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An econometric analysis of orchard replanting in the British Columbia apple industry Calissi, James Joseph 1995

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AN ECONOMETRIC ANALYSIS OF ORCHARD REPLANTING IN THE BRITISH COLUMBIA APPLE INDUSTRY by JAMES JOSEPH CALISSI B.Sc, The University of B r i t i s h Columbia, 1986 A THESIS SUBMITTED IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE i n THE FACULTY OF GRADUATE STUDIES Department of A g r i c u l t u r a l Economics We accept t h i s thesis as conforming to the required standard THE UNIVERSITY OF BRITISH COLUMBIA A p r i l 1995 ® James Joseph C a l i s s i , 1995 In presenting this thesis in partial fulfilment of the requirements for an advanced degree at the University of British Columbia, I agree that the Library shall make it freely available for reference and study. I further agree that permission for extensive copying of this thesis for scholarly purposes may be granted by the head of my department or by his or her representatives. It is understood that copying or publication of this thesis for financial gain shall not be allowed without my written permission. Department of / ^ f < Cfoflfafo/'(^{t^^^y The University of British Columbia Vancouver, Canada Date >4&/ 2-//ftr DE-6 (2/88) Abstract The B r i t i s h Columbia Apple industry, p r i m a r i l y located i n the Southern I n t e r i o r of the province, has undergone varying l e v e l s of tree removal and replanting as growers attempt to maximize p r o f i t s . This study models t h e i r behaviour by using econometrics i n a supply response model. The economic environment of the f r u i t industry i s described. The variables a f f e c t i n g acreage responses to removals and replanting of new and t r a d i t i o n a l apple v a r i e t i e s are estimated using Ordinary Leased Squares i n three separate equations. Data are pooled and aggregated at the regional l e v e l . Several versions of the o r i g i n a l model are run to test for robustness of the variables and of the o r i g i n a l model. The econometric models i l l u s t r a t e d that the plantings of new v a r i e t i e s increases when expected p r o f i t s from vintage trees decline. However, planting and removals of t r a d i t i o n a l v a r i e t i e s are p o s i t i v e l y related to excepted p r o f i t s from vintage trees and th i s does not follow a p r i o r i expectations. More s t r i k i n g i n the model i s the regional differences and t h e i r responsiveness to removals and replanting. Regions with younger, better educated farmers replant to new i i v a r i e t i e s at a faster rate than other regions. Replant programs are shown to have a negative e f f e c t on the rate of replanting. These programs maintain basic c r i t e r i a for t h e i r e l i g i b i l i t y to funding and seemingly decreased the acres replanted. Increasing the monetary value of the replant grants results i n the ef f e c t of increasing the acreage of t r a d i t i o n a l v a r i e t i e s being planted. P o l i c y implications are examined i n a post modelling analysis. The ef f e c t s of top loading subsidy e f f e c t s are shown to have decreased the acreage of trees replanted over time. These ef f e c t s are shown to cause a dead weight loss to society of approximately $13 m i l l i o n over 2 0 years. i i i Table of Contents Page Abstract i i Table of Contents i v L i s t of Tables v i i L i s t of Figures v i i i Acknowledgements i x Chapter 1 Introduction 1 1.1 Problem Setting 1 1.2 Objective of the Study 2 1.3 Research Procedure 2 1.4 Thesis Guide 4 1.5 A b r i e f History of the BC Apple Orchards 4 1.5.1 An Overview of the Present BC Apple Industry 5 1.5.2 Land 8 1.6 Recent Policy Developments 13 1.7 Changes i n Production Technology i n the Past 10 Years 16 1.8 Apple P r i c i n g P o l i c i e s i n the BC Tree F r u i t Industry 21 1.9 Support Payments 27 1.10 Regional Planting Responses 30 2 Li t e r a t u r e Review 33 2.1 Past Endeavors 33 i v 2.1.1 French and Bressler 34 2.1.2 French and Mathews 3 6 2.1.3 Jaramillo 41 2.1.4 Hartley, Nerlove and Peters 45 2.1.5 Zvi G r i l i c h e s 48 2.2 Other Approaches 51 2.3 F i n a l Comments 52 3 Theory 54 3.1 The Investment P o r t f o l i o 55 3.2 Production Inputs 56 3.2.1 Variable Inputs 56 3.2.2 Capital Investments 56 3.2.3 Land 57 3.3 Mathematics of P r o f i t Maximization 57 3.3.1 Land Constraints 59 3.4 Winter Injury 61 4 The Empirical Model 63 4.1 Data Structure 64 4.2 The Dependent Variable 66 4.2.1 Costs 67 4.3 Plantings of New Apple V a r i e t i e s 69 4.4 Plantings of T r a d i t i o n a l V a r i e t i e s 70 4.5 Removals of Vintage Trees 71 4.6 Regression Results 72 4.6.1 Plantings of New V a r i e t i e s 74 4.6.2 Plantings of T r a d i t i o n a l V a r i e t i e s 81 4.6.3 Removals of T r a d i t i o n a l V a r i e t i e s 85 v 4.7 Empirical Values 87 4.7.1 The Eff e c t s of FII and NTSP 87 5 Summary Conclusions and Policy Implications 90 5.1 Summary and Conclusions 90 5.2 Poli c y Implications 92 5.3 Government Policy 93 5.3.1 Ad Hoc Payments 94 5.3.2 Replant Subsidies 95 5.3.3 Regional Differences 95 Bibliography 97 Appendix A 100 Appendix B 101 Appendix C 105 Appendix D 106 Appendix E 109 Appendix F 110 v i L i s t of Tables Page 1.1 Weather Conditions i n the Southern I n t e r i o r F r u i t Growing Regions 1960 to 1990 8 1.2 Real (1991) Prices of Red Delicious, Mcintosh, Gala, and Jonagold During the Period 1985 to 1991 19 1.3 Comparison of Revenues per Acre: A Young vs Old Block of Trees 23 1.4 Acreage of Aging Apple Trees by Region 3 0 2.1 Correlation C o e f f i c i e n t s on the Crop Reporting D i s t r i c t Level 49 4.1 New V a r i e t i e s Regression C o e f f i c i e n t 74 4.2 T r a d i t i o n a l V a r i e t i e s Regression Co e f f i c i e n t 81 4.3 Removals Regression C o e f f i c i e n t 85 v i i L i s t of Figures Page 1.1 Map of the Study Area 6 1.2 Cumulative Cash Position 20 4.1 Demographics and Regional Responsiveness of Plantings of New V a r i e t i e s 79 v i i i Acknowledgements I would l i k e to thank the members of my thesis committee, Mary Bohman, Rick Barichello and Norm Looney. In p a r t i c u l a r my main advisor, Mary for her countless hours of assistance and enthusiasm. Thanks are also due to Boyd Porteous and Tyrone Guthrie at the Okanagan Valley Tree F r u i t Authority for putting together data from t h e i r GIS data system. I would also l i k e to thank the packinghouses i n the industry for supplying me with much needed regional p r i c e data. Special thanks to my wife L i s a for her help and support. ix INTRODUCTION 1.1 Problem Setting The B r i t i s h Columbia apple industry, at the l e v e l of the producer, i s constantly changing as growers introduce new v a r i e t i e s and new practices i n response to prices, costs, and new technology. In p a r t i c u l a r the e f f i c i e n c i e s of higher density plantations and the advent of more valuable new c u l t i v a r s 1 have led many growers to re-examine t h e i r marginal blocks. As well, prices for lower grades of t r a d i t i o n a l v a r i e t i e s have dropped to a point where variable costs are no longer covered. These market forces have made replanting an a t t r a c t i v e option for many growers and created a great deal of discussion i n the a g r i c u l t u r a l community. The B.C. apple industry has been the subject of numerous research studies and government p o l i c y i n i t i a t i v e s intended to foster greater e f f i c i e n c y and competitiveness. Since 1987, qu a l i f y i n g growers have been e l i g i b l e for grants to replant old, lower density orchards to higher densities and ( i f desired) to new v a r i e t i e s . Growers, industry bodies and government departments are interested i n being able to forecast l. The terms c u l t i v a r and v a r i e t y are often interchangeable. the benefits of such orchard renovation i n i t i a t i v e s . 1.2 Objective of the Study The objective of t h i s study i s to construct an econometric model which estimates the extent to which the apple orchardists i n the Southern I n t e r i o r of B r i t i s h Columbia w i l l engage i n replanting (or opt to replant), herein referred to replanting behaviour. The sub-objectives for t h i s study are: 1. To describe the B.C. apple industry. 2. To estimate, using an econometric model, the regional supply response of apple producers. Various inputs, which include government intervention p o l i c i e s (subsidy programs) w i l l be examined. 3. To examine government p o l i c y related to the tree f r u i t industry, and i l l u s t r a t e i t s e f f e c t s on replanting a c t i v i t i e s and the future of the industry. 1.3 Research Procedure To explore these objectives, a supply response model w i l l be constructed which models the removal of vintage trees, and the 2 plantings of new and t r a d i t i o n a l v a r i e t i e s . Three equations w i l l be estimated separately using Ordinary Least Squares (OLS) . Differences i n climate and land a v a i l a b i l i t y e x i s t i n B.C. Therefore, replanting i s analyzed on a regional basis. Due to the fact that regions d i f f e r i n size, the acres replanted w i l l be divided by the t o t a l land planted to tree f r u i t s f o r the region. The t o t a l area of tree f r u i t was used as the denominator since land suitable for other tree f r u i t crops i n the Southern I n t e r i o r i s also suitable for apple production and could be replanted to apples i f economic conditions d i c t a t e . A cost of production model was used to calculate the 2 0 year NPV of a block of apples. Price expectations were varie d i n the model to calculate a NPV for planting of both new and t r a d i t i o n a l v a r i e t i e s . For vintage blocks removed, a cost of production model was taken from an established industry model. The empirical model was constructed and was used to examine replanting behaviour. For example, the e f f e c t s of regional differences and p r o f i t expectations on replanting behaviour are explained. Using the r e s u l t s of the empirical model, the e f f e c t s of how government p o l i c y impacts growers, t h e i r expectations and how t h i s a f f e c t s growers' replanting decisions are discussed. 3 1.4 Thesis Guide The layout and procedure of the study i s as follows: Chapter 1 i s a description and economic h i s t o r y of the apple industry i n the Southern Inte r i o r of B.C. Chapter 2 i s a comprehensive l i t e r a t u r e review of supply response work on perennial crops. Works include some of the pioneering work, and include some of the c l a s s i c a l studies which formulate modern supply response modelling. Chapter 3 covers the fundamentals of theory surrounding supply response modelling. P a r t i c u l a r attention i s focused on theory which accommodates supply response under a land constraint s i t u a t i o n . Chapter 4 contains the empirical model and r e s u l t s . Chapter 5 discusses the r e s u l t s of the empirical model i n the s e t t i n g of the apple industry. The behaviour of orchardists i s examined. As well, the past a g r i c u l t u r a l p o l i c i e s are looked at i n l i g h t of the findings of t h i s study. 1.5 A B r i e f History of B.C. Apple Orchards The f i r s t reported commercial apple production i n B r i t i s h Columbia occurred on Vancouver Island, at Fort V i c t o r i a i n 1843. Orchard plantings i n the i n t e r i o r of B r i t i s h Columbia did not occur u n t i l the Caribou gold rush i n the 1860's (p. 2 Dendy, 1989). The f i r s t orchard planting i n the Okanagan 4 V a l l e y occurred at Okanagan Mission (now part of the c i t y of Kelowna) by the Catholic missionary, Father Pandosy. From these humble beginnings, the tree f r u i t industry expanded across the Southern I n t e r i o r of B r i t i s h Columbia. Most of the early orchards were developed on land with adjacent water. Later, land companies developed water systems and sub-divided and sold land that could be i r r i g a t e d . During the early 1900's, the majority of these buyers were of B r i t i s h descent. A f t e r the f i r s t and second world wars other European immigrants took up orcharding i n the B.C. In t e r i o r . In recent decades many new orchardists have been of Asian (mainly Indian) descent. 1.5.1 An Overview of the Present B.C. Apple Industry Apple production i n B r i t i s h Columbia continues to be concentrated i n the Southern I n t e r i o r . Orchards are located along f e r t i l e benches near r i v e r s and lakes. These water masses ameliorate cold winter and hot summer temperatures. Geographically, orchards are located from the Canada/USA border to as far north as Kamloops and Salmon Arm. The Okanagan, Similkameen, and Kootenay val l e y s are the predominant apple growing regions of the Southern Int e r i o r , with the Okanagan being the largest of the three. 5 The climate of the Southern I n t e r i o r ranges from desert to semi-desert with annual r a i n f a l l varying from 30 to 60 centimetres. I r r i g a t i o n i s required i n a l l regions of the Southern I n t e r i o r . Summer temperatures often exceed 35 Celsius. Winter temperatures hover at the freezing point, with predictable shorter periods of colder temperatures. In a normal winter, temperatures drop to -10 Celsius for up to two weeks and occasionally f a l l to below -20 Celsius. This l a t t e r temperature w i l l cause economic damage to trees or f r u i t buds depending on the time of year and previous acclimation. These r i s k s are si m i l a r to those experienced by producers elsewhere where high f r u i t q u a l i t y i s a c h a r a c t e r i s t i c of the industry. However, because orchards vary i n a l t i t u d e , l a t i t u d e and proximity to bodies of water, orchard micro-climate can vary considerably. The climate of Vernon i s v a s t l y d i f f e r e n t than that of Osoyoos and as such the mix of f r u i t commodities and v a r i e t i e s produced i n the two regions i s d i f f e r e n t . Table 1.1 i l l u s t r a t e s some of the clim a t i c v a r i a t i o n between regions i n the Southern I n t e r i o r : 7 Table 1.1 Weather Conditions i n the Southern I n t e r i o r F r u i t Growing Regions 1960 to 1990 D i s t r i c t Mean Winter Daily Min Temperature (celsius) Mean Summer Daily Max Temperature (celsius) Mean Total Snowfall (centimetres) Mean Total Precip. (centimetres) Vernon -9.4 27 .3 108.7 39.3 Kelowna -8.5 27.8 85.9 33 .6 Oli v e r -7.1 30.0 56.9 29.9 Creston -7.4 27 .5 145.8 53 .3 Source: B.C. Ministry of Agriculture Weather Reports The above table i l l u s t r a t e s that regional differences i n climate do exi s t i n the Southern I n t e r i o r . For example, Vernon i n the North Okanagan, experiences colder winter temperatures than other regions. Creston i s less a r i d than regions i n the Okanagan and Similkameen valleys and experiences cooler winter and summer temperatures. Oliver, i n the south Okanagan, receives less p r e c i p i t a t i o n , i s warmer i n the winter and hotter i n the summer. 1.5.2 Land There i s l i t t l e land available for expansion of the B.C. apple industry. New plantings of apples occur on land previously 8 dedicated to soft f r u i t or (to a lesser degree) wine grape acreage. There i s no i d l e land or s i g n i f i c a n t acreage of land dedicated to other crops or land use that i s suitable for apple production that can be converted to orchards. As discussed e a r l i e r , the land base of the tree f r u i t industry-i s spread across an area that contains a multitude of d i f f e r e n t growing regions, micro-climates, s o i l types, land rents and p r o f i t s from current production. Each of these factors influence the inventory of trees that e x i s t i n any orchard. Orchards i n some regions have a higher proportion of older apple trees, while some may have a higher proportion of other f r u i t crops such as peaches and cherries. I t can be anticipated that these c h a r a c t e r i s t i c s have an impact on replanting decisions. For example, producers with a higher proportion of older (vintage) trees of unprofitable c u l t i v a r s may be i n an economic s i t u a t i o n where an accelerated rate of replanting must occur. Alt e r n a t i v e land uses, including p o t e n t i a l future urban development, and aesthetic value (view l o t s ) , w i l l a f f e c t the land value. Buyers may be land speculators, or may be ind i v i d u a l s who do not need to derive a d i r e c t p r o f i t from the a g r i c u l t u r a l p o t e n t i a l of the land i t s e l f , the way a commercial orchardist must. Instead, the land rent may be skewed to 9 r e a l i z e i t s market value from i t s aesthetics or future urban use. In c e r t a i n regions, land for non-agricultural use has become l i m i t e d i n a v a i l a b i l i t y . This has caused land p r i c e s i n the region to escalate. Orchard land prices have also varied as land speculators view i t for expansion i n future years. This i s not to say that orchard land can become changed to urban use f r e e l y . Most orchard land i s contained i n the A g r i c u l t u r a l Land Reserve (ALR), created with the A g r i c u l t u r a l Land Act of 1973. This p r o v i n c i a l l y l e g i s l a t e d act zones most orchard land as a g r i c u l t u r a l . These lands cannot be subdivided into smaller l o t s , and a grower cannot s e l l into urban uses a l l or a portion of the orchard when a block i s no longer p r o f i t a b l e to him/her, or i f the grower faces f i n a n c i a l d i f f i c u l t y . Only small areas of the ALR are released each year from the land reserve, mostly for urban development. Some believe the ALR holds down land prices i n regions on the edge of urban development because land of extremely high p o t e n t i a l value cannot be urbanized. Others believe that the true p r i c e of land i n these regions i s not accurately known since the small amounts of ALR land released each year masks a true market p r i c e . As well, urban and commercial expansion on lands currently outside of the ALR i s often constrained by municipal zoning and because large land masses i n the Southern I n t e r i o r adjacent to the towns are contained i n the ALR and 10 non-ALR land i s not overly abundant. This constraint c l e a r l y forces up prices of non-ALR land. Often land i s transacted at prices which are far i n excess of that which orcharding i t s e l f can finance. When land i s occasionally released from the ALR, i t s value i s often high since parcel sales are transacted under a s c a r c i t y of supply. In some cases, the ALR lands are released only when there i s a housing boom i n the region, or when the land surrounding the farm land i s so highly developed that i t becomes p h y s i c a l l y impossible to farm the land due to urban/farm interface problems. Farmers i n regions removed from urban development observe what these properties s e l l f or and develop expectations of what t h e i r land would be worth i f the land reserve would be l i f t e d for them as well. The ownership of orchard land i n the Southern I n t e r i o r can be viewed as a p o r t f o l i o of investments. Part of the p o r t f o l i o i s i n the a g r i c u l t u r a l p o t e n t i a l of the land and i s r e a l i z e d annually with p r o f i t s from f r u i t sales. The other part of the p o r t f o l i o i s a r e a l estate investment and i t s p o t e n t i a l c a p i t a l gain. Regional differences i n the size and mix of the p o r t f o l i o are present. In some regions (in p a r t i c u l a r the Kelowna and Penticton areas) land values have increased faster than other 11 regions. As well, i n some regions (eg Summerland and Penticton) orchard l o t sizes are small and tend to maintain a high value since they can be sold as hobby farms. Often what may happen with high valued land holdings i s that an orchardist w i l l s e l l the land, r e a l i z i n g the c a p i t a l gain i n the land instead of replanting the orchard. The new owner often purchases the land for uses other than commercial tree f r u i t production (eg a hobby farm) and tends not to replant the orchard. This entry/exit behaviour that takes place on high p r i c e land can reduce the rate of orchard renovation. Conversely, land sold i n more t r u l y r u r a l areas (eg Cawston) w i l l often be to an i n d i v i d u a l who wishes to operate a commercial farm, since l o t sizes tend to be larger, and the area i s more r u r a l . I f the orchard has not seen some replanting, the new operator w i l l often invest i n c a p i t a l improvements (eg replanting) to improve the future p r o f i t a b i l i t y of the farm. Often the land transfer may be to a younger farmer, who may be more w i l l i n g to take on r i s k and replant using new technology such as new v a r i e t i e s or higher plantation den s i t i e s . Entry/exit behaviour of t h i s nature would tend to increase orchard renovations. 12 1.6 Recent Pol i c y Developments In the mid-1980's, a s i t u a t i o n developed where many orchards needed to be replanted but growers were unwilling to commit the c a p i t a l necessary to do so. Intense lobbying by the B.C. F r u i t Growers Association (BCFGA) resulted i n the implementation of a replanting grant for tree f r u i t producers i n 1987. This grant was administered by the B r i t i s h Columbia M i n i s t r y of Agriculture Fisheries and Food (BCMAFF) and funded by A g r i c u l t u r a l Regional Development Subsidy Agreement (ARDSA). Under t h i s grant growers could receive $2000 per acre to renovate t h e i r orchard. Growers were e l i g i b l e for replanting grants for up to 3 0% of t h e i r acreage. For example, a grower with 10 acres could receive grants to renovate 3 acres of property. The grant was well received and many growers took advantage of the program. Although replanting was viewed, at the time, as being e s s e n t i a l , some individuals f e l t that other elements too were important and needed addressing. These issues were examined i n the Commission of Inquiry into the Tree F r u i t Industry i n 1990. The Inquiry suggested that the industry improve orchard practices, become "leaner and meaner", become less dependent upon top loading subsidy programs l i k e Farm Income Insurance 13 (FIT.) and the National T r i p a r t i t e S t a b i l i z a t i o n Program (NTSP)2 see section 1.9) and improve t h e i r competitive p o s i t i o n i n production and marketing. As a spin o f f from the Inquiry, the Okanagan Valley Tree F r u i t Authority (OVTFA) was formed i n 1990. This p r o v i n c i a l crown corporation took over the r e s p o n s i b i l i t y of replanting programs (including grants) from ARDSA. The maximum value of the grant increased to $3000 per acre. This increase was also accompanied by changes to the e l i g i b i l i t y guidelines. Higher plantation densities and larger minimum replant areas (eg minimum of one acre) , support systems for the trees (eg t r e l l i s i n g ) and high q u a l i t y nursery trees were the major new requirements. In 1992, i t was f e l t that replanting was not occurring at a fas t enough rate and a r i c h e r replant program would escalate the l e v e l s of replanting. Consequently, the OVTFA grants were increased to $3500 per acre plus an additional grant of $1500 per acre, paid i n equal payments of $500 per annum for three years following the planting year. As well, growers i n s t a l l i n g an i r r i g a t i o n system with the capacity of i n j e c t i n g f e r t i l i z e r s along with the i r r i g a t i o n water (considered a more e f f i c i e n t 2 These two programs paid cash subsidies to growers i n years when the industry was unable to meet t h e i r costs of production. Payments were made based on p r i c e s received and a negotiated cost of production. For a b e t t e r explanation of FII and NTSP see section 1.9. 14 way to u t i l i z e f e r t i l i z e r s ) q u a l i f i e d for grants of up to $500 per acre. In 1994, an additional grant of up to $250 per acre for s o i l fumigation was added to the l i s t of e l i g i b l e grants. In 1994, a grower could receive a t o t a l of $5750 per acre i n grants, or roughly 1/3 - 1/2 of the c a p i t a l cost of replanting. 15 1.7 Changes i n Production Technology In the Past 10 Years The advent of improved s t r a i n s 3 of e x i s t i n g v a r i e t i e s has affected the way tree f r u i t s are produced i n the province. Red Delicious production has been greatly enhanced by the s e l e c t i o n of red s t r a i n s . The Starking Delicious s t r a i n , introduced i n the 1950's was the f i r s t of many red str a i n s of t h i s c u l t i v a r . Later, i n the 1960's and 1970's, the development of ever more highly coloured strains and the advent of spur-type Red Delicious enhanced the production of that p a r t i c u l a r v a r i e t y . A spur-type s t r a i n of apple exhibits a more compact tree with a more productive and manageable canopy. Spur-types were e s p e c i a l l y important since growers could plant at higher densities without compromising f r u i t q u a l i t y . Thus, the cost of producing Delicious apples was s l i g h t l y reduced. During t h i s same period, spur-type Mcintosh apples were discovered and widely planted. This allowed Mcintosh to have advantages s i m i l a r to those experienced by the Red Delicious v a r i e t y . In the 1970's and 1980's, Washington State developed t h e i r acreage of high coloured spur-type Red Delicious. The lack of 3 A s t r a i n i s a s e l e c t i o n of a p a r t i c u l a r v a r i e t y that has a t t r i b u t e s which are d i f f e r e n t than those t y p i c a l for that v a r i e t y . These s e l e c t i o n s are u s u a l l y mutations of the o r i g i n a l v a r i e t y . Improved colour and tree growth habit have been predominant s e l e c t i o n c h a r a c t e r i s t i c s i n recent years. 16 a land constraint allowed growers to plant new s t r a i n s of Red Delicious on v i r g i n land, while keeping t h e i r less p r o f i t a b l e older trees i n the ground. Plantings onto new land ensured that production of new strains could develop quickly, without compromising e x i s t i n g acreage. In 1987, the apple production of Washington State reached 100 m i l l i o n boxes for the f i r s t time, the majority of t h i s crop being Red Delicious. This was an astounding l e v e l of production, roughly 10 times as large as B.C.'s 10 m i l l i o n box crop. The large supply of Red Delicious caused prices to drop sharply (see Table 1.4). Growers producing older c u l t i v a r s of Red Delicious, such as the Starking s t r a i n , were unable to cover variable costs. Only newer spur-type Red Delicious and other apple c u l t i v a r s were p r o f i t a b l e . This sudden drop i n apple prices created a pessimistic atmosphere i n the apple growing community as growers expectations of future p r o f i t s appeared bleak. An ever increasing group of growers pressured the government to dismantle the a g r i c u l t u r a l land reserve to allow them to s e l l orchard land without r e s t r i c t i o n s . I t was a confusing time for growers. In hindsight, t h i s was a turning point for the industry. Growers who d i d replant wanted a v a r i e t y that could not be 17 s u c c e s s f u l l y c u l t i v a t e d i n Washington State. They di d not see any sense i n planting a v a r i e t y which appeared p r o f i t a b l e i n the short run to have i t s future p r i c e lowered by increased supply i n Washington. Mcintosh was considered to be a v a r i e t y which could not be successfully produced south of the border, however some growers had concerns that BC's acreage was already adequate and additional acreage could r e s u l t i n lower p r i c e s . Thus other v a r i e t i e s were examined. Gala and Jonagold v a r i e t i e s were commercially introduced into B r i t i s h Columbia i n the l a t e 1980's. Even though these two new v a r i e t i e s were produced i n Washington State, t h e i r p r i c e s (Table 1.2) r e l a t i v e to other v a r i e t i e s , made them tempting to growers who wished to gamble on new v a r i e t i e s . Interest i n Red Delicious was low due to poor short term and long term p r i c e expectations. 18 Table 1.2 Real (1991) Prices of Red Delicious, Mcintosh, Gala and Jonagold During the Period, 1985 to 1991 (cents/lb farm gate) Year Red Del. Mcintosh Gala Jonagold 1985 19.1 19.3 1986 19.4 23.0 30.7 1987 5.2 22 .0 60.7 12 .1 1988 13.2 22.0 86 .7 41.3 1989 7.3 15.1 83 .7 46.9 1990 14.8 21.1 65.5 29.9 1991 14.2 17.0 67.2 39.6 Source: BCMAFF The introduction of new v a r i e t i e s i n the mid 1980's was accompanied by the expanding use of f u l l y dwarfing rootstocks. Such rootstocks enabled growers to keep the tree si z e small, achieve early production (precocity), and allow trees to be planted to greater densities than i n the past. Growers showed in t e r e s t i n using high density technology. At the same time, the farm gate prices of new v a r i e t i e s increased from 30 cents per pound to over 80 cents per pound. This p r i c e increase was perceived to compensate for the r i s k s associated with planting new v a r i e t i e s . Higher prices and the introduction of a replanting grant i n s t i l l e d confidence i n growers. Consequently, a s i t u a t i o n developed where i t appeared 19 to be p r o f i t a b l e to replant. Progressive growers u t i l i z i n g new v a r i e t i e s and high density plantings were able to recover the cost of replanting to new v a r i e t i e s i n 5 years instead of the 8 to 10 years normally anticipated with low de n s i t i e s . The graph below i l l u s t r a t e s the cash p o s i t i o n a grower would experience given 3 d i f f e r e n t management decisions: 1. Leaving i n a one acre block that consistently looses $500 per year (no change), 2. Replanting the block to new v a r i e t i e s , which returns 55 cents per pound to the grower, or 3. Replanting the block to t r a d i t i o n a l v a r i e t i e s which returns 18 cents per pound to the grower. Figure 1.2 Cummulative Cash Position C u m m u l a t i v e C a s h F l o w O v e r 2 0 Y e a r s o n O n e A c r e o f O r c h a r d f o r D i f f e r e n t M a n a g e m e n t O p t i o n s w o Q 120000 100000 80000 + 60000 40000 | 20000 0 -20000 Replant to Traditional Varieties No Change Replant to New Varieties Year 20 The above graph i l l u s t r a t e s the accumulation of money a farmer would experience over 20 years by choosing 3 separate actions. The r e s u l t s are cumulative and include a 7% i n t e r e s t factor for p o s i t i v e accounts and a 10% int e r e s t factor for negative accounts. 1.8 Apple P r i c i n g P o l i c i e s i n the B.C. Tree F r u i t Industry Apple p r i c i n g p o l i c i e s set by industry i t s e l f , determine the revenue growers receive for a pound of apples. P r i c i n g p o l i c y experienced by BCFGA growers i s uniform for the Southern I n t e r i o r ; however, there are some regional p r i c e differences due to brands, grades and va r i e t y mixes. These a f f e c t revenue, which influences replanting decisions. Apple marketing i s dominated by the grower owned B.C. Tree F r u i t s Ltd. (BCTF). Growers producing apples to be sold through t h i s agency d e l i v e r t h e i r f r u i t to cooperative packinghouses. There are six cooperative packinghouses whose growers are members of the BCFGA. Packinghouses are reg i o n a l l y based and source the majority of t h e i r f r u i t from orchards i n the proximity of the packinghouse. For example, Okanagan North Growers Cooperative would source most of i t s f r u i t from the 21 Winfield/Oyama/Vernon areas. It may source some f r u i t from the northern fringes of Kelowna but would not source f r u i t from areas south of that. F r u i t received at the packinghouse i s either packed for immediate sale, stored i n cold storage, or stored i n c o n t r o l l e d atmosphere (CA) storage to be packed at a l a t e r date. Packinghouses and BCTF negotiate when f r u i t from each packinghouse w i l l be sold. Packinghouses w i l l then receive t h e i r 'prorate' from th i s system. The prorate determines how much each packinghouse w i l l s e l l into each time period and market through the s e l l i n g season. F r u i t i s then delivered to the market under i n d i v i d u a l packinghouse brands. Individual packinghouses receive the revenues from t h e i r respective sales. V a r i e t i e s , grades and sizes of each grower's apples are kept separate and are recorded i n the form of a 'packout'. P r o f i t s from the sale of each variety, grade and size of apple are delivered to the grower based on th e i r packout i n the form of a pool p r i c e . For example, a l l growers i n a p a r t i c u l a r packinghouse w i l l receive the same pri c e for box siz e 100 fancy Mcintosh. The grower does not have the option of s e l l i n g his/her f r u i t early or la t e i n the season. The pool pr i c e s are set by the board of directors of the packinghouse. Each packinghouse develops i t s own pool p r i c e based on market returns, packinghouse costs, and board p o l i c i e s . Hence, 22 d i f f e r e n t grower pool prices for separate items can ex i s t across the d i f f e r e n t packinghouses. The prices paid for d i f f e r e n t grades have an e f f e c t on the p r o f i t a b i l i t y of d i f f e r e n t orchards and i n d i r e c t l y on removals and replanting of d i f f e r e n t blocks i n each region. For example, as apple trees age, the percent packout of higher q u a l i t y f r u i t diminishes. An older Mcintosh tree may only produce 30% fancy grade, while a r e l a t i v e l y younger tree of the same s t r a i n w i l l produce 70% fancy grade apples. A t y p i c a l example of revenue per acre from two d i f f e r e n t packouts (assuming 35,000 lbs per acre) i s shown below: Table 1.3 Comparison of Revenues per acre: A Young vs Old Block of Trees. Young Block 70% fancy 24,500 lbs @' $0 .18 = $4410 15% commercial 5,250 lbs @ $0 .01 = $ 53 15% c u l l 5,240 lbs @- $0 .03 =-$ 158 Total 35,000 lbs $4305 Old Block 30% fancy 10,500 lbs @ $0 .18 = $1890 40% commercial 14,000 lbs @ $0 .01 = $ 140 30% c u l l 10,500 lbs @- $0 .03 =-$ 315 Total 35,000 lbs = $1715 23 Growers who remove old Mcintosh trees and replant to the same v a r i e t y receive higher prices from packouts due to improved st r a i n s and younger trees. There i s no pr i c e d i f f e r e n t i a t i o n for the fancy grade f r u i t produced from younger trees, so there i s no other way of increasing revenue to cover c a p i t a l costs of replanting other than from increased revenue from improved packouts (as i l l u s t r a t e d above). Approximately 1/4 of the apple crop i s sent for processing. Sun-Rype Ltd., a company that arose from B.C. Tree F r u i t s Ltd., i s by far the largest apple processor i n B r i t i s h Columbia and has the capacity to process 40,000 tons annually. Apples which are not of high enough qu a l i t y to be sold onto the fresh market w i l l be sent to Sun-Rype. Only packinghouses (whether i n the BCFGA or not) can d e l i v e r BC apples to Sun-Rype. Sun-Rype does not contract d i r e c t l y with i n d i v i d u a l apple growers. In fact, growers never receive a d i r e c t payment from Sun-Rype or any other processor when they contract with a packinghouse. Money from processors i s sent to packinghouses or to B.C. Tree F r u i t s . This money i s used to cover the operating costs of these organizations. When p r o f i t s from Sun-Rype are low, the revenues packinghouses receive are also low. Often i t i s not high enough to recover the cost of handling f r u i t destined for processors and growers may be b i l l e d by the packinghouse for the processing grade f r u i t . When Sun-Rype p r o f i t s are high, 24 packinghouses receive a higher p r i c e for processing grade f r u i t and t h i s i s passed onto the grower. How the p r o f i t s of processing f r u i t are delivered to the grower i s e n t i r e l y determined by the boards of directors of the i n d i v i d u a l packinghouses and B.C. Tree F r u i t s . How much p r o f i t i s retained by Sun-Rype products i s determined by the board of di r e c t o r s of Sun-Rype products. If a grower has apples with no fresh market value, they may be delivered to the packinghouse to be c l a s s i f i e d as "diversion" . This f r u i t w i l l by-pass the conventional storing and packing system and be delivered d i r e c t l y to the processor by the packinghouse. The grower w i l l receive a diversion p r i c e which i s separate from a melded fresh/processing p r i c e . The diversion p r i c e i s determined by the board of d i r e c t o r s of the i n d i v i d u a l packinghouses. The decision to 'divert' i s made by the grower at the time of delivery to the packinghouse, before i t i s placed into storage. In some years the diversion p r i c e may be so low that i t may not cover grower's harvesting and transportation costs and growers w i l l not harvest t h i s type of f r u i t . Examples of diversion f r u i t would be that damaged by h a i l , disease, insect, f r u i t of p a r t i c u l a r l y poor colour, or f r u i t that has previously f a l l e n to the ground p r i o r to harvest. In 1993, the ownership structure of Sun-Rype products changed. 25 Since i t s establishment i n the 1950's, Sun-Rype has been a l i m i t e d company owned by the growers who were members of the BCFGA. The BCFGA held the shares i n trust for the growers. P r o f i t s from the company were d i s t r i b u t e d back to the packinghouses and then to the growers v i a pool returns. Sun-Rype f e l t i t needed a large i n j e c t i o n of c a p i t a l to expand i n food processing and marketing f a c i l i t i e s . To do t h i s , the company d i s t r i b u t e d the' shares of the company back to the growers, based on $5 m i l l i o n i n retained earnings. Each grower received a portion of the shares based on the t o t a l apple tonnage shipped to t h e i r packinghouse since Sun-Rype began to accumulate the $5 m i l l i o n i n retained earnings. Nine m i l l i o n d o l l a r s i n new c a p i t a l was raised from outside investors. Since the ownership change, Sun-Rype pays only the world p r i c e for processing apples. In Sun-Rype's case, t h i s i s the Washington State p r i c e for processing apples plus transportation costs. Any p r o f i t s the company makes are returned to grower/shareholders i n the form of share values or dividends. The pooling of apple prices has an impact on p r o f i t s and a f f e c t s replanting decisions, since the pool prices form the growers' expectations of p r i c e and i t s corresponding p r o f i t expectation. P r i c i n g apples so there i s a large divergence between higher and lower q u a l i t y apples w i l l stimulate the 26 removals of older trees since these aging blocks produce r e l a t i v e l y less higher priced fresh f r u i t and a greater amount of lower quality, lower priced processing f r u i t . 4 1.9 Support Payments During the study period (1985 - 1992) there were two government support programs added to growers' revenues i n B r i t i s h Columbia. Farm Income Insurance (FII) and the National T r i p a r t i t e S t a b i l i z a t i o n Program (NTSP) provided d i r e c t support payments to growers when apple prices were low. They were triggered when f r u i t prices f e l l below a negotiated cost of production and made sizable contributions to the p r i c e that growers eventually received (see Appendix C) . FII was negotiated on a p r o v i n c i a l p r i c e and cost of production basis. NTSP was negotiated on a national p r i c e and cost of production basis. Often the NTSP program triggered a payment to growers i n B r i t i s h Columbia when the national p r i c e was depressed, even though f r u i t prices were p r o f i t a b l e i n B.C. In l a t e r years of these programs, FII and NTSP payments were 4 I t i s important to note that p r i c e pooling i s , i n many cases, regional since the packinghouses receive f r u i t from growers i n a regional fashion. For example, a l l BCFGA growers i n Vernon w i l l receive p r i c e s based on the same pooling formula since they ship through one packinghouse i n that region. The formula may be d i f f e r e n t than that for growers i n the Kelowna area, who ship through a packinghouse located i n that region. 27 not adequate to meet the negotiated cost of production, and s p e c i a l ad hoc payments have been made to top up support payments (see Appendix C). Growers argue that support payments are necessary to market apples i n the subsidised world market. In addition, growers contend that support payments are linked to the A g r i c u l t u r a l Land Reserve (ALR) and subsidy payments are, i n part, p a r t i a l compensation by governments for constraining t h e i r a b i l i t y to u t i l i z e t h e i r land for non-agricultural purposes. C r i t i c s argue that d i r e c t payments of t h i s sort mask growers' true i n t e r p r e t a t i o n of the market place. Subsidy payments were based on cost of production and were paid based on the pounds of commercial or fancy grade apples produced, regardless of the v a r i e t y . This type of p o l i c y directed new market signals to the farmers. Removing unprofitable trees reduced the o v e r a l l pounds of apples and the corresponding e l i g i b l e l e v e l of support payments. Marginally p r o f i t a b l e trees became t r u l y p r o f i t a b l e , and marginally unprofitable trees became p r o f i t a b l e . As well, v a r i e t i e s that may have been r i s k y to produce due to annual v a r i a t i o n i n p r i c e were made less r i s k y . Regardless whether one i s for or against d i r e c t a g r i c u l t u r a l support payments, i t i s safe to conclude that support payments 28 r a i s e growers expectations of prices from vintage apple trees, by making unprofitable apple production p r o f i t a b l e . Blocks which would have been replanted without a subsidy program are maintained. A p r i o r i , one would expect support payments to hinder the removal of blocks of vintage trees. 29 1.10 Regional Replanting Responses Differences i n pooling p o l i c i e s , grower age and education l e v e l s and tree f r u i t commodity composition (eg make up of soft f r u i t and apple acreage) af f e c t s the vintages of trees i n each region. Table 1.4 Acreage of Aging Apple Trees by Region D i s t r i c t Acres of apple trees older than 2 0 Years (Percentage of a l l tree f r u i t s ) Acres of Apples, a l l ages Acres of tree f r u i t s Vernon 1330 (34) 3798 3936 Kelowna 2798 (38) 6128 7402 Summerland 427 (24) 1359 1770 Penticton 410 (21) 1374 1865 Oli v e r 467 (15) 1769 3166 Osoyoos 439 (18) 1485 2471 Caws ton 495 (24) 1512 2046 Creston 161 (21) 640 759 Total 6527 (28) 18065 23415 Source OVTFA Survey (1991) The above table shows that there i s a s i g n i f i c a n t amount of acreage dedicated to older trees i n each region, with the percentage of older trees varying by area. Part of t h i s 30 variance i s due to the range of tree f r u i t s grown i n the d i f f e r e n t regions. For example, the southern regions have more soft f r u i t as a percentage of t h e i r land base. Consequently, i t appears that older apple trees make up a smaller portion of the t o t a l tree f r u i t acreage, r e l a t i v e to more northern regions where apples predominate. Regional differences i n removals and plantings of apples are i l l u s t r a t e d i n Appendix A. These graphs i l l u s t r a t e annual l e v e l s of replanting i n each region. The differences i n each region i l l u s t r a t e the responses to economic conditions i n each region. . The fact that no two graphs are a l i k e suggests that strong regional differences e x i s t . Such differences could be i n economic factors such as f r u i t prices, or c l i m a t i c conditions. For example, one region may not f u l l y adopt a new v a r i e t y due to fewer seasonal heat units, or because extreme winter temperatures deter plantings of unproven v a r i e t i e s . In addition, climate may speed up the rate of removals i f the climate i s responsible for poor f r u i t q u a l i t y from vintage trees. For example, a region may have hotter temperatures from l a t e August and mid September, causing poor f r u i t colouring conditions. A grower producing a poorer colouring s t r a i n on a vintage tree may receive a poorer packout compared to a grower growing the same type of tree i n a region which has a climate 31 which i s more conducive to better colouring conditions. Regional differences i n farmer age and education l e v e l s also e x i s t (see Appendix D) . The more southern regions have a larger group of younger, more educated growers than do the regions i n the north. Older or less educated growers are less apt to take on r i s k by replanting orchards, and i n p a r t i c u l a r , replanting using new technology i n the form of higher densities and new v a r i e t i e s . 32 Chapter 2 Literature Review This chapter covers a selection of the l i t e r a t u r e written on the subject of supply response modelling. Supply response modelling i s a contemporary method of econometric modelling of farmers' behaviours surrounding the planting and removal of perennial crops. Other methods can and have been used to model these behaviours. Some are well out of the scope of t h i s study (eg Knapp and Kazim 1991, and Kalaitsandonakes and Shonkwiler 1992), while others appear too s i m p l i s t i c and do not generate useful elements such as e l a s t i c i t i e s . 2.1 Past Endeavors Supply response l i t e r a t u r e dates back to French and Bressler's work of 1962 (see 2.1.1) and covers a vast array of perennial crops including lemons, tea, rubber, coffee, r a i s i n grapes, peaches, apples and asparagus. I t i s a s e l e c t i o n of these papers that o f f e r s background to the proposed thesis work and i s examined i n t h i s chapter. 33 2.1.1 French and Bressler Modelling of perennial crop supply response has i t s economic roots embedded i n work ca r r i e d out by French and Bressler with t h e i r Nerlov Type Model of the C a l i f o r n i a Lemon Industry (French and Bressler, 1962) . This model, simple by comparison to modern essays, serves as the building block for contemporary work. I t examines the long run p r o f i t a b i l i t y of lemon production, tree ages, and alternative crops. Nt/B,,.! = S 0 + SJTYi + S an\ f t-i + * 3 (A°t-i/Bt-i> where: Nt = Area planted Bt = Bearing area 11%.! = Long run p r o f i t expectations for lemons n e t_x = Long run p r o f i t expectations for a l t e r n a t i v e land use A0 = Area of trees with declining p r o d u c t i v i t y t = Time period French and Bressler f e l t that the r a t i o of planted lemon orchard to bearing orchard was determined by the expected long run p r o f i t a b i l i t y of lemons and a l t e r n a t i v e crops i n the previous season, and the amount of orchard with d e c l i n i n g p r o f i t a b i l i t y . In essence, t h i s work takes into account important 34 h o r t i c u l t u r a l economic considerations which t a i l o r the planting of new lemon orchards. Bear i n mind that growers of perennial crops (in t h i s case, lemons) need a c e r t a i n amount of bearing acreage to generate revenues as a component to p r o f i t s . However, lemon trees decline i n p r o f i t a b i l i t y with age (or vintage) and the area of declining p r o d u c t i v i t y has a d i r e c t bearing on the p r o f i t a b i l i t y of lemon production. The expectations of lemon p r o f i t s have a d i r e c t bearing on the planting of lemons. This i s not necessarily a d i r e c t p r o f i t shown i n the period i n question, but the net present value of the stream of p r o f i t s i n the l i f e of the tree. In addition, as with any p r o f i t maximizing decision, a l t e r n a t i v e crops must be included i n the model to express opportunities for other ventures. The expected p r o f i t i s ac t u a l l y a running average of the p r o f i t a b i l i t y i n the previous 5 years, i e : t - 5 n.% = (1/5) E n ± i = t - l Removals are expressed i n another l i n e a r approximation: Rt/Bt = oc0 + + oc2(A°t/Bt) + oc3(Aut/Bt) where: 35 Rt = Area lemon orchard removed n s t = Expected short-term p r o f i t a b i l i t y A u t = Area removed to accommodate for urban expansion This l i n e a r approximation accounts for the removal of trees due to t h e i r vintage and also allows for the removal due to urban pressure. During the years examined i n the model, urban expansion onto lemon orchards was s i g n i f i c a n t and had to be included i n the model. Unfortunately, i t was included as a physical variable and not as an economic variable (ie land rent). Using land as a rental variable would have allowed the authors to examine land rent when c a l c u l a t i n g e l a s t i c i t i e s , showing how changes i n land rent affected removals. 2.1.2 French and Mathews Later, French and Mathews extend the o r i g i n a l work c a r r i e d out by French and Bressler on work with asparagus (French and Mathews, 1971) . This work i d e n t i f i e s the extended output period experienced by perennial crops, the long gestation period and the gradual deterioration of productivity. French and Mathews go on to say that growers have a long-run normal p r o f i t per unit of output i n mind. This normal or equilibrium rate of p r o f i t a b i l i t y covers a l l costs plus normal p r o f i t s . In addition to t h i s equilibrium p r o f i t , growers form conditional long-run p r o f i t expectations, based on the expected current years prices and y i e l d s . Keeping these two elements i n mind, the grower w i l l adjust output accordingly, i n order to achieve 3 6 a normal or equilibrium rate of p r o f i t a b i l i t y . Producers are aware of other farmers' reactions to pric e s and output. This develops a notion (although not necessarily correct) with each grower, of the t o t a l change i n production to be expected with any change the farmer may make and the e f f e c t of t o t a l production changes a f f e c t i n g prices and p r o f i t a b i l i t y . These p r o f i t maximizing concepts determine how much desired production w i l l be altered for any deviation between conditional and normal p r o f i t , which would occur i f current years prices and y i e l d s d i f f e r from what a grower would consider a normal year. Q*t = Q\-i + bn(n e t - n\) +b 1 2(ir A t - n*At) + M l t where: Q*t = Desired output i n period t Qeb.x = Expected average production i n the previous period n e t = Long run p r o f i t associated with 0%.! n*t = Normal long run p r o f i t for the commodity of concern n e A t = Long run p r o f i t for the alte r n a t i v e land use H*At = Normal long run p r o f i t for alte r n a t i v e land use Lilt = Disturbance term The l i n e a r approximation which describes the output suggests that the current year's desired production (which serves as an element of that year's conditional p r o f i t ) i s a function of expected output i n the previous season and a function of the 37 difference between the expected and conditional p r o f i t for the expectation of long run p r o f i t s r e l a t i v e to normal long run pri c e s w i l l change the output of the crop. Later, the expected p r o f i t of the a l t e r n a t i v e crops was placed into the disturbance term due to the i n a b i l i t y to i d e n t i f y a proper a l t e r n a t i v e crop. This was done because the authors f e l t there was too wide a range of a l t e r n a t i v e crops. Even i f they could properly i d e n t i f y these crops, they would probably not have had s u f f i c i e n t degrees of freedom to model them. Dividing the above equation by the expected y i e l d gives the bearing area. Note: crop under review and a l t e r a t i v e crops. Changes i n the t-i t-i +-b.n ( n e t - n* t ) + b 1 2 ( n e A t - n * A t ) + ^ i t Y\ Y e t Y\ or: B*t = B Y i + s 3 ( n \ - n * t ) + s 4 ( n e A t - n * A t ) + s 5gY% where: ye ye — I t - X , t - 1 38 From t h i s , desired new plantings are derived: N*t = B*t+k - + Rek<t - Nfc.t.! where: N*t = Acres of desired new plantings k = Time needed to bring plants into bearing R e k t = Area expected to be removed during the next k years Nfc,..! = Total area planted a f t e r year t-k-1 This i s the amount of new plantings a grower would contend with i n order to achieve a normal p r o f i t . The actual new planting (Nt) i s a function of the conditional new plantings i n the same period and the previous period: Nt = ocN*t + "S( l - cc )N t , 1 + e t where: oc = C o e f f i c i e n t of adjustment and 0«x^l fi = A term introduced to allow for some dampening of residual e f f e c t s of unattained past desired plantings and 0<&<1 If E=l then the Nerlove type adjustment i s expressed where new plantings are p a r t i a l l y based on a lagged e f f e c t of p r i c e s . I f S=0 then the decision to plant i s s o l e l y based on expectations of p r i c e s i n that p a r t i c u l a r period. For 6 to equal zero, decisions to replant must be made immediately. That i s , nursery stock, land and other resources, including c a p i t a l must be r e a d i l y a v a i l a b l e . In the case of h o r t i c u l t u r a l crops t h i s r a r e l y happens. For example, i t i s normal that nursery or planting stock must be ordered one to three years i n advance. French and Matthew's argue that £ can be zero i f the planting 39 period i s defined i n the same period as when resources, such as nursery stock, are ordered. If thi s i s the case, and & = 0 then the new planting equation can be defined as: Nt = b 5 1(n% - n*t) +b 5 2(n e A t - n*At) + b 5 3 gY% +bS4A°t_i -b^N^^ +b56At_1+/x5t Removals: Removals are expected to occur on blocks with d e c l i n i n g productivity, but are also a function of other factors such as (1) i n s t i t u t i o n a l and physical factors such as urban expansion or winter injury, (2) short run p r o f i t expectations, since high short run p r o f i t expectations may defer removals and v i s a versa, and (3) other random factors associated with producers' plans and actions. French and Mathews described removals as: Rt = b 6 0 + b 6 1A t° + b 6 2A t°(n t a - nt*) + b 6 3A t°(n 8 A t - n*At) + b 6 4z t + b 6 5A t + nt where: Rt = Acreage removed at the end of period t At° = Acreage older than a p a r t i c u l a r age i n year t n t = Short run p r o f i t expectations per unit of product held i n year t or year t+1 n s A t = Short run p r o f i t expectations per unit of product held i n year t for the alt e r n a t i v e land use i n period t+1 nt*, n*At = Long run normal p r o f i t a b i l i t y per unit of product as of year t 40 Zt = Variable to account for i n s t i t u t i o n a l or physical factors of importance At = Bearing acreage i n t fj.t = Disturbance term It was f e l t by the authors that A t°, i f i t were r e l a t i v e l y large, would be roughly proportional to acres removed, i n that growers are always apt to remove blocks with d e c l i n i n g p r o d u c t i v i t y . If At° were r e l a t i v e l y small i t would have l i t t l e e f f e c t on normal removals. Obviously, the authors believed that changes i n short run p r o f i t expectations would have l i t t l e e f f e c t on removals due to the long gestation period. A p r i o r i expectations are that b 6 1, b 6 3, and b 6 5 are p o s i t i v e , i n that as acreage (and i t s r e s u l t i n g supply) increases, p r o f i t s for a l t e r n a t i v e crops look favourable. As the acreage of d e c l i n i n g blocks r i s e , removals would be i n t e n s i f i e d . Conversely, a p r i o r i expectations are that b 6 2 i s negative, because removals would be deferred i f short run p r o f i t s looked a t t r a c t i v e . 2.1.3 Jaramillo Jaramillo expands on French and Mathews work i n a study of the Columbian coffee industry. Jaramillo separates new plantings, replanting, removals and stumping of e x i s t i n g coffee plantings. He i d e n t i f i e s i n s t i t u t i o n a l constraints such as a land 41 constraint and incorporates d i f f e r e n t coffee growing technologies into the model. This work uses the notion of expected prices and wages. In addition, a variable which examines the presence of subsidized c r e d i t i s included i n the work. In t h i s model's basic form, the author describes the decision of whether the farmer w i l l replant as a comparison of net present value of revenues and costs: Ed+rt)'-' {PtQJt> t where: j = Marginal technology VC d t = Variable costs IC j t = Investment costs r = Interest rate t = Time period The objective of the coffee grower i s to maximize p r o f i t s . As such, the grower w i l l invest i n a new planting i f there i s a p o s i t i v e net present value based on a stream of expected revenue and costs. In the same manner, the grower w i l l examine an e x i s t i n g block of coffee trees and determine i f i t i s better to remove the trees since there i s no foreseeable p r o f i t i n the block. E d+rJ"' {lC j t + QjtVCjt}, t Prices come into d i r e c t play with such an equation since a grower's a b i l i t y to forecast into the future i s strongly 42 weighted by the current p r i c e structure. A series of time periods where prices are low may spark the grower into f e e l i n g that a new block may not be a p r o f i t a b l e venture, or an old block (with lower y i e l d s or high variable costs) may not be a good current investment. Low prices would, i n part, encourage the development of a s i t u a t i o n where replanting i s lower and removals are increased. Jaramillo also notes that Columbian growers produce coffee with a land constraint. This constraint i s i n place since there i s no new or unused land which i s suitable for coffee production i n the country. This land constraint forces the grower to examine blocks within the orchard to have the block's net present values compete against each other for the use of the land, i e Ed+r,)"' { P t Q ° t - IC c t - VC CJ > H{l+rt)-t{PbQ\ - IC T t - VC TJ t t where: c and T represent two types of technology In t h i s p a r t i c u l a r s i t u a t i o n , the grower must decide whether to use technology c or T, or whether to replant at a l l . This s i t u a t i o n i s analogous to that faced by growers i n the Okanagan when considering replanting to d i f f e r e n t v a r i e t i e s . Like coffee growers, Okanagan orchardists must decide what v a r i e t y 43 of apples to plant, or whether to replant at a l l . The binding area constraint also forces the grower to immediately replant following a removal. In such a s i t u a t i o n , the discounted marginal revenue product of c a p i t a l of the new planting must counter balance the costs of removing and planting as well as the opportunity cost of the removed production. In the long run i t can be assumed that t h i s type of coffee grower would only remove older trees with d e c l i n i n g p r o f i t a b i l i t y . In the short run, increases i n coffee prices w i l l lead to a postponement of replanting, where the opportunity cost of keeping the block i s greater than the stream of future p r o f i t s of the new block. In addition, there are no a l t e r n a t i v e uses for the land other than for coffee production. The topography of the land l i m i t s the production of a l t e r n a t i v e crops to that of an few minor crops destined for l o c a l consumption. From t h i s , Jaramillo concludes that a corner solution exists and a grower w i l l produce coffee or nothing at a l l . In Jaramillo's theory chapter, Jaramillo points out that a coffee grower with a planting which i s of r e l a t i v e l y young vintage w i l l not remove trees i f prices decline. Instead, the operator w i l l change optimal inputs of f e r t i l i z e r and labour. In a s i t u a t i o n where the tree stock i s d e c l i n i n g i n 44 p r o d u c t i v i t y due to age, drops i n prices w i l l r e s u l t i n replanting. This i n f e r s , as was pointed out by French and Bressler's model, that the amount of d e c l i n i n g acreage should be included as a variable when modelling replanting of perennial crops, since i t has a bearing on removals. 2.1.4 Hartley, Nerlove and Peters In t h i s contemporary work, the authors examine the S r i Lankan rubber industry. There are two separate equations for replanting and new plantings of rubber estates. New plantings are those that have come from alt e r n a t i v e crops. Replantings are a function of expectations of prices, wages, subsidies and the vintage of e x i s t i n g trees. 5 Hartley, Nerlove and Peters' replanting equation i s described below. Rt = oc0 + a i ( P t - P"^) + oc2P% + oc3wt + oc4St + oc5AGEt + fit where: Rt = Acres replanted i n period t Pt = Current prices and near term expectations i n period t Pet_! = Longer term p r i c e expectations i n period t-1 wt = Wages i n period t St = Subsidies i n period t AGEt = Vintage of e x i s t i n g trees 5 I t i s important to note that the farms modelled by Hartley, Nerlove, and Peters are constrained by the a v a i l a b l e land space and plantings can only occur i f removals are preceded. 45 Growers w i l l compare current prices and near-term expectations Pt with longer-term expectations of prices P t e i n order to decide whether to uproot and replant a given stand. Near-term p r i c e expectations are those they expect to receive up to the time a newly replanted stand begins to y i e l d s i g n i f i c a n t l y . The higher the current prices and near-term expectations r e l a t i v e to the normal prices, the less replanting w i l l occur. Of course, the reverse i s true when current prices and near-term expectations are low r e l a t i v e to normal p r i c e s . This type of behaviour i s a r e s u l t of a land constraint, i n that there are no new acres to expand onto and growers must uproot plants before replanting can take place. The authors found modelling the age spectrum a d i f f i c u l t v a r i a b l e to accommodate without s a c r i f i c i n g degrees of freedom. Taking t h i s into account, trees were c l a s s i f i e d by age and modelled likewise. More s p e c i f i c a l l y acres of trees over 40 years and trees aged 35 to 40 years were included as two separate vari a b l e s . It i s anticipated that trees i n these age brackets would probably be declining i n p r o f i t a b i l i t y and would be slated for renovation before trees of a lesser vintage. New plantings were modelled i n a d i f f e r e n t format. I t was assumed that for growers to be encouraged to plant rubber on land dedicated to other crops they would need to examine rubber y i e l d s , and current and expected prices and wages. This i s 46 d i f f e r e n t than the replanting equation, i n that growers would now have to anticipate y i e l d s , prices and wages since there was no cropping hi s t o r y to follow. In addition, there i s no need to consider a vintage aspect of e x i s t i n g trees. Nt = e0 + e±Q\ + e2p\ + e3wt + e t where: Nt = Newly planted acreage i n year t Q*t = Potential output i n year t The authors f e l t the estimation results from t h i s equation were not empirically good since l i t t l e new plantings occurred i n the estimation period. Aside from the data d i f f i c u l t i e s i n modelling new plantings, the new planting equation d i f f e r s considerably from the replanting equation. While both models include expected prices and wages, the new planting equation considers p o t e n t i a l output and has l i t t l e regard for the p r o f i t s of e x i s t i n g crops. The replanting equation does not consider p o t e n t i a l output but does account for the p r o f i t a b i l i t y of e x i s t i n g orchard (explained i n the AGE variable) and the l e v e l of subsidies. 47 2.1.5 Zvi G r i l i c h e s In t h i s paper, the author works with an annual crop, explaining the lag i n uptake of hybrid corn technology i n the United States from 1932 to 1956. Both l o g i s t i c s c o r r e l a t i o n and multiple regression techniques were used to explain d i f f e r e n t aspects of the corn producing industry and cross s e c t i o n a l grower responses to p r o f i t a b i l i t y . The author worked at both the state and d i s t r i c t l e v e l , running separate c o r r e l a t i o n s and regressions for both. Observations i l l u s t r a t e that states, l i k e Iowa, were more progressive and adopted hybrid corn production faster than states such as Texas and Alabama. Part of the d i f f i c u l t y of adapting hybrid corn i s that there i s no one hybrid l i n e that can be planted i n a l l regions and that can show improved y i e l d s . Instead, hybrid l i n e s for s p e c i f i c d i s t r i c t s must be developed, tested and commercially introduced. Farmers may be apprehensive to plant unproved l i n e s , since the l i n e s may not be as productive as expected. The author i l l u s t r a t e d that the rate of adaption of each d i s t r i c t was dependent upon farm structure (farm si z e , importance of corn production), whether the region had adopted to the use of hybrids early, and the genetic make up of the hybrid corn used. 48 Table 2.1 Correlation C o e f f i c i e n t s on the Crop Reporting D i s t r i c t Level N = 31 x 3 b X4 Xio .35 - .62 - .89 .82 .52 .77 .55 - .39 .46 .28 - .36 .68 - .51 - .79 where: Y = Date of Origin. The date an area reached 10 per cent corn acreage planted to hybrid corn. X± = Market Density. For states: average corn acreage 1937-46 times the maximum percentage of land which can i s suitable to hybrid corn planting (referred to as K by the author), divided by land i n farms i n 1945. Similar for crop reporting d i s t r i c t s but averaged over d i f f e r e n t periods, depending on the a v a i l a b i l i t y of data. b = The slope of the l o g i s t i c transform. A measure of the expected rate of acceptance i n d i f f e r e n t areas X4 = "Corn Beltiness" The proportion of a l l inbred l i n e s accounted by "Corn Belt" l i n e s i n the pedigrees of recommended hybrids by areas. X10= E a r l i e s t date of o r i g i n i n the immediate neighbourhood. The development of hybrids began i n the heart of the Corn Belt and spread towards the fringes. This was p a r t l y due to the si z e of a market for a p a r t i c u l a r hybrid and the marketing costs of developing sales for a given area. Areas i n the Corn Belt were more apt to dedicate more s p e c i f i c resources on research and development towards hybrid corn 49 development since the economies of those regions were highly r e l i a n t on the corn industry. In contrast, farm land i n the fringe areas were often considered to be more marginal corn producing areas, and the true economic benefits of corn production would never be attained even i f a "good" s t r a i n was developed. In some cases, the author explained that a farmer i n a marginal corn area may have l i t t l e or no animal production. Corn production may be for human consumption, feed for d r a f t animals or for a few chickens. The farmer i s interested i n only producing a set amount of corn to f i l l those needs, and often i t i s produced on the poorest land, using l e f t - o v e r resources, or on i d l e land. Producing more corn v i a the use of hybrids would not be i n the farmers' economic i n t e r e s t . In a side note, the author says that regional differences are not often cl e a r cut and are not f u l l y described by a handful of v a r i a b l e s . He goes on to say that i n the short run, s o c i o l o g i c a l variables have an impact on the uptake of technology. I t i s d i f f i c u l t to separate whether the slow acceptance of hybrid corn i n a "poor corn area" was due to "poor people" or other economic factors. I t can be expected that the regional e f f e c t s describing the hybrid corn industry w i l l o f f e r some explanation of regional 50 differences i n the apple industry of B r i t i s h Columbia. There are poor apple growing areas and v a r i a b i l i t y i n the competence of apple orchardists; t h i s w i l l o f f e r some explanation of differences i n replanting behaviour. Zvi G r i l i c h e s author brings the element of r i s k and factors that a f f e c t farmers' perceptions of r i s k . Corn Beltiness, the importance of corn as a crop and how such elements affected the rate of acceptance of hybrid corn i n any region, were included as variables i n the model. Like the adaption of hybrid corn, apple produces i n the Southern I n t e r i o r of B r i t i s h Columbia experience differences i n t h e i r rates of replanting and t h e i r rate of adoption to new v a r i e t i e s . 2.2 Other Approaches A l l of the models examined i n t h i s chapter use an econometric approach to modelling supply response. Two modern essays by Knapp and Konyar 1991, and Kalaitsandonakes and Shonkwiler 1992, use a Kalman F i l t e r approach and a State-Space approach to modelling supply response i n perennial crops. The underlying assumptions surrounding t h i s type of modelling d i f f e r s from econometric supply response modelling, hence i t w i l l not be used i n t h i s thesis. 51 2.3 F i n a l Comments In addition to these papers, there are many other papers that use econometric supply response modelling methods. These papers include many of the same models described i n the works examined i n th i s chapter. Note that while the theory supporting these models i s well developed, data can become a l i m i t i n g factor i n the sophistication of the models. As such some authors (eg French and Mathews) have to resort to using an assumption surrounding a ce r t a i n action instead of being able to model a c t i v i t i e s using empirical evidence. These authors assumed there to be no adjustment period required between the time the decision to replant i s made and the time planting occurs. There are no good data available to make an empirical estimation and a reasonable assumption was made. This i s not to say that models should be overly complicated when i n fact a s i t u a t i o n i s simple or degrees of freedom are l i m i t e d . These works o f f e r insight into the development of a replanting model for apples. Independent variables should include prices and costs due to economic theory but h o r t i c u l t u r a l conditions should d i c t a t e the structure of variables such as tree vintage and winter i n j u r y into account. Due to regional differences that e x i s t i n the Southern I n t e r i o r of B r i t i s h Columbia, r e g i o n a l i t y should be accounted for i n the independent va r i a b l e s . Grants or subsidies were important i n Jaramillo's 52 work and they, too, play a role i n t h i s thesis. I t i s favourable to use data at a l e v e l which compliments the structure of the industry being examined, but data l i m i t a t i o n s can often make thi s a luxury. Most of the papers i n the l i t e r a t u r e use data that are highly aggregated and nuances that occur at less aggregated l e v e l s are often missed i n the modelling process, even though they contribute greatly to the o v e r a l l behaviour being modelled. By accounting for these variables instead of dismissing them i n the disturbance term, confidence i n the model i s enhanced and a g r i c u l t u r a l p o l i c y a r i s i n g from supply response modelling better serves the industry and the a g r i c u l t u r a l community. An example would be the regional behaviours of Zvi G r i l i c h e s ' work and how they became woven into a model to create a better understanding of the subjects at hand. 53 Chapter 3 Theory In t h i s chapter, a theoret i c a l supply response model i s described and presented. The model w i l l examine the economic theory which surrounds the planting of apple orchards i n the Southern I n t e r i o r of B r i t i s h Columbia. Two equations are used to describe the planting of new and t r a d i t i o n a l v a r i e t i e s of apples. Plantings are broken into those of t r a d i t i o n a l v a r i e t i e s (eg Mcintosh and Red Delicious) and new v a r i e t i e s (eg Gala and Jonagold). A t h i r d equation i s used to describe the removals of t r a d i t i o n a l v a r i e t i e s . Modelling i s c a r r i e d out on an annual regional l e v e l . There are behavioral differences that occur i n the regions described and i t i s best to account for these differences i n the dependent variables rather than i n the disturbance term. Some reasons for these regional differences have been mentioned i n Chapter 1 and centre around cli m a t i c differences; however, there are regional demographic differences among farmers themselves, as i l l u s t r a t e d i n Appendix D. Because data are not avail a b l e to account for annual changes i n demographics, demographical differences w i l l be explained using numbers c o l l e c t e d from the empirical model i t s e l f . The regional c o e f f i c i e n t values are compared to age and education data for 54 the s p e c i f i e d regions, i n a l i n e graph, showing generalized trends. 3.1 The Investment P o r t f o l i o An orchardist owns an mixture of investments containing blocks of apple v a r i e t i e s and (in some cases) other tree f r u i t commodities, such as pears, sweet cherries, peaches, and apricots. The p r o f i t maximizing grower constantly examines his/her investment i n each block to see how the i n d i v i d u a l block's p r o f i t s are performing r e l a t i v e to a l t e r n a t i v e s . Blocks returning a negative p r o f i t would need to be removed. If there i s a p r o f i t a b l e use for the land once the trees are removed, i e : replanting to apples, another tree f r u i t commodity, or another crop, then those land uses w i l l occur. If the farmer cannot foresee a p r o f i t a b l e use for the land, i t would remain vacant. Apples are a perennial crop and by t h i s nature growers' decisions have a b u i l t i n time factor. Apple trees do not y i e l d t h e i r l i f e ' s p r o f i t i n the year of planting. Trees take time come into bearing and once i n bearing they w i l l y i e l d a stream of p r o f i t a b l e crops over a succession of years, even decades. From t h i s , i t . i s necessary to appreciate that the grower must see p r o f i t s i n the form of a net present value 55 instead of a p r o f i t i n any single period. 3.2 Production Inputs Any p r o f i t s derived from growing f r u i t w i l l require d i f f e r e n t l e v e l s of investments or inputs. In the t h e o r e t i c a l model, p r o f i t w i l l depend on three inputs categories: variable inputs, c a p i t a l investment inputs, and land. 3.2.1 Variable Inputs Variable inputs for the most part are inputs the grower needs to produce the current year's crop. They include items such as harvest labour, chemicals and f e r t i l i z e r s but do not include items that would be used to generate a future crop, such as new trees. 3.2.2 Capital Investment Cap i t a l investment inputs are items used to generate future expected p r o f i t s and are items which must be discounted over time. These items are associated with planting a block of trees. Input items here would include labour (for planting and e s t a b l i s h i n g blocks), new trees, i r r i g a t i o n systems, tree support ( t r e l l i s i n g ) systems, land c l e a r i n g and preparation, and s o i l fumigation. Included i n t h i s input i s the knowledge of a new variety, how to grow i t and how well suited i t i s to 56 a p a r t i c u l a r region. In cert a i n circumstances th i s "know-how" c a p i t a l may have up-front costs i n on-farm research, t r a v e l to other growing regions, etc., which needs to be discounted over time. I t i s important to note that some of the c a p i t a l investment i s sourced from two sources. The f i r s t i s the grower's own equity i n the form of physical c a p i t a l (money, machinery et c . ) , knowledge, management s k i l l s , and labour. The second i s generated from government sources i n the form of subsidies. 3.2.3 Land The value of the land input i s the rental cost of the land. This i s the opportunity cost the grower must charge himself/herself to use the land for apple production. The r e n t a l cost of land i s not necessarily a cash cost. Instead i t may be viewed as an opportunity cost based on the growers' expectations of the land for producing crops. The value of land rent i s what a land owner would charge a farmer to rent land that would have no c a p i t a l improvements. 3.3 Mathematics of P r o f i t Maximization Due to the perennial nature of the crop, the farmer r e a l l y sees a sum of expected p r o f i t s derived from his p o r t f o l i o of blocks. Hence for each in d i v i d u a l block: 57 E t ( l + r ) - t n t e = E t(l+r)- t(P t eQ t-VC e t-IC e t-Land t) where: Land t r t = Interest rate = Time period = Expectations of p r o f i t s = Price expectations i n period t = Quantity produced i n period t = Expected variable cost i n period t = Expected investment cost i n period t = Expected land costs i n period t An e x i s t i n g block with an expected negative net present value (as defined by Jaramillo) would be removed. This could come about through expected low prices, expectations of low y i e l d s or expected high costs. When a grower decides to replant a block to apples or to an alternative commodity, the new block must be expected to generate a p o s i t i v e net present value (NPV) . If the grower cannot see a p o s i t i v e NPV from a new block (including examining an alte r n a t i v e crop) but anticipates a negative NPV from the old block, the grower w i l l remove the old block and not follow up with replanting. This could occur where land re n t a l prices are so high that they overshadow any po t e n t i a l p r o f i t s that could be raised by planting apples. The issue of land i s an important aspect of the replanting of apple orchards i n B.C. and i s discussed at length i n the Introduction. Older growers, e s p e c i a l l y i n regions experiencing a high rate of urban expansion i s often less w i l l i n g to renovate orchards. These growers are often reluctant to s e l l . This behaviour over time slows down the 58 entry and e x i t of old and young farmers. An older farmer who i s close to retirement w i l l manage his/her p o r t f o l i o of investments d i f f e r e n t l y than a younger farmer. The long gestation period between planting and mature y i e l d means a r e t i r i n g farmer may not f u l l y recapture his/her investment i n the s e l l i n g p r i c e of the orchard. The purchaser of the property may (or may not) pay a higher p r i c e for the renovated orchard land and the r e t i r i n g orchardist must bear the r i s k of such an occurrence. If the anticipated value of the land i s so great that i t overshadows expected revenue from a new block, the farmer w i l l not replant since the perceived high cost of land rent would create a negative NPV. A s i m i l a r response would occur i f the r e t i r i n g orchardist anticipates the new orchardist as a non-farmer, who i s not interested i n the p r o f i t a b i l i t y of f r u i t sales from the orchard. 3.3.1 Land Constraints Orchardists i n the Southern I n t e r i o r of B r i t i s h Columbia are constrained by the amount of land they are able to plant to apples or other tree f r u i t s . Idle land does not e x i s t i n any region. This constraint forces growers to remove production before they are able to plant to a new block. Any new planting 59 must be weighed against the loss of production from o l d plantings. The grower must expect a zero or negative NPV i n an old block before a new planting i s considered unless the NPV from the new planting i s greater than from ret a i n i n g the o l d planting. If the grower made the decision to replant, the NPV of avai l a b l e alternatives w i l l compete against each other. For example, suppose the grower had the choice of replanting to Mcintosh (a t r a d i t i o n a l variety) or to Gala (a new v a r i e t y ) . The grower with the land constraint must choose one with the highest NPV, as describe below: max (E t(l+r)- t(P e tQ i t-VC i t-IC i t-Land i t) } i where i = Mcintosh or Gala V a r i e t i e s Given t h i s , the grower would have the following a l t e r n a t i v e s : 1. No replanting, no change i n the ALR. Prices and / or y i e l d s continue to decline from vintage blocks. This would r e s u l t i n a decline i n producing acres of apples as unprofitable trees are removed, and an eventual decline i n o v e r a l l y i e l d s . 2. Same as (1) but some expectation of the ALR being relaxed. The r e s u l t would be the same as (1) . Expectations of changes i n the ALR would lead to a reduction i n replanting 60 due to the increased opportunity cost of land. 3 . Replant to t r a d i t i o n a l v a r i e t i e s . 4 . Replant to new v a r i e t i e s . 5. Replant to an alternative commodity. 6. Remove vintage trees and hold land. 3 . 4 Winter Injury Winter i n j u r y i s the damage to trees caused by severe cold winter temperatures. The damage caused by winter i n j u r y can accumulate i n the tree. That i s , a tree may be p a r t i a l l y injured and may not show economic l e v e l s of in j u r y u n t i l more of the tree i s damaged i n a subsequent period. I t can be expected that removals of older trees are greater i n periods following a cold winter. By the nature that removals occur, replanting would be increased following a cold winter. As has been explained, removals are delayed (lagged) due to the phy s i o l o g i c a l response of the trees. The delay (lag) i n removals i s also required because the grower needs time to prepare the f i e l d for replanting, order nursery trees, and arrange financing. In addition, the period i n which the winter i n j u r y occurred may be lagged one period from replanting due to the nature of the calender year. For example, trees injured i n November 1990 would be recorded as being removed and replanted 61 i n A p r i l 1991. 62 Chapter 4 The Empirical Model To test the theory discussed, replanting a c t i v i t i e s are estimated i n three equations: 1. Plantings of t r a d i t i o n a l v a r i e t i e s ; 2. Plantings of new v a r i e t i e s ; 3. Removals of vintage trees. The types of apple v a r i e t i e s planted can be s p l i t into two groups. One i s the t r a d i t i o n a l v a r i e t y group. These are v a r i e t i e s have been commercially produced i n the Southern I n t e r i o r of B r i t i s h Columbia for a period of time long enough to have established a mature market and long enough that production r i s k s are well known to the grower. The second v a r i e t y group includes those that are new or unfamiliar to the regions, have uncertain production c h a r a c t e r i s t i c s , and have not been produced long enough for farmers to see a trend i n the market. For example, Gala i s treated as a new varie t y . Its winter hardiness, bearing habits, f r u i t size, and storage l i f e were not f u l l y understood by growers when the vari e t y was f i r s t planted. Currently market prices are high, but i t i s uncertain how long the unusually high prices w i l l be maintained. Most of the high 63 p r i c e s for Gala are received i n a r e l a t i v e l y small market (in t h i s case, Southeast Asia) and i f the market becomes saturated soon, prices may drop. 4.1 Data Structure The data used i n the estimation of the empirical model i s i n an annual regional form. Cross sectional data i s used from eight regions: Vernon, Kelowna, Summerland, Penticton, Oliver, Osoyoos, Cawston and Creston. Net present values f o r new and t r a d i t i o n a l v a r i e t i e s are calculated for each region. Prices are weighted i n each region to r e f l e c t the p a r t i c u l a r mix of v a r i e t i e s planted and removed i n each region. For example, the p l a n t i n g p r i c e of new v a r i e t i e s i n Cawston may be higher than that of Vernon i n a p a r t i c u l a r year due to the mix of v a r i e t i e s planted. Price expectations are converted to present values 6. T r a d i t i o n a l apple v a r i e t i e s are considered the best a l t e r n a t i v e to new apple v a r i e t i e s and v i s a versa. Although other tree f r u i t commodities can be planted as an a l t e r n a t i v e to any apple va r i e t y , the number of the choices i s too large to model given the degrees of freedom. As well, the economics of p l a n t i n g other tree f r u i t commodities are not comparable i n a simple 6 A complete d e s c r i p t i o n of data and assumptions used i n the present value c a l c u l a t i o n are provided i n Appendix B. 64 form as the gestation period between planting and f u l l production i s d i f f e r e n t . Also, winter hardiness and other r i s k factors make them less l i k e l y substitutes for other apples. The NPV of trees being removed i s considered important since the land constraint forces growers to remove before they can replant. The growers expectation of trees being removed i s an important factor i n the removal and replanting decision. A v a r i a b l e to account for the percent of vintage trees i n each region i s used. This variable i s the percent of acres of apple trees i n a region which are older than 20 years of age ( r e l a t i v e to the acreage of a l l f r u i t trees of the region) . I t i s expected that a higher percent stock of vintage trees i n a region would spur replanting as growers i n the region step up replanting. Expectations of land prices are not included as a v a r i a b l e i n the equation. They were deemed as not important i n the replant decision. I t i s true that regional and annual differences i n land prices do exist, however, these differences contribute more to an entry/exit decision rather than a replanting decision. Instead, land values and the entry/exit remain embedded i n the regional dummy variables. Explanation for regional differences include an account for grower demographics and how t h i s relates to the entry/exit behaviour and replanting 65 decisions. During the study period there was one year i n which there was no replant subsidy available to farmers, followed by two d i s t i n c t subsidy programs. These two programs are modelled by two dummy variables to account for the two replant subsidy programs, the ARDSA (1986 to 1989) and OVTFA (1990 to 1992) programs. The value 0 i s used for the year 1985, the only year i n the study period i n which no replanting subsidy was avai l a b l e . The actual amount of the grant i s included i n the net present value (NPV) formula. The intent of the dummy i s to account for the presence of the programs' non-cash or grant components, such as farmer education programs and other enhanced extension and communications programs. A dummy variable was constructed to account for extremely low winter temperatures which followed a period of r e l a t i v e l y warm weather. The value 1 i s used to account for winter temperatures cold enough to cause winter i n j u r y to apple trees. 4.2 The Dependent Variable The dependent variable for each equation i s the acreage replanted (or removed) i n each year divided by the t o t a l tree f r u i t acreage for each region. This r a t i o accounts for the 66 uneven d i s t r i b u t i o n of tree f r u i t acreage i n each region. Total tree f r u i t acreage was used as the denominator instead of apple acreage to account for the t o t a l land a v a i l a b l e for replanting, which includes soft f r u i t acreage. 4.2.1 Costs Costs are not modelled as a separate independent v a r i a b l e . There are several reasons for t h i s : 1. In meeting with farmers, they d i d not express concerns over costs of production when considering replanting. Price was more of a motivating factor than cost. 2. The model used i n the estimation r e l i e s on cross sectional observations and times series observations rather than s o l e l y time series over several decades. 3. Costs between regions i n Southern BC do not vary appreciably, and attempting to account for regional p r i c e differences would not add to the robustness of the model. 4 Unlike farmers i n less developed nations, exchange rates and i n f l a t i o n rates experienced by B.C. farmers do not fluctuate widely i n short periods of time. The macro-economic conditions faced by B.C. growers are 67 r e l a t i v e l y stable and are usually not part of the annual decision making process modelled i n t h i s analysis. Instead of c o l l e c t i n g annual regional cost information, costs were included i n the NPV c a l c u l a t i o n . One cost of production model was used for a l l regions and then adjusted for annual changes using the Consumer Price Index (CPI). 68 4.3 Plantings of New Apple V a r i e t i e s The following equation estimates the planting of new apple v a r i e t i e s . PLNT n e w t = oc10 + o c u N P V ^ t + oc12NPV% + oc13NPVetALT + oc14VINTt + oc15SUBl + oc16SUB2 + oc17REGl + oc18REG2 + ^  9REG3 + 10REG4 + 1:LREG5 + ct^  12REG6 + oz1 3REG7 + cc^  1 4Z + CC-L 1 5Grant t + cr^  1 6time + ri1 where: PLNT n e w t = Ratio of the acres of new apple v a r i e t i e s planted i n period t divided by the t o t a l tree f r u i t acreage i n the region. NPV e r e m o v e t = Net present value of trees being removed to make way for the planting. NPVet = Net present value of revenue expected from planting new apple v a r i e t i e s . NPV% ALT = N e t present value of revenue expected from planting t r a d i t i o n a l apple v a r i e t i e s . VINTt = % of acres of trees i n each region that are older than 20 years. SUB1 = Dummy to account for the replant subsidy program between 1986 to 1990. The ARDSA program. SUB2 = Dummy to account for the replant subsidy program between 1991 to 1992. The OVTFA program. REG = Dummy to account for the 8 growing regions. Z = Dummy to account for winter injury. Grant t = Net present value of replant grant i n period t. time = Year 69 4.4 Plantings of Tr a d i t i o n a l V a r i e t i e s The following equation estimates the planting of t r a d i t i o n a l apple v a r i e t i e s . PLNT trad t where: PLNT trad t NPVe remo' NPVet NPVe VINTt SUB1 SUB2 REGn Z Grant t time « 2 0 +a 2iNPV e r e m o v e t cc22NPVet + oc23NPVetAIiT + cc24VINTt + cc25SUBl + oc26SUB2 + oc27REGl + cc28REG2 + cc29REG3 + oc2 10REG4 + oc2 11REG5 + cc2 12REG6 + oc2 13REG7 + cc2 1 4Z + cc2 l sGrant t + oc2 1 6time + p2 Acres of t r a d i t i o n a l apple v a r i e t i e s planted i n period t divided by the t o t a l tree f r u i t acreage i n that region. Net present value of trees being removed to make way for the planting. Net present value of revenue expected from planting t r a d i t i o n a l apple v a r i e t i e s . Net present value of revenue expected from planting new apple v a r i e t i e s . % of acres of trees i n each region that are older than 20 years. Dummy to account for the replant subsidy program between 1986 and 1990. The ARDSA program. Dummy to account for the replant subsidy program between 1991 and 1992. The OVTFA program. Dummy to account for the 8 growing regions. Dummy to account for winter injury. Net present value of replant grant i n period t. Year The p r i c e expectations of t r a d i t i o n a l apple v a r i e t i e s i s described Appendix F, as i s that of new v a r i e t i e s . 70. 4.5 Removals of Vintage Trees The following equation estimates the removals of vintage apples. RMVLvint t where: RMVLvint NPVeremo. NPVet NPV*^ VINTt SUB1 SUB2 REGn Z Grant t time « 3 o +«3iNPV r„ o v. t oc32NPV% + oc 3 3 NPV t J k M + cc 3 4VINT t + oc35SUBl + oc36SUB2 + cc37REGl + oc38REG2 + oc39REG3 + cc3 10REG4 + cc3 X1REG5 + oc3 12REG6 + oc3 13REG7 + oc3 1 4Z + a 3 1 5Grant t + oc3 1 6time + fi3 Acres of apples removed i n period t divided by the t o t a l tree f r u i t acreage i n that region. Net present value of trees being removed to make way for the planting. Net present value of revenue expected from planting t r a d i t i o n a l apple v a r i e t i e s . Net present value of revenue expected from planting new apple v a r i e t i e s . % of acres of trees i n each region that are older than 20 years. Dummy to account for the replant subsidy program between 1986 and 1990. The ARDSA program. Dummy to account for the replant subsidy program between 1991 and 1992. The OVTFA program. Dummy to account for f r u i t the 8 growing regions. Dummy to account for winter injury. Net present value of replant grant i n period t. Year 71 4.6 Regression Results The model was run using the econometrics program Shazam. The three equations were run as independent Ordinary Least Squares (OLS) equations. The model was tested for autocorrelation using the Durbin-Watson test and showed there to be no conclusive evidence regarding the presence or absence of p o s i t i v e f i r s t -order s e r i a l c o r r e l a t i o n . In addition, the models were changed s l i g h t l y to test for the robustness of the model. The s i x reported models are as following: 1. D i s t r i b u t e d lag, as described i n the text of t h i s t h e s i s . 2. Distributed lag, as above, but with no time v a r i a b l e . I t was thought that t h i s variable may be s t e a l i n g some of the e f f e c t s from other variables. 3. D i s t r i b u t e d lag, as i n 1, but with no regional dummy variable s . I t was thought that these regional variables may be masking some of the e f f e c t s of behavioral v a r i a b l e s . 4. D i s t r i b u t e d lag, as i n 1, but p r i c e expectations were generated without the addition of ad hoc payments. Apple prices were deemed as important behavioral variables and t e s t i n g another approach to how they were calculated was 72 considered an appropriate method of tes t i n g the robustness of the model. 5. Distr i b u t e d lag, as i n 1, but three dummy variables were used to account for the replanting programs. This model uses two dummies (instead of one) to account for the OVTFA replant program. Recall, i n the l a t t e r part of the OVTFA program, the amount of grant was decreased and the e l i g i b i l i t y c r i t e r i a of the program were tightened. In th i s model three dummy variables are used, as well, the grant amount i s added to the NPV variables and the grant variable i s eliminated. I t was thought that a test for the robustness of the grant and program variables was needed. 6. This model uses the same variables as 1, except p r i c e expectations and th e i r r e s u l t i n g NPVs are calculated using a geometric, instead of di s t r i b u t e d lag. I t was thought that the NPV variables were important behavioral variables and robustness of the model using an al t e r n a t i v e method of ca l c u l a t i n g the pr i c e lags was needed. 73 4.6.1 Plantings of New V a r i e t i e s Table 4.1 New V a r i e t i e s Regression C o e f f i c i e n t 1 2 3 4 5 6 NPV*t r e m o v. -2.3E-4 -2.3E-4 -3.0E-4 -3.5E-4 -2.5E-4 -5.034 (-1.8*) (-1.9*) (-1.7*) (-0.3) (-1.5) (-2.7*) [0.03] [0.03] [0.03] [0.02] [0.8] [0.5] NPV% t r a d -1.9E-4 -2.5E-4 -8.3E-5 -5.4E-4 -7.2E-5 3.2E-4 (-1.0) (-1.4) (-0.3) (-2.8*) (-0.2) (1.6) [0.03] [0.04] [0.01] [0.2] [0.2] [0.3] NPVet n e w 1.0E-5 7.7E-5 4.7E-5 -7.4E-6 4.3E-4 2.8E-5 (0.3) (0.3) (0.1) (-0.2) (1.0) (1.0) [0.03] [0.03] [0.02] [0.02] [0.3] [0.09] VINTt -1.66 -1.7 -0.1 -1.4 1.6 -1.6 (-4.9*) (-5.0*) (-1.4) (-4.2*) (-4.6*) (-4.1*) Z 0.79 0.76 -2.8 0.9 0.8 -0.4 (0.3) (0.3) (-0.7) (0.3) (0.3) (-0.1) REG Vernon 28.6 28.9 25.9 27.0 24.4 (5.8*) (5.9*) (5.1*) (5.4*) (5.0*) REG Kelown. 24.5 24.8 21.3 22 .4 20.1 (4.7*) (4.8*) (4.1*) (4.2*) (4.0*) REG Summer. 0.1 0.2 0.3 -0.1 -0.6 (0.1) (0.1) (0.2) (-0.1) (-0.4) REG Pentic. -2.7 -2.7 -1.6 -2.1 -2.6 (-1.5) (-1.5) (-0.8) (-1.1) (-1.4) REG O l i v e r -16.4 -16.8 -14.4 -15.2 -14.9 (-4.5*) (-4.7*) (-3.9*) (-4.2*) (-4.2*) REG Osoyoos -6.2 -6.2 -4.4 -5.9 -5.9 (-2.6*) (-2.7*) (-1.9*) (-2.5*) (-2.5*) REG Cawston 9.9 9.7 8.4 10.0 8.9 (5.3*) (5.2*) (4.5*) (5.1*) (4.7*) time 3.5 3.4 -9.9 0.6 -1.9 (0.8) (0.5) (-4.8*) (0.1) (-2.3*) ARDSA -113.0 -25.3 -59.8 218.6 -0.8 38.2 (-1.0) (-1.8*) (-0.4) (5.3*) (-0.3) (4.8*) OVTFA 1 -222.3 -47.0 -111.8 441.5 4.7 82.8 (-1.0) (-1.6) (-0.3) (5.4*) (1.6) (5.4*) OVTFA 2 1.9 (0.6) Grant 0.6 1.3E-2 3.0E-2 -0.1 -2.03-2 (1.0) (1.7*) (0.4) (-5.2*) (-5.1*) R2 .86 .86 .67 0.84 0.86 .86 Durb. Wat. 1.9 1.9 1.2 2.1 1.8 1.9 Mean 6.5 6.5 6.5 6.3 6.5 6.3 Variance 11.0 9.9 20.9 11.0 10.4 10.0 NB: Regression c o e f f i c i e n t values are scaled by a value of 1000 for presentation. To obtain true c o e f f i c i e n t values d i v i d e numbers i l l u s t r a t e d above by 1000. ( ) = s t a t i s t i c [ ] = e l a s t i c i t y * = s i g n i f i c a n t at p =.05 n = 64 observations 74 The s i x models described above, i n general express s i m i l a r r e s u l t s for the independent variables, i n terms of the sign of t h e i r c o e f f i c i e n t s and th e i r s i g n i f i c a n c e . As well, the general model s t a t i s t i c s (mean, variance, Durban Watson R square) are si m i l a r . The only model which i s s t r i k i n g l y d i f f e r e n t i n t h i s regard i s model 3, however the Durban Watson value indicates a high p r o b a b i l i t y of p o s i t i v e 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 and the model should not be used. The lack of regional dummy variables changes the model s i g n i f i c a n t l y . The s i m i l a r i t y of the models i l l u s t r a t e s that the model o r i g i n a l l y chosen (model 1) i s robust. The i n c l u s i o n of the time variable a l t e r s the ARDSA and OVTFA variables (model 1 vs model 2) and as such appears to be s t e a l i n g some of t h e i r e f f e c t s when included. However, the e f f e c t i s only to make them s t a t i s t i c a l l y s i g n i f i c a n t and does not a l t e r t h e i r sign. A l t e r i n g the way price expectations are calculated i s tested by comparing model 1 vs models 4 and 6). The NPV for removals i s s i g n i f i c a n t i n model 1 and 6, and NPV for t r a d i t i o n a l v a r i e t i e s i s s i g n i f i c a n t i n 4 only. This suggests that a l t e r a t i o n s i n the method of c a l c u l a t i n g the pri c e expectations can a l t e r empirical r e s u l t s . Model 1 i s used i n the explanation of the empirical r e s u l t s . 75 This i s the o r i g i n a l model and offers the best explanation of the r e s u l t s . This i s p a r t l y because i t models the behaviour of growers as understood by this author, rather than the f i t of the model r e l a t i v e as compared by i t s R square or number of s i g n i f i c a n t variables. The d i f f e r e n t models do o f f e r some insight into the v a r i a b l e s . For example variations i n model 1 vs 2 suggests that the time factor i s influencing grant and program related v a r i a b l e s . Growers planting to new v a r i e t i e s are responsive to changes i n the p r o f i t a b i l i t y of aging trees i n need of removal. This follows a p r i o r i expectations. Growers are not responsive to the changes i n expected p r o f i t s from planting of new v a r i e t i e s . Perhaps, the r i s k of prices dropping as supply eventually catches up with demand moderates growers decisions. Growers are not responsive to changes i n p o t e n t i a l p r o f i t s of planting to t r a d i t i o n a l v a r i e t i e s . These data suggest that growers do not monitor t r a d i t i o n a l v a r i e t i e s , comparing them as though they were an alt e r n a t i v e "crop" to new v a r i e t i e s . The vintage variable i s negative and s i g n i f i c a n t , and indicates that when there are more vintage trees present i n an area, 76 growers are less apt to replant to new v a r i e t i e s . In regions where the are few vintage trees (and replanting i s more prevalent), growers are r e l a t i v e l y more eager to replant to new v a r i e t i e s . This suggests that growers may be more apt to replant to new v a r i e t i e s i f they have c a r r i e d out replanting i n the past. Their experience with replanting has somehow made them less r i s k averse compared to growers i n regions where l i t t l e replanting has occurred. As well, i t could be that regions with younger orchards may be better able to finance additional replanting. This combined with a greater propensity to take on r i s k , may r e s u l t i n more replanting to new v a r i e t i e s . The Z factor i s not s i g n i f i c a n t and shows that grower's decisions to replant to new v a r i e t i e s are unaffected by a cold winter. Neither the ARDSA or OVTFA replant programs increased the l e v e l of replanting to new v a r i e t i e s . Increasing the value of grants had no e f f e c t on replanting. At f i r s t glance, t h i s seems contrary to a p r i o r i expectations, but i n most cases, when grant amounts were increased, e l i g i b i l i t y c r i t e r i a were also increased r e s u l t i n g i n a no net e f f e c t . 77 Anecdotal evidence indicates that increasing the requirements to q u a l i f y for a grant, there was a p o s i t i v e e f f e c t on the economic v i a b i l i t y of the orchard industry. The ever increasing c r i t e r i a "pushed" replanting so that orchardists planted smaller but more p r o f i t a b l e projects. The time variable i s not s i g n i f i c a n t and indicates that the rate of adoption of the technology of new v a r i e t i e s , by i t s e l f , i s not increasing (or decreasing) over time. Growers i n the Vernon, Kelowna and Cawston regions are more responsive to planting to new v a r i e t i e s , while those i n O l i v e r and Osoyoos are less responsive. Summerland, Penticton and Creston growers do not d i f f e r i n t h e i r responsiveness and engage i n an average l e v e l of replanting. I t i s expected that growers i n Summerland, Penticton, Oliver and Osoyoos w i l l conduct a lower l e v e l of replanting to new v a r i e t i e s , since they have the option of planting other crops such as soft f r u i t s and grapes. Creston growers are less l i k e l y to opt for new v a r i e t i e s because t h e i r shorter growing season and colder winters increase the r i s k s of growing new v a r i e t i e s . 78 Figure 4.1 Demographics and Regional Responsiveness of Plantings of New V a r i e t i e s New Variety Plantings Coefficient vs Age/Education Percent of Growers in Each Region Who are Younger Than 45 Years of Age and Have a College Education The above graph i l l u s t r a t e s that regional differences i n planting to t r a d i t i o n a l v a r i e t i e s i s related to the age and education of the farmers i n the region. When there i s a greater proportion of young and more educated farmers i n a region, there i s more replanting to new v a r i e t i e s . These farmers are w i l l i n g to take on more r i s k , and plant to new v a r i e t i e s . I t could also be that new v a r i e t i e s give a high return to management, something that younger, well educated farmers are looking for. Recall, replanting to new v a r i e t i e s was greatest i n regions where there were fewer vintage trees. It may not be inconceivable that these young and well educated farmers either chose to purchase 79 farms that had a larger proportion of younger trees or are carrying on a well maintained family farm from t h e i r parents. As well, i t seemingly explains why economically depressed regions with poor educational systems that do not encourage students to carry on to college continue to lag behind economically endowed regions. 80 4.6.2 Plantings of Tr a d i t i o n a l V a r i e t i e s Table 4.2 1 2 3 4 5 6 NPVe v t remov. 4.5E-4 4.2E-4 6.1E-4 2.8E-4 1.3E-4 4.7E-5 (3.2*) (2.9*) (3.5*) (1.9*) (0.7) (0.2) [0.04] [0.03] [0.05] [0.09] [0.3] [0.03] NPV\ t r a d -2.8E-4 -4.7E-4 -1.7E-4 -3.6E-4 -4.2E-4 -4.5E4 (-1.2) (-2.2*) (-0.7) (-1.6) (-1.2) (-4.8*) [0.03] [0.05] [0.02] [0.09] [0.9] [0.3] NPVet n e w -1.1E-5 -1.9E-5 -2.3E-5 -2.1E-5 -4.9E-5 -1JE5 (-0.3) (-0.5) (-0.5) (-0.6) (-0.9) (-0.3) [0.03] [0.05] [0.05] [0.05] [0.2] [0.02] VINTt - .32 -0.4 0.2 -0.2 -0.4 -0.3 (-0.8) (-1.0) (1.8*) (-0.4) (-0.9) (-0.8) Z -3.9 -4.0 -4.2 -5.7 -5.3 -4.3 (-1.2) (-1.2) (-1.0) (-1.6) (-1.5) (-1.2) REG Vernon 4.7 5.6 2.0 6.0 5.4 (0.8) (0.9) (0.3) (1.0) (0.9) REG Kelown. -1.7 -0.7 -5.2 -0.2 -1.3 (-0.3) (-0.1) (-0.8) (-0.0) (-0.2) REG Summer. -4.6 -4.6 -6.4 -5.0 -5.4 (-2.5*) (-2.2*) (-3.2*) (-2.4*) (-2.7*) REG Pentic. -9.0 -9.8 -11.4 -10.1 -9.5 (-4.9*) (-4.7) (-4.8*) (-4.5*) (-4.3*) REG O l i v e r -11.6 -12.9 -12.6 -13.4 -12.3 (-2.8*) (-3.1*) (-2.9*) (-3.1*) (-2.8*) REG Osoyoos -9.1 -9.2 -10.1 -9.5 -9.6 (-3.5*) (-3.4*) (-3.6*) (-3.3*) (-3.3*) REG Cawston -8.2 -8.7 -9.8 -9.6 -9.4 (-3.9*) (-4.0*) (-4.4*) (-4.1*) (•4.0*) time 10.7 13.4 -0.3 - .7 -1.2 (2.0*) (1.9*) (-0.1) (-0.9) (-1.2) ARDSA -294.3 -29.1 -339.7 -15.6 0.3 -0.9 (-2.2*) (-1.7*) (-1.9*) (-0.3) (0.1) (-0.1) OVTFA 1 -590.0 -59.8 -679.5 -32.1 -0.5 -3.0 (-2.2*) (-1.8*) (-2.0*) (-0.3) (-0.2) (-0.2) OVTFA 2 -4.5 (-1.1) Grant 0.1 0.2 0.2 0.8 7.3E-4 (2.2*) (1.7*) (2.0*) (0.3) (0.2) R2 0.71 0.68 0.41 0.66 0.66 .64 Durb. Wat. 2.2 2.3 1.3 2.2 2.3 1.9 Mean 8.9 8.9 8.9 8.9 8.8 9.0 Variance 12.7 13.5 22.4 15.1 14.9 15.5 NB: Regression c o e f f i c i e n t values are scaled by a value of 1000 for presentation. To obtain true c o e f f i c i e n t values d i v i d e numbers i l l u s t r a t e d above by 1000. ( ) = t s t a t i s t i c [ ] = e l a s t i c i t y * = s i g n i f i c a n t at p =.05 n =64 observations 81 Growers planting t r a d i t i o n a l v a r i e t i e s do so i n a manner i n which i s p o s i t i v e l y correlated to the NPV of trees being removed. Perhaps growers examine t h e i r returns from t r a d i t i o n a l v a r i e t i e s (eg. Spartan and Mcintosh) and estimate they w i l l increase t h e i r p r o f i t s i f they replant to the same v a r i e t i e s , and improve t h e i r packouts. The c o e f f i c i e n t variable for t r a d i t i o n a l v a r i e t i e s i s not s i g n i f i c a n t , i l l u s t r a t i n g that growers do not change t h e i r replant choices around t r a d i t i o n a l v a r i e t i e s when expectations of p r o f i t s change. Plantings of t r a d i t i o n a l v a r i e t i e s are not influenced by the net present value expected from new v a r i e t i e s and growers planting t r a d i t i o n a l v a r i e t i e s do not view new v a r i e t i e s as an a l t e r n a t i v e crop. Increasing the l e v e l of grants does increase the acreage of replanting to t r a d i t i o n a l v a r i e t i e s . The Vintage variable i s not s i g n i f i c a n t and suggests that growers w i l l replant to t r a d i t i o n a l v a r i e t i e s regardless of the percentage of vintage trees i n the region. Perhaps, growers may tend to replant to t r a d i t i o n a l v a r i e t i e s f i r s t before replanting to new v a r i e t i e s . This would support the regression data, where growers increasingly replant to new v a r i e t i e s i f more replanting 82 had be c a r r i e d out previously. Perhaps there i s a learning curve i n e f f e c t , with replanting to t r a d i t i o n a l v a r i e t i e s (to higher densities) followed be replanting to new v a r i e t i e s . Model 1 estimates that over time, growers are replanting more to t r a d i t i o n a l v a r i e t i e s . The significance of t h i s v a r i a b l e i s d i f f e r e n t across models and i s not a robust v a r i a b l e . Both the ARDSA and OVTFA replant programs have decreased the l e v e l of replanting to t r a d i t i o n a l v a r i e t i e s . In part, t h i s was part of the objectives of the programs, encouraging growers to replant to new v a r i e t i e s . Replanting to new v a r i e t i e s i s one of the objectives of the OVTFA and i s r e f l e c t e d i n t h e i r replant program, which discourages growers from replanting to t r a d i t i o n a l v a r i e t i e s . Growers i n Vernon, Kelowna and Creston are more apt to plant t r a d i t i o n a l v a r i e t i e s than growers i n other regions of the Southern I n t e r i o r . This i s expected since these regions experience colder winter temperatures and growers w i l l often plant hardy t r a d i t i o n a l v a r i e t i e s (eg Mcintosh and Spartan) to hedge against the r i s k of winter injury. Growers i n these regions with colder winter temperatures may f e e l some new v a r i e t i e s are too r i s k y to plant because of unknown winter hardiness. As well, some of the new v a r i e t i e s (eg F u j i and Granny Smith) require growing seasons which are longer than these 83 regions experience i n most years. Regions south of Summerland (including Summerland) are less apt to replant to t r a d i t i o n a l v a r i e t i e s . This i s party because they can replant to al t e r n a t i v e crops, and p a r t l y because i t i s more d i f f i c u l t to obtain good f r u i t colour on Mcintosh and Spartan (the predominantly replanted t r a d i t i o n a l v a r i e t i e s planted during the study period of t h i s t h e s i s ) . 84 4.6.3 Removals of Tr a d i t i o n a l V a r i e t i e s Table 4.3 Removals Regression C o e f f i c i e n t 1 2 3 4 5 6 NPVet r e m o v. 3 .5E-04 -3.2E-4 -4.3E-4 3.1E-4 -3.6E-5 -!L2&4 (2.4*) (-2.1*) (-1.8*) (2.0*) (-0.2) (-0.5) [0.02] [0.02] [0.03] [0.06] [0.07] [0.07] NPV% t r a d -4.3E-04 -6.4E-4 -3.8E-4 -8.2E-4 -2.3E-4 -L3B4 (-1.8) (-2.9*) (-1.1) (-3.3*) (-0.6) (-0.5) [0.05] [0.05] [0.03] [0.4] [0.2] [0.07] N*V% n e w -2.1E-05 -3.0E-5 4.4E-5 -4.7E-5 -2.7E-5 -4.5B4 (-0.6) (-0.8) (0.7) (-1.2) (-0.5) (-0.1) [0.04] [0.05] [0.08] [0.09] [0.08] [0.01] VINTt -2.1 -2.1 -0.2 -1.8 -2.0 -1.8 (-5.1*) (-5.1*) (-1.9*) (-4.1*) (-4.7*) (-3.8*) Z -0.35 -0.46 -3.9 -2.4 -1.7 -2.0 (-0.1) (-0.1) (-0.7) (-0.6) (-0.5) (-0.5) REG Vernon 32 .3 33.4 28.1 32.0 28.6 (5.5*) (5.5*) (4.4*) (5.1*) (4.2*) REG Kelown. 21.4 22.5 16.1 21.0 17.3 (3.4*) (3.5*) (2.4*) (3.2*) (2.5*) REG Summer. -7.3 -7.2 -9.1 -8.0 -8.5 (-3.8*) (-3.6) (-4.2*) (-3.8*) (-3.8*) REG Pentic. -17.4 -17 .3 -18.4 -17.3 -16.8 (-8.2*) (-7.9*) (-7.1*) (-7.5*) (-6.8*) REG O l i v e r -28.1 -29.6 -28.4 -28.6 -26.5 (-6.5*) (-6.7*) (-6.0*) (-6.4*) (-5.4*) REG Osoyoos -18.8 -18.2 -18.1 -18.6 -18.0 (-6.5*) (-6.4*) (-5.9*) (-6.3*) (-5.6*) REG Cawston -0.3 -0.9 -3.7 -1.5 -2.5 (-0.1) (-0.3) (-1.5) (-0.6) (-1.0) time 12.7 12.6 -9.4 -1.5 -2.9 (2.2*) (1.3) (-3.7*) (-1.9*) (-2.6*) ARDSA -360.3 -59.9 - 302.8 174.3 0.2 30.0 (-2.6) (-3.3*) (-1.3) (3.3*) (0.6) (2.7*) OVTFA 1 -717.9 -115.1 -598.1 352.4 6.5 65.5 (-2.6*) (-3.2*) (-1.3) (3.3*) (1.7*) (3.1*) OVTFA 2 0.7 (0.2) Grant 0.2 0.0 0.2 -0.1 -L5E-2 (2.6*) (3.2*) (1.3) (-3.2*) (-2.8*) R2 0.83 0.82 0.41 0.80 0.81 0.78 Durb. Wat. 2.0 2.1 0.9 2.3 2.1 2.2 Mean 11.9 11.9 11.9 11.6 11.9 12.0 Variance 14.0 15.1 43.9 17.6 16.0 19.1 NB: Regression c o e f f i c i e n t values are scaled by a value of 1000 for presentation. To obtain true c o e f f i c i e n t values d i v i d e numbers i l l u s t r a t e d above by 1000. ( ) = t s t a t i s t i c [ ] = e l a s t i c i t y * = s i g n i f i c a n t at p =.05 n =64 observations 85 Removals of vintage trees are p o s i t i v e l y correlated to the p r o f i t expectations from the trees being removed. This does not support the a p r i o r i expectation that growers remove trees when t h e i r p r o f i t a b i l i t y declines. Removals are not driven by the p r o f i t expectations of new or t r a d i t i o n a l v a r i e t i e s . Across models, t h i s statement i s true for the new v a r i e t i e s c o e f f i c i e n t , but the t r a d i t i o n a l v a r i e t i e s c o e f f i c i e n t exhibits a s i g n i f i c a n t l y negative c o e f f i c i e n t e f f e c t . Depending on the model, there seems to be evidence that the p r i c e of t r a d i t i o n a l v a r i e t i e s does e f f e c t removals. Obviously, when there are more vintage trees i n a region there i s a lower degree of tree removal. Conversely, as there i s an increase i n younger trees there i s also an increase i n tree removal. These observations reinforce the notion that, h i s t o r i c a l l y , replanting has followed removals. As well, i t supports the notion that i n regions were there i s a higher percentage of younger trees, growers are more apt to replant. The ADRSA program had no e f f e c t on removals, however, the OVTFA program decreased the l e v e l of removal a c t i v i t y . Increasing the value of the replant grant increased the l e v e l of removals. 86 Removals do not follow a cold winter which could cause economic in j u r y . Incidently, Kelowna, Vernon and Creston, the three areas which h i s t o r i c a l l y experience colder winter temperatures, a l l have a higher dummy variable c o e f f i c i e n t than the other regions. It could be that the regional dummies p a r t i a l l y account for winter i n j u r y . Perhaps these regions i n general have a higher percent of trees that are injured by colder temperatures that occurred i n a period outside of the data set, which the Z vari a b l e could not account for. Over time, there was a increase i n removals of trees. Across models, t h i s time e f f e c t was d i f f e r e n t suggesting that the time variable i s not robust. 4.7 Empirical Values The r e s u l t s of the empirical model can form the basis for estimating the effects of government p o l i c i e s on replant and are described i n th i s section. 4.7.1 The Eff e c t s of FII and NTSP Appendix C i l l u s t r a t e s the nominal values of FII and NTSP over time. In r e a l terms (1991 d o l l a r s , using the CPI) the average payment to growers has been 3.42 cents per pound. This i s the increase i n p r o f i t expectations growers have expected for t h e i r 87 f r u i t . If t h i s increased the expected value of t r a d i t i o n a l v a r i e t i e s , the NPV for t r a d i t i o n a l v a r i e t i e s would have been $4765 higher over the 20 years from 1973 to 1992. Using the c o e f f i c i e n t of t r a d i t i o n a l v a r i e t i e s 7 from the removals equation, the acreage of retained vintage trees that would have been removed (and replanted) without FII or NTSP i n place would be: NPV * c o e f f i c i e n t * t o t a l acres tree f r u i t * 2 0 years 4765 * 4.3E-07 * 23415 *20 = 960 acres NB: This c a l c u l a t i o n underestimates the acres since i t i s a s t a t i c c a l c u l a t i o n . In r e a l i t y , as growers would have replanted more, the increased propensity to replant created by the decline i n vintage trees would have spurred additional removals and replanting. Therefore, the top loading subsidy programs le d to the retention of 960 acres of apples that would have been removed i f FII and NTSP were not implemented. The 1991 OVTFA survey t o t a l l e d 6527 acres of tree f r u i t s over the age of 20 years (Table 1.10). According to t h i s c a l c u l a t i o n approximately 15% of these vintage trees are i n place s o l e l y because of FII and NTSP. The additional costs of these programs from 1973 to 1992 7 The expected NPV of t r a d i t i o n a l v a r i e t i e s from the removals equation i s used i n the c a l c u l a t i o n . These would represent trees that may have been marginally p r o f i t a b l e and required a subsidy payment to keep them from being removed. The expected NPV of removals was not used since the trees being removed for that v a r i a b l e were s l a t e d f or removals regardless of subsidy programs i n place. 8 8 (assuming 20,000 lbs per acre) were: 960 * 20,000 * .0342 * 20 years = $13,132,800.00 Because these two top loading subsidy programs l e f t growers with marginal trees i n the ground, the cost to society to maintain these trees would have been approximately $13 m i l l i o n d o l l a r s . I t i s i n t e r e s t i n g to note that because the programs only brought growers up to the cost of production, that much of the $13 m i l l i o n may not have been expressed as a p r o f i t by the growers and was a dead weight loss to society. 89 5.0 Summary, Conclusions and Policy Implications This chapter summarizes the study and draws conclusions which are used to develop p o l i c y implications. 5.1 Summary and Conclusions The objective of thi s study i s to examine the mechanics of orchard renovation i n the Southern I n t e r i o r of B r i t i s h Columbia. A mathematical model of the supply response of growers was constructed, using plantings of new and t r a d i t i o n a l apple v a r i e t i e s , and removals of t r a d i t i o n a l v a r i e t i e s as dependent var i a b l e s . The structure and environment under which growers i n Southern BC operate are discussed and tested i n an empirical model. The analysis covers a l l eight regions over eight years, t e s t i n g the two plantings equations and one removals equation i n d i v i d u a l l y as Ordinary Least Squares (OLS). Orchardists i n Southern B r i t i s h Columbia are faced with managing a mixture of long term investments. On the one hand orchard renovation can provide increased revenue, but revenues are not experienced immediately and perceptions of r i s k hinder supply 90 responsiveness. When orchard renovation i s considered, the grower has two options to consider. New apple v a r i e t i e s draw considerable notice but growers do not appear to change planting behaviour given changes i n p r i c e s . Perhaps prices are already p r o f i t a b l e enough and increases i n prices do not r e s u l t i n already high l e v e l s of replanting. Conversely, a lowering i n prices (and expected p r o f i t s ) does not necessarily cause a decline i n acres planted. Perhaps the conservative long-term nature of farmers has taken possible declines i n prices into account. The grower takes these elements into consideration and selects the v a r i e t y that w i l l maximize p r o f i t s ; however, not a l l elements are weighted equally. For example the expected p r o f i t s of new v a r i e t i e s i s not used i n the decision process but the expected p r o f i t s of a vintage block i s . As well, growers i n d i f f e r e n t regions w i l l react d i f f e r e n t l y , as supported by region dummy vari a b l e v a r i a t i o n s . Replanting to new v a r i e t i e s i s more l i k e l y i f there i s l o c a l experience with the new c u l t i v a r . Thus regions where replanting has occurred i n the past w i l l see a higher l e v e l of replanting. This i s s i m i l a r to the findings of Zvi G r i l i c h e s , i n that growers are l i k e l y to adapt new technology more ra p i d l y i f they had previous experience with technology adoption i n the past. 91 Regional differences do e x i s t . Regions where growers are younger and better educated (eg Cawston) have seen higher l e v e l s of adoption to new v a r i e t i e s . Areas which contain more marginal growing areas (eg Vernon) have a lesser adoption to new v a r i e t i e s and a greater reliance on t r a d i t i o n a l v a r i e t i e s . Like the r e s u l t s from Zvi G r i l l i c h e s , i t i s unclear which s p e c i f i c elements of a region a f f e c t replanting decisions. Somehow farmer age and education, and the q u a l i t y of the farm land act as inputs. Separating these elements i s a topic f o r future work. It would seem more appropriate to work at a f i n e r l e v e l of data aggregation. Perhaps moving from the regional l e v e l to the producer l e v e l would generate better r e s u l t s 8 . Government programs (including grants) aimed at replanting on a whole can increase the l e v e l of replanting but d i r e c t i n g growers into planting to new v a r i e t i e s , while increasing the c r i t e r i a to q u a l i f y for grants appears to have been successful. However, given the short time period of t h i s study, i t may be too early to draw such concrete conclusions. 5.2 P o l i c y Implications FII and NTSP 8 I n i t i a l l y the author wished to work at the farm l e v e l of aggregation, but l i m i t a t i o n s i n data re s u l t e d i n working at the regional l e v e l . 92 These two programs have h i s t o r i c a l l y been a s i g n i f i c a n t part of the economics of tree f r u i t production i n the province. I t would be f a i r to say that they have increased p r o f i t expectations from older blocks which have resulted i n replanting to more t r a d i t i o n a l v a r i e t i e s and less to new v a r i e t i e s . Estimates from t h i s work show thi s to amount equals 960 acres, costing the government an additional $13 m i l l i o n . These programs also increased the p r o f i t expectations from plantings of t r a d i t i o n a l v a r i e t i e s . This has had two e f f e c t s . The f i r s t i s a reduction i n the l e v e l of replanting to new v a r i e t i e s . The second i s an increase i n the l e v e l of planting to t r a d i t i o n a l v a r i e t i e s by perhaps creating a comfort zone of p r o f i t . Over a period of time, these top loading subsidy programs may have blocked growers from f u l l y examining new v a r i e t i e s that were more hardy or from examining planting to new crops e n t i r e l y . I t may have "locked" growers into r e l y i n g on the top loading subsidy programs. I t becomes more c l e a r why some growers may f e e l that without FII and NTSP, t h e i r a l t e r n a t i v e s are l i m i t e d , and the removal of the ALR i s t h e i r only a l t e r n a t i v e . 5.3 Government Policy The information generated from th i s thesis i l l u s t r a t e s the 93 complex nature of a replanting decision. Past and present p r o v i n c i a l and federal governments have wished replanting to take place at a faster pace. Perhaps they have overlooked the complex long term decisions growers are faced with. The notion of FII and replant programs seem to maintain a c o n f l i c t i n g objective, yet these two programs operated concurrently from 1987 to 1992. 5.3.1 Ad Hoc Payments Perhaps more detrimental i s the e f f e c t of sp e c i a l ad hoc payments, whereby the p r o v i n c i a l government would quickly a i d the industry, when f i n a n c i a l conditions indicated that FII and NTSP payments were not enough. These ad hoc payments kept growers i n business who perhaps would have otherwise exited the industry. As well, such payments allowed growers to keep vintage blocks which should have been replanted. These payments slowed down the on the entry/exit behaviour of growers, thereby hindering the adaptation of new technology needed for orchardists to remain competitive. This not only affected replanting but brought pressures on the ALR. The federal and p r o v i n c i a l governments were not the only government bodies acting i n a c o n f l i c t i n g manner. Municipal governments, wishing to expand t h e i r urban tax base, saw 94 opportunity i n urging growers to challenge the r e s t r i c t i v e ALR. For c e r t a i n , t h i s changed growers' expectations of land values, p a r t i c u l a r l y i n areas on the fringe of urban development. Most recently, the success of a grower has been measured i n his/her a b i l i t y to remove land from the ALR, rather than an achievement rela t e d to the a g r i c u l t u r a l stewardship of the land. 5.3.2 Replant Subsidies The types of programs and l e v e l s of d i r e c t payment to growers have had varying effects on growers' replanting decisions. Increasing the amount of grants has encouraged the removals of vintage trees and has increased the l e v e l s of replanting to t r a d i t i o n a l v a r i e t i e s . However replant programs by themselves has either discouraged c e r t a i n types of replanting or have had no net e f f e c t on replanted acres. In either case, the q u a l i t y of the replant projects have improved, r e s u l t i n g i n better replant proj ects. 5.3.3 Regional Differences Individuals i n the industry and i n various l e v e l s of government f e e l that replant i s a key component to the long term economic s u s t a i n a b i l i t y of the apple industry. To support t h i s d i r e c t i o n , 95 governments have embraced replant programs. These programs have been broad based, and directed to the industry as a whole. However, the analysis i n th i s thesis supports a conclusion that uptake has been highly region s p e c i f i c . This i s i n part due to the endowments of climate and s o i l , and p a r t i a l l y due to the demographics of the farmers i n the region. Regardless of reason, both the l e v e l of replanting and the types of v a r i e t i e s being planted do vary by region. This could a f f e c t the future economic well-being of the regions. For example, growers i n the Cawston region (Similkameen Valley) are planting at a f a s t e r rate than other regions, and are planting more new v a r i e t i e s r e l a t i v e to other regions. In time, t h i s w i l l create a divergence i n the p r o f i t a b i l i t y of apple growing i n d i f f e r e n t regions, that was previously masked by the FII and NTSP subsidy programs. Consequently, i t may be d i f f i c u l t for government and grower associations ( l i k e the BCFGA) to develop p o l i c y for the "industry" as a whole, i f the divergence continues to be s i g n i f i c a n t . 96 Bibliography Akiyama T. and Trevedi P.K. Vintage Production Approach to Perennial Crop Supply: An Application to Tea i n Major Producing Countries. J. Econometrics 36(1987):133-161 A l l a n R.N. and Carman H.Y. A Model of New Zealand Apple Supply Response to Technological Change. Aust J. of Agr. Econ. A p r i l (1975):30-51 Alston J.M., Freebairn J.W. and Quilkey J .J. A model of Supply Response i n the Australian Orange Growing Industry. Aus t r a l i a n Journal of A g r i c u l t u r a l Economics. 24 (1980) :248-267 B a r i t e l l e J.L. and Price D.W. Supply Response and Marketing Strategies for Deciduous Crops. Am. J. Agr. Econ. 56 (2) (1974) : 245-253 French B.C. and Bressler R.G. The Lemon Cycle. Journal of Farm Economics. 44 (1962) : 1021-1036 French B.C., King G.A. and Nunami D.D. Planting and Removal Relationships for Perennial Crops: An a p p l i c a t i o n to C l i n g Peaches. Am. J. Agr. Econ. 67(1985): 215-223 97 French B.C. and Mathews J.L. A Supply Response Model for Perennial Crops. Am. J. Agr. Econ. 53(1971): 478-490 G r i l i c h e s Zvi, Hybrid Corn: An Exploration i n the Economics of Technical Change. Econometrica v o l . 25 no. 4 (1957)501-522 Hartley M.J., Nerlove M., and Peters K.R. J r , An analysis of Rubber Supply i n S r i Lanka. Am. J . Agr. Econ. 69 (1987) :755-761 Kalaitzandonakes N.G. and Shonkwiler J.S. A State-Space Approach to Perennial Crop Analysis. Am J. Agr. Econ. May(1992) 343 -352 Knapp K.C. and Konyar K. Perennial Crop Supply Response: A Kalman F i l t e r Approach. Am. J. Agr. Econ. Aug(1991):841-849 Jaramillo F. An Econometric Analysis of the Columbian Coffee Industry. PhD Thesis. (1989) University of C a l i f o r n i a Berkeley Stennes B.L. Apple Cost of Production at the Farm Level i n B r i t i s h Columbia and Washington State. BCMAFF. (1994). Wickens M.R. and Greenfield J.N. The Econometrics of A g r i c u l t u r a l Supply: An Application to the World Coffee Market. Rev Econ. 98 and S t a t i s t . 55 (1973) :433-40. 99 APPENDIX A 100 APPENDIX B Calc u l a t i o n of Net Present Values Price Expectations Annual regional p r i c e expectations for t r a d i t i o n a l and new apple v a r i e t i e s were calculated by l i s t i n g the farm gate prices received for each i n d i v i d u a l v a r i e t y i n each year. Prices were then made r e a l , using the CPI and then lagged for each variety, i d e n t i f y i n g the importance of p r i c i n g h i s t o r y i n forming p r i c e expectations i n any period. A d i s t r i b u t e d lag was generated which expressed a weighting that placed a stronger emphasis on the t-2 period, i d e n t i f y i n g that i t takes two periods f o r farmers to receive information of crop values. As well, periods t-1 and t-3 were addressed as having influence on replanting decisions. The following d i s t r i b u t e d lag was used: weight(price) = (1/2)i - (1/6)i 2 + (8/1000)i 3 where i=period weight(price) period When i = l 0.35 t-1 i=2 0.42 t-2 i=3 0.28 t-3 From t h i s , a weight was assigned to past years (ie t-1, t-2, t-3). The weight i s mul t i p l i e d by the pri c e i n that year. These 101 . are summed up for three years to from a p r i c e expectation for period t. For example, assume the h i s t o r i c a l r e a l prices for a p a r t i c u l a r v a r i e t y i n a ce r t a i n region i s as following: Year 87 88 89 90 Price 8 12 7 15 Weight .28 .42 .35 0 Period t-3 t-2 t-1 t The p r i c e expectation for 1990 would be: p e i 9 9 o = (8 * 0.28) + (12 * 0.42) + (7 * 0.35) + (15 * 0) = 9.73 For each region, the p r i c e expectations for each year and v a r i e t y are m u l t i p l i e d by the acres of that v a r i e t y planted i n that year. New v a r i e t i e s and t r a d i t i o n a l v a r i e t i e s are l i s t e d separately. The product of acres and p r i c e expectations are summed f o r the two classes of v a r i e t i e s and then divided by the t o t a l acres planted for that c l a s s . This then calculates an average p r i c e expectation for new and t r a d i t i o n a l v a r i e t i e s i n each region. I t i s anticipated that each region would then have a d i f f e r e n t expectation based on the h i s t o r i c a l p r i c i n g of each v a r i e t y and the proportion of acres planted to the d i f f e r e n t v a r i e t i e s . 102 For example: Variety Pe Acres Planted Mcintosh 0.12 2 Red Delicious 0.08 3 Spartan 0.14 8 Golden Delicious 0.10 1 T o t a l : 14 The Pe for t r a d i t i o n a l v a r i e t i e s for would be (1.70 / 14) = 0.12 or 12 cents Acres * Pe 0.24 0.24 1.12 0.10 1.70 t h i s period and region per pound. 103 Net Present Values The p r i c e expectations were then fed into a model which calculated the net present value of planting an acre. Establishment and operating costs, and incremental increases i n y i e l d were assumed. Plantings of t r a d i t i o n a l v a r i e t i e s were calculated assuming a plantation density of 400 trees per acre and new v a r i e t i e s based on 600 trees per acre. In the case of removals, there are no establishment costs so an operating cost of $2900.00 per acre i s used. This i s based on the M i n i s t r y of Agriculture cost of production study, Apple Cost of Production at the Farm Level i n B r i t i s h Columbia and Washington State (Stennes 1994). 104 APPENDIX C B.C. Apple Returns (nominal cents/pound) Including Support Payments (Farm Gate 1973-1992 cee grade and better) Year Market Return NTSP or FIA FII Total Returns 1973 5.86 1.28 7 .14 1974 6.60 0.67 7 .27 1975 2.93 1.18 2 .40 6.55 1976 4.97 2 .14 7 .11 1977 9.10 0.26 9.36 1978 9.82 0.14 9.96 1979 10.58 -0.65 9.93 1980 5.54 1.77 3.62 10.93 1981 8.18 2.31 10.48 1982 5.46 2 .10 3 .31 10.87 1983 6.76 0.50 2.25 9.50 1984 5.59 0.75 2 .87 9.21 1985 13 .77 2.48 16.25 1986 16.20 0.11 16.31 1987 7.64 1.61 2.00 13.00 1988 12 .15 1.72 13 .87 1989 7.72 1.52 2.69 15.93 1990 13 .23 1.81 15.04 1991 16.67 16.67 1992 14.73 0 .25 0.2 15.18 Source: BCFGA Note: 1987 t o t a l contains 1.75 c/lb sp e c i a l payment for Red Delicious 1989 t o t a l contains 4.00 c/lb special payment 105 APPENDIX D Selected Cross-Tabulation of Demographics for the Salmon Arm and Vernon Region Age Education Years 0 1-3 4-7 8-10 11-12 Trade C o l l N/R TOTAL 0-25 0 0 0 0 0 0 1 0 1 26-35 0 0 0 2 1 0 3 0 6 36-45 0 0 0 1 8 3 11 0 23 46-55 0 0 0 4 8 2 11 0 25 56-65 0 0 0 8 10 3 5 1 27 66 + 0 0 3 3 2 0 5 3 16 N/R 0 0 0 0 0 0 0 4 4 TOTAL 0 0 3 18 29 8 36 8 102 Selected Cross Tabulation of Demographics for the Kelowna Area Age Education Years 0 1-3 4-7 8-10 11-12 Trade C o l l N/R TOTAL 0-25 0 0 0 0 1 1 0 0 2 26-35 0 0 0 7 31 10 19 2 69 36-45 0 0 1 8 56 17 46 2 130 46-55 0 0 2 20 57 15 33 7 134 56-65 0 1 15 44 59 9 27 9 164 66 + 1 1 3 20 26 2 11 7 71 N/R 0 0 0 0 1 0 1 23 25 TOTAL 1 2 21 99 231 54 137 50 595 106 Selected Cross Tabulation of Demographics for the Penticton and Summerland Region Age Education Years 0 1-3 4-7 8-10 11-12 Trade C o l l N/R TOTAL 0-25 0 0 0 0 0 0 0 1 1 26-35 0 0 0 3 13 5 7 1 29 36-45 0 0 4 11 26 9 29 3 82 46-55 0 0 7 18 18 10 29 3 85 56-65 0 3 6 18 29 7 17 4 84 66 + 0 1 2 13 14 4 11 0 45 N/R 0 0 0 0 2 0 0 15 17 TOTAL 0 4 19 63 102 35 93 27 343 Selected Cross Tabulation of Demographics for the Oliver-Osoyobs Region Age Education Years 0 1-3 4-7 8-10 11-12 Trade C o l l N/R TOTAL 0-25 0 0 0 1 1 0 0 0 2 26-35 1 0 6 20 30 8 5 0 70 36-45 1 0 20 16 47 15 29 2 130 46-55 0 5 30 14 25 5 15 11 105 56-65 4 4 27 19 24 2 14 17 111 66 + 2 0 6 11 19 1 4 11 54 N/R 0 0 0 0 0 0 0 7 7 TOTAL 8 9 89 81 146 31 67 48 479 107 Selected Cross Tabulation of Demographics for the Cawston-Keromeos Region Age Education Years 0 1-3 4-7 8-10 11-12 Trade C o l l N/R TOTAL 0-25 0 0 0 1 0 0 0 0 1 26-35 0 0 0 5 13 2 1 1 22 36-45 0 0 1 5 14 16 13 1 50 46-55 0 0 1 4 7 1 7 1 21 56-65 0 0 8 7 4 2 5 4 30 66 + 0 0 0 6 4 0 3 4 17 N/R 0 0 0 0 1 0 0 4 5 TOTAL 0 0 10 28 43 21 29 15 146 Selected Cross Tabulation of Demographics for the Creston Region Age Education Years 0 1-3 4-7 8-10 11-12 Trade C o l l N/R TOTAL 0-25 0 0 0 0 0 0 0 0 0 26-35 0 0 0 1 4 2 3 0 10 36-45 0 0 0 0 3 1 2 0 6 46-55 0 0 0 1 3 3 5 0 12 56-65 0 0 1 2 3 4 7 0 17 66 + 0 0 0 0 4 3 2 1 10 N/R 0 0 0 0 1 0 0 0 1 TOTAL 0 0 1 4 18 13 19 1 56 108 APPENDIX E C l a s s i f i c a t i o n of new and t r a d i t i o n a l v a r i e t i e s used i n thi s study: New Tr a d i t i o n a l Akane Breaburn C r i t e r i a n Discovery E a r l i g o l d Empire E l s t a r F i e s t a Fuj i Gala Granny Smith Idared Jonagold Mutsu Sunrise Idared Sinta Sumac Shamrock Gravenstien Red Delicious Golden Delicious Lodi (or Yellow Transparent) Mcintosh Newtown Red Rome Tydeman's Red Spartan Wealthy Winter Banana Winesap 109 Appendix F Summary of Data The data used i n th i s thesis has been aggregated to the regional l e v e l . The table below i s a summary of the variab l e s . Variable Tree Vintage Acres Planted Prices OVTFA and ARDSA Weather (Z) Grants Level Regional Regional Regional Regional Regional Regional Observations 1991 survey Annual 85-92 Annual 80-92 Annual 85-92 Annual 80-91 Annual 85-92 Source OVTFA OVTFA, BCMAFF Industry BCMAFF, OVTFA BC Min Environ. BCMAFF, OVTFA NB. Data i s available for 8 regions The q u a l i t y of the OVTFA data i s exceptionally high. Farm l e v e l data was c o l l e c t e d as part of a comprehensive survey. Farmer demographics were col l e c t e d . As well, information on a tree by tree basis were logged into a geographical information system (GIS) and information on land use were calculated from there. Tree Vintage: Tree vintage i s the acres of trees older than 2 0 years of age. These trees are past t h e i r maximum p r o f i t a b i l i t y and growers w i l l take a view to remove trees of th i s age. Information i s taken from the 1991 OVTFA orchard survey. The survey acts as a bench mark which i s adjusted annually from removals that occurred i n each region. Figures are presented as the percent of vintage trees as r e l a t i v e to the t o t a l acreage of a l l f r u i t trees i n the region. 110 Plantings: Plantings are acres of apples planted r e l a t i v e to the t o t a l apple acreage f o r the region. These figures are reported to government with removal information. This information i s a v a i l a b l e at the farm l e v e l but has been aggregated into a regional form f o r estimation i n t h i s model. Pri c e s : The p r i c e s are the r e a l farm gate prices of apples. Subsidy-payments are included i n the p r i c e . Farm gate prices by grower and v a r i e t y are kept on f i l e at BC Tree F r u i t s from 1986 to 1991. P r i o r to that, prices were kept on a p r o v i n c i a l l e v e l . To adjust for the lack of regional data during those years 1982 to 1985, a small regression, using 1986 to 1991 prices was used to estimate p r i c e differences between regions. These prices were then used to c a l c u l a t e a p r i c e of new or t r a d i t i o n a l v a r i e t i e s i n each region. The composition of v a r i e t i e s that made up new or t r a d i t i o n a l v a r i e t i e s varied by year and region depending on the mix of v a r i e t i e s planted and removed. Each v a r i e t y received a weight depending on the acreage of that v a r i e t y planted or removed. Prices of Red Delicious strains were used separately depending on whether the p r i c e of Red Delicious was required i n the removals 111 or planting equation. New s t r a i n information was used i n the planting equation and old s t r a i n information was used i n the removals equation. Planting Subsidy: These two dummy variables account for replant subsidy programs offered to growers during the periods 1986 to 1990 under the ARDSA program, and 1991 to 1992 under the OVTFA program. A zero value was used for years representing no s p e c i f i c replant programs. Subsidies were provided i n a grant form and have increased i n value through time. The programs offered grants f o r replanting, but e l i g i b i l i t y c r i t e r i a varied between the two programs. Dollar amounts of the grants varied as w e l l . These d o l l a r amounts were either included i n the NPV of the new or t r a d i t i o n a l varies variables, or were included separated under a Grants variable, depending upon the model. This data i s sourced from the B r i t i s h Columbia Ministry of Agriculture, Fisheries and Food and from the Okanagan Vall e y Tree F r u i t Authority. Weather: 112 A dummy variable was constructed to account for temperatures which caused winter injury to f r u i t trees. If the minimum winter temperatures during October or November reached -25 Celsius and i f temperatures i n February or March received temperature of -25 Celsius and then i n 24 hours exceeded 15 Celsius, economic winter i n j u r y occurred. This variable i s a dummy var i a b l e and was recorded as yes (1) or no (0) that such damaging weather conditions occurred. Grants This variable accounts for the value of grants offered i n any year. Grants increased from zero i n 1985 to $3500 i n 1992. 113 

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