i s t r a t i o n o f growers,  a registry  processors.  and l i c e n c e s  quantity  o f each  prediction  i n d u s t r y producers,  I n f o r m a t i o n on volume a n d v a r i e t y  are submitted by t h e producers  i s used  product  t h e Commission wholesalers,  o f crops  t o allow f o r the prediction  that  t o determine  may  reach  grown of the  t h e market.  how much p r o d u c t  will  This  enter the  market. Under t h e N a t u r a l P r o d u c t s M a r k e t i n g authority WGGCA  t o s e t quotas.  decides  producers utilized  how much  based  t o produce.  o n how many  f o r t h e growers'  A new e n t r a n t must they w i l l quota  apply  a n d f a m i l y members  Under commercially  the Natural  authority  feet  allocates  f o r quota  with  quotas  from  c a n be  t h e Commission and Legally, the  c a n be t r a d e d  a penalty  to  basis.  t o m a r k e t demand.  The q u o t a s  t o WGGCA.  o f greenhouse  p r o d u c t i o n on an a n n u a l  value.  f o o t a g e o f 10% a n d z e r o ,  this WGGCA  square  d i s t r i b u t e i t i n response  h a s no m o n e t a r y  producers  BCVMC g r a n t s  (B.C.) A c t , BCVMC h a s t h e  i n terms  between  of  square  respectively. Products  Marketing  (B.C.)  Act,  m a r k e t e d t o m a t o e s , cucumbers, a n d b u t t e r l e t t u c e  a l l must  be  shipped  through  agencies. Scheme,  one  o f the designated  Furthermore, t h e movement  greenhouse  29 marketing  Vegetable  Marketing  have  transport  a c c o r d i n g t o t h e BC of  these  products  must  a  permit. BCVMC a l s o s e t s minimum m a r k e t p r i c e s British large  Columbia  fresh  quantities  California, The p r i c e landed  v e g e t a b l e growers a r e p r i c e  o f produce are imported  Florida,  Mexico,  and some  price  o f i t s major  product  at origin)  current  exchange r a t e .  calculated  consideration. American there  competitors.  point  at  Trade  be  no  To t h i s  of origin  Finally,  appropriate  Agreement  tariffs  rate  palleting,  (NAFTA).  the  accordingly. WGGCA  based  landed  Columbia  import  For exported their  prices  items  price,  c o - o r d i n a t i n g market  i t is  item  January coming  and  like  imported  information  1,  from  cost p e r case  they  premium on t o p o f t h e i m p o r t e d p r i c e By  currency at the  i s calculated  inspection  products on  import  f o r the  under  for their and  the  from t h e  fees  their  Hothouse  products  United  are  Columbia.  adjust  B.C.  1998,  and added i n .  brokerage  added t o g i v e t h e l a n d e d p r i c e p e r c a s e i n B r i t i s h From  The l a n d e d  i s i n effect,  After  on v e g e t a b l e  cooling,  by t h e  i s d i s a p p e a r i n g under t h e North  value, the transportation to British  and O n t a r i o .  determined  Canadian  I f a seasonal t a r i f f  the  Oregon,  ( p r i c e f o r g r a d e d and p a c k e d  and i s c o n v e r t e d i n t o  The s e a s o n a l t a r i f f  Free  will  States.  Alberta  t h a t B.C. g r o w e r s r e c e i v e d i s l a r g e l y  import  t a k e r s because  from Washington,  from  p r i c e i s d e t e r m i n e d u s i n g F.O.B. p r i c e  then  f o r regulated products.  and  prices  products,  they  add  a  superior quality. concentration  of  selling  power  o f a l l growers,  selling prices.  t h e Commission t r i e s  30  t o maximize  I n f o r m a t i o n i s c o l l e c t e d and analyzed weekly  the v a r i o u s North American markets a f t e r which t h e weekly price  i s set.  extremely Commission  Wholesale  aggressive provides  produce buyers  i n their  are w e l l  purchasing  a market  buffer  vegetable  producers  from  wholesale  informed and  activities  and t h e  t o t h e s t r e n g t h o f these  c o r p o r a t e buyers. The  greenhouse  i n t h e Lower  Mainland-  F r a s e r V a l l e y r e g i o n and on Vancouver I s l a n d achieve s i n g l e desk  by b e i n g  members o f t h e BCVMC.  a d v e r t i s e s v a r i o u s commodities  BCVMC a l s o  selling  promotes and  which come under i t s u m b r e l l a .  a l s o o r g a n i z e s and g i v e s d i r e c t i o n s f o r t h e farmers.  It  Furthermore,  i t a c t s as a speaker t o represent them i n promoting t h e i r p r o d u c t s and  i n lobbying  t h e government.  producers a f e e f o r t h e i r s e r v i c e s .  BCVMC  i n turn  charges t h e  31  4.0  MODEL,  In  DATA,  order  regulations for  AND RESULTS  t o determine  and co-operative s t r u c t u r e  B.C. Hothouse  chapter.  the b e n e f i t s  tomatoes  value  f o r WGGCA i n 1994.  these  models  are gathered  and described  accounted Data  o f marketing  f o r WGGCA, a market  i s developed  B.C. Hothouse tomatoes  sales  and costs  model  i n this  f o r 35% of the t o t a l  which are used  and presented.  t o estimate  Finally,  estimation  procedures and r e s u l t s are provided and analyzed. The  market  Hothouse peppers tomatoes  necessary  they  from  market data  f o r B.C. Hothouse  cucumbers  and B.C.  are s i m i l a r t o the market model f o r B.C. Hothouse  i n that  competition domestic  models  both  are both local  export  oriented  and imported  and the export  market.  and have  field We  crops  have  strong in  the  gathered the  f o r the estimation o f these two products  and have  estimated the demand equations and the supply f u n c t i o n s using the same techniques  as we d i d f o r B.C. Hothouse tomatoes.  presented the demand estimation r e s u l t s  o f these  We have  two products by  market i n Appendix C and the cost-of-production estimation r e s u l t s of  these  interested  two products readers  i n Appendix D.  who want  These information are  t o know more  about  for  the demand and  supply f u n c t i o n s o f the other important products that WGGCA s e l l s .  32 4.1  Market: M o d e l f o r B . C .  In  this  section,  Hothouse  Tomatoes  a conceptual  tomato market w i l l be provided.  model  o f the B.C. Hothouse  The two major p l a y e r s i n a given  market are consumers and producers.  The demand curve describes the  consumers and the supply curve describes the producers. The demand f o r B.C. Hothouse products sub-markets: B.C.,  the market  and the market  excluding  i n B.C.,  i n United  B.C. includes  i s divided into  the market States.  the P r a i r i e  i n Canada  The market  excluding i n Canada  of Canada  which  c o n s i s t s of A l b e r t a , Saskatchewan, and Manitoba, and Eastern  Canada  which c o n s i s t s o f Ontario and Quebec. States  are Washington,  Oregon,  regions  three  The main markets i n United  California,  United States such as North-eastern  and other  regions o f  United States, and the Midwest.  These three submarkets are discussed i n d e t a i l e d .  This i s followed  by a d e t a i l e d d e s c r i p t i o n o f the aggregate demand curve. the  industry  demand  and supply  curves  Finally,  are discussed.  These  c o n s t i t u t e the market model f o r B.C. Hothouse tomatoes.  4.1.1  T h e Demand M o d e l i n B . C .  In the B.C. market, WGGCA acts l i k e a monopolistic  competitor.  M o n o p o l i s t i c competition has three main features which are apparent in  the greenhouse  differentiated  vegetable  itself  marketing campaigns.  industry  i n BC.  i n the marketplace Although  First,  WGGCA has  v i a a d v e r t i s i n g and  there are many c l o s e s u b s t i t u t e s f o r  33  greenhouse tomatoes, each p l a y e r has c o n t r o l over i t s own p r i c e . Hence, demand i s not p e r f e c t l y e l a s t i c . number o f competitors player's  actions  Second, there are a l a r g e  i n the industry; t h e r e f o r e , each  will  have  negligible  average p r i c e and t o t a l output.  effects  on the market's  In a d d i t i o n , p l a y e r s i n the market  act independently; that i s , there i s no c o l l u s i o n . free  entry i n the market because WGGCA cannot  Third, there i s  control  and export o f vegetable products i n t o and out o f B r i t i s h  4.1.1.1  monopolistic  4.1  shows  a  competition.  WGGCA faces a s l i g h t l y curve,  WGGCA  short  run e q u i l i b r i u m  Because  o f product  Columbia.  and p r i c e  exceeds average  condition  maximizes  profit  are Q  Given  this  setting  i t s marginal  In the diagram,  the r e s u l t i n g Because  price  cost, WGGCA earns p o s i t i v e economic p r o f i t s .  This  BC  and P ,  by  of  differentiation,  downward-sloping demand curve.  revenue equal t o i t s marginal cost. output  the import  Short-Run E q u i l i b r i u m Under M o n o p o l i s t i c Competition  Diagram  demand  individual  K  respectively.  i s the area represented by (P -AC) *Q . BC  BC  Diagram 4.1:  34  M o n o p o l i s t i c Competition i n the Short-Run  The t o t a l cost f u n c t i o n depends on f i x e d cost and v a r i a b l e costs.  Mathematically, i t i s w r i t t e n  as:  TC = a + bQ where a i s the f i x e d cost, b i s the p r o p o r t i o n of v a r i a b l e cost, Q i s the t o t a l quantity of B.C.  and  Hothouse tomatoes produced.  T h i s assumes that marginal cost i s equal t o average v a r i a b l e c o s t . The unit  average v a r i a b l e cost f u n c t i o n measures the v a r i a b l e costs of  output,  and  the  average f i x e d  f i x e d costs per u n i t of output.  cost  f u n c t i o n measures  per the  35 4.1.1.2  Long-Run E q u i l i b r i u m Under M o n o p o l i s t i c Competition  In the long-run e q u i l i b r i u m , ensures Thus,  the free entry or e x i t  of firms  that a l l i n d u s t r y p a r t i c i p a n t s earn zero economic p r o f i t s . in  the  sustainable  long  run,  a  private  for  economic p r o f i t s , new  the  outcome  in  corporation.  diagram  4.1  Attracted  by  firms w i l l enter the market.  is  positive  Because i t must  share the market with a greater number of competitors, the firm w i l l is,  find  that demand f o r i t s product  i t s demand curve w i l l s h i f t t o the l e f t .  firm's new  long-run demand curve.  p r o f i t maximizing.  the  firm  i s earning  price,  P^,  demand  curve  will  be  As i n Diagram 4.1, BC  zero  e x a c t l y equals i s tangent  that  shows the  the f i r m i s  where marginal  However, even as a p r o f i t maximizer,  economic p r o f i t . i t s average to  typical  reduced;  Diagram 4.2  The firm's optimal output i s Q ,  revenue equals marginal c o s t .  not  At  cost.  i t s average  s e c t i o n analyzes the s i t u a t i o n f o r WGGCA.  this  In f a c t ,  cost  curve.  output, i t s the The  firm's next  36  Diagram 4.2:  4.1.1.3  By  M o n o p o l i s t i c Competition i n the Long-Run  The S i t u a t i o n f o r BC Hothouse Tomatoes  operating  countervailing  market  as  a  single-selling  power with  BC.  desk,  l a r g e r buyers.  buyers i n the l o c a l market are Overwaitea, These three large  Growers  WGGCA  has  The three major  Safeway, and Superstore.  r e t a i l e r s buy 80% of a l l vegetable products i n  10  WGGCA prevents other firms from e n t e r i n g the market and hence s h i f t i n g the demand f o r WGGCA products t o the l e f t  10.  by c o n t r o l l i n g  D i s c u s s i o n with people i n the greenhouse vegetable i n d u s t r y .  the entry o f other firms, as shown i n Diagram 4 . 3 .  37 By c o n t r o l l i n g  supply,  revenue  marginal ability benefits  WGGCA can choose the point where marginal cost.  equals  The optimal p r i c e and quantity i s P* and Q*. The  to control  supply  i n an enforceable manner i s one of the  that the Natural Products  Marketing  (B.C.) Act provides  f o r WGGCA. Diagram 4 . 3 :  The S i t u a t i o n f o r B.C. Hothouse Tomatoes  Price  P*  Quantity  WGGCA w i l l s e l l i t s products at home and i n the export market. WGGCA w i l l less  sell  marketing  w i l l be lower  i t s products risk  i n the l o c a l market because there i s  involved.  For example,  t r a n s p o r t a t i o n cost  i n the l o c a l market, there w i l l be no exchange r a t e  risk,  and the products  transportation to  will  and storage.  be l e s s  susceptible  However, i t w i l l  other p l a c e s because WGGCA can take  favourable U.S.  export  advantage  d o l l a r i f i t s e l l s i n the U.S.  to loss  38 due t o  i t s products  of the present  market.  Also, WGGCA  can r e c e i v e premium p r i c e s f o r i t s products i n the export markets. Finally,  WGGCA can increase i t s sales  volume by s e l l i n g  in  the  other markets. Presently, we can assume that long-run p r o f i t s e x i s t f o r WGGCA because o f i t s a b i l i t y t o c o n t r o l supply. 4.3  under  quotas  area  to  globally,  (A+B).  i t s growers.  especially  from  WGGCA  This i s shown on diagram  restricts  However,  with  California,  entrance  by  increasing  Mexico,  should operate i n the long-run e q u i l i b r i u m .  allocating competition  and Holland, WGGCA  That i s , WGGCA should  produce where p r i c e equals marginal cost which equals average  cost.  This can be achieved by i n c r e a s i n g quota a l l o c a t i o n s .  4.1.2  The Demand Model i n the Rest o f Canada  WGGCA a l s o s e l l s i t s products t o other regions o f Canada. For the export market i n other regions o f Canada, we hypothesize WGGCA  acts  like  a  monopolistic  competitor  because  WGGCA can  d i f f e r e n t i a t e i t s e l f i n the marketplace by q u a l i t y d i f f e r e n c e s . t h i s study, we w i l l determine a  m o n o p o l i s t i c competitor  each market.  whether non-BC markets w i l l act  by estimating the demand  that  In like  equations i n  For the demand model i n the r e s t o f Canada, we w i l l  estimate the demand equations f o r the P r a i r i e Regions o f Canada and  39 Eastern Canada because t h i s i s how WGGCA segments i t s markets i n Canada. That i s , we w i l l determine the p r i c e e l a s t i c i t i e s these two markets.  I f WGGCA faces  then  price  the  optimal  discriminate.  Price  and  i n each o f  d i f f e r e n t demand e l a s t i c i t i e s ,  output  discrimination  strategy  is  occurs when a f i r m  to  price  s e l l s the  same good or s e r v i c e t o d i f f e r e n t buyers at d i f f e r e n t p r i c e s . a firm practices price discrimination, different  market  segments  even  customer group are the same. a l s o charge d i f f e r e n t p r i c e s of  cost  differences  p r i c i n g does not Two  discrimination identify  to  must  segments  o f demand.  segment(s).  i t s cost  Of course,  of serving  firms  hold  for a  cost.  First, that  firm  because  But cost  based  discrimination. to practice  the f i r m  differ  each  such as WGGCA may  f o r the same good or s e r v i c e  profitably.  the more  though  f a l l under the heading o f p r i c e  market  elasticity  i t sets d i f f e r e n t p r i c e s t o  such as t r a n s p o r t a t i o n  conditions  When  with  must  be  respect  price  able to  to  price  The f i r m p r o f i t s by charging a higher p r i c e  inelastic  (i.e.,  less  Second, i t must be p o s s i b l e  p r i c e s p a i d by d i f f e r e n t segments.  price-sensitive)  market  t o enforce the d i f f e r e n t  This means that market segments  r e c e i v i n g higher p r i c e s must be unable t o take advantage o f lower prices.  That  i s , a low-price buyer must be unable t o r e s e l l the  good or s e r v i c e p r o f i t a b l y t o a high-price If  WGGCA  practising different  i s practising  price  buyer.  discrimination,  3rd degree p r i c e d i s c r i m i n a t i o n . types  o f markets  i n one c i t y  i t might be  WGGCA cannot  but they  segment  can d i s t i n g u i s h  40 WGGCA i s able t o p r a c t i c e some form of 3rd  between c i t i e s / r e g i o n s . degree  price  relatively and  discrimination  high  between  markets  t r a n s a c t i o n s costs based  perishability  of  the product.  because  of the  on t r a n s p o r t a t i o n One  of  the  costs  fundamental  hypothesis o f our model i s that they do p r i c e d i s c r i m i n a t e and set quantity  i n each  marginal  cost).  where  demand  revenue.  market Price  t o e q u a l i z e marginal  i s based  i s perfectly  on the demand curve.  elastic,  then  price  Where demand i s downward sloping,  than marginal  revenue.  After  revenue  (equal t o In markets  equals  then p r i c e  marginal  i s greater  the p r e s e n t a t i o n of the r e g r e s s i o n  r e s u l t s i n s e c t i o n s 2.4.1 and 2.4.8, a more d e t a i l e d explanation of WGGCA's a b i l i t y t o p r i c e d i s c r i m i n a t e i s discussed.  4.1.3  T h e Demand M o d e l i n U n i t e d  States  When determining the demand equations i n the U.S., we have t o take exchange r a t e s i n t o account.  The consumers i n the s t a t e s w i l l  base t h e i r buying d e c i s i o n s from what they observe the other products at the grocery s t o r e s . observe will  Therefore, between  we must  i n U.S.  account  Canada and United  l a s t two decades. B.C.  One f a c t o r that they can  i n the grocery stores i s the p r i c e  see the p r i c e s  dollars,  f o r exchange  of the product.  not Canadian rates.  States have been very  When the Canadian  as compared t o  They  dollars.  Exchange volatile  rates in  the  d o l l a r depreciates, export o f  Hothouse products t o the US i s favourable, and v i c e v e r s a .  We  will  California, and  the  and  other regions of USA  Midwest)  equations, these  estimate the demand equations  we  separately.  will  markets  to  From  determine  determine  the  41 f o r Washington, Oregon,  (North-eastern the  estimates  price  United of  elasticities  whether WGGCA p r i c e  States  the in  demand each  of  discriminates i n  these markets.  4.1.4  Aggregate Demand f o r B.C.  From  the  three  demand  determine the aggregate on  the  marginal  Hothouse Tomatoes  curves  each  sub-market,  demand f o r BC Hothouse tomatoes.  decision  relations  s i m p l i f i e d the model to two markets: The  in  by  the  we To  Canada  Aggregate Demand f o r B.C.  diagram  Hothouse Tomatoes  Quantity United States  we  Canada and the United States.  4.3.  Quantity  focus  co-operative,  r e s u l t s can be g e n e r a l i z e d i n t o the model as shown on  Diagram 4.4:  can  Ouanlliy >^jgregate  4.1.5  42  The Supply Model f o r B.C. Hothouse Tomatoes  A f t e r d i s c u s s i n g the demand side of the market model, we now turn our a t t e n t i o n t o the supply s i d e . 45  growers-members  with  (greenhouse tomatoes, WGGCA.  51  greenhouses  cucumbers,  There are approximately  that  ship  t h e i r products  peppers and b u t t e r  lettuces)  These growers vary i n s i z e from an acre t o 37 acres.  11  of them are two t o three acres i n s i z e . are more e f f i c i e n t study  will  at  Competing  the  Brad  Stennes  Farm-Level  Areas,"  he  cost-of-production  on  "Fresh  for British  concluded that  f o r B.C.  greenhouse  From a  Vegetable Costs  Columbia  there  Most  some growers  than others due t o economies of s c a l e .  conducted by  Returns  As a r e s u l t ,  tomatoes,  and  Greenhouses  is a  9% B.C.  to  and  decrease i n greenhouse  cucumber, and B.C. greenhouse peppers by moving from a 8, 000 m t o a 2  25,000 m  2  acres,  operation,  respectively.  i n acreage terms, i t i s 1.976  acres and  6.175  Hence, the supply curve f o r a r e p r e s e n t a t i v e  BC greenhouse vegetable i s stepwise i n manner with the b i g growers producing at low c o s t s and the small producers producing costs.  This  is  shown  in  diagram  4.4.  For  B.C.  at high  greenhouse  tomatoes, 70% of the products are produced by large growers and 30% are produced by small growers.  11.  McMillan, Murray. "Splendor under G l a s s . " Sun. 28 Jun. 1995: CI and C2.  The Vancouver  Diagram 4.5:  Aggregate Supply o f B.C. Hothouse  Tomatoes  43  Price  High Cost (30%)  • Low Cost (70%)  Quantity  4.1.6  The P r i n c i p l e  The p r i n c i p l e members. costs.  Profit  o b j e c t i v e of WGGCA i s t o maximize p r o f i t  parts  section.  for i t s  i s the d i f f e r e n c e between t o t a l revenues and t o t a l  WGGCA s e l l s i t s products t o seven d i f f e r e n t  simplicity, other  Objective o f WGGCA  we presented  the d i s c u s s i o n  of Canada  excluding  The p r o f i t  function  expressed as f o l l o w s :  f o r three  B.C. and United  markets. F o r markets  States)  f o r B.C. Hothouse  (B.C., i n this  tomatoes i s  44 4.1  Max  n  =  P(Q )Q BC  + P(QROC)QROC +  BC  P(QVS)QUS-C(Q +QROC+QUS) BC  where: P (Q^)  i s the p r i c e that WGGCA receives f o r the product i n BC, (assumes that demand curve i s downward sloping) P (Q ) i s the p r i c e that WGGCA receives f o r the product i n Canada excluding BC, (assumes that the demand curve i s downward s l o p i n g ) , P (Q ) i s the p r i c e that WGGCA receives f o r the product i n the US, (assumes that the demand curve i s downward s l o p i n g ) , Q i s the amount o f product s o l d i n BC, Q i s amount o f product s o l d i n Canada excluding BC, Q i s the amount o f product s o l d i n the United States, and C (Q +Q +Q ) i s the t o t a l costs o f producing the product. R0C  us  BC  R0C  DS  1  2  3  Here, we assumed that p r i c e i n the B.C. market i s dependent on the quantity  s o l d because WGGCA has some market power i n the domestic  market through aggressive the  importing  because  markets  WGGCA  a d v e r t i s i n g and marketing.  are a l s o  dependent  can d i f f e r e n t i a t e i t s e l f  The p r i c e s i n  on the quantity  sold  i n the marketplace  by  quality differences. To maximize p r o f i t , order dn  necessary = 0,  dn  we must simultaneously condition  dn  1  = 0, and  equation 4.1 with respect  ^  = 0.  a  Accordingly,  t o Q , Q , and Q BC  d e r i v a t i v e equal t o zero.  R0C  us  we  differentiate  and set the r e s u l t i n g  The r e s u l t i s :  +  UROC  V-R0c  Q  ^ - . P  SQus  °±IROC  A  (  Q  U  S  )  im*d» ^. . Qm  +  Qus  d  §Qvs  0  first-  maximum:  . / ^ ) ^SK>'a« " j £ - - 0 , and  4.3: 4.4:  for  s a t i s f y the  We know that MC  BC  i s equal t o MC  the cost o f producing an extra unit all  markets.  This  i s so because  greenhouse vegetable producers  i s equal t o MC  R0C  of output  i s the same across  a l l products  i n British  US  45 because  are produced by-  Columbia.  Although no  i n d i v i d u a l grower's cost f u n c t i o n i s the same due t o the amount o f resources such as c a p i t a l , production, individual  labour, and management  the i n d u s t r y ' s  cost  function  grower's c o s t - o f - p r o d u c t i o n .  skills  put i n t o  i s the sum o f  each  Hence, the marginal cost  f u n c t i o n s are the same across a l l markets.  4.1.7  The Market Model f o r B.C. Hothouse Tomatoes  The market model which i s shown on Diagram 4.5 c o n s i s t s o f the aggregate  demand  curve  Hothouse tomatoes. markets.  and the aggregate  For s i m p l i c i t y ,  supply  curve  for  B.C.  we show the s i t u a t i o n  f o r two  A more d e t a i l e d diagram w i l l have seven markets.  This i s  not shown here f o r reason o f s i m p l i c i t y but we have c a l i b r a t e d the model  using  t h e demand  f u n c t i o n s that  we have  d e r i v e d i n each  the co-operative  i s step-wise i n  market l e s s t r a n s p o r t a t i o n costs. The nature  supply  with  curve  the large  facing  producers  producing  small producers producing at high costs. positive economic  economic rents.  rents  while  and  The large producers  the small  The co-operative must  at low costs  producers  earn  receive a price  the earn zero  that i s  equal t o the c o s t - o f - p r o d u c t i o n f o r the small growers i n order f o r everyone  t o ship t h e i r  products  t o the co-operative.  Hence, we  46 a p p l i e d the higher c o s t - o f - p r o d u c t i o n as the marginal costs f o r a l l markets.  We, a l s o , assumed that the marginal cost i s equal t o the  competitive p r i c e i n each market. Diagram 4.6:  Market Model f o r B.C.  Hothouse Tomatoes  Price  \ V  Pus-  \ \  Pc-MC \Z\DcAN DcoopCAN  MRus  MRTO  MRCAN  QCAN*  QC  Quantity  Quantity  A Representative Market in Canada (a)  The  Qc Quantity  A Representative Market in United States (b)  single  desk  selling  Aggregate Market  provision  prevents  firms i n t o the B.C. market f o r B.C. products only. restrict  the amount  discriminate).  of product  sold  marginal  overall.  o f other  Thus, WGGCA can  i n the BC market  This could take place without quotas because  markets are the marginal markets. the  entry  market  I f we  because  assume  that  The e f f e c t  quotas WGGCA  cause  o f the quotas WGGCA  optimally  to s e l l  sells  (price other i s on less  i n markets  according t o the highest return, then they s e l l l e s s i n the lowest p r i c e market.  Quotas thus p o s s i b l y  r a i s e the average  price  raise  the marginal p r i c e and  received by growers.  This i s one o f the  p o s s i b l e b e n e f i t s o f the Natural Products Marketing the B.C.  (B.C.) Act and  Vegetable Scheme f o r WGGCA.  The growers want t o expand production i n order t o lower cost-of-production. general because  this  This  would  would  shift  affect  the whole  the supply  curve  their  industry i n where the  low  47 This i s shown i n Diagram  cost region becomes longer, from S t o S . x  2  4.6. Diagram 4.7:  Result from Increasing Production i n the Industry  Price  High Cost (30%)  Low Cost (70%)  ST  S  2  Quantity  Other p o s s i b l e b e n e f i t s of the Natural Products Marketing (BC) Act  and the B.C. Vegetable  Scheme  development, research, and promotion. the  producers  a per-unit  levy.  f o r WGGCA  are  industry  This i s achieved by charging  For example,  WGGCA charges the  producers a p e r - u n i t levy on the products shipped.  As mentioned i n  s e c t i o n 2 o f chapter 3, WGGCA c o l l e c t s l e v i e s from the growers and pays i t t o BCVMC.  Under the Natural Products Marketing  (B.C.)  Act  and the B.C. Vegetable Scheme, the growers must pay l e v i e s t o BCVMC f o r i n d u s t r y development, research, and promotion.  The reason f o r  this  i s that  services.  every  member  i n the i n d u s t r y  benefits  by  48 such  When mandatory l e v i e s are i n place, nonmembers cannot be  excluded;  thereby,  eliminating  free r i d i n g  o f p u b l i c good by non-  participates. By  operating as a co-operative, the growers r e c e i v e a pooled  p r i c e f o r t h e i r products shipped t o WGGCA. the growers r e c e i v e i s based upon t h e i r grade,  and amount.  The pooled p r i c e  own production:  The pooled p r i c e i s the average  that  quality,  p r i c e between  domestic p r i c e and export p r i c e s . Now, we go back diagram Q  EXP  4.5, Q  BC  t o our market  model  on diagram  sold  On  represents the quantity s o l d i n the BC market and  represents the quantity s o l d i n the export market.  total  4.5.  Hence, the  q u a n t i t y s o l d by the co-operative i s equal t o the q u a n t i t y i n the B.C. market  plus  the quantity  sold  i n the export  market.  The t o t a l marginal revenue curve i s d e r i v e d by adding the  marginal  revenue curve  i n B.C. and the marginal  revenue curve i n  the export markets. We estimate the demand and supply equations with the data that we have gathered and simulate the demand and supply equations the  base  determine Our  scenario  t o the c o u n t e r f a c t u a l scenario  the b e n e f i t s o f marketing  base  scenario  counterfactual  is  the  from  i n order t o  r e g u l a t i o n s f o r the producers.  monopolist  situation  scenario i s the competitive s i t u a t i o n .  and our By knowing  the estimates o f the demand and supply equations, we can determine the producer surplus, the consumer surplus and the dead-weight l o s s in  the base  case  and the a l t e r n a t i v e  case.  From  this,  we can  49  determine surplus  the change i n producer 1  surplus,  the change i n consumer  and the e f f e c t that marketing r e g u l a t i o n s  s t r u c t u r e have on s o c i e t y .  and  co-operative  50 Estimation  4.2  o f t h e Demand  Demand E s t i m a t i o n  4.2.1  A description  Model  Procedure  f o r B.C.  Hothouse  of the estimation procedures  Tomatoes  used t o determine  the demand f o r B.C. Hothouse tomatoes w i l l be discussed here. WGGCA s e l l s has c l a s s i f i e d Prairie  i t s sales  regions  California,  i t s products i n Canada and United States. i n t o geographic  o f Canada,  Eastern  regions such  Canada,  WGGCA  as BC,  Washington,  the  Oregon,  and other p a r t s of United States (North-eastern United  States and the Midwest).  We estimate the demand equations base on  these geographic regions. The demand f o r BC Hothouse tomatoes i n BC depends on i t s own price, trend.  the p r i c e  of substitutes  or complements,  income,  and time  In symbols, t h i s i s expressed as: PCQTBC = f(RPTBC, RPVBC, RINCBC, TIME)  where: PCQTBC = p e r - c a p i t a consumption (cases/capita/month) o f BC Hothouse tomatoes i n BC, RPTBC = r e a l p r i c e o f BC Hothouse tomatoes ($/case) at the wholesale l e v e l , RPVBC = r e a l p r i c e index o f f r e s h vegetables i n BC at the r e t a i l level, RINCBC = r e a l income i n BC ( m i l l i o n $/month), and TIME = annual time trend, 1 9 8 8 = 1 , 1 9 9 4 = 7 . The demand f o r BC Hothouse tomatoes outside o f B.C. depends on its  own p r i c e ,  the p r i c e o f i t s s u b s t i t u t e s or complements  i n the  importing region, income i n the importing region, and time t r e n d . I f the product i s exported outside o f Canada, exchange rates must be taken i n t o account.  Mathematically, markets are expressed  Equation 4.2.1:  the  demand f o r BC  Hothouse tomatoes i n  51 these  as follows,  BC Hothouse Tomato Demand i n Canada  PCQT = P, + p RPT„ + P RPV + P RPCY + P 7, + u, it  where: PCQTit  2  3  it  4  tl  5  p e r - c a p i t a consumption (cases/capita/month) of BC Hothouse tomatoes i n region i , r e a l p r i c e of BC Hothouse tomatoes (Canadian $/case) at the wholesale l e v e l i n region i , r e a l p r i c e index of f r e s h vegetables i n region i where (1986=100) at the r e t a i l l e v e l , r e a l p e r - c a p i t a wages and s a l a r i e s i n region i ( m i l l i o n $/month), and annual time trend, 1 9 8 8 = 1 , 1 9 9 4 = 7 , 3 : 1 denoting BC, 2 denoting the P r a i r i e regions of Canada, and 3 denoting Eastern Canada.  RPT  it  RPV  it  RPCY  it  i  Equation 4.2.2:  BC Hothouse Tomato Demand i n Various Regions of United States (Washington, Oregon, California)  PCQTj, = f3, + PzRPTj, + $ RPVWEST + PiRPCYj, + $ T, + u, 3  where: PCQT. t  RPT  jt  RPFVWEST  t  RPCY.,  j  PCQTOTH, t  RPTOTH  t  RPFVOTH  t  RINCOTH  5  p e r - c a p i t a consumption (cases/capita/month) of BC Hothouse tomatoes i n region j , r e a l p r i c e of BC Hothouse tomatoes (US$/case) at the wholesale l e v e l i n region j , r e a l p r i c e index of f r e s h f r u i t and vegetables i n Western United States at the r e t a i l l e v e l , r e a l p e r - c a p i t a personal income i n region j ( M i l l i o n US$/month), and annual time trend, 1 9 8 8 = 1 , 1 9 9 4 = 7 , 3 : 1 denoting Washington, 2 denoting Oregon, and 3 denoting C a l i f o r n i a .  Equation 4.2.3:  where PCQTOTH  t  BC Hothouse Tomato Demand i n Other Parts of United States (North-eastern U.S.A. and the Midwest) = Pi + fi RPTOTH + $ RPFVOTH, + $ RPCYOTH 2  t  3  4  t  + $ T + u, 5  t  - p e r - c a p i t a consumption (cases/capita/month) of BC Hothouse tomatoes i n other p a r t s of United States, - r e a l p r i c e of BC Hothouse tomatoes (US$/case) at the wholesale l e v e l i n other p a r t s of United States, - r e a l p r i c e index of f r e s h f r u i t s and vegetables i n other p a r t s of United States at the r e t a i l l e v e l , - r e a l p e r - c a p i t a personal income i n other p a r t s of United States ( M i l l i o n US$/month), and - annual time trend, 1 9 8 8 = 1 , 1 9 9 4 = 7 .  52  It  i s theoretically  consistent  to  use  quantity-dependent  demand models but such models ignore p o t e n t i a l simultaneity, is,  p r i c e a f f e c t s quantity  affects  quantity  and quantity  and quantity  affects price.  a f f e c t s p r i c e , there  that  If price  i s a feedback  e f f e c t , which means that the two v a r i a b l e s are j o i n t l y  determined.  I f s i m u l t a n e i t y i s ignored and ordinary l e a s t squares applied, the estimates  w i l l be b i a s e d and i n c o n s i s t e n t .  w i l l be b i a s e d and i n c o n s i s t e n t .  Consequently, f o r e c a s t s  In a d d i t i o n , t e s t s of hypothesis  w i l l no longer be v a l i d . The diagram  consequences of i g n o r i n g simultaneity 4.6.  On diagram  four demand curves. w i l l obtain a l i n e curve  4.6, we observe  I f we estimate j o i n i n g supply  four  are i l l u s t r a t e d on supply  curves and  the demand curve using OLS, we  and demand i n each p e r i o d .  (E) i s n e i t h e r a demand curve nor a supply  curve.  This  It i s a  curve that j o i n s the e q u i l i b r i u m points f o r supply and demand.  53 D i a g r a m 4.8:  The  Consequences  of  Ignoring  Simultaneity  Price  /  X  ^ ^ X  D  4 Quantity  In order to estimate a proper exists,  we  demand curve when s i m u l t a n e i t y  need t o use two-stage l e a s t  squares,  type of i n s t r u m e n t a l - v a r i a b l e estimator. least  one  demand  variable  equation.  sunlight.  The  12  Lower Mainland months.  The  I n t e r v i e w s  that The  shifts  best  monthly data  the  To use  supply  variable for solar  a f r e q u e n t l y used  to  2SLS,  equation  use  is  radiation  we  need at  but  solar  not  the  radiation  sunlight  i n the  region i s quadratic, with a peak during the summer supply  w i t h  curve  e x p e r t s  in  the  f o r greenhouse vegetables  i n d u s t r y .  i n the  Lower  Mainland  f u n c t i o n f o r B.C. PCQT where: PCQT  greenhouse tomatoes i s expressed as f o l l o w s : = a + a ftPf, + a L + a L , + a ^DM + a DL + v, 2  U  0  2  t  3  t  5  t  - p e r - c a p i t a supply (cases/capita/month) of BC Hothouse tomatoes at time t i n region i , - p r i c e r e c e i v e d ($/case) of BC Hothouse tomatoes at time t i n region i , -the amount o f s o l a r r a d i a t i o n sunlight at time t , measured i n megajoules per 6-7 week period, -dummy v a r i a b l e denoting mid-season, 1 i f i t i s A p r i l , May, June, July, August, and September, and -dummy v a r i a b l e denoting late-season, 1 i f i t i s October and November.  lt  RPT  it  L  54 Therefore, the supply  f o l l o w s t h i s p a t t e r n very c l o s e l y .  t  DM  t  DL  t  The supply  dummy  but  variables  not  demand  are the other because  these  variables variables  a v a i l a b i l i t y o f greenhouse products very c l o s e l y .  that  affects  f o l l o w the  We segmented the  production i n t o three periods because there are not much greenhouse vegetable s u p p l i e d t o the market at the beginning of the season. Supply  i n w e l l under way i n A p r i l  Then,  i t starts  t o slow  down  and peaks i n July  i n September.  By  and August. October  and  November, the supply o f greenhouse vegetables s t a r t s t o taper o f f . The  reason  that  production  starts  t o taper  o f f i n October and  November i s because there i s l e s s s o l a r r a d i a t i o n the  winter  important it  months.  sunlight  f a c t o r s a f f e c t i n g production.  i s not p r o f i t a b l e  greenhouse November  Solar r a d i a t i o n  vegetable  and/or  t o produce growers  December.  during  start  a  sunlight  i s one of the most  It affects yield; the winter new  avoid the dummy v a r i a b l e t r a p .  months.  production  We d i d not use a dummy  denote the beginning o f the season  during  hence, The  cycle i n  variable to  (February and March) i n order t o  Normally, but  we  we  d i d not  included  in  would use  use  the  i t here.  model  promotional program. exposure  advertising An  because  there  is  The brand name "BC  commercials.  promotional  events.  The  On  top  activities  advertising  demand f u n c t i o n was  variable  an  extensive  on-going regular  t r a n s i t advertisements, regular  exposures,  point-of-purchases  variable  i s usually  Hothouse" receives  of these  at  55 i n the model  variable  advertising  i n newspaper advertisements,  television are  an  that  we  the a c t u a l accumulated  used  and  to  there special  estimate  advertising  f o r the year f o r a l l BC Hothouse products.  and  the  expenditures  The data that  we  have  measures a d v e r t i s i n g expenditures f o r a l l BC Hothouse products f o r all  markets.  cannot  be  These  data  segmented  on  cannot a  be  segmented  monthly  expenditures are p a i d immediately  basis  by  market  because  and i t  advertising  but the advertisements  are  still  advertising.  The  running a f t e r they have been p a i d . Furthermore,  i t is difficult  to  quantify  type of media employed, such as t e l e v i s i o n , newspaper, or p o i n t - o f purchase  has  expenditures different access least  bearing because  groups  to  on  these  of people.  sufficient  dollars  effectiveness sources  as  Usually, a  of  of  the  media  However, the  information on  squares regression.  expenditure  the  these  advertising  exposure  reach  researcher r a r e l y variables  to  has  attempt  data l i m i t a t i o n d i c t a t e s using  measure,  but  this  is  only  an  responses  to  approximation. Furthermore, advertising.  different  For  example,  people a  have  different  particular  person  may  respond  56 t o r e p e t i t i o n of the same stimulus depending on other  differently  f a c t o r s which are too complex t o model.  Hence, i t i s d i f f i c u l t t o  measure  these  the  psychological  effect  of  exposures  on  the  consumers. Also, a d v e r t i s i n g expenditures that i t gets from elsewhere.  do not include other  publicity  For example, there was an a r t i c l e i n  the Vancouver Sun on June 28, 1995 on the front page of the food section.  The a r t i c l e presented  a living  lettuce,  a woman with a  basket o f greenhouse vegetables, a d e s c r i p t i o n of the industry, and recipes the  using BC Hothouse products.  reader  a positive  feeling  This type  of exposures  gives  about the industry and i t promotes  them t o buy BC Hothouse products. Another f a c t o r that the r e a l a d v e r t i s i n g expenditure capture i s the Buy BC Program. the  provincial  government  n a t u r a l products ends i n 1997. of BC food, the  BC  fish, food  i n an  attempt  t o increase  s a l e s of  This program was implemented i n 1993 and  beverages chain,  and a g r i c u l t u r a l including:  products  producers,  throughout processors,  food s e r v i c e operators, r e t a i l e r s and consumers (Buy  Partnership  advertise  The Buy BC Program i s sponsored by  The purpose of t h i s program i s t o increase the use  entire  distributors,  i n BC.  does not  Manual,  the products  1994). that  The BCVMC uses comes  under  this  funding t o  i t s umbrella  and  BC  Hothouse items are among them. We package.  have  estimated  the model  using  SHAZAM,  a  statistical  57 4.2.2  Demand E s t i m a t i o n Data f o r B.C.  For  the  demand  observations  from  observations  are  year. the  side of  1988  to  monthly  the  1994 data  Hothouse Tomatoes  model,  f o r BC from  we  have  February  e s t i m a t i o n of the demand equations,  include  periods  promotional receives  when  purposes  negative  the product.  BC and  Hothouse we  t o November  prices  for  we  gives  These each  i t s products.  For  i n c l u d e d data  away  we  f o r the d i d not  i t s products  include periods  i t s products.  of  of  In p a r t i c u l a r ,  d i d not  years  Hothouse tomatoes.  This i s the p e r i o d i n which WGGCA s e l l s  months when WGGCA s e l l s  seven  These  for  when WGGCA are  few  in  number. The they  data  are  are gathered  gathered  statistical  from  from  WGGCA's  p u b l i c a t i o n s of  Populations Estimates  and  Consumer  Current  Business.  v a r i a b l e s used how  the  13  Price  US and  Index  Appendix A  sources.  Manager's  the  Reports: You,  different  such  For  Report, as  example,  CANSIM,  Current  and  Population  P r o j e c t i o n s , P25-1106, Census  D e t a i l e d Report,  contains a l i s t i n g  and of  Survey  of  some of  the  and Appendix B provides a d e t a i l e d explanation of  variables  are  generated  from  the  data  that  we  have  gathered.  The be  d a t a for l i s t e d .  some  of  the  v a r i a b l e s  is  c o n f i d e n t i a l ;  t h e r e f o r e ,  t h e y  cannot  58  4.2.3  A D i s c u s s i o n o f the Demand V a r i a b l e s  A priori,  the standard assumptions based  on economic theory-  s t a t e that the c o e f f i c i e n t f o r : 1.  Own P r i c e i s negative. B.C. Hothouse tomatoes are considered ordinary goods. That i s , when the p r i c e o f BC Hothouse tomatoes increase, the quantity o f BC Hothouse tomatoes consumed decrease.  2.  Consumer P r i c e Index of Fresh Vegetables or Fresh F r u i t s and Vegetables can be p o s i t i v e or negative depending on how the product i s used. BC Hothouse tomatoes can be eaten with other vegetables such as salads or they can be served with other food products such as meat and seafood. I f i t i s consumed with other vegetables, i t i s considered a complement. In t h i s case, the consumer p r i c e index o f f r e s h vegetables i s p o s i t i v e . I f the consumers r e p l a c e BC Hothouse tomatoes i n t h e i r cooking with other vegetables such as f i e l d tomatoes or imported tomatoes, they are considered s u b s t i t u t e s . In t h i s case, the sign o f the c o e f f i c i e n t i s negative.  3.  Real income i s p o s i t i v e . BC Hothouse products are normal goods. As income increases, demand f o r the product i n c r e a s e s . I f the income e l a s t i c i t y i s greater than 1, i t i s a luxury good; otherwise, i t i s a n e c e s s i t y . The own p r i c e e l a s t i c i t y i s important because i t r e f l e c t s the  w i l l i n g n e s s t o pay f o r the product.  BC Hothouse tomatoes can cost  two  or imported  to five  times  more  than  field  r e t a i l l e v e l i n B r i t i s h Columbia.  tomatoes  at  the  This i s not always t r u e because  i t depends on the strategy of WGGCA.  The reason that consumers are  w i l l i n g t o pay more f o r BC Hothouse products i s because WGGCA has differentiated  itself  i n the marketplace  by doing  promotional  activities. We i n c l u d e d the consumer  price  index  of f r e s h  vegetables or  f r e s h f r u i t s and vegetables i n our model as a proxy f o r s u b s t i t u t e s and complements.  The consumer p r i c e  index o f f r e s h vegetables or  59  f r e s h f r u i t s and vegetables w i l l not a f f e c t our dependent v a r i a b l e because B.C. Hothouse tomatoes i s a small component vegetables or f r e s h f r u i t s  and vegetables i n each market.  i t w i l l not cause any b i a s i n our r e s u l t s . the  consumer  vegetables  price in  index  our  fresh.  or they  can be eaten  vegetable seafood  available not  meat  regional  with  such as  other as  BC  food.  field  complements  f o r a l l geographic  available  Hence,  or f r e s h  Hothouse  fruits  and  products  are  They can be eaten with other vegetables i n salads  products  and  i s because  fresh  The reason that we used  of f r e s h vegetables  model  consumed  of t o t a l  have considered  tomatoes  but  these  as data  are very  Some data expensive  other  s u b s t i t u t e s and are  area under i n v e s t i g a t i o n  on a monthly b a s i s .  l e v e l but they  We  either  not  or they are  are a v a i l a b l e  to o b t a i n .  on a  Hence,  we  have decided t o use the consumer p r i c e index of f r e s h vegetables t o keep our a n a l y s i s c o n s i s t e n t . An  income  variable  i s included  i n the  model  to  test  the  hypothesis that increases i n income r e s u l t i n higher consumption of BC  Hothouse  tomatoes.  For  Canada,  no  data  were  d i s p o s a b l e income on a monthly or q u a r t e r l y b a s i s . used the raw wages and s a l a r i e s as a proxy  available Therefore,  for we  f o r disposable income.  For United States, no data were a v a i l a b l e f o r disposable income on a monthly or quarterly, b a s i s , e i t h e r .  The c l o s e s t s u b s t i t u t e that  we found f o r the income v a r i a b l e i n United States i s q u a r t e r l y data f o r t o t a l p e r s o n a l income. data by using l i n e a r  We  generated  interpolation.  these  data  i n t o monthly  Finally, any  pattern  we  60 an annual time trend v a r i a b l e to capture  included  of change i n consumption which i s not  other independent v a r i a b l e s  included  i n the  explained  model.  An  such v a r i a b l e i s the a d v e r t i s i n g expenditure that we  by  the  example  of  have mentioned  earlier.  4.2.4  Demand E s t i m a t i o n R e s u l t  We squares  have  estimated  (OLS)  BC  a l l the  variable  equations  technique  (IV)."  t r i e d the  present the  know  that  estimating and  equilibrium  and  As  least the  economic theory  most  appropriate.  l o g - l o g form.  We  have  4.9.  2SLS r e s u l t s f o r comparison purposes. is  a  common  is  determined  problem  because by  mentioned i n s e c t i o n  need to use  the  to  ordinary  (2SLS), a l s o known as  the  demand functions  e x i s t s , OLS  Therefore, we w i l l use  and  quantity  demand.  simultaneity  OLS  simultaneity  supply  supply and  We  using  A priori,  l i n e a r form and  presented the r e s u l t s i n Tables 4.3  We  Tomatoes  i n d i c a t e which f u n c t i o n a l form i s the  Therefore, we  We  Hothouse  and two-stage l e a s t squares  instrumental does not  for  the  when  we  equilibrium  are price  intersection  of  2 of t h i s chapter, i f  estimates w i l l be biased  and  inconsistent.  2SLS to estimate proper demand  r e s u l t s from 2SLS to estimate our  functions.  simulation  model  i n Chapter 5.  For  the  Hothouse  i n t e r e s t e d cucumbers  r e a d e r , and  B.C.  see  A p p e n d i x  Hothouse  C  for  p e p p e r s .  the  e s t i m a t i o n  r e s u l t  of  B.C.  We  test  correlation  for  serial  i s normally  correlation  a problem with time  the Durbin-Watson t e s t t o t e s t estimating  the  Multiplier  test  equations to  test  e s t i m a t i n g the equations  first  for serial  using  OLS  using 2SLS.  series  data.  we  use  the  correlation  0  Lagrange  when  we  are  For the Durbin-Watson t e s t ,  the n u l l hypothesis i s there i s no ( f i r s t - o r d e r ) s e r i a l (H :  We use  c o r r e l a t i o n when we are  and  for serial  61 serial  because  correlation  p=0) and the a l t e r n a t i v e hypothesis i s there i s ( f i r s t - o r d e r )  serial  correlation  (E1:  p>0) .  The Durbin-Waston  s t a t i s t i c s are  presented i n Table 4.1. The d e c i s i o n r u l e s are as follows: 1) 2) 3) 4) 5) From  N u l l hypothesis No p o s i t i v e a u t o c o r r e l a t i o n No p o s i t i v e a u t o c o r r e l a t i o n No negative c o r r e l a t i o n No negative c o r r e l a t i o n No a u t o c o r r e l a t i o n + or the Durbin-Watson  correlation  test,  Decision Reject No d e c i s i o n Reject No d e c i s i o n Do not r e j e c t we  found  i n many of the equations.  present, OLS estimates are s t i l l are no longer e f f i c i e n t . method t o c o r r e c t  that  If 0 < d < d dh <. d <. 4-d < d < 4 <, d £ d o^ < d < 4-d„. L  L  L  there  If serial  were  correlation i s  unbiased and consistent  Therefore, we used the  serial  but there  Cochrane-Orchutt  f o r s e r i a l c o r r e l a t i o n i f they are present.  r e s u l t s are presented i n Tables 4.3 to 4.9.  The  62 Table 4.1: Durbin-Watson S t a t i s t i c s f o r Demand Equations Using OLS TOMATOES BY MARKET LINEAR LOG-LOG BC 0.7623 1.6227 PRAI 1.5037 1.7176 EAST 0.7885 1.4772 WASH 1.4256 1.0770 ORE 1.7295* 1.1618 CAL 1.1419 0.9120 OTHER 0.4660 1.2077 * This i m p l i e s that there i s no s e r i a l c o r r e l a t i o n . We  use the modified  serial correlation  Lagrange  using 2SLS . 15  Multiplier  test  to test f o r  The steps are as f o l l o w s :  Estimate the model Y = f3X + u, by 2SLS and save the r e s i d u a l s  1.  t  t  t  A, • 2.  Regress X by Z , the v a r i a b l e s i n the reduced form that serve as instruments, and obtain the f i t t e d values X . Regress p, against X and ji,,! and compute (T-p)R . Serial t  t  t  3.  2  t  c o r r e l a t i o n of order p can be t e s t e d with t h i s using the % d i s t r i b u t i o n with p degrees of freedom. The n u l l hypothesis i s there i s no ( f i r s t - o r d e r ) (H : 0  p=0) and the a l t e r n a t i v e  serial  correlation  presented  i n Table  distribution right  t  4.2.  If  with p degrees  hypothesis.  The  (T-p)R  2  LM >  %  test 2 P  statistics  i n the chi-square  the n u l l hypothesis  The c r i t i c a l  chi-square  i n favor o f the statistic  f o r '£  (0.05) i s equal t o 3.84146.  Ramanathan, E d i t i o n • P u b l i s h e r s ,  Ramu.  U . S . A . : 1992.  I n t r o d u c t o r y The  Dryden  are  of freedom such that the area t o t h e  o f i t i s 0.05, r e j e c t  alternative  correlation  hypothesis i s there i s ( f i r s t - o r d e r )  p*=0) .  (H :  serial  2  Economics  P r e s s ,  w i t h  H a r c o u r t  A p p l i c a t i o n s . B r a c e  Semnri  J o v a n o v i c h  C o l l e g e  1  63 T a b l e 4.2: L a g r a n g e M u l t i p l i e r T e s t S t a t i s t i c s f o r 2SLS TOMATOES BY MARKET LINEAR LOG-LOG BC 25.936060 12.540590 PRAI 12.215330 8.078707 EAST 24.289710 6.602445 WASH 9.711484 23.516540 ORE 3.471468* 12.904494 CAL 18.324890 20.971480 OTHER 10.663440 14.036780 T h i s i m p l i e s t h a t t h e r e i s no ( f i r s t - o r d e r ) s e r i a l c o r r e l a t i o n . From T a b l e these  4.2, we know t h a t s e r i a l  equations  functional  except  form.  correlation  f o r t o m a t o demand i n Oregon f o r t h e l i n e a r  Although  there i s f i r s t  order s e r i a l  i n these equations, t h e estimates are s t i l l b u t t h e y a r e no l o n g e r e f f i c i e n t .  correct f o rserial  correlation  u n b i a s e d and c o n s i s t e n t  T h e r e f o r e , we have t o be c a r e f u l  when we a r e d o i n g h y p o t h e s i s t e s t i n g not  i s a problem w i t h  correlation  on t h e s e  equations.  because c o r r e c t i n g  We  will  fori t will  n o t i m p r o v e o u r e s t i m a t e s b y much g i v e n t h e s m a l l sample s i z e . Next,  we  use t h e T-test  to test  the significance  of the  regression coefficients. Ho-  P = Po  Hi'.  P*Po  The r e s u l t s a r e p r e s e n t e d i n T a b l e s 4.3 t o 4.9, as w e l l .  4.2.4.1  B r i t i s h Columbia  The  results  are presented estimates results  f o r demand e s t i m a t i o n o f B.C. H o t h o u s e t o m a t o e s  i n Table  4.3.  From T a b l e  4.3, we o b s e r v e  u s i n g OLS a n d 2SLS a r e d i f f e r e n t .  f o r 2SLS  from  here  onwards.  We w i l l  The r e s u l t s  that the  analyze the f o r 2SLS a r e  better  than  64 r e s u l t s because they have been c o r r e c t e d f o r  the OLS  s i m u l t a n e i t y , a common problem with supply and demand estimations. We and  found that  the  real  the r e a l p r i c e  consumer  price  s i g n i f i c a n t at the 5% l e v e l . signs.  of greenhouse tomatoes i n  index  of  vegetables  in  B.C.  B.C.  are  Both of these v a r i a b l e s have expected  That i s , as the p r i c e of greenhouse tomatoes increases, the  quantity of greenhouse tomatoes consumed decreases. Furthermore, the  real  consumer p r i c e  index  of  fresh  vegetables  increases, the  quantity of greenhouse tomatoes consumed i n c r e a s e s . conclude  that  the  as  Therefore,  we  sales volume of greenhouse tomatoes depends  on  i t s own p r i c e and the p r i c e of other vegetables. The log-log  time  trend variable  i s negative and  form and negative and  insignificant  significant  f o r the  f o r the l i n e a r  form.  One p o s s i b l e reason f o r t h i s i s that the own p r i c e and the consumer price  index  of  fresh  vegetables  have  captured  the  time  trend  e f f e c t s over time. The  income  insignificant. are  variable  are  an  unexpected  I f we  more  able  dropped to  these v a r i a b l e s ,  capture  the  v a r i a b l e s with which they are c l o s e l y is  a  danger  specification Since  in  dropping  because  economic  substitutes  sign  but  it  is  Normally, we would have dropped the v a r i a b l e s which  insignificant.  variables  has  important  i t would  theory  lead  dictates  effects  associated. variables to b i a s  using  the  of  remaining  the  omitted  However, there from  i n the  own-price,  the  model  estimates. price  of  or complements, income, and time trend f o r the demand  function,  65 keep a l l these v a r i a b l e s i n our r e g r e s s i o n s i n  we w i l l  order t o avoid any b i a s i n our estimates. We have a l s o presented These  elasticities  are c a l c u l a t e d  own-price e l a s t i c i t y l o g - l o g form. increases. vegetable  the e l a s t i c i t i e s  i s elastic  o f these  at the mean data  f o r both  values.  the l i n e a r  This implies that as p r i c e decreases, This  i s probably  growers  one- of the reasons  i n BC wants  t o increase  estimates. The  form and the total  revenue  why greenhouse  production.  If  the  growers i n c r e a s e production, production costs w i l l decrease because of  economies  to scale.  selling prices. can  sell  returns elastic. in price  more i n the market because  the demand  An e l a s t i c will  forms.  implies  that  WGGCA can lower i t s  I f WGGCA can lower i t s s e l l i n g p r i c e s s l i g h t l y , i t and provide curve  demand curve  the growers with  facing  i n d i c a t e s that a small  decrease  greenhouse tomatoes.  amount;  f o r the members o f WGGCA.  cross-price e l a s t i c i t y Therefore,  higher  the co-operative i s  increase quantity demanded by a reasonable  hence, i n c r e a s i n g p r o f i t The  This  a l l other  i s positive  fresh  for  vegetables  both  functional  are s u b s t i t u t e s o f  This i s expected because consumers can switch  t h e i r consumption patterns i f the p r i c e o f one vegetable  increases  r e l a t i v e t o another. The This  income e l a s t i c i t y  i s unexpected  positive.  i s negative f o r both  because  the income  One p o s s i b l e reason  multicollinearity  for  f u n c t i o n a l forms.  elasticity  a negative  with the time trend v a r i a b l e .  sign  i s normally i s there i s  Also, the income  variable  i s insignificant  i n both  cases;  therefore,  i t is  66  not  r e a l l y negative.  DEMAND ESTIMATION RESULTS FOR BC HOTHOUSE TOMATOES Table 4.3: British Columbia Dependent Variable: PCQTBC 2SLS Elasticity Variables OLS*Elasticity OLS* Elasticity 2SLS Elasticity LINEAR at Means LINEAR at Means LOG-LOG at Means LOG-LOG at Means Mean of PCQTBC 7.2556 7.2556 1.4734 1.4734 RPTBC -25.314 -0.5639 -63.189 -1.4077 -3.2356 -3.2356 -5.1885 -5.1885 (-3.690)" (-5.081)" (-4.886)" (-5.213)** RPVBC 4.4978 0.6361 17.448 2.4677 3.5466 3.5466 8.4107 8.4107 (1.140) (3.167)" (1.739)* (3.252)** RPCYBC 3.2924 3.7703 -0.64673 -0.7406 8.346 8.346 -3.3387 -3.3387 (1.767)* (-0.2749) (1.270) (-0.4523) TIME 0.33076 0.1857 -0.34925 -0.1961 -0.32684 -0.3268 -0.82134 -0.82134 (0.8274) (-1.141) (-0.9495) (-2.224)** CONSTANT -22.034 -3.0368 6.3612 0.8767 -22.054 -22.0539 -0.53378 -0.53378 (-1.388) (0.3269) (-1.647) (-0.03654) ESS 379.21 785.24 95.955 1.3597 R 0.6639 0.3041 0.4954 0.3875 R (adj) 0.6426 0.2599 0.4633 0.3486 Durbin- Watson 1.7876 0.9658 1.9404 1.7377 Note: 1. t statistics in brackets 2. ** significant at 95% 3. * significant at 90% 4. * indicates that the regression has been corrected for serial correlation using the Cochrane-Orcutt method. 2  2  4.2.4.2  P r a i r i e Regions o f Canada  Table  4 . 4 presents  the demand  Hothouse tomatoes i n the P r a i r i e  region.  s e c t i o n , we w i l l analyze the r e s u l t s of  greenhouse tomatoes  price  estimation  for  i n the P r a i r i e  Like  2SLS  results  the previous  only.  region,  for  The r e a l  the r e a l  B.C. sub-  price  consumer  index o f fresh vegetables i n the P r a i r i e region, and the r e a l  per-capita  income i n the P r a i r i e  have the expected signs.  region  are s i g n i f i c a n t  and they  67 The time t r e n d v a r i a b l e i s negative and i n s i g n i f i c a n t f o r both functional  forms.  Since  i t i s not s i g n i f i c a n t ,  i t i s not r e a l l y  negative. Diagram  4.7  shows  the production  of  produced i n A l b e r t a and the p r i c e s that they 15 years.  From t h i s  diagram, we  production  of greenhouse  tomatoes  f l u c t u a t e d i n the l a s t few years.  greenhouse  tomatoes  r e c e i v e d i n the l a s t  see a general i n Alberta.  increase  i n the  Production  has  The same holds true f o r p r i c e s .  Greenhouse tomatoes produced i n A l b e r t a are d i r e c t  substitutes for  greenhouse tomatoes produced i n B.C. that are s o l d i n the P r a i r i e region.  How much WGGCA can s e l l t o t h i s market w i l l depend on the  competitors' p r i c e and q u a l i t y .  Diagram 4.9:  68  P r i c e and Production of Greenhouse Tomatoes i n Alberta  Price and Production of Greenhouse Tomatoes in Alberta  o o I Production • Price  o  "•3 U 3  T3 O  1980  1982  1984  1986  1988  1990  1992  1994  Year  Source:  We These  S t a t i s t i c s Canada, A g r i c u l t u r e D i v i s i o n s , H o r t i c u l t u r e Crops Unit, Greenhouse Industry, cat. no. 22-202 (Ottawa: Supply and Services Canada, 1980 through 1994). have a l s o presented the  elasticities  are  own-price e l a s t i c i t y log-log curve  form.  An  calculated  is elastic  elastic  i s relatively  flat.  small amount, the quantity The forms.  cross-price Therefore,  greenhouse tomatoes.  elasticities at  the  of these  mean data  f o r both the  linear  demand curve i n d i c a t e s That  i s , as  the  price  estimates.  values.  The  form and  the  that  the  demand  decreases by  a  demanded increases by a large amount.  elasticity  a l l other  i s positive  fresh  vegetables  for are  both  functional  substitutes  This i s expected because consumers can  of  switch  69  their  buying  habits  i f the p r i c e  of one vegetable  increases  r e l a t i v e t o another. The  income  elasticity  f u n c t i o n a l forms.  i s positive  and s i g n i f i c a n t  for  both  This i s expected because as the r e a l p e r - c a p i t a  income i n the P r a i r i e region increases, the p e r - c a p i t a consumption of  B.C. greenhouse  elasticity  tomatoes  increases,  as w e l l .  Since  income  i s greater than 1 i n t h i s market, B.C. Hothouse tomatoes  are considered a luxury good t o P r a i r i e consumers.  DEMAND ESTIMATION RESULTS FOR BC HOTHOUSE TOMATOES Table 4.4: Prairie Region of Canada Dependent Variable: PCQTPR OLS*Elasticity 2SLS Elasticity OLS* Elasticity Variables 2SLS Elasticity LINEAR at Means LINEAR at Means LOG-LOG at Means LOG-LOG at Means Mean of PCQTPR 2.8197 2.8197 0.65335 0.65335 RPTPR -15.66 -0.9594 -23.231 -1.4233 -2.4002 -2.4002 -4.2268 -4.2268 (-4.815)** (-5.742)** (-5.646)** (-6.444)** RPVPR 11.269 3.6452 13.127 4.2461 5.5225 5.5225 7.9145 7.9145 (6.116)** (7.277)** (4.346)** (5.062)** RPCYPR 3.9022 10.426 2.6477 7.0742 21.629 21.6291 11.126 11.126 (3.579)** (2.345)** (4.232)** (1.747)* TIME 4.65E-02 0.0667 -0.085537 -0.1228 0.32987 0.3299 -0.14432 -0.14432 (0.3905) (-0.7119) (1.418) (-0.4983) CONSTANT -34.338 -12.1777 -24.741 -8.7743 -47.237 -47.2374 -28.522 -28.522 (-3.846)** (-2.665)** (-4.647)** (-2.287)** ESS 51.729 61.804 37.698 49.557 R 0.7118 0.6557 0.6157 0.4948 R (adj) 0.6923 0.6323 0.5897 0.4606 Durbin-Watson 2.0076 1.3968 1.7221 1.3323 Note: 1. t statistics in brackets 2. ** significant at 95% 3. * significant at 90% 4. * indicates that the regression has been corrected for serial correlation using the Cochrane-Orcutt method. 2  2  4.2.4.3  E a s t e r n Canada  Table greenhouse analyzed  4.5 presents tomatoes  here.  the demand  i n Eastern  From Table  estimation  Canada.  results  The 2SLS  4.4, we found that  for  B.C.  r e s u l t s are  the r e a l  p r i c e of  70  greenhouse  tomatoes,  vegetables linear real  the  real  and the time trend  functional price  of  form.  B.C.  consumer variables  price  tomatoes  of  are s i g n i f i c a n t  As f o r the l o g - l o g  Hothouse  index  functional  and  the  fresh  f o r the form, the  time  trend  are  s i g n i f i c a n t at the 5% l e v e l . A l l the v a r i a b l e s i n these two demand equations have expected signs.  The  real  price  of B.C.  Hothouse  tomatoes  i n Eastern  Canada i s negative, i n d i c a t i n g that i t i s an ordinary good. price  of B.C.  Hothouse index  Hothouse  tomatoes  of  fresh  tomatoes  demanded  vegetables  increases,  decreases. i n Eastern  As the  the quantity  The  real  Canada  of  consumer  B.C. price  i s positive.  This  i n d i c a t e s that as p r i c e of other vegetables increases, consumption of B.C. Hothouse tomatoes increases, as w e l l . income  i n Eastern  Canada  i s positive,  The r e a l  indicating  per-capita  that  as  income  increases, consumption increases. The time trend v a r i a b l e i s negative and s i g n i f i c a n t functional  forms.  This  markets which s h i f t s  BC  might  be  caused by  supply  f o r both  from  other  Hothouse tomato demand to the l e f t .  As  shown i n diagrams 4.8 and 4.9, production of greenhouse tomatoes i n Ontario  and  Quebec  has  increased.  produced  i n Ontario  and  Quebec  Hothouse  tomatoes  demand f o r B.C.  sold  Since  are d i r e c t  i n Eastern  Canada,  greenhouse substitutes this  will  tomatoes f o r B.C. cause  the  Hothouse tomatoes i n Eastern Canada t o decrease.  Therefore, the time trend i s negative i n t h i s region. Another negative  possible  reason  that  the  time " trend  i s because the time trend v a r i a b l e  variable  is  should be used as an  instrumental The than  v a r i a b l e and not an independent v a r i a b l e  time t r e n d  variable  demand f a c t o r s  However,  given  might be measuring  because  data  supply  71 f o r demand.  factors  i t i s measured on an annual  limitations,  we  have used  the best  rather basis.  possible  instruments i n our model. 4.5.  The own-  p r i c e e l a s t i c i t i e s f o r both f u n c t i o n a l form are e l a s t i c ,  indicating  The  elasticities  are also presented i n Table  relatively  flat  demand  curves.  relatively  flat,  a small  change i n the p r i c e  result  i n a large  demanded.  The  functional  increase  elasticities  Therefore,  a l l other  s u b s t i t u t e s of B.C. Hothouse tomatoes. positive because  f o r both as  income  demand  curves  that  are  of the product  will  or decrease i n the quantity  cross-price  forms.  For  functional increases,  forms,  of product  are p o s i t i v e fresh  f o r both  vegetables  are  The income e l a s t i c i t i e s are as w e l l .  consumption  This  increases  assume that B.C. Hothouse tomatoes are normal goods.  i s expected because  we  Diagram  4.10: P r i c e and P r o d u c t i o n o f Greenhouse Tomatoes i n Ontario  72  Price and Production of Greenhouse Tomatoes in Ontario  O  Production  o o  Price  3 TJ O  1980  1982  1984  1986  1988  1990  1992  1994  Year  Source:  S t a t i s t i c s Canada, A g r i c u l t u r e D i v i s i o n s , H o r t i c u l t u r e Crops U n i t , Greenhouse Industry, c a t . no. 22-202 (Ottawa: Supply and S e r v i c e s Canada, 1980 through 1994).  Diagram Quebec  4.11:  Production  and  Price  of  Greenhouse  Tomatoes  73 in  Price and Production of Greenhouse Tomatoes in Quebec  1980  1982  1984  1986  1988  1990  1992  1994  Year Source:  S t a t i s t i c s Canada, A g r i c u l t u r e D i v i s i o n s , H o r t i c u l t u r e Crops Unit, Greenhouse Industry, c a t . no. 22-202 (Ottawa: Supply and Services Canada, 1980 through 1994).  74 DEMAND ESTIMATION R E S U L T S F O R B C H O T H O U S E T O M A T O E S T a b l e 4.5: Eastern C a n a d a Dependent Variable: P C Q T E A Variables  O L S * Elasticity LINEAR  Mean of P C Q T E A S T  at Means  0.856  RPTEAST  0.856  -4.018 (-3.550)**  -0.6671  1.5831  1.8671  RPVEAST  (2.735)** 3.45E-02  RPCYEAST  0.3448  TIME  -0.11217 (-1.495) -8.84E-03  -6.6645 (-3.616)**  -1.1064  1.3637 0.045596 -0.14422  -0.0103  (-3.588)** 0.63212  (1.023E-02)  Elasticity at M e a n s  -1.4215  1.6083  1.4452  0.4557  (1.254) 1.0727  -1.5046  1.4452  1.188  1.188  1.0727  (1.151) 1.3582  1.3582  (1.358)  -0.68698  -0.687  -0.68533  -0.68533  -4.9163  (-3.108)** -5.6965  -5.6965  (-2.473)** 0.7385  -4.9163  (0.8388)  (-2.005)**  (-2.662)**  ESS  10.41  17.784  47.708  51.288  R  0.623  0.3559  0.3891  0.3432  R (adj)  0.5961  0.3099  0.3454  0.2963  Durbin-Watson  1.7011  0.8235  2.0852  1.4772  2  2  at M e a n s  -1.5046 (-4.047)**  (0.9395) -0.696  2 S L S Elasticity LOG-LOG -0.60513  -1.4215 (-3.574)**  (0.6685) -0.5414  OLS* LOG-LOG -0.60513  (2.194)**  (0.4581)  CONSTANT  2 S L S Elasticity LINEAR at Means  Note: 1. t statistics in brackets 2. ** significant at 95% 3. * significant at 90% 4.  #  indicates that the regression has been corrected for serial correlation using the Cochrane-Orcutt method.  4.2.4.4 Washington  Table  4.6  presents the r e s u l t s  f o r the demand estimation of  B.C. Hothouse tomatoes i n Washington. for  2SLS here.  significant  For the l o g - l o g  at the 10% l e v e l .  We w i l l analyze the r e s u l t s  form, the time trend v a r i a b l e i s  A l l the remaining v a r i a b l e s are not  s i g n i f i c a n t but they have the expected signs. none of t h e v a r i a b l e s are s i g n i f i c a n t .  For the l i n e a r form,  Also,  the signs  for real  p e r - c a p i t a consumption of B.C. Hothouse tomatoes i n Washington and the  real  consumer p r i c e  index  of f r e s h  fruits  Western United States have unexpected signs.  and vegetables i n  WGGCA s e l l s  p r o p o r t i o n o f i t s products t o t h i s market; t h e r e f o r e , i n s i g n i f i c a n t market.  a small  this  i s an  DEMAND ESTIMATION RESULTS FOR BC HOTHOUSE TOMATOES Table 4.6: Washington Dependent Variable: PCQTWASH OLS* Elasticity 2SLS Elasticity OLS* Elasticity 2SLS Elasticity Variables LINEAR at Means LINEAR at Means LOG-LOG at Means LOG-LOG at Means Mean of PCQTWASH 0.64609 0.64609 -1.1548 -1.1548 RPTWASH -7.0535 -1.191 1.1341 0.1915 -1.2621 -1.2621 -0.52302 -0.52302 (-3.084)" (0.1765) (-4.417)" (-0.5254) RPFVWEST 3.5228 6.2708 -5.2395 -9.3268 10.7 10.7002 0.90071 0.90071 (1.036) (-0.9660) (1.975)* (0.1129) RPCYWEST 11.306 2.5456 130.72 29.4338 14.312 14.3115 35.661 35.661 (0.1427) (1.648) (0.6936) (1.438) TIME -6.44E-02 -0.4069 -0.25105 -1.5872 -1.0442 -1.0442 -2.0234 -2.0234 (-0.3463) (-1.536) (-0.9491) (-1.751)* CONSTANT -4.025 -6.2297 -11.443 -17.7113 23.251 23.2512 68.779 68.779 (-0.3764) (-1.218) (0.5636) (1.339) ESS 29.854 41.124 56.138 77.132 R 0.3047 0.0421 0.4267 0.2122 R (adj) 0.2531 -0.0288 0.3842 0.1539 Durbin-Watson 2.0539 1.3932 1.9109 1.0923 Note: 1. t statistics in brackets 2. ** significant at 95% 3. * significant at 90% 4. * indicates that the regression has been corrected for serial correlation using the Cochrane-Orcutt method. 2  2  4.2.4.5  Oregon  Table B.C.  4.7 presents  Hothouse  results  tomatoes  the r e s u l t s i n Oregon.  f o r 2SLS here.  significant  f o r the demand estimation o f We are going  None o f the estimated  i n t h i s market.  t o analyze the c o e f f i c i e n t s are  For the l i n e a r f u n c t i o n a l  form, the  estimated c o e f f i c i e n t s f o r r e a l p r i c e o f B.C. Hothouse tomatoes and r e a l consumer p r i c e index o f f r e s h f r u i t s and vegetables i n Western United  States have unexpected  signs.  F o r the l o g - l o g  functional  form, the r e a l p r i c e  o f B.C. Hothouse tomatoes t o t h i s market i s  negative,  consumer  vegetables capita  the r e a l  i n Western  income  United  i n Oregon  price  index  States  i s negative,  i s positive,  of f r e s h  f r u i t s and  the r e a l p e r -  and the time  trend i s  negative.  Normally, the r e a l consumer p r i c e index o f f r e s h  and vegetables negative. of  other  i s expected t o be p o s i t i v e .  In t h i s case,  76 fruits it  is  This implies that B.C. Hothouse tomatoes are s u b s t i t u t e s fresh  fruits  and vegetables.  Overall,  the estimated  demand equation using the l i n e a r form and the l o g - l o g form does not explain  much about the demand  market, e i t h e r .  f o r B.C. Hothouse tomatoes i n t h i s  WGGCA does not s e l l much of i t s products t o t h i s  market; hence, i t i s an i n s i g n i f i c a n t market f o r WGGCA, as w e l l .  DEMAND ESTIMATION RESULTS FOR BC HOTHOUSE TOMATOES Table 4.7: Oregon Dependent Variable: PCQTORE OLS Elasticity 2SLS Elasticity OLS* Elasticity Variables 2SLS Elasticity LINEAR at Means LINEAR at Means LOG-LOG at Means LOG-LOG at Means Mean of PCQTORE 0.92786 0.92786 -0.58223 -0.58223 RPTORE -12.566 -1.1103 16.297 1.44 -1.3618 -1.3618 -0.26625 -0.26625 (-2.818)" (0.8213) (-4.483)** (-0.2723) RPFVWEST 1.9799 2.4458 -12.603 -15.5689 4.5501 4.5501 -2.9067 -2.9067 (0.5042) (-1.149) (0.9203) (-0.3694) RPCYORE -34.815 -4.8903 54.153 7.6067 1.1302 1.1302 1.5006 1.5006 (-0.3667) (0.3773) (7.012E-02) (0.1222) TIME 0.004446 0.0198 -0.091006 -0.4058 -0.33301 -0.333 -0.31138 -0.31138 (0.02772) (-0.3952) (-0.4876) (-0.5635) CONSTANT 4.2078 4.535 7.3561 7.928 -2.025 -2.025 2.5656 2.5656 (0.3363) (0.4224) (-6.037E-02) (0.1035) ESS 43.411 82.941 37.477 53.757 R 0.4023 0.1874 -0.5526 0.1426 R (adj) 0.3503 0.1167 -0.6876 0.0681 Durbin-Watson 1.7306 1.3079 1.7295 1.6553 Note: 1. t statistics in brackets 2. ** significant at 95% 3. * significant at 90% 4. * indicates that the regression has been corrected for serial correlation using the Cochrane-Orcutt method. 2  2  77  4.2.4.6  California  The  demand estimation  California  i s presented  analyze the r e s u l t s real  per-capita  significant.  results  i n Table  f o r 2SLS.  income  f o r B.C. Hothouse tomatoes i n 4.8.  Again,  For the l i n e a r  i n California  For the l o g - l o g  and  functional  we  are going t o  functional the  time  form, the trend  form, the r e a l  are  price  of  B.C. Hothouse tomatoes i n C a l i f o r n i a , the r e a l p e r - c a p i t a income i n California,  and the time trend v a r i a b l e are s i g n i f i c a n t .  For both  functional  forms, a l l the v a r i a b l e s have expected signs.  The r e a l  price  of  B.C.  indicating  that  Hothouse  B.C. Hothouse  r e a l consumer p r i c e United  States  tomatoes  tomatoes  index of fresh  i s positive,  in  California  is  are ordinary  negative,  goods.  The  f r u i t s and vegetables i n Western  indicating  that  as  price  of  other  vegetables increases, consumption of B.C. Hothouse tomatoes i n the Californian California luxury  market  i s positive  good.  The  real  per-capita  and greater than 1 i n d i c a t i n g  As income  tomatoes i n c r e a s e s . the  increases.  increases,  the demand  income  that  in  i t is a  f o r B.C.  Hothouse  The time trend v a r i a b l e i s p o s i t i v e .  Unlike  other markets that we have analyzed thus f a r , the time t r e n d  variable  in  significant,  the  California  indicating  market  a positive  trend.  is  positive  and  highly  DEMAND ESTIMATION RESULTS FOR BC HOTHOUSE TOMATOES Table 4.8: California Dependent Variable: PCQTCAL OLS*Elasticity 2SLS Elasticity OLS* Elasticity 2SLS Elasticity Variables LINEAR at Means LINEAR at Means LOG-LOG at Means LOG-LOG at Means Mean of P C Q T C A L 0.32158 0.32158 -1.8138 -1.8138 RPTCAL -3.0431 -0.8793 -2.0132 -0.5817 -1.7051 -1.7051 -3.2338 -3.2338 (-3.187)" (-0.9900) (-3.673)" (-2.538)** RPVCAL 1.2959 4.6294 1.0078 3.6001 5.4715 5.4715 15.91 15.91 ( 1 . 2 1 3 ) ( 0 . 6 8 9 8 ) ( 0 . 8 1 6 9 ) ( 1 . 5 2 6 ) RPCYCAL 104.55 49.7606 107.06 50.9542 40.278 40.2776 40.398 40.398 ( 4 . 1 5 1 ) " ( 5 . 6 3 5 ) " ( 1 . 9 3 2 ) * ( 2 . 455)** TIME 0.16787 2.1676 0.17023 2.1982 1.367 1.367 1.4745 1.4745 ( 4 . 1 1 7 ) " ( 5 . 5 0 2 ) " ( 1 . 8 7 7 ) * ( 2 . 5 46)** CONSTANT -17.587 -54.6878 -17.742 -55.1708 67.141 67.1414 62.015 62.015 (-4.282)" (-5.507)" (1.742)* (1.979)* ESS 2.4071 3.0421 72.928 117.27 R 0.5731 0.4605 0.4881 0.1769 R (adj) 0.5415 0.4206 0.4502 0.1159 Durbin-Watson 1.7702 1.1094 1.699 0.9819 2  2  Note: 1. t statistics in brackets 2. ** significant at 95% 3. * significant at 90% 4. * indicates that the regression has been corrected for serial correlation using the Cochrane-Orcutt method.  4.2.4.7  Other Parts o f United and t h e Midwest)  Table  4 . 9 presents  States  the demand  (North-eastern United  estimation  results  States  for  B.C.  Hothouse tomatoes i n other regions o f United States such as Northeastern United States and the Midwest. that  the r e a l  significant  price  From Table 4 . 9 , we observe  o f B.C. Hothouse tomatoes i n t h i s  at the 10% l e v e l .  area i s  For the l i n e a r f u n c t i o n a l form, the  r e a l p r i c e o f B.C. Hothouse tomatoes i n the other regions o f United States implies  i s negative, that  indicating  that i t i s an ordinary good which  the demand f o r B.C. Hothouse tomatoes i n c r e a s e s as  price increases. vegetables  indicating  The r e a l consumer p r i c e index o f f r e s h f r u i t s and  i n the other  regions  o f United  States  i s positive,  that the consumption of B.C. Hothouse tomatoes depends  on the p r i c e s  o f other goods.  79 The r e a l p e r - c a p i t a income i n other  regions o f United States i s negative and i n s i g n i f i c a n t . is  insignificant,  variable  i t i s not r e a l l y  The time  i t  trend  i n t h i s region i s p o s i t i v e .  For the l o g - l o g is  negative.  Since,  negative,  form, the r e a l p r i c e o f B.C. Hothouse  the r e a l  consumer p r i c e  index o f f r e s h  tomatoes  f r u i t s and  vegetables i s p o s i t i v e ,  the r e a l p e r - c a p i t a income i s p o s i t i v e and  the  time trend v a r i a b l e  i s positive.  has  a l l the expected signs.  The l o g - l o g  The own-price  functional  form  e l a s t i c i t y i s greater  than one, i n d i c a t i n g that  i t i s e l a s t i c ; the cross p r i c e e l a s t i c i t y  is  that  positive,  tomatoes  indicating  i n this  vegetables;  the consumption  region depends on the p r i c e  and the income  of B.C. Hothouse  o f other  e l a s t i c i t y i s positive,  f r u i t s and  indicating  a  normal good.  DEMAND ESTIMATION RESULTS FOR BC HOTHOUSE TOMATOES Table 4.9: Other Regions of United States Dependent Variable: PCQTOTH Variables OLS* Elasticity 2SLS Elasticity OLS* Elasticity 2SLS Elasticity LINEAR at Means LINEAR at Means LOG-LOG at Means LOG-LOG at Means Mean of PCQTOTH 0.10178 0.10178 -3.744 -3.744 RPTOTH -7.80E-02 -0.0779 -3.1071 -3.1063 -1.024 -1.024 -5.6313 -5.6313 ( 0 . 3 1 9 5 ) ( 1 . 7 2 8 ) * ( 1 .537) (-1.741)* RPFVOTH -0.35843 -3.8968 0.66159 7.1926 -4.7913 -4.7913 16.274 16.274 ( 0 . 7 9 4 6 ) ( 0 . 4 8 6 7 ) ( 0 . 3 8 1 0 ) ( 0 .6419) RPCYOTH 11.999 17.7253 -1.7071 -2.5218 1.7678 1.7678 3.8339 3.8339 (0.9649) (-0.1022) (5.843E-02) (0.1168) TIME 1.34E-02 0.6309 0.019888 0.9335 1.9853 1.9853 1.2086 1.2086 ( 0 . 5 0 8 3 ) ( 0 . 6 9 8 9 ) ( 1 . 8 0 0 ) * ( 0 .8970) CONSTANT -1.3808 -13.5655 -0.15248 -1.498 -5.2803 -5.2803 -13.28 -13.28 (-0.7189) (-5.022E-02) (-9.1E-02) (0.2097) 0.22512 ESS 1.2233 117.89 285.95 0.7431 0.4626 R -0.3962 -0.3034 0.7174 0.4089 R (adj) -0.5358 -0.4338 0.7599 1.9476 Durbin-Watson 1.078 1.3603 Note: 1. t statistics in brackets 2. ** significant at 95% 3. * significant at 90% 4. * indicates that the regression has been corrected for serial correlation using the Cochrane-Orcutt method. 2  2  80  4.2.4.8  Comparing Results Across Regions  From t h e demand e s t i m a t i o n found  that  theory  the r e s u l t s that  f o r a l l markets  W a s h i n g t o n a n d Oregon B.C.  Hothouse  we have  except  we have  are consistent  f o r Washington  obtained, with  and  From  i n 1994.  here  Hence,  onwards,  we  these  we  economic Oregon.  comprised of 4 percent of the t o t a l  tomatoes  insignificant.  r e s u l t s that  sales of  two m a r k e t s a r e  are not going  to  analyze  t h e s e two m a r k e t s any f u r t h e r . From t h e e s t i m a t e s in  o f t h e r e a l p r i c e o f B.C. Hothouse  e a c h m a r k e t , we f o u n d t h a t  goods.  That  quantity found  i s , a s t h e own p r i c e  o f B.C. H o t h o u s e  that  B.C. Hothouse  most  California.  tomatoes  o f t h e demand  An  elastic  decreases by a s m a l l  increases, the  i n that  decreases.  amount, q u a n t i t y  that  of the real  or fresh fruits  positive  and i n s i g n i f i c a n t  consumer  price  each  market  index  implies depends  increases flat.  except f o r  that  as  price  by a l a r g e  amount  By d e c r e a s i n g  price,  p r i c e index  i n t h e Canadian markets and  vegetables  t h e demand  on t h e p r i c e s  of fresh  i n e a c h m a r k e t , we f o u n d  f o r t h e U.S. m a r k e t s .  of fresh  that  consumer  and v e g e t a b l e s  i t i s p o s i t i v e and s i g n i f i c a n t  vegetables  implies  We  increase.  From t h e e s t i m a t e s vegetables  market  are e l a s t i c  curve  b e c a u s e t h e demand c u r v e i s r e l a t i v e l y revenue f o r growers  are ordinary  i n each market  functions  demand  tomatoes  tomatoes  or  A positive fresh  o f B.C. Hothouse of other  fruits  real and  tomatoes i n  vegetables.  As t h e  price  of other vegetables  81 Hothouse  i n c r e a s e s , c o n s u m p t i o n o f B.C.  tomatoes i n t h a t market i n c r e a s e s , as w e l l . The  income  Eastern  Canada,  because  B.C.  increases, Hothouse Regions  Hothouse  demand  products  are  considered  coefficients  estimated  i n these  United  States  negative.  The  income  expected  As  income  well.  B.C.  i n the  Prairie  as  goods  coefficients  the P r a i r i e They  are  variable  United  For the other States  and  Quebec  has caused  Conversely,  the estimated  o f Canada,  and E a s t e r n  i n t h e B.C.  coefficients Canada a r e  market  i n E a s t e r n Canada.  from other markets  t h e demand  inwards.  the  f o r t h e time t r e n d v a r i a b l e i s  and t h e There a r e  f o r t h e n e g a t i v e s i g n i n E a s t e r n Canada.  i s that the supply  is  This implies that sales o f  (North-eastern  Regions  reason  regions t o s h i f t  insignificant;  trend  a r e a has i n c r e a s e d .  are i n s i g n i f i c a n t  p o s s i b l e reasons  are  f o r the time  P r a i r i e market but i t i s s i g n i f i c a n t two  goods.  two m a r k e t s  the estimated c o e f f i c i e n t  p o s i t i v e but i n s i g n i f i c a n t . B.C.,  luxury  i n California.  B.C. H o t h o u s e t o m a t o e s t o t h i s  in  normal  is  Canada,  negative.  coefficient  p o s i t i v e and s i g n i f i c a n t  Midwest),  This  increases,  and C a l i f o r n i a .  hence, they a r e n o t r e a l l y  of  are  of  i n t h e B.C. m a r k e t and t h e O t h e r P a r t s o f U n i t e d S t a t e s .  income  parts  Regions  are p o s i t i v e .  f o r t h e product  o f Canada  The  i n the P r a i r i e  and C a l i f o r n i a  products  negative The  coefficients  f o r BC  such  Hothouse  Another reason  One  as O n t a r i o and  tomatoes  i n those  i s t h a t our i n s t r u m e n t a l  variable  i s n o t a s good a s i t needs t o be and some s i m u l t a n e i t y  remains.  This could create a biased estimate of the c o e f f i c i e n t .  82  However, i t i s t h e b e s t p o s s i b l e instrument g i v e t h e data t h a t we have. In  general,  t h e estimated  demand  equations  that  we  have  e s t i m a t e d a r e c o n s i s t e n t w i t h economic t h e o r y .  4.2.4.9  WGGCA's A b i l i t y t o Price Discriminate  From Tables 4 . 3 t o 4 . 9 , we have observed t h a t t h e own-price e l a s t i c i t i e s a r e d i f f e r e n t i n each market.  As we have mentioned i n  section  are d i f f e r e n t  one, i f t h e p r i c e  elasticities  market, WGGCA can maximize p r o f i t is,  by p r i c e d i s c r i m i n a t i n g .  That  i t s h o u l d s e t q u a n t i t i e s s o l d a t where m a r g i n a l revenue equals  m a r g i n a l c o s t and charge a p r i c e on the demand curve. the  i n each  cross-price  different  elasticities  a c r o s s markets.  Furthermore,  and t h e income  e l a s t i c i t i e s are  Since t h e own-price  e l a s t i c i t i e s , the  c r o s s - p r i c e e l a s t i c i t i e s , and the income e l a s t i c i t i e s are d i f f e r e n t for  each market, i t i s best i f WGGCA develops d i f f e r e n t  strategies present,  f o r each  t h e people  market  i n order  t o maximize  a t WGGCA analyze t h e i r  marketing  profit.  own p r i c e s  At  and t h e i r  c o m p e t i t o r s ' p r i c e s i n each market and they use these i n f o r m a t i o n as a guide f o r t h e i r marketing s t r a t e g i e s .  4.3  Estimation  4.3.1  Cost  The  of  of  the  Production  Production  co-operative's  83  Model  Estimation  production  for  B.C.  Greenhouse  Tomatoes  f u n c t i o n i s expressed as:  Y = F (K, L, R, BL, RD, MGMT) where:  K L R BL RD MGMT  i s t h e c a p i t a l s u p p l i e d by t h e c o - o p e r a t i v e , i s t h e l a b o r s u p p l i e d by t h e c o - o p e r a t i v e , i s t h e raw p r o d u c t s s u p p l i e d by member-farmers, i s t h e marketing and p r o m o t i o n a l a c t i v i t i e s conducted by t h e c o - o p e r a t i v e t o develop brand loyalty, i s t h e amount o f r e s e a r c h a n d d e v e l o p m e n t c o n d u c t e d by t h e c o - o p e r a t i v e , and i s t h e management a n d / o r p r o f e s s i o n a l e x p e r t i s e a t the  With the exception farmers,  co-operative. o f t h e c o s t o f raw p r o d u c t  a l l other  production  costs  mentioned  function are incorporated  in the cost-of-production  schedule  s u p p l i e d b y member-  in  the  co-operative's  i n the post-harvest  presented  charges  i n T a b l e 4.10.  A c o s t - o f - p r o d u c t i o n m e t h o d was u s e d t o d e t e r m i n e t h e s u p p l y f u n c t i o n o f greenhouse tomatoes. used  t o estimate  t h e supply  o f greenhouse  econometrics because p r o d u c t i o n Once  t h e growers  s u n k . Hence, t h e y in  particular  schedule  t o estimate study  factors  that  crops,  Furthermore, data  study.  Another  their  Therefore,  t h e supply which  rather  the costs  we u s e d  a  year.  incurred are  investment  availability  than  alternatives  i s limited for  cost-of-production  functions.  i s being  influence  tomatoes  d e c i s i o n s a r e made o n c e a  do n o t h a v e many o t h e r  the short-run.  this  the  planted  A c o s t - o f - p r o d u c t i o n m e t h o d was  supply.  conducted  right  Dr. Wei L i n ,  now  analyzes  one o f t h e  84 i s working on a b i o l o g i c a l  l e a d i n g crop s c i e n t i s t s i n t h i s f i e l d , model which  estimates  actual  harvest.  He  i s using time-series  data t o estimate t h i s  function.  His p r o j e c t  and  by  of 1995.  will  the  be  most  completed important  process.  Other  the end  aspect  aspects  of  of  He  physical  yield  runs  said  yield  include  f o r two  years  t h a t one  is  number  of  biological of  acreage  p l a n t e d and s k i l l s of the managers and workers.  4.3.2  Cost of Production Estimation Data f o r B.C. Tomatoes  Greenhouse  The c o s t - o f - p r o d u c t i o n f u n c t i o n i s estimated u s i n g data v a r i o u s sources Costs  and  Returns  Greenhouses p u b l i s h e d by Vegetable  4.3.3  and  at  the  Competing  BCMAFF, and  r e p o r t on "Fresh  Farm-Level  Areas",  for  Planning  British For  P r e p a r i n g a Business  Vegetable Columbia  Profit  Plan:  Sheets  Greenhouse  Example.  Cost of Production Estimation Procedures and Results  In t h i s on  such as Brad Stennes'  from  Fresh  study, we  Vegetable  used the f i n d i n g s of Brad Stennes'  Costs  and  British  Columbia  Greenhouses  analyzed  the  of  cost  and peppers i n an  8, 000  producing m  2  Returns and  at  the  Competing  greenhouse  greenhouse and  report  Farm-Level  for  Areas.  Stennes  tomatoes,  cucumbers,  a 25, 000  m  2  greenhouse.  The  greenhouse  tomato  results  p r e s e n t e d i n Table 4.10. The cost costs.  function  based  on  Stennes'  breakdown  of  85 are  16  i s divided  into variable  The c o s t s p r e s e n t e d here are very  detailed  report  the cost  costs  general.  structure,  see  and f i x e d F o r a more  "Preparing  a  Business Plan, a Guide f o r A g r i c u l t u r a l Producers" and "Planning f o r P r o f i t " sheets.  Both p u b l i c a t i o n s are a v a i l a b l e at BCMAFF.  Table 4.10: Cost of Production for Greenhouse Tomatoes in B.C., 1993 8,000 rrf Greenhouse $/m2 Total$ 14.07 112560 13.75 110000 13.24 105920  Variable Costs Material Inputs Heat & Utiltities Labour Variable Building & Machinery Post Production Costs* Other Variable Costs Total Variable Costs  $/case** 2.54 2.54 2.45  25,000 n f Greenhouse $/m2 Total $ 13.37 334250 11.16 279000 12.58 314500  $/case** 2.45 2.00 2.27  1.36  10880  0.27  1.36  34000  0.27  19.73  157840  3.63  19.73  493250  3.63  1.29  10320  0.27  1.23  30750  0.27  63.44  507520  11.70  59.43  1485750  10.89  Fixed Costs Overhead  3.05  24400  0.54  2.77  69250  0.54  Equipment  4.76  38080  0.91  2.94  73500  0.54  Buildings  7.43  59440  1.36  6.19  154750  1.09  Land  0.61  4880  0.09  0.61  15250  0.09  15.85  126800  2.90  12.51  312750  2.27  79.29  634320  14.61  71.94  1798500  13.15  Total Fixed Costs  Total Costs  **There are 9.07 kilograms o f tomatoes i n a case. Source: Stennes, Brad. Fresh Vegetable Costs and Returns at the Farm-Level F o r B r i t i s h Columbia Greenhouses and Competing Areas. B.C., 1995. From  Tables  4.10, v a r i a b l e  heat and u t i l i t i e s ,  costs  include  material  inputs,  l a b o r , v a r i a b l e b u i l d i n g and machinery, post  For t h e i n t e r e s t e d reader, see Appendix D f o r the cost o f p r o d u c i n g B.C. greenhouse cucumbers and B.C. greenhouse peppers.  production costs  costs,  deserve  and  other  special  variable costs.  mention  because  this  packing, marketing and  co-op a d m i n i s t r a t i o n  no  f o r patronage  attempt  a l l three  to  costs  depreciation  include  costs.  requirements operation,  detailed  of  land,  normally  equipment  overhead  Before we  go  costs,  II)  The  to  86 production  includes  the  Stennes made  co-op members i n  a  greenhouse  f u r t h e r i n t o the  and  appreciate  in  list  of the  in  value  we  will  operation.  building,  decrease  opportunity  equipment value;  over  components that  b u i l d i n g s c o n s i s t of:  1.  greenhouse  and  2.  p a c k i n g a r e a / b o i l e r room.  The  equipment c o n s i s t s o f :  1. Heating & c l i m a t e c o n t r o l , 2. I r r i g a t i o n & drainage, 3. R e c y c l i n g system, 4. C0 d i s t r i b u t i o n system, 5. A u x i l i a r y power, 6. Spray equipment, 7. S c a l e s , meters and t o o l s , 8. P a l l e t jacks, 9. E l e c t r i c carts, 10. Computer equipment, 11. Automotive equipment, and 12. O f f i c e equipment. 2  start  are  The  discussion the a  greenhouse  following  BC.  of  capital  Land  buildings  comprise the in  and  required.  whereas,  time.  costs,  discuss  To  equipment of a t y p i c a l greenhouse o p e r a t i o n I)  cost  costs.  refund  Stennes determined f i x e d c o s t s ,  values  post  cases.  Fixed  how  account  The  and is  buildings  a and  A  detailed  for  break-down  of these  costs  (buildings  87 equipment)  and  a 10,000 square meter o p e r a t i o n i n Aldergrove i s p r e s e n t e d i n  P r e p a r i n g a Business P l a n : Stennes  used  a  A Guide f o r A g r i c u l t u r a l  straight-line  method  to  d e p r e c i a t i o n c o s t s of b u i l d i n g s and equipment. buildings  and  the  equipment  are  presented  without  and  the  equipment  method i s a l s o used by Table life  4.12. is  The  the  declining  total  same  amount  whether  balance  method  of  the is  4.11.  life  of  d e p r e c i a t i o n over straight-line  because Hence,  the the  calculate  Stennes growers  amount the  of  d i d not  used.  entered  use  Some  the  growers  declining at  depreciation varies of  balance  or  the  used  the  can w r i t e o f f more of the  production  depreciation costs  years  i t s useful  method  a s s e t ' s c o s t i n the e a r l i e r years of an a s s e t ' s l i f e years.  15  These r a t e s are l i s t e d i n  d e c l i n i n g balance method because they  later  He  of 20 years with no  However, the d e c l i n i n g  some growers.  the  The v a l u e s of the  have a u s e f u l  salvage value, as w e l l .  calculate  i n Table  assumed t h a t the b u i l d i n g s have a u s e f u l l i f e salvage v a l u e  Producers.  the  than i n i t s  balance  different  method  periods.  amongst  growers.  To  average  grower  an  on  annual b a s i s , the s t r a i g h t - l i n e method i s the most a p p r o p r i a t e . Table 4.11: C a p i t a l Cost Schedule Item 8, 000 in G'House 25, 000 in G'House Buildings $699,000 $1,820,300 T o t a l Equipment $374,850 $724,120 Source: Stennes, Brad. Fresh Vegetable Costs and Returns at the Farm-Level For B r i t i s h Columbia Greenhouses and Competing Areas. B.C., 1995.  Table 4.12: Rate o f D e p r e c i a t i o n f o r C a p i t a l Buildings 5% per annum Equipment 15% per annum Computer Equipment 30% per annum Automotive Equipment 30% per annum O f f i c e Equipment 20% per annum The real  opportunity  rate  capital  cost  of c a p i t a l  i s calculated  assets.  I t i s important  because the i n v e s t o r s  real  rate  of i n t e r e s t  derived  equipment  and  depreciation buildings,  i s common  incorporated to  the  region  cost  -is  include  insurance,  interest  management  fees,  for this costs  the  derive  4%  type  of land,  the  total  producing  A 7%  business.  buildings, cost  fixed  of  opportunity  of  opportunity  of t o t a l  consulting and  office  bank  with  cost  of  17  and the land,  charges,  f o r every  Examples garbage  legal  property  of  and  size fixed  removal,  accounting,  taxes,  repair  and  miscellaneous.  f o l l o w i n g t a b l e presents greenhouse tomatoes  costs.  and research,  supplies,  maintenance, telephone, and The  value  and equipment.  every  overhead  a 7%  can use t h i s money elsewhere.  the opportunity  cost  to calculate  Stennes assumed that the f i x e d overhead cost and  using  o f i n t e r e s t based on 50% of the replacement  cost  Stennes  88  Assets  a summary of the t o t a l costs of  i n BC.  This  i s based  on Stennes'  report.  _Table 4.13: Product:  T o t a l Costs of iiProducing Greenhouse Tomatoes i n B.C. i i » i 8, 000 in 25, 000 in $/m $/case $/m $/case Greenhouse Tomatoes 79.29 14.61 71.94 13.15 II  2  Interviews with people i n t h i s  2  field.  •  89 5.0  MEASURING THE BENEFITS AND COSTS OF MARKETING REGULATIONS AND CO-OPERATIVE STRUCTURE FOR B . C . GREENHOUSE TOMATOES GROWERS  In  this  chapter,  measure the s o c i a l and c o - o p e r a t i v e First,  we  we w i l l  benefits  structure  present  w e l f a r e impacts.  a  provide  and c o s t s  a description o f marketing  o f how  regulations  f o r B.C. greenhouse tomato  graphical  illustration  of  we  growers.  the  economic  Then, we d e s c r i b e the s i m u l a t i o n model used t o  measure these impacts.  Finally,  c o n c l u s i o n s and  recommendations  w i l l be made based on these f i n d i n g s .  5.1  GRAPHICAL ILLUSTRATION OF THE ECONOMIC WELFARE IMPACTS  In model  chapter  4,  we  provide  a description  o f the c o n c e p t u a l  and the mathematical model used t o estimate the demand and  supply f u n c t i o n s f o r B.C. greenhouse tomatoes. the  demand  findings Returns  equations i n each market  o f Brad Stennes' r e p o r t  and we  Areas."  simulation  model  government  We to  will  measure  regulations  and  have  Columbia  use these r e s u l t s the  p r e s e n t e d the  on "Fresh Vegetable Costs and  at the Farm-Level f o r B r i t i s h  Competing  We have estimated  economic  co-operative  Greenhouses  and  and c o n s t r u c t  welfare  impacts  structure  for  a of  B.C.  greenhouse tomato growers. Before greenhouse  estimating tomato  t h e economic  welfare  impacts  f o r B.C.  growers, we need t o know the f u n c t i o n  o f the  aggregate demand curve and i t s r e s p e c t i v e marginal revenue curve. To  estimate  the  aggregate  demand  curve  and  i t s respective  marginal  revenue  individual curves.  curve,  demand  curves  Once, we  demand curves  we  need  and  to  their  have determined  and  their  determine  the  shape  of  r e s p e c t i v e marginal the  shape of each  r e s p e c t i v e marginal  90 the  revenue  individual  revenue  curves,  can add them up i n order t o o b t a i n the aggregate demand curve  we and  the aggregate marginal revenue curve. For the  supply  function,  l a r g e growers producing at  high  cost.  The  The  marginal  cost  at low  large  greenhouse tomatoes and  i t i s stepwise cost and  growers  i n manner w i t h  small growers  produce  70%  f o r the  large  growers  producing  of  the. s m a l l growers produce  the  the  30%  B.C.  of them.  i s $13.16/case and  the  m a r g i n a l c o s t f o r the s m a l l growers i s $14.60/case. To  simplify  situation a  f o r two  our  markets:  representative  situation shows  situation  S t a t e s , and diagram We  have  markets i n Chapter a  U.S.  of 5.1  for  United  we  a r e p r e s e n t a t i v e Canadian  market.  a  Diagram  5.1  drew  the  market  and  shows  the  (a)  i n Canada, diagram  r e p r e s e n t a t i v e market  in  estimated  the  demand curves  i n Canada  States.  The  and  D  us  demand  5.1  United  of  i s shown  on  diagram -*  5.1  as  D  „ and  rB  coopCAN  these  as D  CAN  for  for a representative curve  facing  the  o p e r a t i v e i s the d e r i v e d demand curve l e s s t r a n s p o r t a t i o n This  (b)  aggregate  i n each  4 and are presented on diagram  5.1  the  (c) shows the s i t u a t i o n f o r the  r e p r e s e n t a t i v e market  market  illustration,  of a r e p r e s e n t a t i v e market  the  market.  graphical  D  n5  .  coopuS  The  co-  costs.  marginal -*  revenue curves are d e r i v e d from the c o - o p e r a t i v e ' s d e r i v e d demand curves l e s s t r a n s p o r t a t i o n c o s t s 'in each market and are shown on  diagram  5.1, as w e l l .  The marginal  markets and i s shown on diagram 5.1, We  use t h e h i g h e r  because t h i s in  order  who  marginal  cost  i s t h e same  in  91 all  as w e l l .  cost  f o r our supply  function  i s t h e minimum p r i c e that t h e growers' must r e c e i v e  t o stay i n p r o d u c t i o n .  In the short-run, t h e growers  are r e c e i v i n g l e s s than t h e i r c o s t - o f - p r o d u c t i o n w i l l stay i n  production industry.  but i n t h e long-run,  these  growers  Conversely, t h e low cost producers  economic p r o f i t s . production.  will  leave t h e  are making p o s i t i v e  Hence, they are t h e ones who want t o i n c r e a s e  As we have mentioned  i n chapter  want t o i n c r e a s e p r o d u c t i o n , the f a c i l i t y  1, i f t h e growers  at WGGCA must i n c r e a s e  i n order t o handle the a d d i t i o n a l products. In is  our model, we hypothesize t h a t the m o n o p o l i s t i c s i t u a t i o n  t h e base  alternative base  scenario  scenario.  s c e n a r i o because  selling  desk,  tomatoes. marginal  and t h e competitive  is  the  as  our  We use t h e m o n o p o l i s t i c s i t u a t i o n this  i s the most  extreme  i n t h a t there i s no competition  In t h i s  case,  WGGCA w i l l  revenue equals marginal  demand curve.  situation  case  of single  f o r B.C. Hothouse  set quantity sold  cost and charge  at where  a price  on t h e  The o p t i m a l p r i c e and q u a n t i t y i n a r e p r e s e n t a t i v e  Canadian market a r e shown as P* „ and Q* , i n f i g u r e 5.1. CAN  In  the  discriminates elasticities people compare  other because i n each  markets, from  CAN  we  chapter  market  assume  that  4, we found  are d i f f e r e n t .  a t WGGCA analyze what t h e competitors themselves  against  their  competitors.  WGGCA that  price  the price  In r e a l i t y , t h e a r e doing  and they  They make  their  92  marketing  s t r a t e g i e s based on these i n f o r m a t i o n .  G e t t i n g back t o  our h y p o t h e s i z e d model, we assume t h a t WGGCA maximizes p r o f i t s by price discriminating. at where marginal  In t h i s case, WGGCA w i l l set q u a n t i t y s o l d  revenue equals marginal cost and charge a p r i c e  on the demand curve, as shown on diagram 5.1 For our a l t e r n a t i v e  s c e n a r i o , we assume t h a t WGGCA  i n a c o m p e t i t i v e environment. price  and q u a n t i t y  supply  revenue  curve  individual  c  marginal  F o r each  consumers  l o s e area  co-operative  region,  the producers  adding by  area area  under  a  adding  (A + B + A + B ) , area 1  area  2  1  1  (C + C ) . 1  2  the producers  g a i n area  and  loses  society  area  2  monopolistic Area  area  2  2  measures  individual (A+B), t h e (C)  situation  by  (C) i s determined  From diagram 5.1 (c) , we observe (A+B) , the consumers l o s e area (C) i f WGGCA  i f  as  (A+B+C) i s determined  2  the  (A+B) i s determined by  (A + B + C + A + B + C ) , and area 1  welfare  and  (A+B+C) , and the s o c i e t y l o s e s area  operates  1  gain  marginal  curves  t h e welfare measures i n each  compared t o a c o m p e t i t i v e s i t u a t i o n . adding  demand  The t o t a l  of the  i n each market.  c  and t h e aggregate  the i n d i v i d u a l  revenue curves.  by adding  market.  the  demand curve  by adding  are determined  by the i n t e r s e c t i o n  This i s t h e p o i n t P and Q  We d e r i v e t h e aggregate  operates  In a c o m p e t i t i v e environment, t h e  i s determined  and demand.  (b).  can operate  that  (A+B+C) , under  a  m o n o p o l i s t i c environment as compared t o competitive environment.  5.2  In t h i s we m e a s u r e d  s e c t i o n , we p r o v i d e  a s t e p - b y - s t e p p r o c e d u r e o f how  t h e economic w e l f a r e  impacts o f marketing r e g u l a t i o n s  and c o - o p e r a t i v e of  t h e demand  function  structure. function  marginal  cost  price.  the  price.  competitive  demand  functions  and i n t e r c e p t  we w i l l  We h a v e  determine t h e  assumed t h a t t h e  facing  market.  We a d d t h e c h a n g e  consumer  surplus,  surplus,  q u a n t i t y and  and q u a n t i t y and  and t h e l o s s t o s o c i e t y i n each  i n producer surplus,  change  t h e model t o  we c a n d e t e r m i n e t h e g a i n s t o  a n d t h e change thetotal  price  equilibrium  WGGCA a n d t h e  and optimal  the optimal  p r o d u c e r s , t h e l o s s t o consumers,  i n consumer  facing  function  p r i c e and q u a n t i t y ,  change  demand  we a r e g o i n g t o s i m u l a t e  Once we h a v e  t o derive  demand  i s equal t o the competitive  equilibrium quantity  market  and t h e i n v e r s e  Later,  i n each market.  function,  competitive  optimal  function.  the inverse  cost  and i n t e r c e p t  Then, we d e t e r m i n e t h e s l o p e  function  From  marginal obtain  function  market  and t h e i n v e r s e  t h e m a r g i n a l revenue  marginal cost  We d e t e r m i n e t h e s l o p e  i n each  i n each market  WGGCA i n e a c h m a r k e t . of  94  SIMULATION MODEL USED TO MEASURE THE ECONOMIC WELFARE IMPACTS OF B.C. GREENHOUSE TOMATOES  i n dead-weight  t h e change i n loss  i nproducer surplus,  and t h e t o t a l  change  i n each the total  i n dead-weight  loss. Before procedure use  preceding  with  f o r our simulation  the discussion model,  t h e r e s u l t s from t h e l i n e a r  log-log  form  f o rour analysis.  of the  estimation  we want t o m e n t i o n t h a t  f u n c t i o n a l form r a t h e r A l t h o u g h we have  we  than t h e  estimated the  demand  equations  priori, is  u s i n g t h e l i n e a r form  economic theory  the most  linear  functional  analysis  does not i n d i c a t e  appropriate. form  Hence, we  rather  it  will  which  use the r e s u l t s the l o g - l o g  because the absolute value  of own p r i c e  exhibit  constant  form, a  functional  than  demand i n c r e a s e s as p r i c e i n c r e a s e s .  95  and the l o g - l o g  from  form  That  the  f o r our  elasticity  I f we use the l o g - l o g  elasticity.  form  of  form,  i s , the demand  curve  i s convex; at low p r i c e s i t i s r e l a t i v e l y f l a t and at high p r i c e s it  i s relatively  elasticity  steep.  Therefore,  we  can  use  the  assumption i f p r i c e s do not f l u c t u a t e much.  the p r i c e  of most p e r i s h a b l e produce f l u c t u a t e s  over  periods.  T h i s i s t r u e f o r greenhouse v e g e t a b l e s .  However, short  form.  D e t e r m i n a t i o n o f t h e Demand F u n c t i o n s , t h e Inverse Demand F u n c t i o n s , t h e I n v e r s e Demand F u n c t i o n s F a c i n g t h e C o - o p e r a t i v e , and t h e M a r g i n a l Revenue F u n c t i o n s  First, of  time  Hence, we use  the r e s u l t s from the l i n e a r form r a t h e r than the l o g - l o g  5.2.1  constant  we are going  the demand  equation  t o determine  i n each  the slope and  market.  We  intercept  can determine  the  slope and the i n t e r c e p t of the demand equation from the estimated coefficient.  The demand equation i s expressed as: PCQT -ft+ P RPT + P RPV + P RPCY + ^T, it  The  slope  «• • coefficients  of  the  , because  2  demand  it  3  U  equation  dPCQT =  ~ 6, .  4  is  U  the  estimated  price  We can o b t a i n the i n t e r c e p t dRPT ^ by adding the i n t e r c e p t of a l l other c o e f f i c i e n t s . That i s , the 2  96 intercept use  this  demand  t o d,  i s equal method  t o estimate  o f B.C. H o t h o u s e  d, = P, + $ RPV + $ RPCY + $ T .  where  3  t h e slopes  tomatoes  it  4  U  and i n t e r c e p t s  i n a l lregions.  t  We  for  the  5  T a b l e 5.1  presents these r e s u l t s . In the we  diagram  5.1, we p l o t  curves  using  y - a x e s a n d q u a n t i t i e s demanded a s t h e x - a x e s . need  t o determine  demand f u n c t i o n  t h e inverse  demand  function  inverse  demand  In this  function.  o f the inverse  demand f u n c t i o n  case,  The i n v e r s e  i s the inverse of  e s t i m a t e d p r i c e c o e f f i c i e n t and t h e i n t e r c e p t  demand  p r i c e s as  i s expressed mathematically as:  Hence, t h e s l o p e the  t h e demand  i s (-ocyp.,) . functions  The s l o p e s  i n each market  of the inverse  and i n t e r c e p t s are estimated  of  the  and these  r e s u l t s a r e p r e s e n t e d t h r o u g h o u t T a b l e 5.1, a s w e l l . Next, The  we d e t e r m i n e t h e i n v e r s e  inverse  function respective has  demand  i n each  transportation  decision  United  States,  curves  less  affects  facing  the transportation  cost  cost  demand i n each  i n Canada, t h e c o - o p e r a t i v e into  the final  f o r the product.  WGGCA.  WGGCA i s t h e i n v e r s e  F o r t h e markets  costs  account price  because t h e that  the  co-  This,  i neffect, affects the  made b y t h e c o - o p e r a t i v e .  F o r t h e markets i n  t h eco-operative  exchange r a t e  demand  facing  transportation  receives  sales  and  market  market.  t o take  operative  function  demand c u r v e  i n t o account  facing  has t o take  transportation  f o r s i m i l a r reason.  WGGCA a r e shown on f i g u r e  cost  The i n v e r s e  5.1 (a) a s D  and  figure  function and  5.1  (b) as D  operative  that 18  o f the i n v e r s e demand  i s the i n t e r c e p t  transportation  markets.  97 The slope of t h e i n v e r s e demand  .  f a c i n g WGGCA i s the same as the i n v e r s e demand f u n c t i o n  the i n t e r c e p t  costs  coopEXP  o f the i n v e r s e  c o s t s i n the Canadian  have  been  curve  adjusted  These c a l c u l a t i o n  facing  demand  the c o -  curve  less  markets and t r a n s p o r t a t i o n  f o r exchange  are determined  rates  in  U.S.  and the r e s u l t s are  p r e s e n t e d i n Table 5.1, as w e l l . Next, total  we  determine  the marginal  revenue  revenue i s equal t o p r i c e times  function.  Since  q u a n t i t y and i s expressed  m a t h e m a t i c a l l y as: TR = RPT * PCQT = (—)' PCQT +  P  =  we  can determine  first  quantity.  ("^)'( PCQT)  2  the marginal  derivative  of  total  *PCQT ,  revenue  revenue  =  function  function  = 2(—)'PCQT  5 7 7 ?  bPCQT  this  + (-^-y  by  with  t a k i n g the respect  to  Mathematically, marginal revenue i s w r i t t e n as: MR  From  (-?±y*PCQT Pi  2  equation,  revenue curve  we  know  i s 2 times  +  py  that  (-%. P Y  the slope  o f the  marginal  the slope of the i n v e r s e demand  curve  f a c i n g the c o - o p e r a t i v e and the i n t e r c e p t o f the marginal revenue  The w i t h  t r a n s p o r t a t i o n p e o p l e  i n  the  c o s t s f i e l d .  to  each  r e g i o n  are  b a s e d  on  p e r s o n a l  i n t e r v i e w s  curve i s the same as the i n t e r c e p t facing  the c o - o p e r a t i v e .  We  have  98 f o r the i n v e r s e demand curve calculated  the slopes  and  i n t e r c e p t s o f the marginal revenue f u n c t i o n and we have p r e s e n t e d the  r e s u l t s i n Table 5.1, as w e l l .  Table 5.1: Results from the determination of the demand functions, the inverse demand functions, the inverse demand functions facing the co-operative and the marginal revenue functions.  B.C. Prairie Regions of Canada Eastern Canada Washington Oregon California Other Parts of United States  Estimated Coefficients for the linear form CONSTANT RPT RPV RPCY T 6.3612 -63.189 17.448 -0.64673 -0.34925 -24.741 -23.231 13.127 2.6477 -0.08554 0.63212 -6.6645 1.3637 0.045596 -0.14422 -11.443 1.1341 -5.2395 130.72 -0.25105 7.3561 16.297 -12.603 54.153 -0.09101 -17.742 -2.0132 1.0078 107.06 0.17023 -0.15248 -3.1071 0.66159 -1.7071 0.019888  Calculations Slope-Demand Intercept-Demand Slope-Inverse Demand Intercept-Inverse Demand Slope-Derived Demand Intercept-Derived Demand Slope-Marginal Revenue Intercept-Marginal Revenue  BC -63.18900 15.78804 -0.01583 0.24985 -0.01583 0.24902 -0.03165 0.24902  PRAI -23.23100 5.37460 -0.04305 0.23135 -0.04305 0.22214 -0.08609 0.22214  EAST -6.66450 1.38611 -0.15005 0.20798 -0.15005 0.18848 -0.30010 0.18848  Calculations Slope-Demand Intercept-Demand Slope-Inverse Demand Intercept-Inverse Demand Slope-Derived Demand Intercept-Derived Demand Slope-Marginal Revenue Intercept-Marginal Revenue  Wash 1.13410 0.46622 0.88176 -0.41109 0.88176 -0.41506 1.76351 -0.41506  Ore 16.29700 -0.55430 0.06136 0.03401 0.06136 0.03004 0.12272 0.03004  Cal -2.01320 0.76270 -0.49672 0.37885 -0.49672 0.37110 -0.99344 0.37110  Other -3.10710 0.45278 -0.32184 0.14573 -0.32184 0.13599 -0.64369 0.13599  99 5.2.2  Determination of the Competitive and the Optimal Solutions  Our  next  solutions  step  i s t o determine  and the optimal  o f Canada,  s o l u t i o n s f o r each  dollars  per  California,  case  index  and  the  market.  We  The p r i c e s f o r B.C.,  Canada  have  Prairie  are measured i n Canadian  prices  for  Washington,  Oregon,  and other p a r t s of U n i t e d States are measured i n U.S.  d o l l a r s per case. simulation  and E a s t e r n  Solutions  the c o m p e t i t i v e e q u i l i b r i u m  estimated the p r i c e s i n r e a l terms. regions  Equilibrium  A l l the p r i c e  model  o f food  have  i n each  been  data t h a t we  adjusted  region.  using  have used i n our  the  The CPI of food  consumer  price  i s measured i n  1986 as 100 i n Canada and 1982-84 as 100 i n U n i t e d S t a t e s .  The  q u a n t i t i e s are measured i n cases per thousand people per month i n each r e g i o n . the  The reason  that we have estimated  q u a n t i t i e s of the competitive  optimal  situation  equilibrium situation  f o r our s i m u l a t i o n model u s i n g these  because we have estimated the demand equations such  terms.  RPCY,  and  estimation generate  We T  like  Hence,  ones  demand  and  that  i n chapter  the  those  have as  that  generated  well. we  terms i s  as  RPV,  f o r the  I f we  d i d not  used  f o r the  have  4, we w i l l change the s l o p e s and the demand equations  results  the optimal  we  and the  i n chapter 4 u s i n g  the other v a r i a b l e s such  equations,  of the estimated  affecting  solutions  the  variables like  demand equations intercepts  have generated  of the  the  the p r i c e s and  of  the  i n each  competitive  s o l u t i o n s i n each  market.  equilibrium  market.  For our  s i m u l a t i o n model, we used the average monthly data f o r 1994.  As  we  equations demand does  have  mentioned  i n Chapter  4,  100 demand  the estimated  f o r Washington and Oregon do not e x p l a i n much about the  f o r B.C. Hothouse tomatoes not  sell  therefore, estimates  much  these  of  two  i n these  i t s products  markets  are  o f the demand equations  to  two r e g i o n s . these  two  insignificant.  i n these  WGGCA  markets; Since  two markets  the  f o r the  l i n e a r f u n c t i o n a l form have unexpected signs, we assumed t h a t the own  price  elasticity  at the mean  elastic  demand  percent,  q u a n t i t y demanded decreases  we  curve  a l s o assumed t h a t  equal t o -1, as w e l l .  implies  i s equal  that  the slope  as  t o -1.  price  A unitary  increases  by 1 p e r c e n t .  by  1  Furthermore,  o f the i n v e r s e demand  curve i s  We w i l l use these i n f o r m a t i o n t o determine  the c o m p e t i t i v e e q u i l i b r i u m s i t u a t i o n and the optimal s o l u t i o n i n these  two markets  markets  (B.C.,  California, the  (Washington and Oregon) . Prairie  Regions  of  For the r e s t  Canada,  Eastern  and other p a r t s of U n i t e d S t a t e s ) , we w i l l  competitive  equilibrium situation  and the optimal  o f the Canada,  determine situation  u s i n g the estimated equations t h a t we have d e r i v e d i n Chapter We  determine  market, f i r s t .  marginal  cost  function.  a l l markets.  market  situation  equilibrium situation  The competitive  a p p l i e d the higher for  competitive  The c o m p e t i t i v e  5.2 i s p o i n t C. to  the  equilibrium price  As we  have  c o s t as the marginal  mentioned  in  4. each  i n diagram  i s the equal earlier,  we  cost and i t i s the same  However, the marginal cost f i g u r e s t h a t we have  are f o r 1993 but we have used 1994 data i n our s i m u l a t i o n model. To  convert  the marginal  cost  figures  back  t o 1994 d o l l a r s ,  we  need  t o determine  products.  the rate  of i n f l a t i o n  of producing  101 farm  From Farm Input P r i c e Index, we found t h a t t h e average  F I P I o f a l l - i t e m s i n B.C. i n 1993 i s 116.375 and t h e average F I P I of  all-items  i n B.C. i s 120.65, an i n c r e a s e  implies that the cost-of production is  o f 3.67%.  f o r the high cost  This  producers  $15.15 p e r case and t h e c o s t - o f - p r o d u c t i o n f o r t h e low c o s t  producers  i s $13.63 p e r case.  We a d j u s t e d t h e m a r g i n a l  cost i n  each market u s i n g t h e a p p r o p r i a t e consumer p r i c e index o f f o o d i n each market. are  The c o m p e t i t i v e e q u i l i b r i u m p r i c e s f o r each market  d e t e r m i n e d and t h e r e s u l t s  knowing t h e c o m p e t i t i v e competitive  are presented  equilibrium price,  equilibrium quantity.  quantity  f o r a l l markets  expressed  mathematically as: PCQT  C  =  other  competitive  Washington presented  5.2. By-  we can determine t h e  The c o m p e t i t i v e e q u i l i b r i u m  than  Washington  and Oregon i s  ((/^ )/(J-)')-((-|L)7(J_y). c  P2  The  i n Table  P  2  P2  e q u i l i b r i u m q u a n t i t i e s f o r a l l markets  and Oregon  a r e determined  i n Table 5.2, as w e l l .  except  and t h e r e s u l t s a r e  Diagram 5.2:  Form  102 •  equilibrium quantities  and the  A Market Model Using L i n e a r F u n c t i o n a l  Price  P* B  P =MC  \ \  C  u  Q*  By symmetry, competitive  Q  Quantity  c  the competitive  equilibrium  prices  Washington and the market 5.3.  coop  are the same  i n Oregon.  This  f o r the market  in  i s shown on Diagram  The r e s u l t s are p r e s e n t e d i n Table 5.2, as w e l l .  103 Diagram 5.3: A L i n e a r Demand Curve with E l a s t i c i t y at Mean of -1 and a Slope of -1  Finally, optimal  price  quantity  and  revenue  we in  function  a  each  optimal  maximizes p r o f i t charges  are going t o determine  price  q u a n t i t y of B.C.  market. price  and  in  the  We  the optimal q u a n t i t y and  can  each  determine  market  marginal  cost  from  the the  function.  optimal marginal A  where marginal revenue equals marginal cost, on  the  demand  curve.  The  firm and  optimal p e r - c a p i t a  Hothouse tomatoes consumed i n a l l markets except  Washington and Oregon i s equal t o : MC-(-^y PCQT*  a.  py  =  2(-f)' p  and  the  optimal p r i c e  of B.C.  2  Hothouse tomatoes  except Washington and Oregon i s equal t o : RPT*  =  1  (—ypcQT* $2  +  ( - a, ^Y  P  2  i n a l l markets  F o r Washington and Oregon, t h e o p t i m a l q u a n t i t y i s o n e - h a l f o f  104  t h e c o m p e t i t i v e q u a n t i t y and t h e o p t i m a l p r i c e i s one-and-onehalf of the optimal price.  T h i s i s shown i n D i a g r a m 5.3. The  optimal p r i c e s and optimal q u a n t i t i e s are determined f o r a l l markets and t h e r e s u l t s are presented  T a b l e 5.2.  We h a v e s u m m a r i z e d t h e r e s u l t s t h a t we h a v e o b t a i n e d monopolistic situation, situation  for the  t h e c o m p e t i t i v e s i t u a t i o n and t h e a c t u a l  i n T a b l e 5.2. Monopolistic Situation  Actual Situation  Price 0.18224 0.17071 0.15659 0.10244 0.10253 0.21969 0.09912  Price 0.1267 0.1495 0.1370 0.1018 0.0957 0.1006 0.0850  Quantity 4 .21951 1.19490 0.21251 0.03415 0.03418 0.30481 0.11457  Competitive Situation  Quantity 10.0660 2.0796 0.5100 0.4442 0.6640 0.6171 0.1744  Price Quantity 0.11546 8. 43902 0.11927 2.38980 0.12470 0.42503 0.06829 0.06829 0.06835 0.06835 0.06829 0.60962 0.06224 0.22914 r a i , and East and t h e y a r e m e a s u r e d i n US $ / c a s e i n Wash, O r e , C a l i f , a n d Other. T h e s e r e s u l t s h a v e b e e n a d j u s t e d u s i n g t he c o n s u m e r p r i c e index o f food i n each r e g i o n . * * Q u a n t i t y a r e measured i n cases/thousand people/month i n each region.  BC Prai East Wash Ore Calif Other  From t h e r e s u l t s i n T a b l e the  highest  the  actual  situation.  p r i c e under t h e m o n o p o l i s t i c situation, This  the co-operative situation, then in  i s true  and then  receives  situation,  f o l l o w e d by  the competitive  equilibrium  f o r a l l markets.  I t i s expected  that  c a n r e c e i v e t h e h i g h e s t p r i c e under t h e monopoly  followed  the competitive t h e marketplace  therefore,  5.2, we f o u n d t h a t WGGCA  i t cannot  by t h e m o n o p o l i s t i c situation. with  other  This  competitive  situation,  i s b e c a u s e WGGCA c o m p e t e s  vegetable  charge p r i c e s that  producing  companies;  a r e out o f t h e range o f  other  vegetables.  Otherwise,  Hothouse tomatoes w i t h cannot  charge  prices  than  as  monopoly  types  prices.  desk;  105 s u b s t i t u t e B.C.  will  of vegetables.  However,  the p e r f e c t l y competitive  a single selling  the  others  consumers  therefore,  Hence, WGGCA  WGGCA r e c e i v e s  situation  because  higher i t acts  i tcan b e t t e r bargain  with  wholesalers. An  unexpected  situation  consumption  o f B.C. H o t h o u s e  Washington,  Oregon  scenario,  these  situation  that  rather B.C.  than  because  WGGCA  monopolist  vegetable  they  f o r the actual  scenario  and then t h e  sell  more o f t h e i r p r o d u c t s  the monopolistic  scenario  because  a pure  greenhouse  other  than  the actual  two ranges  i s highest  Canada,  I n o u r m o d e l , we h a v e assumed t h a t B.C.  greenhouse tomato growers can s e l l  expected  the per-capita  i n B.C., E a s t e r n  by t h e c o m p e t i t i v e  scenario.  competitive  i n which  tomatoes  and C a l i f o r n i a  followed  monopolistic  arises  will i s a  situation. somewhere  monopolistic  o r a pure  producers their  fall  competitor.  do n o t compete  products  under  i n the  a  We  between  competitor That i s , with  each  single-selling  desk.  5.2.3  Determination  Now t h a t the  of  the Economic Welfare  we h a v e t h e c o m p e t i t i v e  monopolistic  solutions  f o r each  determine t h e economic w e l f a r e  Measures  e q u i l i b r i u m s o l u t i o n s and market,  we  are going  e f f e c t s f o r each market.  case s c e n a r i o f o r t h e economic w e l f a r e  effect  to  The b a s e  i sthe monopolistic  situation  and  situation. on  the a l t e r n a t i v e  We have determined  our d i s c u s s i o n  that loses  the  producers  in a l l  1 of t h i s  i n Table 5.3.  gain,  the  106 competitive  i s the  the economic welfare e f f e c t s based  i n section  p r e s e n t e d these r e s u l t s  scenario  chapter  and we  have  From our r e s u l t s , we know  consumers  lose,  and t h e  sc  markets.  Table 5.3 : Results from tl ie Simulation Model Producers Gain Consumers Lose Society Loses 0.28176 0.42264 BC 0.14088 0.06146 Prai 0.09219 0.03073 0.00676 0.01016 East 0.00339 0.00116 Wash 0.00175 0.00058 0.00117 Ore 0.00175 0.00058 0.04615 0.06922 Calif 0.02307 0.00422 0.00634 Other 0.00211 *Measured i n $/case/thousand people/month. Since each  we have  market,  estimated  the welfare  we can sum t h e economic  economic  welfare  market t o determine t h e t o t a l economic welfare doing t h a t ,  effects  Before  we a r e going t o convert e v e r y t h i n g back i n t o  nominal  a r e presented  i n Table  s o l d f o r each market.  5.4.  Table  BC Prai East Wash Ore Calif Other Total  Simulated Results i n Terms of Nominal 1994 $  Monopolistic Situation Price Quantity 23.9117 15543.41 21. 6836 5813.79 19.0241 3880.65 22.7266 182.70 22.7256 105.55 48.7388 9586.97 24.1259 12924.64 48036.71  *Quantities  a r e expressed  Competitive Situation Price 15.15 15.15 15.15 15.15 15.15 15.15 15.15  i n thousand cases,  These  5.5 p r e s e n t s t h e  w e l f a r e measures i n nominal 1994 Canadian d o l l a r s . Table 5.4:  i n each  effects.  Canadian d o l l a r and t o t a l q u a n t i t i e s results  effects for  Quantity 31086.82 11627.57 7761.47 365.35 211.07 19171.94 25849.28 96073.51  107  Table 5.5: Welfare Results In Terms of Nominal 1994 $ Producers Gain Consumers Lose Society Loses 136194.52 BC 204291.8 68097.3 37986.75 56980.1 Prai 18993.4 15034.85 22552 . 6 East 7517.8 1384.20 Wash 2076.1 691.9 799.65 1199.4 Ore 399.7 321977.90 Calif 482966.8 160988.9 116019.40 174029.2 Other 58009.7 629397.30 Total 944096.0 314698.7 ^Economic w e l f a r e e f f e c t s are measured i n Thousand Canadian $. The  results  extreme  that  cases.  scenario w i l l  The economic not be as l a r g e  the extreme case, consumers  we have  lose  presented welfare  effects  5.5 are  for  f o r the actual  as the ones c a l c u l a t e d  t h e producers g a i n  $944,096.00  i n Table  here.  In  $629,397.30 p e r month, t h e  p e r month,  and t h e s o c i e t y  loses  $314,698.70 per month.  5.2.4  The P o s s i b i l i t i e s of Remaining As a S i n g l e - S e l l i n g Desk After Privatization I f t h e greenhouse growers i n B r i t i s h Columbia remain u n i t e d  after privatization,  then, WGGCA w i l l  desk.  happen  This  might  produced by a few growers. price  because Also,  remain as a s i n g l e - s e l l i n g most  o f t h e products a r e  t h e growers r e c e i v e a premium  f o r greenhouse products because WGGCA markets i t s products  under t h e BC Hothouse  label.  I f the greenhouse growers do not  market t h e i r p r o d u c t s under the BC Hothouse l a b e l , they might not be able t o r e c e i v e the premium p r i c e s because greenhouse products and f i e l d  products  a r e very  similar.  In t h i s  case,  WGGCA  will  remain  as a s i n g l e - s e l l i n g  desk  f o r B.C. greenhouse  108 vegetable  growers even i f i t i s p r i v a t i z e d .  5.3  CONCLUSIONS AND RECOMMENDATIONS  The  purpose  of t h i s  study  i s t o determine  should remain as a c o - o p e r a t i v e or whether This  issue  factors of  came  about  as a r e s u l t  facing the co-operative.  one-member-one-vote  finance there  i s the issue  increasing parts  o f Canada,  Internally,  from  more  United  the co-operative  decisions quickly.  and e x t e r n a l  there  i s the issue  of r a i s i n g  market States,  capital  to  Externally,  responsive. Mexico,  has t o make  WGGCA  privatize.  at the c o - o p e r a t i v e .  o f being  competition  i t should  of internal  and the i s s u e  additional f a c i l i t i e s  whether  With  and other  i t s business  Hence, t h e r e was a need t o c o n s i d e r about t h e  r e s t r u c t u r i n g of the co-operative. Western  Greenhouse  important  because  greenhouse  vegetables  been very last  five  because  i t sells  successful. years.  i t pools  Growers'  maintain  approximately  produced i n B r i t i s h Sales have  As a resources  r e s e a r c h and development, to  Co-operative  Association i s  96.5% o f a l l Columbia.  i n c r e a s e d very  co-operative, together  the  WGGCA has  rapidly  i n the  i t has i t s advantages  f o r professional expertise,  a d v e r t i s i n g and marketing, and c a p i t a l  and expand f a c i l i t i e s at the c o - o p e r a t i v e .  The c o - o p e r a t i v e  i s e f f e c t i v e at r e s t r i c t i n g  entry i n t o the  i n d u s t r y because greenhouse tomato growers i n the Lower Mainland-  Fraser  Valley  region  and t h e Vancouver  109  Island  and t h e G u l f  I s l a n d s need quotas t o produce greenhouse tomatoes. B.C. V e g e t a b l e  Scheme, t h e B r i t i s h  Columbia M a r k e t i n g  Commission has t h e power t o promote, production, regulated  t r a n s p o r t a t i o n , packing, vegetables  control storage  i n the Province  year  f o r quota  allocate  quotas  exclusive  By  Columbia.  and i t n o r m a l l y  and i t a l s o  domestically  gives  produced  them t h e greenhouse  i s established  under  the Natural  Products  how  t h e B.C. greenhouse  vegetable  industry  and by knowing i t s r e g u l a t o r y environment, we were a b l e  construct  and e s t i m a t e  a market  model.  Our market  estimate  statistical  B.C., Oregon,  o u r demand technique.  equations, We e s t i m a t e d  we  Region  California,  o f Canada,  and o t h e r  Eastern  parts  dependent  on r e a l  price  into  side.  econometrics, equations  seven  Canada,  of United  N o r t h e a s t e r n U n i t e d S t a t e s and t h e Midwest. are  used  t h e demand  WGGCA d i v i d e s i t s s a l e s r e g i o n Prairie  model  The demand r e p r e s e n t s t h e  consumption s i d e and t h e supply r e p r e s e n t s t h e p r o d u c t i o n  market.  takes  Scheme i s e s t a b l i s h e d under t h e  c o n s i s t s o f demand and s u p p l y c u r v e s .  To  of  (B.C.) A c t . knowing  operates  sell  The B.C. V e g e t a b l e  and BCVMC  Marketing  to  to  and m a r k e t i n g  BCVMC g i v e s WGGCA t h e r i g h t t o  t o i t s producers  right  vegetables. BCVMC  allocation.  Vegetable  and r e g u l a t e t h e  of British  Greenhouse tomatoes a r e r e g u l a t e d p r o d u c t s a  Under t h e  a by  markets: Washington,  States  such as  Our demand f u n c t i o n s  o f B.C. Hothouse tomatoes i n each  market, t h e r e a l p r i c e index o f f r e s h v e g e t a b l e s o r f r e s h f r u i t s  and  vegetables  in  each  market,  income i n each market, and  an  the  real  110 personal  per-capita  annual time t r e n d .  Our  dependent  v a r i a b l e i s the p e r - c a p i t a consumption of B.C.  Hothouse tomatoes  i n each market.  using  These equations  of monthly data different  from 1988  sources.  We  r e s u l t s are p r e s e n t e d The  supply  schedule.  and  the  1994.  have  The  estimated  i n chapter  Stennes'  the  growers must r e c e i v e i n order  found i n 1993  s i m u l a t i o n model because t h a t  Farm Input P r i c e Index, we  used an  to  adjust  1994  these  and  that  the  i s $14.61 per  figures into  results  model  to  of  the  determine  operative  under the  private.  We  monopolistic  case  i n 1993  i n production.  inflation  is  terms.  Based  f a c t o r of  Hence,  f o r the l a r g e growers i s $13.63 per  the  the  cost-of-  the  situation  competition.  the  present  hypothesized  and  impacts  regulatory  of  the  our  model, we  remaining  company  as  a  versus  operates  we co-  going  under a  operates  under  have assumed t h a t WGGCA  a u t h o r i t y of the N a t u r a l Products  a c t s as a s i n g l e - s e l l i n g desk i n B.C.;  functions,  environment  private  cost-  case.  supply  that the c o - o p e r a t i v e  and In  demand  3.67%  cost-of-  f o r the small growers i s $15.15 per case and the  of-production  under the  equations  i s the minimum p r i c e t h a t  to stay  on  perfect  from  used the c o s t - o f - p r o d u c t i o n f o r small growers  our  a  gathered  f o r l a r g e growers i n B.C.  for  build  these  we  f o r s m a l l growers i n B.C.  $13.15 per case. We  From  are  years  4.  report,  cost-of-production  production  data  seven  f u n c t i o n i s determined u s i n g a c o s t - o f - p r o d u c t i o n  From  production  to  are estimated  Marketing  thereby,  (B.C.) Act  setting  quantity  s o l d at where marginal  revenue equals marginal  p r i c e on t h e demand curve.  Ill cost and charge a  I f WGGCA decides t o go p r i v a t e , t h e  worst s c e n a r i o would be competition amongst greenhouse growers i n B.C.  which  determined  would  lead  to perfect  t h e demand and supply  the economic w e l f a r e impacts being the  a p e r f e c t competitor. consumers  remaining  lose,  a monopolist  competition.  Therefore,  f u n c t i o n s and then  o f being a monopolist We found  we measured  as opposed t o  t h a t t h e producers  and t h e s o c i e t y  loses  as a  as oppose t o being a p e r f e c t  other  non-measured  tax  i m p l i c a t i o n s of a co-operative  management's operative our  time  factors  spent  on  i t i s best  of  competitor. There  t h a t we d i d not i n c l u d e such as versus  individual  a private  members  system as oppose t o a p r i v a t e f i r m .  model,  gain,  result  We have measured p a r t o f t h e whole p i c t u r e i n our model. are  we  i f WGGCA remains  opposed t o b e i n g a p r i v a t i z e company.  f i r m and  under  a co-  However, base on  as a c o - o p e r a t i v e as  112 BIBLIOGRAPHY  1.  Abrahamsen. A g r i c u l t u r a l Co-operation i n the U n i t e d S t a t e s . The P l u n k e t t Foundation f o r Co-operative Studies, Parchment L t d . , 1980.  2.  A g r i c u l t u r e Canada. 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(1994) "Marketing C o o p e r a t i v e s and Supply Management: The Case of the B r i t i s h Columbia D a i r y Industry," unpublished M.Sc. t h e s i s , Department of A g r i c u l t u r a l Economics, U n i v e r s i t y of B r i t i s h Columbia.  53.  K o t l e r , P h i l i p , Gordon McDougall, and Gary Armstrong. Marketing Canadian E d i t i o n . Scarborough: Prentice-Hall Canada Inc., 1988.  54.  Latham, S u s i e . (1993) "Marketing C o o p e r a t i v e s : A Model of the Output D e c i s i o n s of the C l o v e r d a l e L e t t u c e and Vegetable C o o p e r a t i v e , " unpublished M.Sc. t h e s i s , Department of A g r i c u l t u r a l Economics, U n i v e r s i t y of B r i t i s h Columbia.  55.  116 Maas, E.F. a n d R.M. Adamson. S o i l l e s s C u l t u r e o f C o m m e r c i a l G r e e n h o u s e Tomatoes. Ottawa: M i n s t e r o f S u p p l y and S e r v i c e s C a n a d a , 1980.  56.  M a d d a l a , G.S.. Introduction to Econometrics. M a c m i l l a n P u b l i s h i n g Company, 1988.  USA:  57.  McBride, Glynn. A g r i c u l t u r a l Cooperatives: T h e i r Why a n d T h e i r How. Connecticut: A v i P u b l i s h i n g Company, I n c . , 1986.  58.  Nahanni H o r t i c u l t u r a l S e r v i c e s . A Case S t u d y : Financial S t a t e m e n t s f o r a 10,000 sqm V e g e t a b l e G r e e n h o u s e O p e r a t i o n i n t h e B.C. Lower M a i n l a n d . Nanaimo: N a h a n n i H o r t i c u l t u r a l S e r v i c e s , A u g u s t 1991.  59.  Nahanni H o r t i c u l t u r a l S e r v i c e s . Preparing a Business Plan, a Guide f o r A g r i c u l t u r a l Producers: Greenhouse V e g e t a b l e Example. Victoria: B.C. M i n i s t r y o f A g r i c u l t u r e , F i s h e r i e s a n d F o o d , 1992.  60.  Nahanni H o r t i c u l t u r a l S e r v i c e s . 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Samuelson, W i l l i a m and Stephen Marks. (1992) Economics. F o r t Worth: The D r y d e n P r e s s .  65.  S e x t o n , R i c h a r d and J u l i e Iskow. F a c t o r s C r i t i c a l t o t h e Success or F a i l u r e o f Emerging A g r i c u l t u r a l C o o p e r a t i v e s . Oakland: G i a n n i n i F o u n d a t i o n I n f o r m a t i o n S e r i e s No. 88-3, 1988 .  66.  S o c i e t e - c o n s e i l Maheu-Noiseux. Innovative Challenge. Quebec: N o i s e u x , 1992.  Managerial  Financing Cooperatives: S o c i e t e - c o n s e i l Maheu-  An  67.  117 Stennes, Brad. (1995) Fresh Vegetable Costs and Returns at the Farm-Level f o r B r i t i s h Columbia Greenhouses and Competing Areas. B.C.: BCMAFF.  68.  Tomek, W i l l i a m and Kenneth Robinson. (1990) A g r i c u l t u r a l Product P r i c e s . T h i r d E d i t i o n . New York: Cornell U n i v e r s i t y Press.  69.  U n i t e d S t a t e s Department of A g r i c u l t u r e . Agricultural Cooperative Service. Cooperative Theory: New Approaches. Washington: USDA, ACS, S e r v i c e Report Number 18, 1987.  70.  USDA, Tennessee V a l l e y A u t h o r i t y . Tennessee V a l l e y Greenhouse Vegetable Workshop. Tennessee: Tennessee V a l l e y A u t h o r i t y , 1975.  71.  Van Der G u l i k , David. (1988) "BC Greenhouse Vegetable I n d u s t r y : A P r o f i l e , " unpublished B.Sc. paper, Department of A g r i c u l t u r a l Economics, U n i v e r s i t y o f B r i t i s h Columbia.  APPENDIX A: DATA TABLES  Table A1: Monthly Estimates of Population for Canada, and Selected Provinces* (in thousands) 1  Column 1 Yr/Mon  B.C.  Column 2  Column 3  Column 4  Column 5"  2  Column 6  Column 7  Column 8'  3  Column 9  Alta.  Man.  Sask.  Prairie  Ont.  Que.  East  Canada  198801  3088.53  2444.07  1101.10  1034.87  4580.03  9760.60  6823.57  16593.97  26667.73  198802  3092.47  2446.33  1101.70  1034.03  4582.07  9771.40  6826.33  16609.03  26687.77  198803  3096.40  2448.60  1102.30  1033.20  4584.10  9782.20  6829.10  16624.10  26707.80  198804  3100.47  2451.17  1102.83  1032.87  4586.87  9795.37  6833.37  16643.43  26733.17  198805  3104.53  2453.73  1103.37  1032.53  4589.63  9808.53  6837.63  16662.77  26758.53  198806  3108.60  2456.30  1103.90  1032.20  4592.40  9821.70  6841.90  16682.10  26783.90  198807  3115.13  2458.53  1104.17  1032.03  4594.73  9842.60  6848.07  16712.07  26820.87  198808  3121.67  2460.77  1104.43  1031.87  4597.07  9863.50  6854.23  16742.03  3128.20  26857.83  198809  2463.00  1104.70  1031.70  4599.40  9884.40  6860.40  16772.00  3137.03  26894.80  198810  2465.90  1104.33  1030.80  4601.03  6869.47  16804.80  26942.17  198811  3145.87  9911.07  2468.80  1103.97  1029.90  9937.73  6878.53  16837.60  26989.53  198812  3154.70  4602.67  2471.70  1029.00  4604.30  9964.40  6887.60  16870^40  27036.90  198901  3159.93  1103.60  2475.77  1103.77  1027.70  4607.23  9982.07  6893.73  16894.90  27070.17  2479.83  1103.93  1026.40  4610.17  9999.73  6899.87  16919.40  27103.43  2483.90  1104.10  1025.10  4613.10  10017.40  6906.00  16943.90  27136.70  2487.60  1104.50  1024.70  4616.80  10038.43  6912.83  16972.10  27174.90  2491.30  1104.90  1024.30  4620.50  10059.47  6919.67  17000.30  27213.10  2495.00  1105.30  1023.90  4624.20  10080.50  6926.50  17028.50  27251.30  2498.10  1105.60  1023.60  4627.30  10104.00  6933.67  17059.57  27293.97  2501.20  1105.90  1023.30  4630.40  10127.50  6940.83  17090.63  27336.63  2504.30  1106.20  1023.00  4633.50  10151.00  6948.00  17121.70  27379.30  2507.80  1105.87  1021.77  4635.43  10172.10  6955.57  17145.57  27421.53  2511.30  1105.53  1020.53  4637.37  10193.20  6963.13  17169.43  27463.77  2514.80  1105.20  1019.30  4639.30  10214.30  6970.70  17193.30  27506.00  2519.43  1105.33  1017.70  4642.47  10221.53  6973.47  17206.73  27526.20  2524.07  1105.47  1016.10  4645.63  10228.77  6976.23  17220.17  27546.40  2528.70  1105.60  1014.50  4648.80  10236.00  6979.00  17233.60  27566.60  2533.03  1106.00  1013.93  4652.97  10252.03  6985.20  17257.33  27600.63  2537.37  1106.40  1013.37  4657.13  10268.07  6991.40  17281.07  27634.67  2541.70  1106.80  1012.80  4661.30  10284.10  6997.60  17304.80  27668.70  2546.60  1107.33  1012.13  4666.07  10303.20  7005.30  17330.97  27709.33  2551.50  1107.87  1011.47  4670.83  10322.30  7013.00  17357.13  27749.97  3310.10  2556.40  1108.40  1010.80  4675.60  10341.40  7020.70  17383.30  27790.60  3320.10  2561.37  1108.30  1009.70  4679.37  10357.90  7027.77  17401.97  27829.10  3330.10  2566.33  1108.20  1008.60  4683.13  10374.40  7034.83  17420.63  27867.60  2571.30  1108.10  1007.50  4686.90  10390.90  7041.90  17439.30  27906.10  199101  3335.50 3340.90  2574.43  1108.43  1007.03  4689.90  10394.40  7044.07  17453.53  27921.27  199102  3346.30  2577.57  1108.77  1006.57  4692.90  10397.90  7046.23  17467.77  27936.43  199103  3357.47  2580.70  1109.10  1006.10  4695.90  10401.40  7048.40  17482.00  27951.60  199104  3368.63  2587.57  1110.23  1006.17  4703.97  10424.77  7059.13  17512.37  28007.77  199105  3379.80  2594.43  1111.37  1006.23  4712.03  10448.13  7069.87  17542.73  28063.93  199106  3390.50  2601.30  1112.50  1006.30  4720.10  10471.50  7080.60  17573.10  28120.10  199107  3401.20  2606.13  1112.67  1005.73  4724.53  10485.13  7087.60  17591.60  28157.30  199108  3411.90  2610.97  1112.83  1005.17  4728.97  10498.77  7094.60  17610.10  28194.50  199109  3418.40  2615.80  1113.00  1004.60  4733.40  10512.40  7101.60  17628.60  28231.70  2619.10  1113.50  1004.83  4737.43  10524.37  7106.47  17647.03  28260.37  198902 198903 198904 198905 198906 198907 198908 198909 198910 198911 198912 199001 199002 199003 199004 199005 199006 199007 199008 199009 199010 199011 199012  199110  3165.17 3170.40 3175.70 3181.00 3186.30 3193.93 3201.57 3209.20 3219.83 3230.47 3241.10 3246.93 3252.77 3258.60 3264.83 3271.07 3277.30 3284.90 3292.50 3300.10  Table A 1 : Monthly Estimates of Population for Canada, and Selected Provinces* (in thousands) -Continued from previous page 1  Yr/Mon  Column 1  Column 2  Column 3  Column 4  Column 5"  Column 6  Column 7  Column 8"  Column 9  B.C.  Alta.  Man.  Sask.  Prairie  Ont.  Que.  East  Canada  2  199111  3424 90  2622.40  1114.00  1005.07  4741.47  10536 33  7111 33  17665 47  28289 03  199112  3431 40  2625.70  1114.50  1005.30  4745.50  10548 30  7116 20  17683 90  28317 70  199201  3438 33  2629.27  1115.03  1005.90  4750.20  10563 63  7122 67  17705 63  28352 53  199202  3445 27  2632.83  1115.57  1006.50  4754.90  10578 97  7129 13  17727 37  28387 37  199203  3452 20  2636.40  1116.10  1007.10  4759.60  10594 30  7135 60  17749 10  28422 20  199204  3461 17  2640.60  1116.83  1007.57  4765.00  10611 47  7142 00  17773 90  28462 20  199205 199206  3470 13  2644.80  1117.57  4770.40  10628 63  3479 10  1118.30  4775.80  199207  28502 20 28542 20 28584 93  1119.17  4780.53 4785.27  17798 70 17823 50 17844 53  2657.93  1008.33 1008.17  10645 80 10663 17  7148 40 7154 80 7162 43  199208  3490 83 3502 57  2649.00 2653.47  1008.03 1008.50  199209  3514 30  1119.60  1008.00  4790.00  199210  3520 30  2662.40 2665.17  1120.03  1008.23  199211  3526 30  2667.93  1120.47  199212  3532 30  1120.90  199301  3538 73  2670.70 2673.47  199302  3545 17  2676.23  199303 199304  3551 60  1118.73  7170 07  17865 57  28627 67  4793.43  10680 53 10697 90 10707 60  7177 70 7181 37  17886 60 17902 63  28670 40 28693 97  1008.47  4796.87  10717 30  7185 03  17918 67  1008.70  4800.30  10727 00  7188 70  28717 53 28741 10  1121.50  1009.23  4804.20  10739 40  7195 03  17934 70 17954 13  1122.10  1009.77  4808.10  10751 80  17973 57  28800 83  2679.00  1122.70  1010.30  4812.00  17993 00  3559 03 3566 47 3573 90  2682.03 2685.07 2688.10  1123.73 1124.77 1125.80  1010.83 1011.37  7214 73 7221 77  18016 53 18040 07  28830 70 28867 33 28903 97  1011.90  4816.60 4821.20 4825.80  10764 20 10780 53 10796 87  7201 37 7207 70  10813 20  7228 80  2691.60  1126.03  1012.10  4829.73  10825 80  7236 00  18063 60 18078 87  28940 60  3584 63  199308  3595 37  2695.10  1126.27  1012.30  4833.67  10838 40  7243 20  18094 13  29012 20  199309  3606 10  2698.60  1126.50  1012.50  4837.60  10851 00  7250 40  18109 40  29048 00  199310  3613 00  2699.93  1126.70  1012.77  4839.40  10854 80  7253 07  18117 23  29063 47  199311  3619 90  2701.27  1126.90  1013.03  4841.20  10858 60  7255 73  18125 07  29078 93  199312  3626 80  2702.60  1127.10  1013.30  4843.00  10862 40  7258 40  18132 90  29094 40  199401  3633 77  2705.23  1127.73  1013.80  4846.77  10873 37  7262 43  18147 40  29120 63  199402  3640 73  2707.87  1128.37  1014.30  4850.53  10884 33  7266 47  18161 90  29146 87  199403 199404  3647 70 3654 60  2710.50  1129.00  29173 10  199405  3661 50  2714.30  1130.40  1015.73  4860.43  10906 13 10916 97  7270 50 7274 03 7277 57  18176 40  1129.70  4854.30 4857.37  10895 30  2712.40  1014.80 1015.27  15760 20 13344 00  29198 10 29223 10  199406  3668 40  2716.20  1131.10  1016.20  4863.50  10927 80  7281 10  10927 80  29248 10  199407  3678 97  2717.77  1131.20  1016.27  4865.23  10949 30  7285 10  13380 33  29285 97  199408  3689 53  2719.33  1131.30  1016.33  4866.97  7289 10  15832 87  29323 83  199409  3700 10  2720.90  1131.40  1016.40  4868.70  10970 80 10992 30  7293 10  18285 40  29361 70  199410  3731 80  2725.60  1131.70  1016.60  4873.90  11056 80  7305 10  25643 00  29475 30  199411 199412  3763 50 3795 20  2730.30 2735.00  1132.00 1132.30  1016.80 1017.00  4879.10 4884.30  11121.30 11185.80  7317 10 7329 10  33000 60 40358 20  29588 90 29702 50  199305 199306 199307  Source: Statistics Canada - Cat. No. 91-002, or C A N S I M : S E R I E S D1. D6, D7, D8, D9, D10, D11 '  1  " *  3  Generated from quarterly data by linear interpolation  2  Column 5 = (Column 2 + Column 3 + Column 4)  3  Column 8 =(Column 6 + Column 7)  28770 97  28976 40  Table A2: Monthly Estimates of Resident Population for the United States, and Selected States, Divisions, and Regions' (in thousands, including armed forces residing in each State) 1  Column 1 Column 2 Column 3 Column 4 Column 5 Column 6 Column 7 Wash. Ore. Cal. Northeast Midwest Other U.S.A. U.S. 4595.0 2724.3 28177.8 50466.5 59155.7 109622.2 243578.2 4604.0 2727.7 28235.0 50490.0 59175.3 109665.3 243762.3 4613.0 2731.0 28292.3 50513.5 59195.0 109708.5 243946.5 4622.0 2734.3 28349.5 50537.0 59214.7 109751.7 244130.7 4631.0 2737.7 28406.8 50560.5 59234.3 109794.8 244314.8 4640.0 2741.0 28464.0 50584.0 59254.0 109838.0 244499.0 4648.8 2745.2 28532.1 50598.4 59271.8 109870.3 244692.3 4657.7 2749.3 28600.2 50612.8 59289.7 109902.5 244885.7 4666.5 2753.5 28668.3 50627.3 59307.5 109934.8 245079.0 4675.3 2757.7 28736.3 50641.7 59325.3 109967.0 245272.3 4684.2 2761.8 28804.4 50656.1 59343.2 109999.3 245465.7 4693.0 2766.0 28872.5 50670.5 59361.0 110031.5 245659.0 4701.8 2770.2 28940.6 50684.9 59378.8 110063.8 245852.3 4710.7 2774.3 29008.7 50699.3 59396.7 110096.0 246045.7 4719.5 2778.5 29076.8 50713.8 59414.5 110128.3 246239.0 4728.3 2782.7 29144.8 50728.2 59432.3 110160.5 246432.3 4737.2 2786.8 29212.9 50742.6 59450.2 110192.8 246625.7 4746.0 2791.0 29281.0 50757.0 59468.0 110225.0 246819.0 4758.5 2796.6 29331.2 50763.7 59494.1 110257.8 247033.3 4771.0 2802.2 29381.3 50770.3 59520.2 110290.5 247247.7 4783.5 2807.8 29431.5 50777.0 59546.3 110323.3 247462.0 4796.0 2813.3 29481.7 50783.7 59572.3 110356.0 247676.3 4808.5 2818.9 29531.8 50790.3 59598.4 110388.8 247890.7 4821.0 2824.5 29582.0 50797.0 59624.5 110421.5 248105.0 4833.5 2830.1 29632.2 50803.7 59650.6 110454.3 248319.3 4846.0 2835.7 29682.3 50810.3 59676.7 110487.0 248533.7 4858.5 2841.3 29732.5 50817.0 59702.8 110519.8 248748.0 4871.0 2846.8 29782.7 50823.7 59728.8 110552.5 248962.3 4883.5 2852.4 29832.8 50830.3 59754.9 110585.3 249176.7 4896.0 2858.0 29883.0 50837.0 59781.0 110618.0 249391.0 4905.7 2863.3 29922.8 50847.3 59819.2 110666.5 249621.8 4915.3 2868.7 29962.5 50857.7 59857.3 110715.0 249852.5 4925.0 2874.0 30002.3 50868.0 59895.5 110763.5 250083.3 4934.7 2879.3 30042.0 50878.3 59933.7 110812.0 250314.0 4944.3 2884.7 30081.8 50888.7 59971.8 110860.5 250544.8 4954.0 2890.0 30121.5 50899.0 60010.0 110909.0 250775.5 4963.7 2895.3 30161.3 50909.3 60048.2 110957.5 251006.3 4973.3 2900.7 30201.0 50919.7 60086.3 111006.0 251237.0 4983.0 2906.0 30240.8 50930.0 60124.5 111054.5 251467.8 4992.7 2911.3 30280.5 50940.3 60162.7 111103.0 251698.5 5002.3 2916.7 30320.3 50950.7 60200.8 111151.5 251929.3 5012.0 2922.0 30360.0 50961.0 60239.0 111200.0 252160.0 5022.3 2926.6 30402.3 50974.1 60278.5 111252.6 252401.8 5032.7 2931.2 30444.5 50987.2 60318.0 111305.2 252643.7 5043.0 2935.8 30486.8 51000.3 60357.5 111357.8 252885.5 Z  Yr/Mon 198801 198802 198803 198804 198805 198806 198807 198808 198809 198810 198811 198812 198901 198902 198903 198904 198905 198906 198907 198908 198909 198910 198911 198912 199001 199002 199003 199004 199005 199006 199007 199008 199009 199010 199011 199012 199101 199102 199103 199104 199105 199106 199107 199108 199109  Table A2: Monthly Estimates of Resident Population for the United States, and Selected States, Division, and Region* (in thousands, including armed forces residing in each State) -continued from previous page Column 1 Column 2 Column 3 Column 4 Column 5 Column 6* Column 7 Yr/Mon Wash. Ore. Cal. NE MW Other U.S.A. U.S. 199110 5053.3 2940.3 30529.0 51013.3 60397.0 111410.3 253127.3 199111 5063.7 2944.9 30571.3 51026.4 60436.5 111462.9 253369.2 199112 5074.0 2949.5 30613.5 51039.5 60476.0 111515.5 253611.0 199201 5084.3 2954.1 30655.8 51052.6 60515.5 111568.1 253852.8 199202 5094.7 2958.7 30698.0 51065.7 60555.0 111620.7 254094.7 199203 5105.0 2963.3 30740.3 51078.8 60594.5 111673.3 254336.5 199204 5115.3 2967.8 30782.5 51091.8 60634.0 111725.8 254578.3 199205 5125.7 2972.4 30824.8 51104.9 60673.5 111778.4 254820.2 199206 5136.0 2977.0 30867.0 51118.0 60713.0 111831.0 255062.0 199207 5146.3 2981.8 30896.2 51131.3 60740.1 111871.3 255288.8 199208 5156.5 2986.7 30925.3 51144.5 60767.2 111911.7 255515.5 199209 5166.8 2991.5 30954.5 51157.8 60794.3 111952.0 255742.3 199210 5177.0 2996.3 30983.7 51171.0 60821.3 111992.3 255969.0 199211 5187.3 3001.2 31012.8 51184.3 60848.4 112032.7 256195.8 199212 5197.5 3006.0 31042.0 51197.5 60875.5 112073.0 256422.5 199301 5207.8 3010.8 31071.2 51210.8 60902.6 112113.3 256649.3 199302 5218.0 3015.7 31100.3 51224.0 60929.7 112153.7 256876.0 199303 5228.3 3020.5 31129.5 51237.3 60956.8 112194.0 257102.8 199304 5238.5 3025.3 31158.7 51250.5 60983.8 112234.3 257329.5 199305 5248.8 3030.2 31187.8 51263.8 61010.9 112274.7 257556.3 199306 5259.0 3035.0 31217.0 51277.0 61038.0 112315.0 257783.0 199307 5266.0 3039.3 31234.8 51286.9 61067.7 112354.6 257996.2 199308 5273.0 3043.5 31252.7 51296.8 61097.3 112394.2 258209.3 199309 5280.0 3047.8 31270.5 51306.8 61127.0 112433.8 258422.5 199310 5287.0 3052.0 31288.3 51316.7 61156.7 112473.3 258635.7 199311 5294.0 3056.3 31306.2 51326.6 61186.3 112512.9 258848.8 199312 5301.0 3060.5 31324.0 51336.5 61216.0 112552.5 259062.0 199401 5308.0 3064.8 31341.8 51346.4 61245.7 112592.1 259275.2 199402 5315.0 3069.0 31359.7 51356.3 61275.3 112631.7 259488.3 199403 5322.0 3073.3 31377.5 51366.3 61305.0 112671.3 259701.5 199404 5329.0 3077.5 31395.3 51376.2 61334.7 112710.8 259914.7 199405 5336.0 3081.8 31413.2 51386.1 61364.3 112750.4 260127.8 199406 5343.0 3086.0 31431.0 51396.0 61394.0 112790.0 260341.0 199407 5350.0 3090.3 31448.8 51405.9 61423.7 112829.6 260554.2 199408 5357.0 3094.5 31466.7 51415.8 61453.3 112869.2 260767.3 199409 5364.0 3098.8 31484.5 51425.8 61483.0 112908.8 260980.5 199410 5371.0 3103.0 31502.3 51435.7 61512.7 112948.3 261193.7 199411 5378.0 3107.3 31520.2 51445.6 61542.3 112987.9 261406.8 Source: U.S. Bureau of the Census, Current Population Reports: Populations Estimates 1  and Projections, P25-1106; and Census and You, February 1994 and January  1995 issues. Generated from annual data by linear interpolation " Column 6 = (Column 4 +Column 5) 1  2  Table A3: Monthly Wages and Salaries for Canada and Selected Provinces, raw. (Millions of dollars) Column 1 Column 2 Column 3 Column 4 Column 5 Column 6 Column 7 Column 8 * BC Alta Sask Man Prai Ont Que. East 198801 2519847 2167317 624353 787250 3578920 9881860 5286368 15168228 198802 2522855 2184344 619485 784759 3588588 9952779 5309227 15262006 198803 2607308 2213107 633889 802088 3649084 10088822 5400802 15489624 198804 2646712 2214627 642737 813518 3670882 10323465 5486396 15809861 198805 2728509 2274945 674790 832687 3782422 10514736 5659638 16174374 198806 2799469 2335982 687208 864528 3887718 10842404 5831877 16674281 198807 2726783 2374589 660444 863624 3898657 10866674 5812789 16679463 198808 2735443 2369965 661000 860366 3891331 10789009 5791197 16580206 198809 2841457 2370490 678167 873178 3921835 10957006 5814708 16771714 198810 2851597 2371848 668979 875359 3916186 10958705 5826878 16785583 198811 2823994 2336314 660904 856012 3853230 10964422 5805507 16769929 198812 2787248 2303537 649598 851539 3804674 10853142 5745805 16598947 198901 2783330 2318125 639132 835879 3793136 10894321 5657814 16552135 198902 2791998 2316493 629809 828051 3774353 11007886 5679494 16687380 198903 2895865 2360117 647763 845761 3853641 11077736 5728927 16806663 198904 2920012 2346548 650153 857851 3854552 11303761 5828089 17131850 198905 3021809 2398901 679225 876813 3954939 11531183 6002290 17533473 198906 3134493 2498816 706764 917257 4122837 12028787 6252476 18281263 198907 3035724 2523598 670423 898795 4092816 11928342 6147879 18076221 198908 3067298 2528384 674799 893597 4096780 11816722 6139829 17956551 198909 3202352 2543865 692227 904550 4140642 11868283 6089587 17957870 198910 3221560 2555908 690274 902819 4149001 11815311 6157187 17972498 198911 3210488 2523915 681947 887093 4092955 11756072 6108039 17864111 198912 3171805 2493899 676922 880580 4051401 11622873 6108364 17731237 199001 3146555 2518672 663328 874014 4056014 11425691 5976058 17401749 199002 3112574 2524202 658235 871246 4053683 11471016 5953095 17424111 199003 3200902 2562473 669414 885298 4117185 11567546 6006223 17573769 199004 3248229 2556581 680919 896180 4133680 11723639 6090144 17813783 199005 3387194 2655011 719363 927160 4301534 11923084 6470509 18393593 199006 3420010 2695771 732272 951077 4379120 12090092 6694768 18784860 199007 3305019 2741084 708476 935520 4385080 12111096 6472149 18583245 199008 3336679 2745305 711944 926424 4383673 11909489 6403451 18312940 199009 3454581 2743734 729812 947285 4420831 11941943 6429240 18371183 199010 3453406 2745303 739657 944735 4429695 11979916 6440962 18420878 199011 3387003 2688661 732007 926376 4347044 11829321 6386559 18215880 199012 3315866 2639651 705412 918023 4263086 11675948 6281773 17957721 199101 3253310 2674834 696587 893855 4265276 11452149 6146600 17598749 199102 3241055 2662963 689870 897170 4250003 11486597 6141466 17628063 199103 3349886 2699079 700945 904305 4304329 11515220 6175469 17690689 199104 3390956 2701653 712084 911182 4324919 11688512 6272499 17961011 199105 3494534 2775422 730139 923235 4428796 12001386 6483480 18484866 199106 3536638 2821875 764034 941787 4527696 12251027 6657007 18908034 199107 3391945 2844437 733198 927721 4505356 12164428 6575895 18740323 199108 3394184 2835015 743518 925487 4504020 12017943 6498869 18516812 199109 3535157 2817963 763758 943641 4525362 11975739 6486898 18462637 1  Column 9 Canada 22770342 22873374 23278704 23683284 24326272 25096900 25061562 24964428 25282536 25279792 25142218 24860922 24752380 24862188 25191582 25575166 26276422 27454272 27097198 27010102 27168022 27189726 26966436 26730400 26333244 26313078 26644166 26969472 27983832 28559088 28268872 28014856 28197392 28233028 27840704 27379184 26904724 26900702 27137374 27489324 28319648 28970960 28669952 28442558 28507716  Table A3: Monthly Wages and Salaries for Canada and Selected Provinces, raw. (Millions of dollars) -continued from previous page Column 1 Column 2 Column 3 Column 4 Column 5 Column 6 Column 7 Column 8 * Sask BC Alta Man Prai Ont Que. East 766102 949511 4516087 12012227 6469301 18481528 199110 3557321 2800474 199111 3530184 2752326 748939 933396 4434661 11843723 6421408 18265131 199112 3461079 2708036 738277 931263 4377576 11761037 6326491 18087528 199201 3420596 2694731 719100 917878 4331709 11498891 6196861 17695752 199202 3436269 2678465 711625 917561 4307651 11526392 6220850 17747242 199203 3521700 2685702 720261 923215 4329178 11536019 6284712 17820731 199204 3551928 2727807 728757 930899 4387463 11680886 6361239 18042125 199205 3697256 2787376 748694 947202 4483272 12002142 6615005 18617147 199206 3693814 2838702 775873 978043 4592618 12339748 6787214 19126962 199207 3557517 2869833 740372 962845 4573050 12246369 6719299 18965668 199208 3581279 2864331 740525 950513 4555369 12050280 6633622 18683902 199209 3754574 2866999 766315 974743 4608057 12049564 6620218 18669782 199210 3759840 2831091 760956 977752 4569799 12079203 6609621 18688824 199211 3732631 2797916 743888 961205 4503009 12008701 6531013 18539714 199212 3666593 2770689 737174 961288 4469151 11880365 6467456 18347821 199301 3623158 2760788 722093 943480 4426361 11648084 6351133 17999217 199302 3645424 2773712 714603 948035 4436350 11679237 6365521 18044758 199303 3747092 2796124 732484 949168 4477776 11776385 6418792 18195177 199304 3800570 2796465 735952 956022 4488439 11906130 6462696 18368826 199305 3872876 2833404 751715 958308 4543427 12103147 6655818 18758965 199306 3967897 2900315 779336 990802 4670453 12485494 6904491 19389985 199307 3817581 2932240 753156 963284 4648680 12377952 6807431 19185383 199308 3820245 2907579 743310 957214 4608103 12159248 6717497 18876745 199309 3961708 2906679 766870 981653 4655202 12235931 6744681 18980612 199310 3972111 2868786 763435 975113 4607334 12218776 6700297 18919073 199311 3942797 2831013 751846 966635 4549494 12162346 6618078 18780424 199312 3921916 2790612 748524 955142 4494278 12009257 6524118 18533375 199401 3865174 2822108 730447 945032 4497587 11732396 6422171 18154567 199402 3860288 2818076 728252 946396 4492724 11842411 6423580 18265991 199403 3934463 2869413 734615 963642 4567670 11874637 6529570 18404207 199404 4016818 2902753 750255 982123 4635131 12079757 6627851 18707608 199405 4134102 2949287 768479 987971 4705737 12301186 6751044 19052230 199406 4260726 3032845 804055 1040466 4877366 12901996 7055902 19957898 199407 4062823 3031430 763632 1013998 4809060 12693023 6972545 19665568 199408 4034173 3028329 762026 999108 4789463 12486236 6845293 19331529 199409 4166466 3034658 779800 1020405 4834863 12676893 6885182 19562075 199410 4168458 2980578 779948 1016400 4776926 12636624 6857423 19494047 199411 4141194 2960913 777758 1007194 4745865 12674226 6779165 19453391 199412 4131629 2911017 769196 998437 4678650 12602111 6731111 19333222 Source: Statistics Canada - Cat. No. 72-005, or CANSIM: Series D5230, D5231, D5232, D5233, D5234, D5235, and D5248 Column 5 = (Column 2 + Column 3 +Cdumn 4) Column 8 = (Column 6 + Column 7) 1  Column 9 Canada 28502640 28152652 27792966 27254942 27298504 27483900 27825912 28735036 29435294 29150968 28858658 29059628 29001728 28715370 28380254 27887520 27968872 28279048 28529610 29130432 30090718 29731240 29380352 29657880 29519722 29241032 28871144 28388996 28485306 28786876 29275790 29872304 31202856 30681770 30272902 30685950 30502696 30350932 30111838  Table A4: Total Personal Income of United States, Selected Regions and States (Millions of dollars, seasonally adjusted at annual rates)* 1  Column 1 Column 2 Column 3 Column 4 Column 5 Wash. Ore. Cal. New Middle England Atlantic 73513.7 39494.7 514185.7 252482.0 687765.0 73720.3 39691.3 515516.3 253913.0 691968.0 73927.0 39888.0 516847.0 255344.0 696171.0 74457.7 40121.3 520801.3 257133.0 699833.0 74988.3 40354.7 524755.7 258922.0 703495.0 75519.0 40588.0 528710.0 260711.0 707157.0 75912.7 40899.3 532477.3 262539.3 712243.7 76306.3 41210.7 536244.7 264367.7 717330.3 76700.0 41522.0 540012.0 266196.0 722417.0 77380.0 41938.3 544119.3 268565.0 728342.3 78060.0 42354.7 548226.7 270934.0 734267.7 78740.0 42771.0 552334.0 273303.0 740193.0 79491.3 43046.3 555585.0 274928.3 745037.7 80242.7 43321.7 558836.0 276553.7 749882.3 80994.0 43597.0 562087.0 278179.0 754727.0 81675.0 43990.7 565307.0 278950.7 758300.7 82356.0 44384.3 568527.0 279722.3 761874.3 83037.0 44778.0 571747.0 280494.0 765448.0 83554.3 45045.0 574378.0 280914.7 767769.3 84071.7 45312.0 577009.0 281335.3 770090.7 84589.0 45579.0 579640.0 281756.0 772412.0 85357.3 45985.7 581453.0 282881.7 775819.7 86125.7 46392.3 583266.0 284007.3 779227.3 86894.0 46799.0 585079.0 285133.0 782635.0 88493.0 47176.3 592318.0 285774.3 788000.0 90092.0 47553.7 599557.0 286415.7 793365.0 91691.0 47931.0 606796.0 287057.0 798730.0 92308.0 48260.7 609205.0 287829.7 802845.0 92925.0 48590.3 611614.0 288602.3 806960.0 93542.0 48920.0 614023.0 289375.0 811075.0 94046.7 49087.0 616073.3 290136.3 814143.7 94551.3 49254.0 618123.7 290897.7 817212.3 95056.0 49421.0 620174.0 291659.0 820281.0 95834.7 49738.7 623356.7 291690.0 821662.3 96613.3 50056.3 626539.3 291721.0 823043.7 97392.0 50374.0 629722.0 291752.0 824425.0 97865.0 50554.7 629163.0 292650.3 826658.3 98338.0 50735.3 628604.0 293548.7 828891.7 98811.0 50916.0 628045.0 294447.0 831125.0 99268.0 51121.0 629854.3 294842.7 833576.3 99725.0 51326.0 631663.7 295238.3 836027.7 100182.0 51531.0 633473.0 295634.0 838479.0 100658.0 51717.7 634868.0 295528.3 839592.3 101134.0 51904.3 636263.0 295422.7 840705.7 101610.0 52091.0 637658.0 295317.0 841819.0 2  Yr/Mon 198801 198802 198803 198804 198805 198806 198807 198808 198809 198810 198811 198812 198901 198902 198903 198904 198905 198906 198907 198908 198909 198910 198911 198912 199001 199002 199003 199004 199005 199006 199007 199008 199009 199010 199011 199012 199101 199102 199103 199104 199105 199106 199107 199108 199109  Column 6 Great Lakes 662536.0 665539.0 668542.0 670911.3 673280.7 675650.0 678776.0 681902.0 685028.0 689496.7 693965.3 698434.0 705999.0 713564.0 721129.0 722798.3 724467.7 726137.0 727515.7 728894.3 730273.0 734597.0 738921.0 743245.0 747802.7 752360.3 756918.0 760152.7 763387.3 766622.0 769126.3 771630.7 774135.0 776745.3 779355.7 781966.0 782927.3 783888.7 784850.0 786637.0 788424.0 790211.0 792759.0 795307.0 797855.0  Column 7 Column 8 Plains Other U.S.A. 268961.0 1871744.0 268448.0 1879868.0 267935.0 1887992.0 268716.7 1896594.0 269498.3 1905196.0 270280.0 1913798.0 268766.3 1922325.3 267252.7 1930852.7 265739.0 1939380.0 269361.0 1955765.0 272983.0 1972150.0 276605.0 1988535.0 280295.0 2006260.0 283985.0 2023985.0 287675.0 2041710.0 287957.3 2048007.0 288239.7 2054304.0 288522.0 2060601.0 288462.3 2064662.0 288402.7 2068723.0 288343.0 2072784.0 291581.7 2084880.0 294820.3 2096976.0 298059.0 2109072.0 301046.3 2122623.3 304033.7 2136174.7 307021.0 2149726.0 307258.0 2158085.3 307495.0 2166444.7 307732.0 2174804.0 307473.3 2180879.7 307214.7 2186955.3 306956.0 2193031.0 310591.7 2200689.3 314227.3 2208347.7 317863.0 2216006.0 317721.7 2219957.7 317580.3 2223909.3 317439.0 2227861.0 318618.3 2233674.3 319797.7 2239487.7 320977.0 2245301.0 320752.7 2248632.3 320528.3 2251963.7 320304.0 2255295.0 3  Column 9 U.S. 3925152.7 3939394.3 3953636.0 3977939.7 4002243.3 4026547.0 4047062.7 4067578.3 4088094.0 4121017.0 4153940.0 4186863.0 4221915.0 4256967.0 4292019.0 4309536.3 4327053.7 4344571.0 4355134.0 4365697.0 4376260.0 4403515.3 4430770.7 4458026.0 4495773.7 4533521.3 4571269.0 4591090.7 4610912.3 4630734.0 4647469.0 4664204.0 4680939.0 4700205.3 4719471.7 4738738.0 4751155.7 4763573.3 4775991.0 4790589.7 4805188.3 4819787.0 4829835.0 4839883.0 4849931.0  Table A4: Total Personal Income of United States, Selected Regions and States (Millions of dollars, seasonally adjusted at annual rates)' 1  Column 1 Column 2 Column 3 Column 4 Column 5" Column 6 Column 7 Yr/Mon Wash. Ore. Cal. New Middle Great Plains England Atlantic Lakes 199110 102392.7 52440 0 638575.3 296392.7 845025.0 801687.7 323312.0 199111 103175.3 52789 0 639492.7 297468.3 848231.0 805520.3 326320.0 199112 103958.0 53138 0 640410.0 298544.0 851437.0 809353.0 329328.0 199201 104685.7 53403 3 644894.7 299736.7 856757.3 814255.0 331633.3 199202 105413.3 53668 7 649379.3 300929.3 862077.7 819157.0 333938.7 199203 106141.0 53934 0 653864.0 302122.0 867398.0 824059.0 336244.0 199204 106718.0 54220 3 656889.7 303131.0 870559.3 829002.3 337052.0 199205 107295.0 54506 7 659915.3 304140.0 873720.7 833945.7 337860.0 199206 107872.0 54793 0 662941.0 305149.0 876882.0 838889.0 338668.0 199207 108538.7 55237 0 665134.7 305947.7 880211.0 841669.7 339750.3 199208 109205.3 55681 0 667328.3 306746.3 883540.0 844450.3 340832.7 199209 109872.0 56125 0 669522.0 307545.0 886869.0 847231.0 341915.0 199210 111379.7 56619 7 673996.7 311168.0 898629.7 856919.3 346746.3 199211 112887.3 57114 3 678471.3 314791.0 910390.3 866607.7 351577.7 199212 114395.0 57609 0 682946.0 318414.0 922151.0 876296.0 356409.0 199301 113408.7 57652 0 678791.7 315872.7 911611.3 873300.0 355199.0 199302 112422.3 57695 0 674637.3 313331.3 901071.7 870304.0 353989.0 199303 111436.0 57738 0 670483.0 310790.0 890532.0 867308.0 352779.0 199304 112309.0 58017 0 674484.7 313349.3 899954.3 872328.3 353424.7 199305 113182.0 58296 0 678486.3 315908.7 909376.7 877348.7 354070.3 199306 114055.0 58575 0 682488.0 318468.0 918799.0 882369.0 354716.0 199307 114355.3 58785 0 683758.3 320028.0 921247.7 884264.7 351859.0 199308 114655.7 58995 0 685028.7 321588.0 923696.3 886160.3 349002.0 199309 114956.0 59205 0 686299.0 323148.0 926145.0 888056.0 346145.0 199310 115718.0 59580 0 688445.7 323812.3 928668.0 893187.7 352424.7 199311 116480.0 59955 0 690592.3 324476.7 931191.0 898319.3 358704.3 199312 117242.0 60330 0 692739.0 325141.0 933714.0 903451.0 364984.0 199401 117411.7 60772 0 689279.7 327148.7 937298.3 910826.7 366352.3 199402 117581.3 61214 0 685820.3 329156.3 940882.7 918202.3 367720.7 199403 117751.0 61656 0 682361.0 331164.0 944467.0 925578.0 369089.0 199404 118772.7 62021 3 692423.7 332444.7 949822.7 929247.3 370758.0 199405 119794.3 62386 7 702486.3 333725.3 955178.3 932916.7 372427.0 199406 120816.0 62752 0 712549.0 335006.0 960534.0 936586.0 374096.0 199407 121508.3 63132 7 715008.7 336531.7 964944.3 940956.7 374804.7 199408 122200.7 63513 3 717468.3 338057.3 969354.7 945327.3 375513.3 199409 122893.0 63894.0 719928.0 339583.0 973765.0 949698.0 376222.0 199410 123585.3 64274.7 722387.7 341108.7 978175.3 954068.7 376930.7 199411 124277.7 64655.3 724847.3 342634.3 982585.7 958439.3 377639.3 Source: U.S. Bureau of Economic Analysis, Survey of Current Business, various issues. Generated from quarterly data by linear interpolation The States included in Middle Atlantic are New Jersey, New York, and Pennsylvania. Column 8 = (Column 4 + Column 5 + Column 6 + Column 7) 1  2  J  Column 8 Other U.S.A. 2266417.3 2277539.7 2288662.0 2302382.3 2316102.7 2329823.0 2339744.7 2349666.3 2359588.0 2367578.7 2375569.3 2383560.0 2413463.3 2443366.7 2473270.0 2455983.0 2438696.0 2421409.0 2439056.7 2456704.3 2474352.0 2477399.3 2480446.7 2483494.0 2498092.7 2512691.3 2527290.0 2541626.0 2555962.0 2570298.0 2582272.7 2594247.3 2606222.0 2617237.3 2628252.7 2639268.0 2650283.3 2661298.7 J  Column 9 U.S. 4872408.7 4894886.3 4917364.0 4948957.7 4980551.3 5012145.0 5035721.3 5059297.7 5082874.0 5097913.3 5112952.7 5127992.0 5191073.3 5254154.7 5317236.0 5291307.7 5265379.3 5239451.0 5275764.7 5312078.3 5348392.0 5359357.0 5370322.0 5381287.0 5417266.7 5453246.3 5489226.0 5507222.7 5525219.3 5543216.0 5577965.7 5612715.3 5647465.0 5672352.3 5697239.7 5722127.0 5747014.3 5771901.7  Table A5: Consumer Price Index of All-items Consumer Price Index of All-items in Canada and Selected Provinces, 1986=100 Col. 1  Col. 2  Col. 3  Col. 4  Col. 5 '  Col. 6  Col. 7  Col. 8 "  Col. 9  Yr/Mon  BC  Alta  Sask.  Man  Prai  Ontario  Quebec  East  Canada  198801  105.1  105.6  108.2  106.0  106.6  107.0  106.2  106.6  106.3  198802  105.1  105.6  108.6  106.2  106.8  107.5  106.9  107.2  106.7  198803  105.8  106.3  108.8  107.3  107.5  108.0  107.2  107.6  107.3  198804  106.2  106.9  109.0  108.0  108.0  108.4  107.5  108.0  107.6  198805  106.4  107.0  109.2  108.0  108.1  109.7  107.9  108.8  108.3  198806  106.2  106.9  109.3  108.3  108.2  110.0  108.1  109.1  108.5  198807  107.1  107.3  109.9  108.6  108.6  110.7  108.5  109.6  109.1  198808  107.1  107.2  110.2  109.2  108.9  111.1  109.0  110.1  109.4  198809  107.6  107.3  109.9  109.7  109.0  111.2  108.9  110.1  109.5  198810  107.8  107.4  110.6  110.4  109.5  111.9  109.4  110.7  110.0  198811  108.2  107.4  111.0  110.4  109.6  112.2  109.8  111.0  110.3  198812  107.9  107.1  110.9  110.8  109.6  112.3  109.9  111.1  110.3  198901  108.8  107.7  111.6  111.1  110.1  112.9  110.1  111.5  110.9  198902  109.3  108.3  112.3  111.6  110.7  113.7  111.1  112.4  111.6  198903  109.9  109.2  112.8  112.1  111.4  114.3  111.3  112.8  112.2  198904  109.9  109.5  112.7  112.2  111.5  114.9  111.7  113.3  112.5  198905  110.9  111.0  114.2  113.2  112.8  116.0  112.8  114.4  113.7  198906  111.2  111.7  114.8  113.2  113.2  116.6  113.4  115.0  114.3  198907  111.9  112.6  115.6  114.7  114.3  117.5  113.9  115.7  115.0  198908  112.3  112.6  115.7  114.8  114.4  117.6  113.9  115.8  115.1  198909  112.8  113.0  115.6  114.9  114.5  117.6  113.7  115.7  115.3  198910  113.4  113.0  115.7  115.0  114.6  118.3  114.3  116.3  115.7  198911  113.7  113.4  116.3  116.0  115.2  118.7  114.7  116.7  116.1  198912  113.8  113.8  116.0  115.7  115.2  118.7  114.2  116.5  116.0  199001  114.8  114.8  116.7  116.4  116.0  119.6  115.4  117.5  117.0  199002  115.6  115.2  118.1  117.0  116.8  120.3  115.9  118.1  117.7  199003  116.2  115.5  118.4  117.6  117.2  120.7  116.3  118.5  118.1  199004  116.4  116.3  118.5  117.6  117.5  120.7  116.1  118.4  118.1  199005  116.9  116.7  118.6  118.0  117.8  121.3  116.9  119.1  118.7  199006  117.6  117.4  119.2  118.6  118.4  121.8  117.3  119.6  119.2  199007  117.9  118.2  119.9  119.1  119.1  122.4  117.9  120.2  119.8  199008  118.1  118.5  120.0  119.4  119.3  122.4  118.1  120.3  119.9  199009  118.6  119.0  120.1  119.7  119.6  122.6  118.4  120.5  120.2  199010  119.1  119.9  121.0  120.6  120.5  123.6  119.6  121.6  121.2  199011  120  120.6  121.2  121.2  121.0  124.3  120.4  122.4  121.9  199012  119.7  120.5  121.7  121.7  121.3  123.9  120.4  122.2  121.8  199101  123  123.9  124.5  124.2  124.2  126.4  124.9  125.7  125.0  199102  123.3  122.7  124.0  124.1  123.6  126.4  124.9  125.7  125.0  199103  123.5  123.4  124.5  124.6  124.2  126.8  125.6  126.2  125.5  199104  123.4  123.4  126.2  124.5  124.7  126.9  125.8  126.4  125.5  199105  123.5  124.4  126.5  124.4  125.1  127.7  126.3  127.0  126.1  199106  124.2  124.7  126.0  125.0  125.2  128.4  126.8  127.6  126.7  199107  124.1  125.4  126.8  125.4  125.9  128.6  126.8  127.7  126.8  199108  124  125.7  126.8  125.5  126.0  128.6  126.9  127.8  126.9  199109  124.1  125.5  126.5  125.5  125.8  128.2  127.0  127.6  126.7  Table A5: Consumer Price Index of All-items Consumer Price Index of All-items in Canada and Selected Provinces, 1986=100 Col. 2 Col. 1 Col. 3 Col. 4 Col. 5 ' Col. 7 Col. 6 Col. 8" Yr/Mon Sask. BC Alta Man Ontario Quebec Prai East 199110 124.1 125.2 124.9 126.3 125.5 127.7 127.2 127.5 199111 124.6 125.5 125.4 126.2 125.7 128.3 127.4 127.9 199112 124 124.9 124.9 125.7 125.2 127.7 126.9 127.3 125.2 199201 125.3 125.1 125.6 125.3 127.9 127.9 127.9 199202 125.2 125.5 125.5 125.6 125.4 128.1 127.9 128.0 126.2 199203 126.1 125.7 125.7 125.8 128.4 128.2 128.3 199204 126.7 126.0 125.7 126.4 126.0 128.5 128.2 128.4 199205 127.1 126.8 126.1 125.8 126.3 128.8 128.3 128.6 199206 126.9 126.4 127.1 126.5 126.7 129.1 128.6 128.9 199207 127.5 126.9 127.1 127.5 127.2 129.4 129.0 129.2 127.7 199208 127.4 126.9 127.8 127.4 129.4 129.0 129.2 199209 127.5 126.8 127.7 127.7 127.4 129.1 128.9 129.0 199210 126.7 128.1 127.2 127.8 127.2 129.3 129.3 129.3 199211 128.9 128.4 127.5 128.1 128.0 129.9 129.7 129.8 199212 129 127.1 128.3 128.3 127.9 129.8 129.8 129.8 199301 130.2 127.7 129.1 128.6 128.5 130.2 130.3 130.3 199302 130.5 127.8 129.4 129.2 128.8 130.8 130.3 130.6 199303 130.6 126.1 129.2 129.5 128.3 130.9 130.6 130.8 199304 130.7 126.8 130.6 129.8 129.1 130.7 130.4 130.6 199305 131.4 127.1 131.1 130.1 129.4 130.8 130.3 130.6 199306 131.2 127.7 131.0 130.0 129.6 131.0 130.3 130.7 199307 131.7 128.3 131.0 130.3 129.9 131.4 130.3 130.9 199308 132.1 128.2 130.4 131.3 130.0 131.4 130.2 130.8 199309 132.4 128.4 131.3 130.3 130.0 131.6 130.3 131.0 199310 132.6 128.3 131.7 130.9 130.3 131.8 130.2 131.0 199311 133 132.2 128.9 131.6 130.9 132.2 131.3 131.8 199312 132.9 132.1 128.9 131.6 130.9 132.1 131.1 131.6 199401 133.4 128.9 132.4 131.2 130.8 131.9 130.9 131.4 199402 133.6 128.7 132.1 131.3 130.7 131.1 128.5 129.8 199403 133.5 128.4 132.1 131.3 130.6 130.7 128.6 129.7 199404 133.2 128.9 132.7 131.4 131.0 130.9 128.4 129.7 199405 133.6 129.1 131.4 132.6 131.0 130.5 127.8 129.2 199406 133.9 129.3 133.0 131.4 131.2 130.7 128.4 129.6 199407 134.4 130.1 133.4 132.1 131.9 131.4 128.4 129.9 199408 134.6 130.2 133.6 132.0 131.9 131.5 128.4 130.0 199409 134.8 130.7 134.1 132.5 132.4 128.4 131.5 130.0 199410 134.9 130.4 133.6 132.5 132.2 131.3 128.2 129.8 199411 135.3 130.6 134.1 133.1 132.6 129.1 132.0 130.6 199412 135.6 131.2 134.3 133.5 133.0 132.4 129.0 130.7 Source: CANSIM: Series P682470, P682196, P681922, P681647, P681371, P681096, P484000 Column 5 = (Column 2 + Column 3 + Column 4)/3 Column 8 = (Column 6 + Column 7)/2  Col. 9 Canada 126.5 127.0 126.4 127.0 127.1 127.5 127.6 127.8 128.1 128.4 128.4 128.3 128.5 129.1 129.1 129.6 130.0 129.9 129.9 130.1 130.2 130.5 130.6 130.7 130.9 131.5 131.3 131.3 130.3 130.1 130.2 129.9 130.2 130.7 130.8 130.9 130.7 131.4 131.6  Table A5: Consumer Price Index of Food Consumer Price Index of Food in Canada and Selected Provinces, 1986=100 Col. 1  Col. 2  Yr/Mon  BC  198801 198802  Col. 4  Col. 5 '  Col. 6  Col. 7  Alta  Col. 3 Sask  Man.  Prai  Ont  Quebec  East  Canada  105.5  105.8  106.6  105.4  105.9  105.4  106.5  106.0  105.8  105.1  105.6  107.0  105.2  105.9  105.6  105.9  105.8  105.6  198803  105  105.5  106.3  104.3  105.4  104.9  106.1  105.5  105.3  198804  106.3  105.7  107.0  105.5  106.1  105.5  106.5  106.0  105.8  198805  106.3  106.2  107.8  106.5  106.8  106.4  107.2  106.8  106.5  198806  106.5  106.9  108.3  107.0  107.4  107.9  107.7  107.8  107.4  198807  106.5  107.7  109.7  108.0  108.5  108.7  108.9  108.8  108.4  198808  107.1  107.6  110.1  107.6  ' 108.4  109.1  109.1  109.1  108.7  198809  107.4  108.0  109.8  107.3  108.4  108.6  108.8  108.7  108.4  198810  106.9  107.0  110.8  108.7  108.8  108.5  109.2  108.9  108.4  198811  106.4  105.3  110.3  107.5  107.7  108.3  108.8  108.6  108.0  198812  106.9  102.6  109.4  108.5  106.8  107.9  108.9  108.4  107.6  198901  108.2  104.6  111.9  109.3  108.6  109.3  109.8  109.6  108.9  198902  108.6  105.5  111.1  109.3  108.6  110.2  111.2  110.7  109.8  198903  108.4  105.4  111.8  110.4  109.2  110.6  110.7  110.7  109.9  198904  106  105.6  111.9  109.5  109.0  111.6  111.7  111.7  110.3  198905  107.3  107.4  113.2  110.3  110.3  111.5  112.9  112.2  111.0  198906  107.4  108.3  113.9  111.1  111.1  112.5  113.6  113.1  111.8  198907  108.4  109.3  115.1  112.6  112.3  113.6  114.3  114.0  112.8  198908  109.2  108.9  115.3  112.4  112.2  112.8  112.7  112.8  112.1  198909  109.9  109.8  114.8  112.2  112.3  112.4  111.5  112.0  111.6  198910  110.4  108.8  115.0  112.7  112.2  112.5  112.9  112.7  112.0  198911  109.5  108.3  115.7  113.6  112.5  112.6  112.7  112.7  111.9  198912  110.2  108.4  113.5  112.5  111.5  112  111.3  111.7  111.3  199001  112.1  111.3  116.6  115.5  114.5  114.5  115  114.8  114.1  199002  112.9  111.3  116.9  116.4  114.9  115.6  116.3  116.0  115.1  199003  113.5  111.4  117.7  116.7  115.3  115.9  116.2  116.1  115.4  199004  113.5  112.1  117.2  115.4  114.9  115  114.5  114.8  114.5  199005  113.5  111.7  117.3  115.9  115.0  115.5  115  115.3  114.8  199006  115.8  113.5  119.5  117.8  116.9  117.5  115.9  116.7  116.4  199007  116.4  114.7  120.5  119.5  118.2  117.8  117.1  117.5  117.2  .  Col. 8  d  Col. 9  199008  115.6  114.0  119.2  117.9  117.0  116.7  115.8  116.3  116.1  199009  116.4  114.5  119.9  118.2  117.5  116.9  114.2  115.6  115.9  199010  116.7  114.9  120.3  118.0  117.7  117.4  115.3  116.4  116.5  199011  116.8  114.5  120.7  118.5  117.9  117.4  115.7  116.6  116.6  199012  116.7  114.7  121.0  118.5  118.1  116.2  115.5  115.9  116.1  199101  121.9  120.1  125.4  123.0  122.8  121.1  119.9  120.5  120.9  199102  122.6  120.2  125.0  122.8  122.7  120.8  119.9  120.4  120.9  199103  123.6  119.6  125.4  123.1  122.7  121.4  120.1  120.8  121.3  199104  124.2  120.0  129.3  123.5  124.3  121.6  120.7  121.2  121.8  199105  123.3  120.8  128.6  122.6  124.0  122.2  121.1  121.7  122.0  199106  126.2  123.0  130.4  126.0  126.5  124.2  123.5  123.9  124.3  199107  125  122.3  129.0  124.6  125.3  123.9  122.1  123.0  123.5  199108  122  120.7  128.4  122.8  124.0  122.7  120.8  121.8  122.0  199109  122  120.5  127.7  122.4  123.5  120.8  118.2  119.5  120.4  Table A5: Consumer Price Index of Food Consumer Price Index of Food in Canada and Selected Provinces, 1986=100 -continued from previous page Col. 1 Col. 2 Col. 3 Col. 4 Col. 5 Col. 6 Col. 7 Col. 8 Yr/Mon BC Alta Sask Man. Prai Ont Quebec East 199110 122.0 118.9 126.4 121.0 122.1 119.4 117.4 118.4 199111 123.4 119.4 124.9 122.6 122.3 119.1 117.9 118.5 199112 122.7 118.8 124.4 122.3 121.8 117.7 117.3 117.5 199201 123.7 120.1 125.0 122.8 122.6 118.6 118.7 118.7 124.9 199202 121.4 125.5 123.2 123.4 118.0 119.1 118.6 199203 126.3 126.4 120.5 123.9 123.6 118.5 119.8 119.2 199204 127.0 121.1 125.9 124.4 123.8 119.2 119.9 119.6 199205 126.0 120.6 126.1 123.5 123.4 119.3 119.2 119.3 199206 125.8 121.3 126.5 123.6 123.8 120.7 120.4 120.6 199207 126.5 120.0 126.7 123.9 123.5 120.3 120.4 120.4 199208 127.0 120.7 127.1 124.4 124.1 120.4 119.2 119.8 199209 126.2 120.6 127.9 125.6 124.7 120.0 118.5 119.3 199210 125.8 120.4 127.8 125.6 124.6 119.9 118.3 119.1 199211 126.8 120.3 127.9 126.3 124.8 120.0 118.5 119.3 199212 128.0 120.2 128.1 127.7 125.3 119.9 119.3 119.6 199301 129.2 121.0 129.1 126.7 125.6 121.0 120.6 120.8 199302 130.3 120.6 129.5 127.4 125.8 122.2 120.4 121.3 199303 129.5 111.4 129.3 126.4 122.4 123.1 120.6 121.9 199304 128.1 112.9 130.0 128.6 123.8 122.5 120.5 121.5 199305 131.0 114.6 131.5 130.6 125.6 123.5 121.0 122.3 199306 129.7 116.6 131.0 130.0 125.9 124.1 120.7 122.4 199307 129.8 117.5 130.7 130.0 126.1 123.9 120.4 122.2 199308 130.3 116.7 130.9 129.2 125.6 123.4 119.2 121.3 199309 130.7 116.7 131.3 129.6 125.9 122.5 118.1 120.3 199310 130.2 116.2 131.8 130.4 126.1 122.9 118.1 120.5 199311 130.4 116.1 131.9 130.0 126.0 123.0 119.8 121.4 199312 131.2 117.2 131.9 130.2 126.4 123.4 120.1 121.8 199401 132.0 117.0 131.8 129.7 126.2 123.8 120.7 122.3 199402 131.7 115.9 131.0 129.3 125.4 123.4 120.2 121.8 199403 130.6 116.0 131.5 129.7 125.7 121.4 120.4 120.9 199404 130.5 116.0 132.8 130.8 126.5 122.7 120.1 121.4 199405 130.8 116.6 133.2 131.0 126.9 121.9 120.7 121.3 199406 131.6 116.8 133.3 130.7 126.9 121.8 121.7 121.8 199407 131.4 117.7 133.6 131.2 127.5 123.0 121.9 122.5 199408 131.3 116.8 133.5 130.5 126.9 123.1 121.0 122.1 199409 131.2 117.5 134.2 130.5 127.4 122.4 119.2 120.8 199410 131.8 118.7 134.1 131.0 127.9 122.6 119.2 120.9 199411 131.2 118.0 134.0 130.6 127.5 123.0 120.3 121.7 199412 133.3 119.2 134.3 132.0 128.5 122.8 120.3 121.6 Source: CANSIM: Series P682471, P682197, P681923, P681648, P681372, P681097, and P484001 1  * ' Column 5 = (Column 2 + Column 3 + Column 4)/3 Column 8 = (Column 6 + Column 7)/2 1  2  Col. 9 Canada 119.4 119.6 118.7 119.7 119.9 120.4 120.9 120.6 121.6 121.4 121.2 120.7 120.6 120.8 121.2 122.3 122.9 122.4 122.1 123.3 123.4 123.4 122.9 122.2 122.4 122.9 123.3 123.8 123.3 122.5 123.0 123.0 123.3 124.0 123.7 122.9 123.2 123.4 123.7  Table A5: Consumer Price Index of Fresh Vegetables Consumer Price Index of Fresh Vegetables in Canada and Selected Provinces, 1986=100  Yr/Mon 198801 198802 198803 198804 198805 198806 198807 198808 198809 198810 198811 198812 198901 198902 198903 198904 198905 198906 198907 198908 198909 198910 198911 198912 199001 199002 199003 199004 199005 199006 199007 199008 199009 199010 199011 199012 199101 199102 199103 199104 199105 199106 199107 199108 199109  Col. 1 Col. 2 B.C. Alta. 124.7 118.8 114.5 108.8 100.3 101.0 112.3 106.7 112.2 107.0 104.8 104.3 100.8 106.8 98.2 101.3 99.6 103.8 99.2 94.9 101.6 87.0 98.2 83.9 107.9 94.4 122.2 115.5 114.8 105.0 110.1 101.5 123.6 113.5 121.0 111.0 120.0 114.8 93.4 108.6 98.2 90.7 98.0 91.2 92.1 96.1 83.4 93.8 120.0 113.8 140.7 123.7 138.7 120.1 117.4 98.1 118.0 97.8 125.5 106.1 114.6 105.5 103.6 96.6 105.2 96.1 106.7 101.9 108.7 95.4 99.8 89.8 113.2 101.8 116.8 103.1 113.5 97.2 130.4 110.3 137.6 113.7 165.6 138.9 141.7 121.8 103.5 94.8 92.6 86.5  Col. 3 Sask. 97.6 100.5 88.8 93.6 98.3 104.9 101.1 95.9 90.5 98.8 91.1 92.0 97.0 99.8 103.7 106.4 114.1 114.6 119.2 109.1 98.9 101.5 101.0 90.4 110.2 119.2 116.8 101.4 100.8 105.5 114.6 106.3 96.0 91.8 98.6 94.8 112.4 109.9 113.1 123.5 122.3 141.1 131.1 115.4 104.9  Col. 4 Man. 116.8 114.6 95.7 101.3 104.7 97.9 104.1 101.7 95.7 103.8 91.4 94.4 108.3 118.4 116.0 119.1 131.7 127.3 133.4 116.4 94.3 98.5 109.8 93.0 130.7 140.8 132.7 103.0 101.6 106.3 117.6 106.3 89.2 92.8 103.7 94.8 109.4 110.4 105.5 119.5 121.3 157.2 135.8 103.1 90.4  Col. 5* Prairie 111.1 108.0 95.2 100.5 103.3 102.4 104.0 99.6 96.7 99.2 89.8 90.1 99.9 111.2 108.2 109.0 119.8 117.6 122.5 106.3 94.6 97.1 102.3 88.9 118.2 127.9 123.2 100.8 100.1 106.0 112.6 103.1 93.8 95.5 99.2 93.1 107.9 107.8 105.3 117.8 119.1 145.7 129.6 104.4 93.9  1  Col. 6 Ontario 122.1 117.0 103.4 102.7 109.7 112.1 117.1 105.3 98.3 98.5 100.7 109.0 117.6 130.4 116.2 119.5 127.6 142.4 140.0 111.7 100.4 103.8 115.4 104.0 129.9 146.6 140.0 117.5 117.1 126.8 123.2 104.8 89.9 104.5 108.1 101.7 111.9 110.9 106.4 119.9 130.5 162.0 144.6 113.5 95.6  Col. 7 Quebec 124.5 110.8 100.8 108.3 115.8 110.3 115.4 109.8 96.5 100.6 103.2 110.7 114.1 132.1 115.8 121.1 141.1 146.7 141.8 114.7 91.1 107.7 118.6 94.5 144.6 163.1 147.0 116.0 114.8 121.7 126.8 101.8 83.1 101.1 114.9 103.9 113.0 113.2 106.1 132.5 138.2 174.1 150.2 116.6 94.5  Col. 8"* East 123.3 113.9 102.1 105.5 112.8 111.2 116.3 107.6 97.4 99.6 102.0 109.9 115.9 131.3 116.0 120.3 134.4 144.6 140.9 113.2 95.8 105.8 117.0 99.3 137.3 154.9 143.5 116.8 116.0 124.3 125.0 103.3 86.5 102.8 111.5 102.8 112.5 112.1 106.3 126.2 134.4 168.1 147.4 115.1 95.1  Col. 9 Canada 122.4 114.1 101.5 105.7 111.1 109.0 112.8 105.4 98.2 99.3 100.3 105.4 113.2 128.2 115.3 117.5 130.7 138.4 136.5 111.9 96.5 103.0 111.3 97.8 131.6 149.1 140.3 115.5 114.7 122.5 121.6 103.8 91.1 103.3 109.3 101.4 111.8 112.6 107.1 125.0 132.1 164.2 144.6 111.8 94.2  Table A5: Consumer Price Index of Fresh Vegetables Consumer Price Index of Fresh Vegetables in Canada and Selected Provinces, 1986=100 -continued from previous page Cd. 1 B.C.  Col. 2 Alta.  199110  93.9  85.9  98.0  83.9  89.3  92.0  93.6  92.8  92.2  199111  117.0  93.1  107.6  100.9  100.5  109.0  113.6 122.5  87.9 97.9  104.4  109.3  199203 199204  140.9 154.4 155.4  105.5 105.6  96.3 106.6  106.5 102.7  106.7  199112  104.0 103.4  112.6 118.9  122.5 118.7  199205 199206 199207  128.1 122.1 119.4  199208 199209 199210 199211 199212  126.9 123.3 122.9 143.5 143.9 144.2  102.5 101.6 99.8 107.4 102.5 105.4  108.9 110.5 111.4 116.1 118.0 111.5  101.3 99.3 105.8  114.0 115.4  107.0 96.2 94.1  199305 199306 199307 199308  152.0 162.0 144.0 176.5 156.9 131.1 125.9  111.5 112.3 124.3 134.5 123.0 119.3 114.3  199309 199310 199311 199312  128.0 123.3 132.7 147.2  199401 199402  155.5 145.2  90.1 80.6 90.8 94.8 105.4  199403 199404  136.8 133.2  88.5 91.6  116.7  199405  136.2  92.2  199406 199407  142.2  199408  Yr/Mon  Col. 3 Sask.  Col. 4 Man.  Col. 5 ' Prairie  96.2  Col. 6 Ontario  Col. 7 Quebec  Col. 8* East  Col. 9 Canada  111.9 119.7  102.0 114.8 126.7 139.2  126.1 113.7 120.0 118.5 105.6 97.3 100.0  148.6 130.8 131.1 127.3 98.7 94.5 101.4  137.4  102.2 95.9 100.7  120.0 121.9 120.0 107.4 101.4 104.9  104.6 109.6 114.2  113.9 120.0 142.2  109.3 114.8 128.2  113.6 117.1 126.4  112.8 112.9 120.4  121.0 132.0 126.1  144.3 153.4  131.1 139.4 133.4  139.5 141.1 128.8 115.6  140.1 139.7  137.6 119.6 113.6 107.3 109.9 110.0 114.5 120.2 121.2  132.7 142.7 137.4 151.2  128.1  112.0  137.5 130.7  114.2  116.6 115.7  113.6  114.9  134.0  115.8  96.9  121.3 116.4  128.7  128.9  88.5  116.1  127.2  85.5 76.6  110.1  113.7  199409  120.9 110.8  107.9  103.6  199410 199411  111.1 128.6  79.1 91.2  104.8 107.2  100.2 110.5  199201 199202  199301 199302 199303 199304  114.3 98.3 97.3 90.7  93.5  110.1  119.8 125.2 124.3 125.7 118.5 114.3 118.6  116.0 136.2 135.7 109.7 107.1 109.1 116.2 116.7 114.5 116.1 120.6 116.9 119.8 130.2 142.8 163.9 137.6 124.3 116.8 119.7 124.1 128.4  103.3 110.3 123.8 124.4 107.0 106.4 106.8 113.2 112.4 110.5 110.5 111.8 110.9  106.5  104.0 106.0 115.8 120.0 125.5  148.6 162.8 158.4 149.9 120.9 97.1 112.7 132.8  110.7 119.3 129.5 122.3 125.6 122.9  149.8 139.4 118.3 100.6 109.4  103.1 110.9 121.1 130.9 137.2  150.9 145.0 133.4 117.7 105.1 109.4 122.1  124.3 131.2  129.4  139.3 123.0  137.6 123.6  127.7 130.4  121.7 122.7  121.4  117.3  140.9  129.1  126.3  114.0 110.6  122.4  157.6  140.0  134.8  127.2  158.3  142.8  135.1  103.1 96.0 94.7 103.0  110.9 92.8 97.9 111.0  122.7  116.8 94.3 101.7 114.6  115.3 96.2  142.3 153.0 129.3  95.8 105.5 118.1  121.5  101.3 114.6  Source: CANSIM: Series P682519, P682245, P681894, P681696, P681420, P681145, and P484095 *  1  '  2  Column 5 = (Column 2 + Column 3 + Column 4)/3 Column 8 = (Column 6 + Column 7)/2  Table A6: Consumer Price Index for All Urban Consumers (CPI-U) in United States: Consumer Price Index of All-items, 1982-84=100, by region Col. 1 Yr/Mon  Col. 2  Northeast North Central  Col. 3 South  Col. 4 West  Col. 5 Other  1  Col. 6"* U.S.  198801  118.9  113.4  114.1  116.7  116.2  115.8  198802  119.2  113.7  114.4  116.9  116.5  116.1  198803  119.6  114.3  114.8  117.5  117.0  116.6  198804  120.4  114.9  115.4  117.9  117.7  117.2  198805  120.7  115.5  115.6  118.5  118.1  117.6  198806  121.4  116.0  116.1  118.7  118.7  118.1  198807  121.8  116.6  116.6  119.2  119.2  118.6  198808  122.5  117.2  117.0  119.6  119.9  119.1  198809  123.9  117.7  117.7  120.2  120.8  119.9  198810  124.1  118.1  118.2  120.7  121.1  120.3  198811  124.4  118.1  118.3  120.7  121.3  120.4  198812  124.5  118.2  118.5  120.9  121.4  120.5  198901  125.4  118.7  118.9  121.7  122.1  121.2  198902  125.8  119.3  119.2  122.3  122.6  121.7  198903  126.7  119.8  119.8  123.1  123.3  122.4  198904  127.4  120.8  120.8  123.8  124.1  123.2  198905  128.3  121.3  121.3  124.5  124.8  123.9  198906  128.5  121.8  121.7  124.6  125.2  124.2  198907  129.0  122.0  122.0  125.1  125.5  124.5  198908  129.1  122.0  122.1  125.3  125.6  124.6  198909  130.0  122.5  122.5  125.6  126.3  125.2  198910  130.6  123.0  123.0  126.1  126.8  125.7  198911  131.1  123.2  123.2  126.3  127.2  126.0  198912  131.3  123.2  123.4  126.8  127.3  126.2  199001  132.9  124.5  124.6  127.8  128.7  127.5  199002  133.1  124.9  125.4  128.8  129.0  128.1  199003  134.1  125.5  126.0  129.6  129.8  128.8  199004  134.5  125.8  126.1  129.6  130.2  129.0  199005  134.7  126.0  126.5  130.0  130.4  129.3  199006  134.9  126.9  127.3  130.8  130.9  130.0  199007  136.0  126.9  127.8  131.3  131.5  130.5  199008  137.4  128.4  128.7  132.2  132.9  131.7  199009  138.6  129.4  129.7  133.5  134.0  132.8  199010  139.4  130.0  130.7  134.3  134.7  133.6  199011  139.7  130.4  130.9  134.5  135.1  133.9  199012  139.7  130.2  130.9  135.0  135.0  134.0  199101  140.9  130.5  131.4  136.0  135.7  134.7  199102  141.2  130.8  131.7  135.9  136.0  134.9  199103  141.4  131.3  131.9  135.8  136.4  135.1  199104  141.6  131.5  132.1  136.2  136.6  135.4  199105  141.7  132.3  132.5  136.3  137.0  135.7  199106  142.1  132.6  132.8  136.8  137.4  136.1  199107  142.4  132.4  133.0  137.3  137.4  136.3  199108  142.9  133.3  137.9  137.9  136.7  199109  143.6  132.8 133.4  133.8  138.6  138.5  137.4  Table A6: Consumer Price Index for All Urban Consumers (CPI-U) in United States: Consumer Price Index of All-items, 1982-84=100, by region -continued from previous page Col. 1  Col. 2  Col. 3  Col. 4  Col. 5"  Yr/Mon  Northeast  North Central  South  West  Other  199110  143.7  133.6  134.1  199111  144.3  134.0  199112  144.6  199201  1  Col. 6"*  138.6  138.7  137.5  134.4  139.0  139.2  137.9  134.1  134.3  139.0  139.4  138.0  144.9  134.1  134.4  139.8  139.5  138.3  199202  145.3  134.3  134.9  140.5  139.8  138.8  199203  146.2  134.8  135.5  141.1  140.5  139.4  199204  146.3  135.1  135.9  141.3  140.7  139.7  199205  146.3  135.5  136.2  141.4  140.9  139.9  199206  147.0  136.0  136.7  141.6  141.5  140.3  199207  147.5  136.3  136.8  141.9  141.9  140.6  199208  148.2  136.7  137.0  142.3  142.5  141.1  199209  148.5  137.2  137.3  142.9  142.9  141.5  199210  148.9  137.4  137.8  143.7  143.2  142.0  199211  149.0  137.6  138.1  143.9  143.3  142.2  199212  148.9  137.7  137.9  143.9  143.3  142.1  199301  149.7  138.1  138.4  144.7  143.9  142.7  199302  150.4  138.6  139.1  145.2  144.5  143.3  199303  150.9  139.0  139.7  145.2  145.0  143.7  199304  151.1  139.4  140.2  145.7  145.3  144.1  199305  150.8  139.8  140.7  146.0  145.3  144.3  199306  151.2  140.0  140.8  146.0  145.6  144.5  199307  151.4  140.0  140.9  146.0  145.7  144.6  199308  151.7  140.4  141.5  146.2  146.1  145.0  199309  151.8  140.9  141.6  146.6  146.4  145.2  199310  152.5  141.5  142.2  147.1  147.0  145.8  199311  152.7  141.4  142.3  147.5  147.1  146.0  199312  152.7  141.2  142.2  147.8  147.0  146.0  199401  153.2  141.5  142.5  148.1  147.4  146.3  199402  154.0  142.1  142.9  148.3  148.1  146.8  199403  154.3  142.6  143.6  149.0  148.5  147.4  199404  154.4  142.9  143.8  148.9  148.7  147.5  199405  154.2  143.3  144.3  148.8  148.8  147.7  199406  154.8  144.0  144.7  148.9  149.4  148.1  199407  155.2  144.3  145.0  149.5  149.8  148.5  199408  155.9  145.2  145.5  150.1  150.6  149.2  199409  156.1  145.6  145.8  150.6  150.9  149.5  199410  156.4  145.3  145.9  151.0  150.9  149.7  199411  156.7  145.8  146.0  151.1  151.3  149.9  199412  156.3  145.7  146.1  151.2  151.0  149.8  Source: Bureau of Labor Statistics, CPI Detailed Report, various issues. 1  "  2  Column 5 = (Column 1 + Column 2) / 2 Column 6 = (Column 1 + Column 2 + Column 3 + Column 4) / 4  U.S.  Table A6: Consumer Price Index for All Urban Consumers (CPI-U) in United States: Consumer Price Index of Food, 1982-84=100, by region Yr/Mon  Col. 1 Col. 2 Northeast North Central  Col. 3 South  Col. 4  1  West  Col. 5" Other  Col. 6"* U.S.  198801  118.6  113.7  115.1  115.2  116.2  115.7  198802  118.8  113.6  115.2  115.1  116.2  115.7  198803  118.4  113.7  115.6  115.5  116.1  115.8  198804  119.7  114.3  115.8  116.1  117.0  116.5  198805  119.8  114.9  116.3  116.7  117.4  116.9  198806  120.8  115.4  116.9  116.8  118.1  117.5  198807  121.9  116.5  118.2  118.0  119.2  118.7  198808  122.6  117.2  118.8  118.6  119.9  119.3  198809  123.3  118.1  119.7  119.2  120.7  120.1  198810  122.9  118.3  120.0  119.7  120.6  120.2  198811  123.0  118.1  119.9  119.5  120.6  120.1  198812  123.4  118.4  120.1  120.3  120.9  120.6  198901  125.3  119.8  121.4  121.9  122.6  122.1  198902  126.1  120.3  122.0  122.9  123.2  122.8  198903  126.9  120.9  122.4  123.6  123.9  123.5  198904  127.6  121.3  123.4  124.2  124.5  124.1  198905  128.5  121.8  124.0  125.0  125.2  124.8  198906  129.2  121.9  124.2  124.6  125.6  125.0  198907  129.8  122.4  124.7  124.9  126.1  125.5  198908  129.9  122.7  124.9  125.2  126.3  125.7  198909  129.9  123.2  125.2  125.7  126.6  126.0  198910  130.0  123.5  125.7  126.3  126.8  126.4  198911  130.6  123.9  125.9  126.7  127.3  126.8  198912  130.8  124.5  126.7  127.3  127.7  127.3  199001  133.8  127.4  129.9  130.1  130.6  130.3  199002  135.0  128.2  130.6  131.2  131.6  131.3  199003  135.1  128.4  130.8  131.4  131.8  131.4  199004  135.0  128.3  130.3  131.1  131.7  131.2  199005  135.1  128.6  130.1  131.1  131.9  131.2  199006  135.7  129.5  131.0  131.4  132.6  131.9  199007  136.5  130.3  131.6  131.9  133.4  132.6  199008  136.7  130.5  132.0  132.1  133.6  132.8  199009  136.6  130.7  132.6  132.6  133.7  133.1  199010  136.9  130.8  133.2  133.2  133.9  133.5  199011  137.2  131.3  133.3  134.0  134.3  134.0  199012  137.4  131.7  133.3  134.1  134.6  134.1  199101  139.0  132.9  134.6  136.7  136.0  135.8  199102  139.1  132.5  134.3  135.9  135.8  135.5  199103  139.4  132.8  134.6  136.1  136.1  135.7  199104  140.7  133.6  135.1  137.2  137.2  136.7  199105  140.6  134.1  135.1  137.1  137.4  136.7  199106  141.2  134.3  135.8  137.4  137.8  137.2  199107  140.2  133.8  135.4  136.2  137.0  136.4  199108  139.5  133.3  135.2  135.4  136.4  135.9  199109  139.4  133.6  135.2  135.4  136.5  135.9  Table A6: Consumer Price Index for All Urban Consumers (CPI-U) in United States: Consumer Price Index of Food, 1982-84=100, by region -continued from previous page Col. 1  Col. 2  Col. 3  Col. 4  Col. 5"  Yr/Mon  Northeast  North Central  South  West  Other  U.S.  199110  139.0  133.4  134.6  135.7  136.2  135.7  199111  139.5  133.8  134.7  136.7  136.7  136.2  199112  140.0  134.2  135.1  137.3  137.1  136.7  199201  140.8  134.4  135.9  137.6  137.6  137.2  199202  141.1  134.4  136.1  138.0  137.8  137.4  199203  141.8  134.9  136.4  139.0  138.4  138.0  199204  142.0  134.9  136.6  138.7  138.5  138.1  199205  141.6  134.8  135.6  137.6  138.2  137.4  199206  141.8  134.7  135.3  137.7  138.3  137.4  199207  141.4  134.4  135.5  137.2  137.9  137.1  199208  142.0  135.0  136.4  138.6  138.5  138.0  199209  142.3  135.5  136.7  139.3  138.9  138.5  199210  142.5  135.1  136.3  139.5  138.8  138.4  1  199211  142.5  135.5  136.1  139.1  139.0  138.3  199212  142.9  135.9  136.2  139.7  139.4  138.7  199301  144.3  136.4  137.3  141.2  140.4  139.8  199302  144.3  136.4  137.9  140.9  140.4  139.9  199303  144.7  136.6  138.0  141.2  140.7  140.1  199304  145.3  137.0  138.0  142.1  141.2  140:6  199305  145.4  138.3  138.6  142.3  141.9  141.2  199306  144.6  137.5  138.0  141.4  141.1  140.4  199307  144.5  137.8  137.9  141.3  141.2  140.4  199308  145.0  138.0  138.9  141.2  141.5  140.8  199309  145.1  138.4  138.9  141.6  141.8  141.0  199310  145.5  138.9  139.7  142.3  142.2  141.6  199311  146.1  139.0  139.8  142.8  142.6  141.9  199312  146.8  139.3  140.5  144.2  143.1  142.7  199401  147.7  140.2  141.6  145.2  144.0  143.7  199402  146.9  139.7  140.9  144.3  143.3  143.0  199403  146.9  139.9  141.4  144.3  143.4  143.1  199404  147.3  139.9  141.7  144.4  143.6  143.3  199405  147.4  140.5  141.7  144.2  144.0  143.5  199406  147.7  140.4  141.6  144.2  144.1  143.5  199407  148.4  140.8  142.6  144.9  144.6  144.2  199408  149.1  141.4  143.2  145.1  145.3  144.7  199409  149.4  141.6  143.4  145.5  145.5  145.0  199410  149.5  141.6  142.9  146.1  145.6  145.0  199411  149.6  141.9  146.6  145.8  145.4  199412  150.8  143.0  143.3 144.7  148.8  146.9  146.8  Source: Bureau of Labor Statistics, CPI Detailed Report, various issues. 1  "  2  Col. 6 "  Column 5 = (Column 1 + Column 2) / 2 Column 6 = (Column 1 + Column 2 + Column 3 + Column 4) / 4  Table A6: Consumer Price Index for All Urban Consumers (CPI-U) in United States: Consumer Price Index of Fruits and Vegetables, 1982-84=100, by region Yr/Mon  Col. 1 Col. 2 Northeast North Central  Col. 3 South  Col. 4  1  Col. 6 *  West  Col. 5" Other  U.S.  198801  129.5  123.0  122.8  130.4  126.3  126.4  198802  129.0  121.2  121.5  126.8  125.1  124.6  198803  125.2  119.0  120.9  126.7  122.1  123.0  198804  131.2  121.8  122.3  128.8  126.5  126.0  198805  130.7  124.1  123.2  130.5  127.4  127.1  198806  132.2  121.6  122.8  127.4  126.9  126.0  198807  135.2  123.5  127.6  128.7  129.4  128.8  198808  136.5  125.5  128.0  128.7  131.0  129.7  198809  138.2  128.5  132.2  133.0  133.4  133.0  198810  133.2  128.5  130.9  133.7  130.9  131.6  198811  131.9  125.4  129.0  131.1  128.7  129.4  198812  132.8  128.4  128.9  133.9  130.6  131.0  198901  136.8  131.6  131.3  139.6  134.2  134.8  198902  138.4  132.9  135.2  142.2  135.7  137.2  198903 198904  137.8  130.8  133.4  141.0  134.3  135.8  140.5  132.5  136.8  141.9  136.5  137.9  198905  146.1  137.2  140.1  147.0  141.7  142.6  198906  144.2  134.7  139.8  141.5  139.5  140.1  198907  145.1  134.9  140.3  139.3  140.0  139.9  198908  142.9  132.8  139.8  138.9  137.9  138.6  198909  140.2  129.9  136.7  139.0  135.1  136.5  198910  138.2  130.2  137.7  142.0  134.2  137.0  198911  140.6  129.7  137.7  142.6  135.2  137.7  198912  138.3  127.8  137.1  143.2  133.1  136.6  199001  154.6  144.5  156.9  158.1  149.6  153.5  199002  159.4  148.6  160.5  162.2  154.0  157.7  199003  156.4  145.5  154.8  158.4  151.0  153.8  199004  152.1  140.6  148.2  154.5  146.4  148.9  199005  151.8  140.9  143.1  153.8  146.4  147.4  199006  152.8  141.0  144.7  149.5  146.9  147.0  199007  154.4  144.7  146.9  151.0  149.6  149.3  199008  151.2  140.1  144.8  147.7  145.7  146.0  199009  147.7  138.3  145.3  148.5  143.0  145.0  199010  146.8  137!1  144.2  150.2  142.0  144.6  199011  148.6  139.7  144.4  154.2  144.2  146.7  199012  147.8  141.6  144.0  152.9  144.7  146.6  199101  157.7  148.8  151.8  170.0  153.3  157.1  199102  156.1  147.6  152.2  162.8  151.9  154.7  199103  157.3  147.7  152.7  164.6  152.5  155.6  199104  167.0  155.4  157.4  171.9  161.2  162.9  199105  166.5  158.0  156.1  172.2  162.3  163.2  199106  170.2  161.0  161.5  175.0  165.6  166.9  199107  161.2  153.0  156.7  161.2  157.1  158.0  199108  152.5 151.8  146.4  150.8 152.1  150.0 151.8  149.5 149.3  149.9  199109  146.8  150.6  Table A6: Consumer Price Index for All Urban Consumers (CPI-U) in United States: Consumer Price Index of Fruits and Vegetables, 1982-84=100, by region -continued from previous page Col. 1 Yr/Mon  Col. 2  Col. 3  Col. 4  Col. 5"  Northeast North Central  South  West  Other  U.S.  1  Col. 6"*  199110  147.7  144.2  144.5  151.6  146.0  147.0  199111  150.2  149.8  146.3  159.3  150.0  151.4  199112  152.6  151.8  147.5  160.6  152.2  153.1  199201  157.6  150.2  151.3  160.6  153.9  154.9  199202  161.9  149.5  153.7  162.4  155.7  156.9  199203  163.3  153.5  159.2  169.2  158.4  161.3  199204  164.7  155.7  160.4  166.9  160.2  161.9  199205  160.8  153.0  150.1  156.4  156.9  155.1  199206  158.7  147.9  148.0  152.5  153.3  151.8  199207  157.1  144.4  147.3  147.9  150.8  149.2  199208  158.5  146.9  152.3  156.3  152.7  153.5  199209  160.7  145.3  154.0  161.5  153.0  155.4  199210  158.2  144.6  151.2  160.5  151.4  153.6  199211  159.6  146.1  150.0  160.0  152.9  153.9  199212  162.9  149.2  150.4  162.1  156.1  156.2  199301  165.3  152.4  155.5  170.6  158.9  161.0  199302  164.8  149.3  157.9  165.2  157.1  159.3  199303  163.7  151.1  156.5  164.8  157.4  159.0  199304  166.7  150.2  155.6  171.0  158.5  160.9  199305  169.1  157.6  160.9  170.4  163.4  164.5  199306  159.0  147.5  152.0  157.8  153.3  154.1  199307  158.1  145.1  149.2  155.2  151.6  151.9  199308  160.7  145.9  154.7  154.0  153.3  153.8  199309  162.4  148.2  157.9  158.8  155.3  156.8  199310  163.5  150.9  158.8  160.8  157.2  158.5  199311  164.5  152.6  157.8  166.4  158.6  160.3  199312  169.4  156.2  163.4  177.2  162.8  166.6  199401  170.1  159.7  169.2  180.3  164.9  169.8  199402  163.8  153.8  160.1  169.2  158.8  161.7  199403  164.8  153.1  161.9  170.8  159.0  162.7  199404  164.7  151.3  160.8  169.9  158.0  161.7  199405  166.9  153.9  163.2  168.1  160.4  163.0  199406  166.7  151.2  161.3  166.3  159.0  161.4  199407  171.1  151.6  166.5  167.0  161.4  164.1  199408  168.7  149.8  167.3  163.3  159.3  162.3  199409  168.5  150.6  164.0  168.7  159.6  163.0  199410  166.3  150.1  161.9  173.0  158.2  162.8  199411  168.1  153.4  163.9  177.4  160.8  165.7  199412  180.7  166.8  178.4  195.6  173.8  180.4  Source: Bureau of Labor Statistics, CPI Detailed Report, various issues. *  1  Column 5 = (Column 1 + Column 2) / 2  *  2  Column 6 = (Column 1 + Column 2 + Column 3 + Column 4) / 4  Table A7: Canada-U.S. Exchange Rates Exchange Rates are expressed in Canadian cents per U.S. dollar. Yr/Mon Exchange  Yr/Mon  Rates  Exchange Rates  198801  128.53  199108  114.47  198802  126.79  199109  113.68  198803 198804  124.91  199110  112.79  123.51 123.69 121.74  113.03 114.57  120.73  199111 199112 199201 199202  198808  122.43  199203  119.26  198809  199204  118.75  198810  122.65 120.52  199205  119.90  198811  121.74  198812  119.60 119.14  199206 199207  119.59 119.17  198805 198806 198807  198901  115.65 118.25  199208  119.09  199209 199210  122.23  198903  118.90 119.53  198904  118.86  199211  126.80  198905  119.27  199212  127.27  198906  119.83  199301  127.76  198907  118.88  199302  125.97  198908  117.54  199303  124.69  198909  118.26  199304  126.20  198910  117.48  199305  127.01  198911  116.96  199306  127.86  198912  116.12  199307  128.17  199001  117.14  199308  130.88  199002  119.65  199309  132.12  199003  117.98  199310  199004  116.39  199311  132.61 131.77  199005  117.46  199312  133.07  199006  117.28  199401  131.74  199007  115.68  199402  134.21  199008  114.44  199403  136.43  199009  115.82  199404  138.25  199010  115.98  199405  138.10  199011  116.31  199406  138.38  199012  116.00  199407  138.25  199101  115.59  199408  137.76  199102  115.46  199409  135.37  199103  115.69  199410  135.00  199104  115.33  199411  136.49  199105  114.96  199106 199107  114.37  198902  124.50  114.91  Source: Bank of Canada International Department. CANSIM: Series B40001.  140  APPENDIX B:  Before e s t i m a t i n g  VARIABLE CONSTRUCTION  the demand equations, we must generate the  v a r i a b l e s i n t o t h e i r d e s i r a b l e forms.  The d e s i r a b l e forms are  generated as f o l l o w s : The  f o l l o w i n g v a r i a b l e s are used t o estimate the demand equations  in the various (1)  PCQf  (2)  RPf  =  (3)  RPVt  =  (4)  RPCY  regions Total  =  Sales  in  Population  in  Price  -  (5)  A  i  CP I  of  Food  CP I  of  Fresh Vegetables in Region of  in Region  Food  in  i'  Region  i  Population in Re gion i i i s expressed as:  Cumulative Advertisine  n  RAD  i  Real Income in Re gion i  =  and  Expenditure  for  the year  -  CPI The  i  Wages and Salaries in Region i CPI of all —items in Region i  ' „  i  Region  where r e a l income i n r e g i o n RINC  Region  in Region  CP I  =  (  o f Canada:  of  .  all-items  in Region  i  f o l l o w i n g v a r i a b l e s are used t o estimate the demand equations  i n Washington, Oregon, and C a l i f o r n i a : . <c\  ur-n^r  (6)  rL(Jlj  T  =  o  t  a  l  a  l  e  S  — — Population (Price  RPT  S  i  ^8  n  ; in Region  in Region CPI  ,  :  j)  J  j  i o n  of  Food  j  ( Re a/ Exchange Rate in Western US  )  141  No minal Exchange Rate * CPI of all - items in Western US where: Real Exchange Rate = CPI of all-items in BC /os  p ,  , r P T  (8)  RPFVWEST =  (9)  RPCY =  n  n  m  CPI of Fresh Fruits and Vegetables in Western US CPI of Food in Western US Real Income in Region j Population in Re gion j  where r e a l income i n r e g i o n j i s expressed as: „„ ^, RINC: = T  (10) RAD —  Total Personal Income in Region j -, and CPI of all-items in Western US {Cumulative Advertising Expenditure for the year){ Real Exchange Rate CPI of all — items in Western US  The f o l l o w i n g v a r i a b l e s are used t o estimate i n other p a r t s o f United (11)  PCQTOTH  (12)  RPTOTH  =  the demand  )  equation  States:  ° ° °f Population in Other Parts of US T  t a l  S a l e S  i n  t h e r  P a r t S  (Price in Other Parts of = CPI  of  US  US) (  — R e a / Exchange Food in Other Parts of US  ) Rate  where Re  Nominal Exchange Rate * CPI of all - items in Other parts of US al L L x e n a n g e Mate — , CPI of all —items in BC D D C T / / 1 T U  CPI of Fresh Fruits and Vegetables in Other Parts of US CPI of Food in Other Parts of US  (14)  DD/^V RrCYj =  Real Income in Re gion o ; , Population in Re gion o  where r e a l income i n r e g i o n o i s expressed as:  142 ...„„ „  n  T  KlINLOlti  =  Total CPI  (15) RAD —  Personal of  Income in Other Parts of USS , and — . and all - items in Other Parts of US  (Cumulative Advertising Expenditure for the year)( —) ^ Rea/ Exchange Rate CPI of all — items in Other Parts of US  143 APPENDIX C :  DEMAND E S T I M A T I O N R E S U L T S F O R B . C . HOTHOUSE CUCUMBERS AND B . C . HOTHOUSE P E P P E R S  The demand equations f o r BC Hothouse cucumbers and BC Hothouse peppers are estimated using the same techinques as the demand equations f o r BC Hothouse tomatoes.  We use the same method because  the products are s i m i l a r i n that they are export o r i e n t e d and have strong competition from both l o c a l and imported f i e l d crops i n the domestic market and the export market.  For the estimation of  greenhouse cucumber demand, we use seven years of data and f o r the estimation o f greenhouse pepper demand, we use two years of data. The r e s u l t s presented here are f o r those who are i n t e r e s t e d i n knowing how the demand f u n c t i o n s f o r the r e s t of the greenhouse products i n BC looks l i k e .  An a n a l y s i s of these r e s u l t s w i l l not  be provided here. DEMAND ESTIMATION T a b l e C1:  British  RESULTS FOR B CHOTHOUSE CUCUMBERS  Columbia  Dependent Variable:  PCQCBC  Variables  O L S * Elasticity LINEAR  Mean of P C Q C B C RPCBC RPVBC RPCYBC TIME CONSTANT  at  Means  10.467 -118.33 (-8.674)** 6.159 (1.916)* 1.3117 (0.8359) 0.13859 (0.3244) 7.1691 (0.4807)  2SLS E l a s t i c i t y LINEAR  at M e a n s  10.467 -192.26 (-9.021)**  -2.2487  0.6038  10.745 (3.221)** -0.67814 (-0.3872) -0.3513 (-1.219) 30.043 (1.766)*  1.0534  0.0539 0.6849  Elasticity at  Means  2.1375  -1.384  1.0412  OLS* LOG-LOG  -0.5383 -0.1367 2.8704  -2.9739 (-10.71)** 0.84724 (1.738)* 0.24612 (0.1311) -0.23226 (-1.957)* -4.4441 (-1.138)  2SLS E l a s t i c i t y LOG-LOG  -2.9739 0.8472 0.2461 -0.2323 -4.4441  -4.0056 (-10.29)** 1.2143 (2.454)** -0.65364 (-0.3342) -0.46052 (-3.683)** -4.4548 (-1.110)  ESS  402.05  687.02  10.713  14.099  R  0.8062  0.6688  0.7274  0.6413  0.7939  0.6478  0.7101  0.6185  1.6384  1.0947  1.9016  1.4588  2  R (adj) Durbin-Watson 2  at M e a n s  2.1375 -4.0056 1.2143 -0.65364 -0.46052 -4.4548  Note: 1. t statistics in brackets 2. ** significant at 95% 3. * significant at 90% 4. * indicates that the regression has been corrected for serial correlation using the Cochrane-Orcutt method.  144  DEMAND ESTIMATION RESULTS FOR BC HOTHOUSE CUCUMBERS Table C2: Prairie Region of Canada Dependent Variable: PCQCPR Variables  OLS Elasticity LINEAR at Means  2SLS Elasticity LINEAR at Means  Mean of P C Q C P R  0.38944  0.38944  RPCPR RPVPR RPCYPR TIME CONSTANT ESS R  1.7145 (1.575) 1.4579 (2.072)" 0.79875 (2.352)" 0.10784 (2.776)" -7.5813 (-2.591)"  0.424 3.4784 15.4518 1.1129 -19.4671  7.6397 0.1866 0.1174 1.868  2  -2.1062 -0.424 3.4943 12.8277 0.9454 -15.8434  9.2526 0.0149 -0.0689 1.9441  R (adj) Durbin-Watson Note: 1. t statistics in brackets 2. " significant at 95% 3. * significant at 90% 2  -1.7144 (-0.7368) 1.4645 (1.891)* 0.6631 (1.736)* 0.091603 (2.092)** -6.17 (-1.856)*  OLS" Elasticity LOG-LOG at Means  1.5951 (10.47)** 3.1553 (1.555) 25.688 (3.317)" 1.3543 (3.375)** -51.179 (-3.232)**  2SLS Elasticity LOG-LOG at Means -2.1062  1.5951 3.1553 25.688 1.3543 -51.179  63.905 0.7307 0.7078 1.8534  1.3684 (3.339)** 2.9898 (1.511) 28.647 (4.022)" 1.3591 (4.006)** -57.755 (3.943)"  1.3684 2.9898 28.647 1.3591 -57.755  71.852 0.6972 0.6714 1.4566  4. * indicates that the regression has been corrected for serial correlation using the Cochrane-Orcutt method. DEMAND ESTIMATION RESULTS FOR BC HOTHOUSE CUCUMBERS Table C3: Eastern Canada Dependent Variable: PCQCEA Variables Mean of P C Q C E A S T  OLS Elasticity LINEAR at Means 0.46495  RPCEAST  -0.25297 (-0.1171)  -0.0443  RPVEAST  -0.04696 (-0.1281) 0.36475 (8.075)** 0.078262 (3.097)** -2.9924 (-6.044)**  -0.1046  RPCYEAST TIME CONSTANT  6.9073 0.6776 -6.436  2SLS Elasticity LINEAR at Means 0.46495 1.24 (0.2556) -0.11023 (-0.2673) 0.36555 (8.026)** 0.082532 (2.916)" -3.0727 (-5.583)**  OLS Elasticity LOG-LOG at Means -1.253  0.2172 -0.2456 6.9224 0.7146 -6.6086  0.19187 (0.7275) 0.10488 (0.1053) 5.0385 (4.101)" 0.28258 (1.339) -12.03 (-4.428)**  2SLS Elasticity LOG-LOG at Means -1.253  0.19187 0.10488 5.0385 0.28258 -12.03  0.25522 (0.2709) 0.03937 (2.8816-02)  0.25522  5.0626 (3.966)" 0.28731 (1.295) -11.922 (-3.814)"  5.0626  ESS  3.2488  3.2944  23.131  23.17  R  0.7127  0.7087  0.3683  0.3672  0.679 2.1016  0.6744 2.093  0.2939 2.131  0.2927 2.1281  2  R (adj) Durbin-Watson 2  Note: 1. t statistics in brackets 2. " significant at 95% 3. * significant at 90%  0.03937  0.28731 -11.922  145  DEMAND ESTIMATION RESULTS FOR BC HOTHOUSE CUCUMBERS Table C4: Washington Dependent Variable: PCQCWASH Variables OLS Elasticity 2SLS Elasticity OLS Elasticity 2SLS Elasticity LINEAR at Means LINEAR at Means LOG-LOG at Means LOG-LOG at Means Mean of P C Q C W A S H RPCWASH RPFVWEST RPCYWEST TIME CONSTANT  0.46404  -10.988 (-5.745)" -1.5295 (-2.015)" 0.5534 (2.838E-02) 0.040018 (0.8902) 2.7077 (1.031)  0.46404  -1.5631 -3.7886 0.1731 0.3436 5.8351  -14.968 (-5.001)" -1.2211 (-1.516) 1.2747 (6.309E-02) 0.027427 (0.5822) 2.5614 (0.9409)  -1.2019  -2.1293 -3.0246 0.3986 0.2355 5.5198  -2.9419 (-5.927)" -2.3217 (-0.6357) 9.8896 (0.6174) -0.31248 (-0.3727) 10.499 (0.3300)  -1.2019  -2.9419 -2.3217 9.8896 -0.31248 10.499  -6.4089 (-5.369)" 3.4418 (0.6616) 15.145 (0.6979) -1.0722 (-0.9292)  -6.4089  11.231 (0.2612)  11.231  ESS R  3.5425  3.8025  56.904  103.96  0.4901  0.4527  0.4292  -0.0428  R (adj) Durbin-Watson  0.4555 1.7884  0.4156 1.9279  0.3905 1.8201  -0.1135 2.0284  2  2  3.4418 15.145 -1.0722  Note: 1. t statistics in brackets 2. " significant at 95% 3. * significant at 90%  DEMAND ESTIMATION RESULTS FOR BC HOTHOUSE CUCUMBERS Table C5: Oregon Dependent Variable: PCQCORE Variables OLS* Elasticity 2SLS Elasticity OLS* Elasticity 2SLS Elasticity L I N E A R a t M e a n s L I N E A R a t M e a n s L O G L O G a t M e a n s L O G -LOG at Means Mean of P C Q C O R E 0.61585 0.61585  RPCORE RPFVWEST RPCYORE TIME CONSTANT ESS R  2  R (adj) Durbin-Watson 2  -15.291 (-4.801)** 1.2114 (1.035)  -1.6529  19.624 (0.4554) -1.94E-02 (-0.2697) -2.2359 (-0.3957)  4.1471  2.2624  -0.1276 -3.6305  -0.77402  -28.464 (-4.397)** 0.9568 (0.8666)  -3.0768  3.8382 (0.1116) 0.013312 (0.2353) 0.85679 (0.1881)  -0.77402  -1.8612 (-3.354)**  -1.8612  -7.6767  -7.6767  0.42203 (0.1146)  0.42203  (-3.930)** 0.546 (0.1051)  0.546  0.8111  -7.7213  -7.7213  -22.452  -22.452  0.0875  (-0.5666) 0.40717  1.7869  1.3912  (0.7159) -22.161 (-0.7748)  0.40717 -22.161  (-1.367) 1.138 (1.644) -69.012 (-1.882)*  4.8617  6.983  33.31  107.36  0.472  0.2416  0.3521  -1.0883  0.4336 1.8754  0.1864 1.395  0.3049 1.8168  -1.2402 1.4129  1.138 -69.012  Note: 1. t statistics in brackets 2. ** significant at 95% 3. * significant at 90% 4. * indicates that the regression has been corrected for serial correlation using the Cochrane-Orcutt method.  146  DEMAND ESTIMATION RESULTS FOR BC HOTHOUSE CUCUMBERS Table C 6 : California Dependent Variable: PCQCCAL Variables  OLS Elasticity LINEAR at Means  2SLS Elasticity LINEAR at Means  Mean of P C Q C C A L  0.12231  0.12231  RPCCAL RPVCAL RPCYCAL TIME CONSTANT ESS R 2  R (adj) Durbin-Watson 2  -1.8683 (-2.510)** -0.502 (-2.067)** 12.363 (1.974)* 0.030502 (2.988)** -1.2136 (-1.193)  -2.4312  -0.872  -2.577.7 (-1.664)  -1.2031  -4.7078  -0.48489 (-1.961)* 11.656 (1.804)* 0.028923 (2.695)** -1.0779 (-1.018)  -4.5474  15.478 1.0248 -9.923  OLS Elasticity LOG-LOG at Means  14.5918 0.9717 -8.813  -1.7669 (-4.461)** -10.394 (-3.767)** 18.36 (2.363)** 1.2108 (4.422)** 26.821 (1.853)*  2SLS Elasticity LOG-LOG at Means -2.4312  -1.7669 -10.394 18.36 1.2108 26.821  -2.4806 (-2.345)** -10.252 (-3.592)** 17.588 (2.175)** 1.1768 (4.110)** 23.332 (1.488)  0.28065  0.28574  24.885  26.501  0.2997  0.287  0.5015  0.4691  0.2437 2.053  0.23 2.0735  0.4616 2.1191  0.4267 2.0972  -2.4806 -10.252 17.588 1.1768 23.332  Note: 1. t statistics in brackets 2. ** significant at 95% 3. * significant at 90% DEMAND ESTIMATION RESULTS FOR BC HOTHOUSE CUCUMBERS Table C 7 : Other Regions of United States Dependent Variable: PCQCOTH Variables Mean of P C Q C O T H RPCOTH  OLS Elasticity LINEAR at Means 0.0096467  2SLS Elasticity LINEAR at Means 0.0096467  -0.27184 (-3.850)** 0.051041 (1.117)  -1.7848  0.085675 (0.1079) -0.000421  1.3373  OLS* Elasticity LOG-LOG at Means -5.3231  2SLS Elasticity LOG-LOG at Means -5.3231  -0.52751 (-2.692)** 0.0045697 (7.419E-02)  -3.4634  -9.6294  CONSTANT  (-0.4233) -0.041032 (-0.2842)  -0.61693 (-0.5970) -0.1987 -7.7702E-05 (-6.674E-02) -4.2535 0.13121 (0.6417)  ESS  0.0029433  0.0038622  61.239  593.02  0.3253  0.1146  0.4271  0.261 2.0279  0.0303 2.0345  0.3725 1.7882  -4.5478 -5.0762 1.5802  RPFVOTH RPCYOTH TIME  R  2  R (adj) Durbin-Watson 2  5.8998  0.5282  -0.0367 13.6014  -2.1759 -2.1759 (-3.555)** -6.89E-03 -6.89E-03 (-8.518E-04) -11.429 (-0.4466) 0.66695 (0.8488) -34.001 (-0.6904)  -11.429 0.66695 -34.001  -14.179 (-1.990)* -40.264 (-1.218)  -14.179  -82.32 (-1.356) 1.017 (0.7241) -197.96 (-1.556)  -82.32  -40.264  1.017 -197.96  Note: 1. t statistics in brackets 2. ** significant at 95% 3. * significant at 90% 4. * indicates that the regression has been corrected for serial correlation using the Cochrane-Orcutt method.  147 DEMAND ESTIMATION RESULTS FOR BC HOTHOUSE PEPPERS Table C8: British Columbia Dependent Variable: PCQPBC Variables  OLS" Elasticity LINEAR at Means  Mean of P C Q P B C RPPBC RPVBC RPCYBC TIME CONSTANT ESS R  8.6297 -53.026 (-2.015)* -13.379 (-1.569) 6.024 (1.425) -2.6057 (-1.094) -16.151 (-0.4544)  8.6297 -0.8145 -1.6186 5.7332 -0.4529 -1.8716  153.93 0.631  2  0.5326 1.993 Note: 1. t statistics in brackets 2. ** significant at 95% 3. * significant at 90% 2  #  -33.818 (-0.5242) -15.251 (-0.9686) 10.874 (2.344)** -2.0305 (-0.8326) -57.228 (-1.555)  OLS Elasticity LOG-LOG at Means 1.4477  -0.5195 -1.8451 10.3491 -0.3529 -6.6316  183.46 0.5602 0.4429 1.355  R (adj) Durbin-Watson  4.  2SLS Elasticity LINEAR at Means  1.7968 (0.8677) -11.618 (-2.155)** 63.69 (3.539)** -3.0816 (-2.178)** -127.47 (-3.397)**  2SLS Elasticity LOG-LOG at Means 1.4477  1.7968 -11.618 63.69 -3.0816 -127.47  44.338 0.5443 0.4228 1.9191  6.0231  6.0231  (1.586) -19.658 (-2.358)** 68.309 (3.315)** -4.3583 (-2.373)** -127.77 (-3.012)**  -19.658 68.309 -4.3583 -127.77  56.649 0.4178 0.2626 1.8523  indicates that the regression has been corrected for serial correlation using the Cochrane-Orcutt method.  DEMAND ESTIMATION RESULTS FOR BC HOTHOUSE PEPPERS Table C9: Prairie Region of Canada Dependent Variable: PCQPPR Variables Mean of P C Q P P R RPPPR RPVPR RPCYPR TIME  OLS* Elasticity LINEAR at Means 2.5018 -20.336 (-2.161)** 5.2847 (1.165) 2.8842 (1.154) -0.38478  15.087 -1.3591 1.8716 8.4915 -0.2307  (-0.480) CONSTANT  -19.469 (-1.044)  2SLS Elasticity LINEAR at Means  0.71827  -36.872 (-1.690) 10.985 (1.375)  -2.4643  1.956 (0.5759) 0.60777  5.7585  -0.3703 (-0.4025) 3.8906 -0.12826 (-5.295E-02)  0.3644  (0.4206) -7.7819  -16.385 (-0.7196)  OLS* Elasticity LOG-LOG at Means  -6.5492  2SLS Elasticity LOG-LOG at Means 0.71827  -0.3703  -7.0742 (-1.485) 11.912 (1.254)  -7.0742  31.993 (3.422)** -1.2749  -2.392 (-7.877E-02) -1.2749 2.4981  -2.392  (-1.844)*  (0.8628) -6.7189 (-0.1235)  -63.395 (-3.539)**  -0.12826 31.993  -63.395  ESS  10.989  15.087  4.4055  19.29  R  0.5757  0.4175  0.5757  -0.8581  0.4451 1.8463  0.2382 1.3296  0.4451 2.0403  -1.4298 1.3334  2  R (adj) Durbin-Watson 2  11.912  2.4981 -6.7189  Note: 1. t statistics in brackets 2. ** significant at 95% 3. * significant at 90% 4. * indicates that the regression has been corrected for serial correlation using the Cochrane-Orcutt method.  148  DEMAND ESTIMATION RESULTS FOR BC HOTHOUSE PEPPERS Table C10: Eastern Canada Dependent Variable: PCQPEA Variables Mean of P C Q P E A S T RPPEAST RPVEAST RPCYEAST TIME CONSTANT ESS R 2  R (adj) Durbin-Watson 2  OLS* Elasticity LINEAR at Means 1.553 -14.203 (-7.037)** 5.1511 (6.607)** 0.35578 (7.617)** 1.2637 (6.737)** -6.5943 (-9.699)**  2SLS Elasticity LINEAR at Means 1.553  -1.3285 3.4316 1.938 1.1992 -4.2463  2.1548 0.9331 0.914 2.1271  -16.398 (-4.667)** 5.4449 (4.466)** 0.3435 (4.914)** 1.2794 (4.357)** -6.4893 (-6.110)**  OLS* Elasticity LOG-LOG at Means -0.22088  -1.5338 3.6273 1.8711 1.2141 -4.1787  2.9156 0.9095 0.8837 2.6809  -4.6058 (-4.541)** 7.7713 (2.875)** 0.91124 (0.7112) 3.2845 (3.588)** -12.504 (-4.603)**  2SLS Elasticity LOG-LOG at Means -0.22088  -4.6058 7.7713 0.91124 3.2845 -12.504  16.677 0.6918 0.6038 1.5802  -5.518 (-4.123)** 9.1073 (2.910)** 0.54421 (0.3867) 3.7153 (3.511)** -13.721 (-4.497)**  -5.518 9.1073 0.54421 3.7153 -13.721  17.49 0.6768 0.5845 1.6403  Note: 1. t statistics in brackets 2. ** significant at 95% 3. * significant at 90% 4. * indicates that the regression has been corrected for serial correlation using the Cochrane-Orcutt method. DEMAND ESTIMATION RESULTS FOR BC HOTHOUSE PEPPERS Table C11: Washington Dependent Variable: PCQPWASH Variables Mean of P C Q P W A S H RPPWASH RPFVWEST RPCYWEST TIME CONSTANT  OLS* Elasticity LINEAR at Means 1.3929 -16.983 (-1.799)* 3.5694 (0.5149) 112.65 (0.4979) -0.15515 (-0.1972) -17.542 (-0.5201)  2SLS Elasticity LINEAR at Means 1.3929  -1.3292  -22.23 (-1.391) 2.9613 4.1794 (0.4596) 12.1147 -25.029 (-8.805E-02) -0.1671 0.38697 -12.594  (0.4169) 2.1554 (5.483E-02)  -1.7398 3.4674 -2.6917 0.4167 1.5474  OLS* Elasticity LOG-LOG at Means  2SLS Elasticity LOG-LOG at Means  -0.071766  -O.071766  -1.9182 (-1.360) 10.714 (0.9685) 83.47 (1.906)* -2.7945 (-1.860)* 153.47 (1.798)*  -1.9182 10.714 83.47 -2.7945 153.47  -4.5471 (-1.644) 19.066 (1.172) 13.991 (0.2321) -0.48891 (-0.2555) 13.693 (0.1133)  ESS  6.5076  8.49  12.052  17.587  R  0.4906  0.3354  0.5003  0.2707  0.3338 1.9204  0.1309 1.0693  0.3465 1.8753  0.0463 1.3084  2  R (adj) Durbin-Watson 2  -4.5471 19.066 13.991 -0.48891  Note: 1. t statistics in brackets 2. ** significant at 95% 3. * significant at 90% 4. * indicates that the regression has been corrected for serial correlation using the Cochrane-Orcutt method.  13.693  149  DEMAND ESTIMATION RESULTS FOR BC HOTHOUSE PEPPERS Table C12: Oregon Dependent Variable: PCQPORE Variables Mean of P C Q P O R E RPPORE RPFVWEST RPCYORE TIME CONSTANT ESS R  2  R (adj) Durbin-Watson 2  OLS* Elasticity LINEAR at Means 2.339 -23.824 (-1.472) -6.1566 (-0.4563) 433.74 (0.7771) -1.6655 (-0.6986) -43.773 (-0.6043)  2SLS Elasticity LINEAR at Means 2.339  -1.0901 -3.0416 24.9132 -1.068 -18.7142  -20.514 (-0.6914) -11.8 (-0.6541) 368.44 (0.5660) -1.2423 (-0.4694) -29.466 (-0.3764)  OLS* Elasticity LOG-LOG at Means 0.52568  -0.9386 -5.8297 21.1626 -0.7966 -12.5976  -2.2574 (-2.707)" 9.506 (1.111) 81.614 (1.871)* -3.772 (-1.997)* 159.13 (1.794)*  2SLS Elasticity LOG-LOG at Means 0.52568  -2.2574 9.506 81.614 -3.772 159.13  -2.2699 (-1.299) 4.8883 (0.3962) 39.885 (0.7861) -1.5862  -2.2699 4.8883 39.885 -1.5862  (-0.6935) 75.283 (0.7114)  24.989  25.922  7.7631  9.6909  0.43  0.4087  0.513  0.3921  0.2546 1.8833  0.2267 1.6777  0.3632 1.6944  0.2051 1.2724  75.283  Note: 1. t statistics in brackets 2. " significant at 95% 3. * significant at 90% 4. * indicates that the regression has been corrected for serial correlation using the Cochrane-Orcutt method. DEMAND ESTIMATION RESULTS FOR BC HOTHOUSE PEPPERS Table C13: California Dependent Variable: PCQPCAL Variables  OLS* Elasticity LINEAR at Means  2SLS Elasticity LINEAR at Means  Mean of P C Q P C A L  0.25253  0.25253  RPPCAL RPVCAL RPCYCAL TIME CONSTANT  -2.0068 (-1.334) 0.75406 (0.6267) 38.479 (1.299) -9.36E-02 (-0.9190) -6.0498 (-1.284)  -0.8544 3.4507 22.8635 -0.5557 -23.9571  OLS* Elasticity LOG-LOG at Means -1.6551  -2.6581 (-1.114) -0.027144 (-0.01944)  -1.1317  17.551 (0.5229) -0.049023 (-0.5947) -1.9902 (-0.4059)  10.4284  -0.1242  -0.2912 -7.8813  -1.9293 (-2.300)** 11.093 (1.683) 54.345 (2.656)** -1.4577 (-1.997)* 95.844 (2.405)**  2SLS Elasticity LOG-LOG at Means -1.6551  -1.9293 11.093 54.345 -1.4577 95.844  -4.5296 (-2.373)** 14.884 (1.408) 1.3244 (4.341 E-02) -0.73036 (-1.094) -11.281 (-0.1815)  ESS  0.2063  0.25779  4.4409  8.1278  R  0.4856  0.3573  0.6942  0.4402  0.3274 1.8258  0.1595 1.1933  0.6001 1.9337  0.268 1.4725  2  R (adj) Durbin-Watson 2  -4.5296 14.884 1.3244 -0.73036 -11.281  Note: 1. t statistics in brackets 2. ** significant at 95% 3. * significant at 90% 4. * indicates that the regression has been corrected for serial correlation using the Cochrane-Orcutt method.  150 DEMAND ESTIMATION RESULTS FOR BC HOTHOUSE PEPPERS Table C14: Other Regions of United States Dependent Variable: PCQPOTH Variables  OLS* Elasticity LINEAR at Means  2SLS Elasticity LINEAR at Means  Mean of P C Q P O T H  0.14563  0.14563  RPPOTH RPFVOTH RPCYOTH TIME  -0.4745 (-1.809)* -0.78927 (-0.880) 40.933 (1.975)* -0.17757  -0.487 -5.984 42.9269 -1.829  -1.3423 (-2.689)** -0.951 (-0.7760) 50.55 (1.799)* -0.22942  OLS* Elasticity LOG-LOG at Means -2.1733  -1.3777 -7.2103 53.012 -2.3631  -0.6905 (-1.511) 0.11528 (9.617E-03) 115.58 (2.981)** -4.8485 (-3.161)** 215.33 (2.943)**  2SLS Elasticity LOG-LOG at Means -2.1733  -0.6905  -1.9677  (-2.441)** 0.11528 0.96418 (5.935E-02) 115.58 114.44 (2.279)** -4.8485 -4.6843 (-2.351)** 215.33 210.5 (2.234)**  CONSTANT  (-2.033)* -4.8976 (-1.403)  ESS  4.47E-02  0.084174  6.5211  11.876  0.5102  0.0767 -0.2074 1.6928  0.5644 0.4304 1.669  0.2068 -0.0373 1.3073  R  2  R (adj) Durbin-Watson 2  0.3595 1.8405  -33.6306  (-1.936)* -5.9797 (-1.234)  -41.061  -1.9677 0.96418 114.44 -4.6843  Note: 1. t statistics in brackets 2. ** significant at 95% 3. * significant at 90% 4. * indicates that the regression has been corrected for serial correlation using the Cochrane-Orcutt method.  210.5  APPENDIX D :  COST OF PRODUCTION RESULTS FOR B . C . GREENHOUSE CUCUMBERS AND B . C . GREENHOUSE PEPPERS  151  Table D1: Cost of Production for Greenhouse Cucumbers in B.C., 1993 8,000 m Greenhouse  25,000 m Greenhouse  2  Variable Costs Material Inputs Heat & Utiltities Labour Variable Building & Machinery  $/m 9.97  Total $ 79760  13.85 12.78 1.26  Post Production Costs* Other Variable Costs Total Variable Costs  2  2  $/Case"  $/m  2  Total $ 237500  $/Case** 1.56 1.87  110800 102240 10080  1.63 2.27 2.10 0.21  9.50 11.44 12.17 1.26  17.45  139600  2.86  17.45  436250  2.86  1.22  9760  0.19  452240  1.15 52.97  28750  56.53  0.20 9.27  1324250  8.69  2.79 5.26 7.43 0.61 16.09  22320 42080  2.51 3.10 6.19 0.61 12.41  62750 77500 154750 15250 310250  0.41  59440 4880 128720  0.46 0.86 1.22 0.10 2.64  72.62  580960  11.91  65.38  1634500  10.73  286000 304250 31500  2.00 0.21  Fixed Costs Overhead Equipment Buildings Land Total Fixed Costs  Total Costs  0.51 1.02 0.10 2.04  **There a r e 18 seedless cucumbers i n a case. Source: Stennes, Brad. Fresh Vegetable Costs and Returns at the Farm-Level F o r B r i t i s h Columbia Greenhouses and Competing Areas B.C. , 1995  152 Table D2: Cost of Production for Greenhouse Peppers in B.C., 1993 8,000 m Greenhouse Variable Costs $/m2 Total $ Material Inputs 15.43 123440 Heat & Utiltities 9.08 72640 Labour 12.27 98160 Variable Building & Machinery 1.36 10880 Post Production Costs* 12.22 97760 Other Variable Costs 1.51 12080 Total Variable Costs 51.87 414960 2  25,000 m Greenhouse $/m2 Total $ $/case** 14.66 366500 3.50 7.44 186000 1.75 11.66 291500 2.80 1.36 34000 0.35 12.22 305500 2.90 1.41 35250 0.30 48.75 1218750 11.60 2  $/case** 3.70 2.15 2.90 0.35 2.90 0.35 12.35  Fixed Costs Overhead Equipment Buildings Land Total Fixed Costs  2.59 4.76 7.43 0.61 15.39  20720 38080 59440 4880 123120  0.60 1.15 1.75 0.15 3.65  2.35 2.94 6.19 0.74 12.22  58750 73500 154750 18500 305500  0.55 0.70 1.50 0.20 2.95  Total Costs  67.26  538080  16.00  60.97  1524250  14.55  **There are 5 k i l o g r a m s of peppers i n a case. Source: Stennes, Brad. F r e s h Vegetable Costs and Returns at the Farm-Level For B r i t i s h Columbia Greenhouses and Competincr Areas • B.C., 1995.  

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