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Farmer response to lift. Winchell, Robert Leslie 1972

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FARMER RESPONSE TO LIFT by Robert Leslie Winchell B.Sc., University of Alberta, 1966, A THESIS SUBMITTED IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE in the Department of Agricultural Economics We accept this thesis as conforming to the required standard THE UNIVERSITY OF BRITISH COLUMBIA March, 1972 In presenting t h i s thesis i n p a r t i a l f u l f i l m e n t of the requirements for an advanced degree at the University of B r i t i s h Columbia, I agree that the Library s h a l l make i t f r e e l y available for reference and study. I further agree that permission fo r extensive copying of t h i s thesis for scholarly purposes may be granted by the Head of my Department or by his representatives. It i s understood that copying or publication of t h i s thesis for f i n a n c i a l gain s h a l l not be allowed without my written permission. Department of Agricultural Economics The University of B r i t i s h Columbia Vancouver 8 , Canada Date April 26, 1972 - i -ABSTRACT The LIFT Program was introduced by the Canadian Wheat Board and the Federal Cabinet in March of 1970. The program was designed to reduce the number of acres seeded to wheat in the spring of 1970 and thereby reduce the size of wheat stocks in Canada. The objectives of this study of the LIFT Program were; 1. to determine which factors were important in predicting the extent of participation by individual farmers in the LIFT Program; 2. to determine how effective the LIFT Program was in reducing wheat acreage. Data for the study was collected by means of interviewing a random sample of farm operators in the grain growing areas of Alberta and Saskatchewan. Multiple linear regression was used to determine the factors xvhich were most important in predicting the extent of participation in the LIFT Program. The importance of qualitative variables was analysed by chi-square and analysis of variance techniques. The following eight variables were found to be important in predicting the extent of participation in the LIFT Program. 1. number of bushels of wheat on hand per cultivated acre 2. age of operator 3. knowledge of the LIFT Program 4, acres of wheat in 1969 5. grade completed in school by operator's wife 6. "attitude towards change" score 7. attitude towards the LIFT Program, and 8. percentage of summer fallow in the normal crop rotation. These eight variables explained 61.94% of the variation in the extent of participation in the LIFT Program. - i i -It was concluded that knowledge of the LIFT Program, attitude towards the LIFT Program, dissemination of information about the program by group methods and by government sources a l l had an important influence on the extent of participation. It was further concluded that the LIFT Program either directly or indirectly influenced about two thirds of the wheat acreage reduction that occurred in 1970. i i i -TABLE OF CONTENTS Chapter Page I INTRODUCTION 1 A. The LIFT Program 1 B. I m p l i c a t i o n s of the Study 3 C. Objectives of the Study 4 D. C o l l e c t i o n of the Data 4 I I PREDICTION OF PARTICIPATION IN THE LIFT PROGRAM . 5 A. A Decision-Making Model f o r P a r t i c i p a t i o n i n the LIFT Program 5 B. The Dependent V a r i a b l e 10 C. The Net Cash Income Maximizing Model 14 D. E m p i r i c a l R e s u l t s f o r the Net Cash Income Maximizing Model 17 E. An Extension of the Net Cash Income Maximizing Model 21 F. E m p i r i c a l R esults f o r the Extension of the Net Cash Income Maximizing Model 24 I I I ANALYSIS OF THE SOURCES OF INFORMATION 28 A. T h e o r e t i c a l O r i e n t a t i o n 28 B. A n a l y s i s of Information Sources 32 C. Information Sources and Extent of P a r t i c i p a t i o n 36 IV AN EVALUATION OF THE EFFECTIVENESS OF THE LIFT PROGRAM 49 A. Reasons f o r Reducing Wheat Acreage and Amount of Wheat Acreage Reduction . . . . 50 - i v -Chapter Page V SUMMARY AND CONCLUSIONS 56 A. Summary 56 B. Conclusions 59 BIBLIOGRAPHY 61 APPENDIX A. Representativeness of the Sample 64 B. D e s c r i p t i v e A n a l y s i s of V a r i a b l e s Studied . . . 67 C. Means and 9-5% Confidence I n t e r v a l s of V a r i a b l e s Studied 117 D. Chi-Square Values f o r the R e l a t i o n s h i p Between Information Sources Used and Selec t e d V a r i a b l e s 122 E. C o r r e l a t i o n M a t r i x 125 F. M u l t i p l e Regression A n a l y s i s of 60 Q u a n t i t a t i v e and 14 Q u a l i t a t i v e V a r i a b l e s . . 134 G. Stepwise Regression A n a l y s i s of the 16 V a r i a b l e s Included i n Both the Net Cash Income Maximizing Model and the Extension of the Net Cash Income Maximizing Model; Data i n Log Form 138 H. B u l l e t i n s Issued on the LIFT Program . . . . . 140 I . Interview Schedule 151 -V-LIST OF TABLES Table Page 1. An Example of the Calculation of Acres of Participation -. 10 2. An Example of Maximum Participation 11 3. Empirical Analysis of the Net Cash Income Maximizing Model 18 4. Empirical Analysis of the Extension of the Net Cash Income Maximizing Model 25 5. * Classification of the Sources of Information About the LIFT Program 31 6. Use of the Various Sources of Information About the LIFT Program 32 7. Sources of Information About the LIFT Program Classified by Method 33 8. Sources of Information About the LIFT Program Classified by Origin 33 9. Sources of Information About the LIFT Program Classified by the Nature of the Contact . . . . 34 10. Combination of Information Sources Used by Nature of the Contact 34 11. Combination of Information Sources Used as Classified by Method of the Contact .35 12. Combination of Information Sources Classified by Cosmopoliteness 36 13. Acres of Participation and Sources of Information Classified by Method of Dissemination 36 14. Acres of Participation and Sources of Information Classified by Origin of the Information 37 - v i -Table Page 15. Acres of P a r t i c i p a t i o n and Sources of Information C l a s s i f i e d by Nature of the Contact 38 16. Combination of Information Sources Used by Nature of the Contact and Acres of P a r t i c i p a t i o n 38 17. Combination of Information Sources Used C l a s s i f i e d by Cosmopoliteness and Acres of P a r t i c i p a t i o n 39 18. Combination of Information Sources Used as C l a s s i f i e d by the Method of Contact 40 19. Percentage of Summer Fal l o w and Information Sources C l a s s i f i e d by Method 41 20. Percentage of Summer Fallow and Information Sources C l a s s i f i e d by Nature of the Contact . 41 21. Knowledge of the LIFT Program and Information Sources C l a s s i f i e d by Method 42 22. Value of Wheat Sold and Information Sources C l a s s i f i e d by Method 43 23. Feed G r a i n to be Fed or Sold and Information Sources C l a s s i f i e d by Method of Dissemination 43 24. Province W i t h i n the Brown S o i l Zone and Information Sources C l a s s i f i e d by Method of Dissemination 44 25. Plans to Make Changes and Information Sources C l a s s i f i e d by Method of Dissemination . . . . 44 26. Reasons f o r I n c r e a s i n g Summer Fallow Acreage and Information Sources C l a s s i f i e d by O r i g i n . . . 45 27. Information Sources C l a s s i f i e d by Method of Dissemination and Acres of P a r t i c i p a t i o n ; Corrected f o r D i f f e r e n c e s i n Wheat Stocks Per Acre 47 28. Information Sources C l a s s i f i e d by O r i g i n and Acres of P a r t i c i p a t i o n ; Corrected For D i f f e r e n c e s i n Wheat Stocks 48 - v i i -Table Page 29. Reasons for Reducing Wheat Acreage Compared with Reduction in Wheat Acreage and Acres of _ Participation 51 30. Reasons for Reducing Wheat Acreage Compared with Mean Reduction in Wheat Acreage and Mean Acres of Participation 52 31. Test of Difference Between Mean Values of Acres of Participation as Categorized by Reasons for Reducing Wheat Acreage 52 32. Test of Difference Between Mean Value of Acres of Reduction as Categorized by Reasons for Reducing Wheat Acreage 53 33. Reasons for Reducing Wheat Acreage Compared to the Extent of Reduction in Wheat Acreage . 54 34. Reasons for Reducing Wheat Acreage Compared to the Extent of Participation 54 - v i i i -LIST OF FIGURE Figure Pake 1. The Survey Area 4a CHAPTER I INTRODUCTION A. The LIFT Program The LIFT Program (Lower Inventories For Tomorrow) was announced in March of 1970 by the Hon. 0. E. Lang, Minister in charge of the Canadian Wheat Board. The conditions which led up to the i n i t i a t i o n of this program were a reduction in export wheat sales during the past and a build up of wheat stocks in the terminal elevators, the country elevators and on farms. Government o f f i c i a l s had estimated that the stockpile of wheat would be almost one b i l l i o n bushels at the end of the 1969-70 crop year (July 31, 1970)-. A stockpile of wheat of this size was deemed to be undesirable due to the costs of storage and the stockpile put the Canadian Wheat Board in a poor bargaining position in international markets. The aim of the LIFT Program was to reduce the amount of wheat in storage by half through the reduction of wheat acreage and at the same time to discourage the shift of wheat land into other crops. It was also intended that the LIFT Program would provide financial help for cash short prairie farmers who had experienced very low market quotas for wheat in the past. These goals were to be achieved by a set of regulations (the LIFT Program) involving the allocation of wheat quota for the 1970-71 crop year and a program of incentive payments. 1 See appendix -2-The LIFT Program promised a market quota of eight bushels of wheat per el i g i b l e acre. Eligible acres were defined as; 1970 summer fallow acreage plus 25% of 1969 summer fallow acreage plus increase in perennial forage crops from 1969 to 1970 plus the acreage in non-cereals, non-oilseeds (Buck wheat, Peas) in 1970. Quotas for other grains (barley, oats, rapeseed) were to be allocated on the basis of "X" bushels per acre seeded to each crop. No announcement or indication of the size of the quota for oats and barley was given at seeding time in the spring of 1970. This new market quota allocation scheme represented a marked change from the manner in which quotas had been allocated in the past. In previous years the quota for a l l grains was based on "X" bushels for the total number of cultivated acres in the farm plus an i n i t i a l unit quota equivalent to 400 bushels of wheat. The quota was allocated gradually as the crop year progressed and sales of grains were made by the Wheat Board. The farmer could deliver the grain of his choice on this quota but supplementary quotas for specific kinds and grades of grains were issued periodically to reflect market demand. The essence of the new quota scheme was that wheat quotas would be based on summer fallow acreage rather than total cultivated acreage in the farm. The LIFT Program provided a payment of $6.00 per acre for a reduction in wheat acreage that was matched by an increase in summer fallow acreage. A payment of $10.00 per acre was provided for a reduction in wheat acreage that was matched by an increase in perennial forage crop acreage. Given these rules and regulations of the LIFT Program, i t was up to the individual farmer to decide for his own situation i f he would -3-participate in the LIFT Program and i f so, to what extent. It was expected that variation would occur in the extent of participation from one farmer to another depending upon how each farmer assessed his own situation and depending upon how various non-economic or social factors influenced his decision. B. Implications of the Study The study of how farmers responded to the LIFT Program provided an opportunity to assess the variation in participation among prairie wheat producers and to observe how much of this variation was due to economic factors and how much was due to socio-logical factors. In developing programs involving change, technological or non-technological, the planner must be aware of the importance of both economic and social factors that influence the acceptance or rejection of change. In this instance the study of the LIFT Program is a study of adoption of different production patterns due to a marketing change. It was f e l t that the study of farmer response to the LIFT Program could make a valuable contribution to the study of adoption. The study also offered an opportunity to assess the influence of three specific factors which are important to a l l programs involving change; attitude toward the program, sources of information about the program, and amount of knowledge about the program. These three factors were referred to as "policy variables" in the study. It was also f e l t that the study would provide information that would be useful in evaluating the success of the LIFT Program in terms of the stated goals of the program or, in other words, to find out what the effect of the LIFT Program had on the reduction of wheat acreage in 1970. -4-C. Objectives of the Study The objectives of this study were stated as follows: 1. To determine which factors were important for predicting the extent of participation in the LIFT Program. 2. To determine how effective the LIFT Program was in reducing wheat acreage. D. Collection of the Data The collection of the data for this study was by means of personal interviews with a sample of farmers. An interview schedule was constructed for this purpose (see appendix). The sample was a str a t i f i e d random sample which included farmers in each of three s o i l zones; Dark Brown, Thin Black and Black Soil zone. The Dark Brown s o i l zone included respondents in the Provinces of Alberta and Saskatchewan, (see Figure 1) A complete up to date l i s t of names of farm operators was not available so the area method of sampling was used. Townships from within the outlined area were selected at random by use of a table of random numbers. A l l farmers residing within each selected township were then interviewed. A working rule was followed that i f a farm operator could not be interviewed after two attempts to contact him, he was not interviewed. A l l contacts were made by directly v i s i t i n g the farmstead without prior notification by telephone or mail. The interview schedules were coded and the data was put onto cards for processing at the U.B.C. computing center. The two programs used to analyse the data were U.B.C. TRIP for correlation, regression, means and standard deviations. The MVTAB program was used for frequency distributions and Chi-square analysis. s - 4 a -F i g u r e I THE SURVEY AREA - boundary of the survey -5-CHAPTER II PREDICTION OF PARTICIPATION IN THE LIFT PROGRAM A. A Decision-Making Model for Participation in the LIFT Program In order that the important factors explaining the extent of participation in the LIFT Program could be identified i t was necessary to formulate a model of farmer decision-making in relation to p a r t i c i -pation. This model was built from a series of hypotheses about the relationship of selected variables and the extent of participation and was then subjected to empirical analysis using multiple regression techniques. The model encompasses theory drawn from the literature on Decision-Making, Adoption, and Economics. Eisgruber and Neilson state that the elements of a decision-2 making model are "...a set of courses of action, a set of states of nature, consequences associated with actions and states of nature, and a choice criterion." Based on these elements the following generalized statement of the decision model for participation in the LIFT Program can be expressed; Extent of participation in the LIFT Program depends jointly upon; 1. a decision criterion, 2. economic factors, 3. sociological factors, 4. knowledge. Economic factors, sociological factors, and knowledge are specific categories of "states of nature". Extent of participation represents "a set of courses of action". 2 Eisgruber, Ludwig and James Neilson, "Decision-Making Models in Farm Management.", Canadian Journal of Agricultural Economics• Vol. 11, No. 1, pp. 60-70 The d e c i s i o n c r i t e r i o n provides a method f o r judging the d e s i r a b i l i t y of the va r i o u s outcomes. A commonly used c r i t e r i o n f o r dec i s i o n s i n economics i s a maximizing c r i t e r i o n where the p o s s i b l e outcomes, v a r i o u s l e v e l s of net income, f o r example, are compared and the a c t i o n r e s u l t i n g i n the l a r g e s t net income i s taken. The d e c i s i o n c r i t e r i o n s e l e c t e d f o r t h i s model was a maximizing c r i t e r i o n where the outcome to be maximized was net cash income over a two year p e r i o d . Although i t may be argued t h a t farmers i n , f a c t do not achieve maximi-z a t i o n of p r o f i t s i t was assumed by the w r i t e r that they act i n d e c i s i o n -making s i t u a t i o n s as i f they were attempting to maximize p r o f i t s . F a i l u r e t o achieve maximum p r o f i t s can u s u a l l y be explained by a l a c k of knowledge of such r e l e v a n t s t a t e s of nature as p r i c e s and q u a n t i t y marketable, technology and weather. Maximization of net cash income was t h e r e f o r e s e l e c t e d as the choice c r i t e r i o n f o r t h i s d e c i s i o n -making model. Net income i s described i n the f o l l o w i n g equation. Net Income a Bushels of wheat s o l d X P r i c e of wheat + Bushels of other grains s o l d X p r i c e of other g r a i n -Acres of g r a i n seeded X Cost per acre - Acres of summer f a l l o w X Cost per acre f o r summer f a l l o w + LIFT payments where bushels of wheat s o l d equals quota per e l i g i b l e acre X number of e l i g i b l e acres (an 8 bushel quota was promised) and l i m i t e d by the amount of wheat i n storage plus the amount produced during the 1970 growing season. -7-A two year time period was chosen because i t can be demon-strated that the decision-making time horizon of the wheat producers encompasses a period of at least sixteen months from the time that plans for seeding the crop are made un t i l the end of the crop marketing year in which the production of that crop is sold. In recent years when markets have been such that the production of one year is frequently not a l l disposed of in the current crop marketing year the time horizon for planning of the production of wheat must often extend into a second crop year. Thus a period of 28 months is frequently involved. In this context an approximate time period of two years was selected as being the relevant planning period over which i t was assumed the wheat producers attempt to maximize net cash income. Net cash income was selected as the relevant outcome since the period of two years could be considered as a short-run period particularly since there was essentially no market for fixed assets such as farm land. In the short-run situation the relevant measure of net income is gross income minus variable costs. Farmers were short of cash with which to meet commitments such as land taxes and mortgage payments. In this situation i t can be argued that cash income rather than income in the form of increased inventories is the most r e a l i s t i c outcome to be considered. The basis of the decision-making model of participation in the LIFT Program can be summarized as follows: assume that the farmers w i l l attempt to select that level of participation which w i l l maximize their expected net cash income over the next two years. -8-The "economic factors" make up one dimension of the decision-making environment. They are those factors which are related to the decision-making criterion in a manner which can be described by economic theory. For example such factors as the price of wheat, the quota for wheat, the stock of wheat in storage on the farm, etc. are economic factors. The "sociological factors" are another dimension of the decision-making environment. They are those factors which are related to the decision-making criterion in a manner which can be described by the theories of the social sciences. Examples of such factors include the age of the farm operator, the educational level achieved by the operator, the social participation score of the operator, etc. "Knowledge" is the state of nature as perceived by the decision maker. In the decision-making model for "extent of parti-cipation" 'knowledge" was specified as a separate part of the model because one specific variable, knowledge of the LIFT Program, was to be studied. An essential characteristic of the proposed model of decision-making is the implied multiple causation between the four independent elements and the outcome. The model lends i t s e l f to analysis by techniques of multiple regression. It is important at this point to establish a relationship between the measure, "extent of participation" and the measure, "innovativeness". Adoption studies have focused on the adoption of technological innovations. Participation in the LIFT Program is not -9-a technological innovation but i t can be interpreted as a managerial innovation. It has been established that participation in the LIFT Program involves the decision-making process. Rogers states that 3"The adoption process is one type of decision-making". Rate of adoption is the length of time required to adopt an innovation 4. Innovativeness is the degree to which an individual is earlier to adopt new innovations or ideas than are other members of the society-*. Extent of participation in the LIFT Program is measured in acres and has no reference to the element of time as do the above two measures. It can be argued however that two similarities do exist between adoption and extent of participation. Rogers states that ^"the relative advantage of a new idea, as perceived by other members of the social system, affects i t s rate of adoption". It has been asserted by the model of participation that the relative advantage, net cash income, w i l l affect the extent of participation. Rogers also states that ^"the compatability of a new idea, as perceived by members of a social system affects i t s rate of adoption." It can be hypothesized and tested that the extent of participation is affected by the attitude of the farmer towards the LIFT Program. On these grounds i t can be asserted that innovativeness and extent of participation are similar in nature. If this similarity can be accepted the significant independent variables and the amount of variation in extent of participation explained by these variables can be compared to the results obtained in other adoption Q studies. 3 Rogers, Evertt M., Diffusion of Innovations, New York, The Free Press, 1962, p. 77 4 Ibid, p. 134 5 Ibid, p. 289 ^ Rogers, Diffusion of Innovations, p. 126 7 Ibid, p. 127 8 Ibid, pp. 288 - 289 -10-B. The Dependent Variable The dependent variable in the model of participation is defined as Acres of Participation. Acres of Participation is the number of acres of reduction in wheat acreage matched by an increase in summer fallow and/or forage crop acreage and/or the number of acres seeded to non-cereals., non-oilseed crops (buckwheat, peas, etc.) in 1970. Table 1 (i) An Example of the Calculation of Acres of Participation C r ° P Wheat Summer Fallow Forage Crops Cereals other than Wheat Oilseeds Non-cereals/Non-oilseeds Acres 1970 300 450 0 50 0 0 800 Acres 1969 400 400 0 0 0 Q 800 • 100 acres • 50 acres s 0 acres a 0 acres decrease in wheat acreage increase in summer fallow acreage increase in forage crop acreage acreage of non-oilseeds/non-cereals decrease in wheat acreage that is matched by an increase in summer fallow + increase in forage crops + acreage of non-oilseeds/non-cereals • 50 acres Acres of Participation • 50 acres Crop -11-Table 2 ( i i ) An Example of Maximum Participation Acres 1970 Wheat Summer Fallow Forage crops Cereals other than wheat Oilseeds Non-cereals/non-oilseeds 0 800 0 0 0 0 800 Acres 1969 400 400 0 0 0 0 800 - 400 acres • 400 acres s 0 acres s 0 acres decrease in wheat acreage increase in summer fallow acreage increase in forage crop acreage acreage of non-oilseeds/non-cereals decrease in wheat acreage that is matched by an increase in summer fallow plus increase in forage crops plus acreage of non-oilseeds/non-cereals s 400 acres Acres of participation a 400 acres ( i i i ) An Example of Economically Optimum Participation The economically optimum level of participation is that level of participation at which the farm operator w i l l realize the largest net cash return within the two year time period being considered in the model. The following set of assumptions and simplified budgets w i l l i l l u s t r a t e three alternative cropping programs and also indicate the program that w i l l yield the greatest net cash return. -12-Assumptions; The farmer's expectation of prices is as follows: (a) wheat $1.00/bu. for Can. Wht. Brd. deliveries (b) wheat $ ,75/bu. for non-wheat board sales (c) barley $ ,50/bu. a l l sales (d) wheat quota 8 bu./eligible acres (e) wheat sales over quota 1000 bu. ( f ) cost of producing wheat $10.00/acre cash costs (g) cost of producing barley $10.00/acre cash costs (h) cost of summer fallowing $4.00/acre cash costs Also assume that crops other than wheat or barley have been ruled out by the farmer due to his own s o i l and climatic conditions and lack of experience in growing any other crops, (i) stock of wheat on hand 10,000 bu. (j) expected yield of wheat 25 bu./acre (k) expected yield of barley 35 bu./acre (1) barley market expected 5000 bu. max. Alternative 1 Maximum Participation Expected Total 1970 cropping pattern Acres Return  Wheat Summer fallow Other crops 0 800 0 $ 7950 $ 2400 0 Expected Expected Cost Net returns 0 $ 7950 $ 3200 -$ 800 0 0 Total 800 $10,350 $ 3200 $ 7150 -13-Altentative 2 No Participation and No Change in Wheat Acreage Expected Total Expected Expected 1970 cropping pattern Acres Return Cost Net returns Wheat 400 $ 4750 $ 4000 $ 750 Summer fallow 400 0 $ 1600 $-1600 Total 800 $ 4750 $ 5600 $- 850 Alternative 3 Participation and Partial Diversion to Barley Expected Total Expected Expected 1970 cropping pattern Acres Return Cost Net returns Wheat 0 $ 6830 0 $ 6830 Summer fallow 660 $ 1560 $ 2640 $-1080 Barley 140 $ 2450 $ 1400 $ 1050 Total 800 $10,840 $ 4040 $ 6800 The above three budgets il l u s t r a t e the type of decisions to be made by the farm operator i f he i s to achieve an economically optimum level of participation. In this example Alternative No. 1 yielded the maximum net cash return. It was found that farm operators interviewed were generally unable to express quantitatively their expectations relating to price, quota, yield and costs. Thus i t was not possible to use budgeting or linear programming methods to determine the economically optimum level of participation for each respondent. To achieve the objectives of this study the basic decision-making model for participation in the LIFT Program was divided into two parts. The f i r s t part was referred to as the "Net Cash Income Maximizing Model". Sociological factors were not considered in this model. In the -14-second formulation of the model sociological factors were taken into consideration. This model was referred to as "An Extension of the Net Cash Income Maximizing Model". Independent variables were selected for each sub-model on the basis of specific hypothesis relating these selected variables to the dependent variable. C. The Net Cash Income Maximizing Model The general form of the Net Cash Income Maximizing Model i s : Acres of Participation depends on: 1. a decision c r i t e r i a 2. economic factors 3. knowledge of the LIFT Program The Net Cash Income Maximizing Model stated in terms of specific selected variables i s : Acres of Participation w i l l be positively affected by: 1. acres of wheat in 1969 2. bushels of wheat on hand 3. average wheat yield 4. knowledge of the LIFT Program And negatively affected by: 1. amount of available storage space 2. amount of grain to be disposed of as feed and/or non-Board feed grain 3. percentage of summer fallow in the normal crop rotation 4. amount of variation with respect to wheat yields -15-Th e hypothesized relationships between each of the selected variables and Acres of Participation are described below. 1. Acres of wheat in 1969: Due to the definition of Acres of P a r t i c i -pation (see page 10) acres of wheat in 1969 imposed a limit on the size of the dependent variable. That is i t was not possible to have Acres of Participation in excess of the 1969 wheat acreage. It was also reasoned that those farmers with large acreages in wheat in 1969 would, other things being equal, also have a large number of improved acres and would have larger commitments in terms of land taxes, payments for machinery as well as face large cash outlays for variable inputs such as fuel, seed, f e r t i l i z e r , herbicides, etc. In this situation the farmer could be expected to reduce his cropping operations in 1970 so as to conserve cash in order to meet commitments for land taxes and mortgage payments. Therefore i t was hypothesized that a larger number of acres of wheat in 1969 would be associated with a greater amount of participation in the LIFT Program. 2. Bushels of wheat on hand per cultivated acre: A stock of wheat in storage on the farm provided an opportunity for the farmers to obtain increased net cash revenue by marketing the wheat. Participation in the LIFT Program provided that opportunity. Therefore i t was hypothesized that a larger stock of wheat on hand relative to size of the farm would cause a greater amount of participation. 3. Amount of available storage space: A lack of storage space for the upcoming crop would make i t necessary to build additional storage space. This would reduce net cash income due to the additional -16-building costs involved. This situation could be avoided by participating in the LIFT Program. It was hypothesized that a smaller amount of available storage space would cause a greater amount of participation in the LIFT Program. 4. Amount of grain to be disposed of by feeding or by selling as  non-Board feed grain: Feeding wheat or other grains to livestock or selling grain as feed grain through non-Board marketing channels was an alternative to participation in the LIFT Program. It was hypothe-sized that those operators who expected to dispose of larger amounts of grain by feeding or by selling through non-Board channels would participate less in the LIFT Program. 5. Percent summer fallow in the normal rotation: Summer fallowing land for two years in succession w i l l reduce the protective trash cover and expose the s o i l to erosion. This practise could reduce income in the next production period due to lower productivity of the s o i l . It was hypothesized that those farmers with a higher percentage of land in summer fallow last year would not participate as f u l l y in the LIFT Program as those farmers with a smaller percentage of their land in summer fallow last year. 6. Average yield of wheat: A higher yield of wheat per acre would produce more to be marketed per acre. Since access to the market, and thus gross cash income, was determined by the extent of participation in the LIFT Program i t was hypothesized that an expectation of a higher yield for wheat would cause a greater amount of participation in the LIFT Program. -17-7. Amount of variation with respect to wheat yield: A greater amount of variation in wheat yield experienced in the past indicates a greater possibility of yields significantly below mean yields occurring in the future. The occurrence of a low yield for wheat could result in a loss of net cash income i f stocks of wheat were not large enough to f i l l the market opportunity. It was hypothesized that a farmer who had experi-enced a larger amount of variation in wheat yield in the past would seed more land to wheat and therfore participate less in the LIFT Program. 8. Knowledge of the LIFT Program: Johnson and Halter have described the learning situation as one of a series of knowledge situations^. The learning situation is described as the situation in which information is inadequate for decision and in which the value of acquiring knowledge exceeds i t s costs. It was assumed that as the extent of participation being considered by the farmer increases he also perceives the consequences of being wrong to become more serious. It was hypothesized that knowledge about the LIFT Program was a constraint on the number of acres of participation. Higher levels of participation would not occur unless the level of knowledge was also high. D. Empirical Results for the Net Cash Income Maximizing Model Data representing the eight independent variables of the Net Cash Income Maximizing Model for each of the respondents was analysed using a Stepwise Regression routine^. (See Appendix B for a description of the data). The following variables were s t a t i s t i c a l l y significant at Johnson, Glen L. and Albert N. Halter, "Introduction" pp. 1-23, A Study of Managerial Processes of Midwestern Farmers Iowa State University Press, 1961 ed. Glen L. Johnson, Albert N. Halter, Harold R. Jensen, D. Woods Thomas p. 10 1 0Bjerning, James H., J.R.H. Dempster, Ronald H. Hall, U.B.C. TRIP, University of British Columbia Computing Center, Jan.1968 pp. 55-64 -18-the .05 level: (a) bushels of wheat on hand per cultivated acre (b) percentage summer fallow in the normal crop rotation (c) knowledge of the LIFT Program (d) acres of wheat in 1969 The Stepwise Regression Routine selects the combination of variables that best accounts for the variation in the dependent variable. As a result an equation Y « a b i x l b2x2 b3&3 is selected from a larger set of independent variables x i , x 2, X 3 , x n. The independent variable that is most significantly related to the dependent variable is selected f i r s t . Other variables are added to the equation i f their addition results in a significant (at the 5% level) reduction in the standard error of Y. Independent variables are added in this manner u n t i l i t is not possible to further reduce the standard error of Y. These four variables explain 52.677. of the variation in the Extent of Participation in the LIFT Program. The following table presents s t a t i s t i c a l information relevant to the empirical analysis of the Net Cash Income Maximizing Model. Table 3 Empirical Analysis of the Net Cash Income Maximizing Model R 2 s 0.5267 i F Prob B 0.0000 Std. Error Y a 88.1354 acres Variable Coefficient Std. Error F-ratio F-prob Constant -9.5639 39.8287 Bushels of wheat on hand per cultivated acre 5.6013 1.3090 18.3101 0.0001 -19-Table 3. (cont'd.) Variable Coefficient Std. Error F-ratio F-prob Percentage of summer fallow in the normal crop rotation -2.8793 0.7872 13.3785 0.0005 Knowledge of the LIFT Program 18.4101 6.6591 7.6433 0.0067 Acres of wheat in 1969 0.3505 0.0471 55.2928 0.0000 Thus on the basis that the farm operator attempts to maximize his net cash return under conditions of uncertainty i t has been empirically determined that four specific variables had a significant influence upon the extent of participation. The number of bushels of wheat in storage on the farm relative to' the size of the farm was one of the main factors that encouraged the farm operator to participate in the LIFT Program. This relationship was not unexpected since the LIFT Program was specifically aimed at those operators with larger stocks of wheat. The larger the stock of wheat in relation to size of farm the more hopeless was the marketing opportunity and thus the LIFT Program became more attractive. The "percentage of summer fallow in the normal crop rotation" was an important factor which tended to have a negative effect on the extent of "Participation". Those farmers who had summer fallowed a large portion (50%) of their land as a normal practice f e l t they could not increase their summer fallow acreage without leaving certain fields fallow for two successive years and then face possible loss -20 due to erosion. On the other hand those farmers who had been following an intensive cropping program with no summer fallow or one third summer fallow in their normal rotation found i t relatively easy to increase their summer fallow acreage in response to the LIFT Program. This point drew many frank comments from those farm operators who normally followed a 50% summer fallow operation (51.85% normally summer fallowed between 41 and 50% of their land - see Appendix B page 71). These operators expressed the opinion that those farmers who had been following more intensive cropping patterns were largely responsible for creating the surplus problem that had caused low prices for a l l . They also f e l t that these same farmers who, in their opinion, had caused the wheat surplus were gaining the most benefit from the LIFT Program by being able to increase summer fallow acreage without risking loss through erosion. "Knowledge of the LIFT Program" was also an important variable in determining the amount of variation in "Acres of Parti-cipation", It was hypothesized that "Knowledge of the LIFT Program" would act as a constraint on "Acres of Participation". In other words i f such factors as stocks of wheat were high enough to cause the operator to consider participation in the LIFT Program he would also make special efforts to familiarize himself with the LIFT Program before taking action. The correlation coefficients of "Knowledge of the LIFT Program" and the other significant variables of the Net Cash Income Maximizing Model (see Appendix E) indicate that in this model -21-"Knowledge of the LIFT Program" acted independently to influence "Acres of Participation". Those farmers who were more knowledgeable of the LIFT Program also participated more in the LIFT Program. As was hypothesized (p. 14) "Acres of Participation" would be limited by "Acres of Wheat in 1969" due to the manner in which "Acres of Participation" was calculated and also that those farmers with larger acreages would be in a more d i f f i c u l t cash position. They thus would, other things being equal, find the cash incentives and extra market opportunity of the LIFT Program more attractive. E. An Extension of the Net Cash Income Maximizing Model The general form of the Extension of the Net Cash Income Maximizing Model was expressed as follows: Acres of Participation depends jointly on: 1. a decision criterion 2. economic factors 3. knowledge 4. sociological factors The Extension of the Net Cash Income Maximizing Model thus leads to the conclusion that Acres of Participation w i l l be determined by: (A) Those variables determined by empirical analysis of the Net Cash Income Maximizing Model as well as: (B) Positively by: 1. grade completed in school by the operator. 2. grade completed in school by the operator's wife 3. attitude towards change score -22-4. social participation score 5. total extension contact score 6. use of formal management techniques score 7. attitude towards the LIFT Program, and (C) Negatively by: 1. age of the operator The hypothesized relationships between each of the selected variables and Acres of Participation are described below. These hypotheses have been based on generalizations formulated by Rogers*!. 1. Age of the operator: Based on the generalization that earlier adopters tend to be younger in age than later adopters i t was hypothesized that older farmers would participate less than would younger farmers. 2. Grade completed in school by the operator: The generalization has been advanced by Rogers^ that earlier adopters have a type of mental a b i l i t y different from that of later adopters. If i t can be accepted that years completed in school has some influence on mental a b i l i t y and particularly an a b i l i t y to obtain information from mass media sources a relationship between the above generalization and participation in the LIFT Program can be inferred. It was hypothesized that those operators who completed more years at school would participate more in the LIFT Program because they would be better able to make an independent assessment of the program. 3. Grade completed in school by the operator's wife: If i t can be accepted that education of the operator's wife w i l l influence the decisions made by the operator the generalization that earlier *"*Rogers, E.M. Diffusion of Innovations, pp. 311-314 1 2 I b i d , p. 313, p. 177 -23-adopters have a different mental a b i l i t y than later adopters can be used to relate education of the operator's wife and participation. It was hypothesized that those operators whose wives, had completed more years in school would participate to a greater extent in the LIFT Program than would those operators whose wives had fewer years of schooling. 4. Attitude towards change score: It has been generalized by Rogers^ that earlier adopters are more cosmopolite than later adopters. Cosmopoliteness is defined by Rogers^-4 as "...the degree to which an individual's orientation is external to a particular social system". The attitude towards change score is an indicator of the cosmopolite-ness of the respondent in that i t measures the respondent's attitude towards changes in place of residence and/or occupation. It was hypothesized that those farmers with a high attitude towards change score would participate more in the LIFT Program then would those farmers with a lower score. 5. Social participation score: Based on the generalization that laggards are more likely to drop out of the social system i t was hypothesized that those farmers with ai higher social participation score would participate more in the LIFT Program than would those farmers with a lower score. 6. Total extension contact score: It has been generalized that cosmopolite sources of information are more important than localite sources for relatively earlier adopters. Localite sources of information are those that exist within the user's social system while cosmopolite 1 3 I b i d , p. 313 ^ I b i d , p. 17 -24-sources occur outside of the user's social system. It was assented that extension represented a cosmopolite sources of information and that those farmers who had a high extension contact score would tend to be seekers of other cosmopolite sources of information. It was therefore hypothesized that those farmers with a higher extension contact score would participate more in the LIFT Program than would those farmers with a lower score. 7. Use of formal management techniques score: It has been generalized that earlier adopters have a type of mental a b i l i t y different from that of later adopters. It was asserted that the use of written management aids represented a particular type of mental a b i l i t y . It was therefore hypothesized that those farmers with a higher use of formal management techniques score would participate more in the LIFT Program. 8. Attitude towards the LIFT Program: It had been generalized that the compatability of a new idea, as perceived by members of a social system, affects its rate of adoption. It was hypothesized that those farmers who had a more favorable attitude towards the LIFT Program would participate more than would those farmers who were opposed to the LIFT Program. F. Empirical Results for the Extension of the Net Cash Income Maximizing  Model Data representing the four significant variables of the Net Cash Income Maximizing Model and data representing the eight variables of the Extension of the Net Cash Income Maximizing Model were analyzed -25-using a stepwise multiple regression routine. In this routine the four significant variables of the f i r s t model were included f i r s t and the regression routine selected from among the eight variables of the second model to determine which of these additional variables would make a significant contribution towards explaining Acres of P a r t i c i -pation. The following variables were s t a t i s t i c a l l y significant in addition to the four variables of the f i r s t model: (a) age of the operator (b) grade completed by the operator's wife (c) attitude towards change score (d) attitude towards the LIFT Program These eight variables explain 61.94% of the variation in the Extent of Participation in the LIFT Program. The following table presents s t a t i s t i c a l information relevant to the empirical analysis of the Extension of the Net Cash Income Maximizing Model. Table 4 Empirical Analysis of the Extension of the Net Cash Income Maximizing Model R 2 . 0.6194 F-prob a 0.0000 Std. Error of Y = 80.7330 Variable Coefficient Std.Error F-ratio F-probability Constant -318.1121 78.9452 Age of operator 2.9914 0.7987 14.0260 0.0004 Grade completed by operator's wife 12.4336 4.6729 7.0798 0.0090 •26-Table 4. (cont'd.) Variable Coefficient Std.Error F-ratio F-probability Bushels of wheat on hand per cultivated . acre 5.1452 1.2204 Percentage of summer fallow in normal rotation - 2.7121 0.7359 Attitude towards change score 10.9245 5.2706 Knowledge of the LIFT Program 13.9153 6.6296 Acres of wheat in 1969 0.3634 0.0455 Attitude towards the LIFT Program 45.6650 17.7747 0.0001 13.5809 0.0005 4.2962 0.0387 4.4056 0.0364 63.7304 0.0000 5.6203 0.0189 19.2620 The Extension of the Net Cash Income Maximizing Model involved the addition of sociological variables to the existing empirically tested Net Cash Income Maximizing Model. The R value was increased from 0.5267 to 0.6194. The addition of four sociological variables increased the percentage of variation in "Acres of Participation" explained by the model of 9.27%. The hypothesis that "age of operator" would negatively affect "Acres of Participation" was rejected in view of the empirical results. Older farmers tended to participate more in the LIFT Program than did younger farmers. It could be concluded from this finding that Participation in the LIFT Program was different from the nature of the adoption studies from which Rogers generalized that earlier adapters are younger in age. -27-"Grade completed in school by the operators wife" was also significantly related to "Acres of Participation". Since the "grade completed in school by the operator" did not significantly explain variation in "Acres of Participation" i t could be concluded that level of education alone was not an important factor but that those wives with a higher level of education influenced their husbands to participate in the LIFT Program. "Attitude towards change score" was significantly and posi-tively related to "Acres of Participation". This supports the genera-lization proposed by Rogers that earlier adopters are more cosmopolite or more amiable to change. The most important variable in the Extension of the Net Cash Income Maximizing Model is "Attitude towards the LIFT Program", The multiple regression coefficient value of this variable indicates that the difference between a negative and a positive attitude towards the LIFT Program,other factors being equal, is 45.665 Acres of Participation. This amount of change appears to be important in as much as the mean value of Acres of Participation was 99.19 acres and the 95% confidence interval of the mean was 123.36 acres to 75.02 acres or a range of 48.34 acres. -28 CHAPTER III ANALYSIS OF THE SOURCES OF INFORMATION A. Theoretical Orientation Research into the adoption of innovations has established the importance of the relationship between sources of information about an innovation and the innovativeness of the adopters. Rogers*-* has presented the following generalizations with respect to information sources and innovativeness. "Impersonal sources of information are more important than personal sources for relatively earlier adopters of innovations than for later adopters*" "Earlier adopters u t i l i z e information sources that are in closer contact with the origin of the new idea than later adopters." "Impersonal information sources are most important at the awareness stage, and personal sources are most important at the evaluation stage in the adoption process." "Cosmopolite information sources are most important at the awareness stage, and localite information sources are most important at the evaluation stage." These generalizations were used as the basis for a set of specific hypotheses related to sources of information and the extent of parti-cipation in the LIFT Program. 1 5Rogers pp. 311-314, pp. 179-181 -29-Also relevant to the sources of information and change in general is the method by which the individual learns about the change. VernerlG states that "Institutions seeking changes in behaviour that result from rational thought employ procedures for the systematic diffusion of knowledge. This necessitates the design and construction of specific situations for learning that are characterized by a con-tinuous and direct exchange between the institution through i t s agent and the learning public." The decision to participate in the LIFT Program is an example of change involving the rational thought processes. Different schemes have been developed for the classification of information sources. These classifications are relevant to the generalizations presented by Rogers and to the statements made by Verner. Verner and M i l l a r d ^ have used a classification scheme based on the method by which farmers receive information about an innovation. The categories in this classification by Method are: 1. Mass: Those informational methods which contact large numbers of individuals at one time and which disseminate information generally. 2. Group.: Those informational methods which are educational in nature and provide opportunities for systematic learning through instructional groups. 3. Individual: Those informational methods which enable individual farmers to acquire information systematically on a personal basis. This includes personal influence through contacts of farmers with each other, or with other individuals. ^Verner, Coolie, A Conceptual Scheme for the Identification and Classification of Processes Adult Education Assoc. of the USA Washington, 1962, p. l^Verner and Millerd, Adult Education and the Adoption of Innovations, pp. 34-35 -30-Verner and GubbelsA used a classification scheme based on the origin of the information source. Categories of this classification are: 1. Government: Information sources originating with the Federal or Provincial Governments. 2. Commercial: Information sources originating with business agents, or establishments dealing with farmers. 3. Farm Organizations: Information sources originating from farmers organizations. 4. Personal: Information sources that l i e within the farmer's personal domain such as friends, neighbours or his family. A classification of sources of information based on the nature of the contact through which the farmer obtained information was used by Verner and M i l l e r d ^ . xhe categories in the classification by Nature of the Contact are: 1. Impersonal: Informational processes which do not involve extensive face to face contact with the farmer. 2. Personal: Informational processes which tend to involve direct contact with the farmer and allow for an interaction among the individuals involved. For the purposes of this study the information sources used by farmers in obtaining information about the LIFT Program were classified as shown in the following table. °Verner and Gubbels, Adoption or Rejection of Innovations by Dairy Farmers in the Lower Fraser Valley Agricultural Economics Research Council of Canada p.29. l^Vemer and Millerd op. c i t . pp. 35-36 -31-Table 5 Classification of the Sources of Information about  the LIFT Program Source of Information Method Classification by Origin Nature of Contact 1. Farm papers M 2. Gov't. Leaflets M 3. Radio M 4. T.V. M 5. Dist r i c t Agriculturist I 6. Elevator Agent I 7. Neighbours I 8. Family and Friends I 9. Letter or telephone c a l l to LIFT headquarters I 10.Other Gov't, personnel I 11.Special meetings on LIFT G 12.Farm Union representative I 13.Salesmen or Dealers I 14.M.P. or M.L.A. I 15.Other sources C G C C G C P P G G G FO C G I I I I P P P P P P P P P P Method Origin Nature of Contact Key M a Mass P • Personal P a Personal G a Group G s Gov't. I a Impersonal I - Individual C a Commercial FO s Farm Organization -32-B. Analysis of Information Sources Each respondent indicated what he f e l t his best sources of information about the LIFT Program were. A summary of the number of times each different source of information was given is presented in the following table. Table 6 Use of the Various Sources of Information about  the LIFT Program Source Number of Times Used % of Total Times Used 1. Farm Papers 57 21.757. 2. The Government Leaflets on operation LIFT 62 23.66% 3. Radio 16 6.1G% 4. Television 21 8.01% 5. District Agriculturist 10 3.81% 6. Elevator Agent 49 18.70% 7. Neighbours 13 4.96% 8. Family and friends 8 3.05% 9. Letter or phone c a l l to operation LIFT head-quarters 3 1.14% 10. Other Government Personnel 0 0 11. Special Meetings on LIFT Program 16 6.10% 12. Farm Organizations 0 0 13. Salesmen or Dealers 0 0 14. M.P. or M.L.A. 7 2.67% 15. Other Sources 0 0 262~ 100.0% -33-The sources of information used by the respondents were categorized by Method of Dissemination, Origin of the Information, and Nature of the Contact. The distribution of information sources used classified by Method is given in the following table. Table 7 Sources of Information About the LIFT Program Classified by Method Source by Method Number of times used % of total times used Mass 156 59.54% Individual 90 34.35% Group 16 6.11% 262 100.0% The distribution of the use of information sources by Origin is given in the following table Table 8 Sources of Information About the LIFT Program  Classified by Origin  Source by Origin Number of times used % of total times used Commercial 143 54.58% Government 98 37.40% Personal 21 8.02% Farm Organizations 0 0 262 100.0% The distribution of the use of information sources classified by the Nature of the Contact is given in the following table. -34-Table 9 Sources of Information About the LIFT Program  Classified by the Nature of the Contact Source by Nature of the Contact Number of times used % of total times used Personal 106 40.46% Impersonal 156 59.54% 262 100.0% The use of information sources was analysed according to the combination of source types used. The distribution of farmers using personal sources only, impersonal sources only, and both personal and impersonal sources is presented in the following table. Table 10 Combination of Information Sources Used by Nature  of the Contact Combination of Sources Number of Respondents % of Respondents Personal sources only 8 7.41% Impersonal sources only 25 23.15% Both personal and impersonal sources 74 68.52% No response 1 .92% 108 100.0% The distribution of farmers using various combinations of information sources as classified by method of the contact i s given in the following table. Table 11 Combination of Information Sources Used as  Classified by Method of the Contact Combination of Sources by Method of Contact Number of Respondents % of Respondents Mass only 25 23.15% Individual only 5 4.63% Group only 3 2.78% Mass and individual 61 56.48% Mass and group 8 7.41% Individual and group 1 .93% Mass and individual and group 4 3.70% No response 1 .92% 108" 100.0% The distribution of respondents using localite sources only, cosmopolite sources only, and both localite and cosmopolite sources is presented in the folloxtfing table. For purposes of this analysis the specific information sources classified as localite sources were "neighbours" and "family and friends". A l l other sources were classified as cosmopolite sources. -36-Table 12 Combination of Information Sources Used Classified by Cosmopoliteness Combination of Sources Number of Respondents % of Respondents Localite sources only 3 2.78% Cosmopolite Sources only 87 80.56% Both Localite and cosmopolite sources 17 15.74% No response 1 .92% 108 100.0% C. Information Sources and Extent of Participation The extent of participation in the LIFT Program was signi-ficantly related to the method by which the respondents obtained information about the program. The following table shows that a proportionately greater number of farmers who obtained information via group methods also had larger acreages of participation than did those farmers who obtained information via other methods. Table 13 Acres of Participation and Sources of Information  Classified by Method of Dissemination Acres of Sources of Information Participation Mass Individual Group  100 acres or less 110 65 5 180 101 acres or more 46 25 11 82 __ _ _ __ chi-square value • 11.19 degrees of freedom a 2 chi-probability s 0.004 -37»-The Extent of Participation in the LIFT Program was signi-ficantly related to the origin of the information about the LIFT Program. Proportionately more of those farmers who obtained information from government sources also had larger acreages of participation than did those farmers who obtained information from other sources. Table 14 Acres of Participation and Sources of Information Classified by Origin of the Information Acres of Sources of Information by Origin  Participation Commercial Government Personal Farm Organizations 100 acres or less 108 58 14 0 180 101 acres or more 35 40 7 0 82 _ _ _ _ __ chi-square value • 7.27 degrees of freedom s 2 chi-probability • 0.03 The extent of participation in the LIFT Program was not significantly related to the nature of the contact by which information was obtained. -38-Table 15 Acres of Participation and Sources of Information Classified by Nature of the Contact Acre of Sources of Information by Nature of Contact  Participation Personal Impersonal  100 acres or less 70 110 180 101 acres or more 36 46 82 106 156 262~ chi-square value = 0.40 degrees of freedom a 1 chi-probability a 0.53 The relationship between the combination of information sources used and the extent of participation in the LIFT Program was analysed as shown in the three following tables. Table 16 Combination of Information Sources Used by Nature of the Contact and Acres of Participation Combination of Information Sources  Acres of Personal Impersonal Both Personal Participation Sources only Sources only and Impersonal sources 100 acres or less 5 18 50 73 101 acres or more 3 7 24 34 - —- — — chi-square s 0.2997 degrees of freedom a 2 Chi-square value not significant at the 5% level of confidence. -39-The combination of information sources used by each respondent as classified according to nature of the contact was not significantly related to the extent of participation in the LIFT Program. The extent of participation was not influenced by the combination of information source contacts used. Table 17 Combination of Information Sources Used Classified by Cosmopoliteness and Acres of Participation Combination of Information Sources  Acres of Localite Cosmopolite Both Localite and Participation Sources only Sources only Cosmopolite sources 100 acres or less 2 60 11 73 101 acres or more 1 27 6 34 3 87 17 lOT" chi-square a 0.1222 degrees of freedom z 2 Chi-square value not significant at the5% level of confidence. The combination of information sources used as classified according to the nature of the source (cosmopolite-localite) was not significantly related to the extent of participation. Extent of participation was not influenced by the combination of information sources used by each farmer. -40-Table 18 Combination of Information Sources Used as Classified by the Method of Contact Combination of Acres of Participation Information Sources 100 acres or less 101 acres or more Mass only 18 7 25 Individual only 5 0 5 Group only 0 3 3 Mass and individual 45 16 61 Mass and group 4 4 8 Individual and group 0 1 1 Individual and group and mass 1 3 4 73 34 107 (chi-square analysis invalid) The above table indicates that although no definite pattern of relationship can be established the exclusive use of group methods of obtaining information tended to be associated with larger amounts of participation. The exclusive use of individual methods of obtaining information tended to be associated with smaller amounts of participation. Information sources were significantly related to the per-centage of summer fallow in the normal crop rotation. Those respondents with above average percentage of summer fallow tended to obtain information by group methods as illustrated in the following table. -41-Table 19 Percentage of Summer Fallow and Information Sources  Classified by Method Information Sources Mass Individual Group Above average per« centage summer fallow Below average per-centage summer fallow 73 83 56 34 11 140 122 156 90 chi-square a 7.07 degrees of freedom 5 2 chi-prob » 0.03 16 262 Table 20 Percentage of Summer Fallow and Information Sources  Classified by Nature of the Contact Information Sources Personal Impersonal Above average percentage summer fallow Below average percentage summer fallow 67 39 73 83 140 122 106 chi-square s 6.18 degrees of freedom = 1 chi-prob a 0.01 156 262 -42-Those respondents with above average percentage of summer fallow tended to obtain information by personal contact. The use of information sources was significantly related to knowledge of the LIFT Program. Those respondents who had better than average knowledge of the details of the LIFT Program tended to obtain information by group methods. Table 21 Knowledge of the LIFT Program and Information  Sources Classified by Method Information Sources Mass Individual Group Below average knowledge 84 53 4 141 Above average 72 37 12 121 156 90 16 262 chi-•square = 6.28 degrees of freedom = 2 chi-prob a 0.04 Those respondents who sold more than the average value of wheat in the previous year tended to obtain information about the LIFT Program by group methods. The relationship between Value of Wheat sold and information sources as classified by method is given below. Table 22 Value of Wheat Sold and Information Sources Classified by Method Information Sources Mass Individual Group  Below average value sold 94 54 5 153 Above average value sold 47 29 10 86 _ _ _ 239 chi-square = 6.60 degrees of freedom a 2 chi-prob s 0,04 The total amount of feed grain that the operator expected to feed or s e l l as non-Board feed grain was significantly related to the use of information sources as classified by Method of Dissemination. Those respondents who expected to feed or s e l l less than the average amount of feed grains tended to obtain information about the LIFT Frogram by group methods as indicated in the following table. Table 23 Feed Grain to be Fed or Sold and Information Sources Classified by Method of Dissemination Information Sources  Mass Individual Group  Below average amount of feed grain 94 47 13 154 Above average amount of feed grain 51 38 2 91 145 85 15 245 -44-chi-square a 5.97 degrees of freedom r 2 chi-prob • 0.05 The sources of information used were compared between Alberta and Saskatchewan within the brown s o i l zone. Saskatchewan farmers obtained more information by group methods and relatively fewer sources by individual contact. Table 24 Province Within the Brown Soil Zone and Information Sources Classified by Method of Dissemination Sources of Information  Mass Individual Group  Alberta 33 26 0 59 Saskatchewan 64 32 16 112 97 58 16 TTT chi-square a 11.17 degrees of freedom s 2 chi-prob a 0.004 Those respondents who had no definite plans to make changes in their farming operations tended to obtain more information by group methods. Table 25 Plans to Make Changes and Information Sources Classified by Method of Dissemination Sources of Information Mass Individual Group  Have plans to make changes 75 51 4 130 No plans to make changes 81 39 12 132 — 90 16 262 -45-chi-square s 5.82 degrees of freedom u 2 chi-prob • 0.05 Respondents who increased their summer fallow acreage in order to get more wheat quota or because of excess stocks of wheat on hand tended to make more use of information originating from government sources. Those respondents who increased their summer fallow acreage due to wet spring weather or because the rotation worked out that way tended to make more use of commercial and personal sources of information. Table 26 Reasons for Increasing Summer Fallow Acreage and Information Sources Classified by Origin Information Sources  Commercial Government Personal To get more wheat quota 48 48 6 102 Wet weather or rotation 45 22 8 75 _ _ __ ___ chi-square • 6.06 degrees of freedom o 2 chi-prob = 0.05 No other significant relationships between sources of information and other variables were discovered. Appendix C summarizes the various relationships examined. -46-Considerable evidence existed in the previously described relationships to indicate that the group method of dissemination of information was important. A higher incidence of the use of group methods by farmers with greater than average percentage acreage in summer fallow, higher than average sales of wheat, lower than average expected disposition of feed grains, and no plans for changes in the farming operation indicated that farmers for whom wheat production was the major activity and who had few alternatives to wheat production tended to attend the group meetings on the LIFT Program. In order to assess the influence of information sources on Acres of Participation independently of some of the above factors the sample was divided with respect to stocks of wheat on hand per cultivated acre. The objective of this exercise was to determine i f the use of group methods appeared to influence participation or i f farmers who used this particular method did so because they were in extreme d i f f i c u l t y and were therefore more interested in the LIFT Program and would have participated anyway, because of economic reasons rather than due to the influence of the group method. The categorization with respect to stocks of wheat per acre was chosen since that particular variable most closely represented the degree of marketing d i f f i c u l t y faced by the farm operator. The following tables illustrate the relation-ship between information sources and extent of participation after taking into consideration differences in size of wheat stocks. -47-Table 27 Information Sources Classified by Method of Dissemination and Acres of Participation; Corrected for Differences in Wheat Stocks Per Acre Information Sources  Mass Individual Group No. No. % No. % No. %  (a) Stocks less than average 152 Participation less than average 120 77 64.2% 41 34.2% 2 1.6% Participation more than average 32 16 50.0% 12 37.5% 4 12.5% (b) Stocks more than average 110 Participation less than average 60 32 53.3% 24 40.0% 4 6.7% Participation more than average 50 29 58.0% 15 30.0% 6 12.0% The preceeding analysis indicates that i t didn't matter i f wheat stocks were above or below average. A high level of participation occurred more frequently where Group Methods were used. Thus i t was concluded that the influence of the group method was independent of the level of wheat stocks per acre which was an important indication of level of participation. The relationship between the origin of the information source and extent of participation after allowing for size of wheat stocks was calculated and is given in the following table. -48-Table 28 Information Sources Classified by Origin and Acres of Participation; Corrected for Differences in Wheat Stocks Information Sources  Commercial Government Personal No. No. % No. % No. % (a) Stocks less than average 152 Participation less than average 120 72 60.0% 38 31.7% 10 8.3% Participation more than average 32 12 37.5% 14 43.8% 6 18.7% (b) Stocks more than average 110 Participation less than average 60 36 60.0% 20 33.3% 4 6.7% Participation more than average 50 23 46.0% 26 52.0% 1 2.0% The preceeding analysis indicates that commercial sources of information were used more frequently by those farmers participating less than average regardless of wheat stocks per acre. Government sources of information were used more frequently by those farmers participating more than average regardless of wheat stocks per acre. Personal sources of information were used most by those who p a r t i c i -pated by more than average where wheat stocks per acre were less than average. -49-CHAPTER IV AN EVALUATION OF THE EFFECTIVENESS OF THE LIFT PROGRAM The aims of the LIFT Program were to reduce the amount of grain in storage by one half through the reduction of wheat acreage and at the same time prevent a shift of wheatland into other crops. The important question to be answered in evaluating the f i r s t objective of the LIFT Program is 'what effect did the LIFT Program have on the reduction of wheat acreage in 1970' or 'would the reduction in wheat acreage have occurred without the LIFT Program?' It was not possible to answer this question directly because the LIFT Program applied to a l l of the prairie grain growing area, thus there was no control area with which to compare the actual reduction in wheat acreage 2^. The study did however include the collection '.of informa-tion from each farmer as to his reasons for reducing wheat acreage. The reasons given by the respondents were listed as follows: - no response - to get more wheat quota - lack of storage space - wet spring weather - that's the way the rotation worked out - to improve the land - lack of labour - a surplus of wheat on hand - depressed wheat markets 'An Ontario wheat or B.C. wheat growing control was not economically feasible. Some information exists in B.C. to suggest substantial reduction in wheat acreage even where the LIFT Program did not apply. -50-- substituted other crops - lack of capital These reasons were used to differentiate those farmers who reduced their x^heat acreage for reasons that were specifically related to the LIFT Program, those farmers who reduced their wheat acreage but for whom i t was not possible to determine the extent of the influence of the LIFT Program, and those farmers who reduced their wheat acreage for reasons that were specifically unrelated to the LIFT Program. Appendix B, page 87 of this paper outlines the method of categorizing the reasons given. A. Reasons for Reducing Wheat Acreage and Amount of Wheat Acreage  Reduction Of the ninety-three respondents who actually reduced their wheat acreage from 1969, 27 (29,0327.) gave reasons that were directly related to the LIFT Program, 24 (25.8067.) gave reasons indirectly related to the LIFT Program, and 42 (45.1617„) gave reasons that were not related to the LIFT Program. This analysis indicates that 45.1617. of the farmers in the sample who actually did reduce their wheat acreage did so for reasons entirely unrelated to the LIFT Program. Those farmers who reduced wheat acreage for reasons directly related to the LIFT Program accounted for 40.8097. of the total number of wheat acres reduced in the sample studied. Those farmers who reduced wheat acreage for reasons indirectly related to the LIFT Program accounted for 28.0147. of the total reduction in wheat acreage. 31.1777. of the total reduction in wheat acreage was accounted for by those respondents who gave reasons not related to the LIFT Program. -5D-45.132% of the total acres of participation in the sample was accounted for by those respondents who gave reasons for reducing wheat acreage that were directly related to the LIFT Program. Those respondents who reduced their wheat acreages for reasons indirectly related to the LIFT Program and for reasons not related to the LIFT Program accounted for 30.701% and 24.167% respectively of the Acres of Participation. The above described relationships between reasons for reducing wheat acreage and Acres of Reduction and Acres of Participation is summarized in the following table. Table 29 Reasons for Reducing Wheat Acreage Compared With Reduction in Wheat Acreage and Acres of Participation Reasons  Direct Relevance Indirect Relevance No Relevance to LIFT to LIFT to LIFT  Acres of Participation 4835 3289 2589 10,713 % of total 45.132% 30.701% 24.167% 100.0% Acres of Reduction 6232 4278 4761 15,271 % of total 40.809% 28.014% 31,177% 100.0% Where reasons for reducing wheat acreage were directly related to LIFT 77.58% of the wheat reduction involved LIFT participation. Similarly 76.88% and 54.38% of the Wheat Acreage Reduction involved participation where reasons for reducing wheat acreage were indirectly related to LIFT and not related to LIFT respectively. -.52-The mean number of Acres of Participation and Acres of Reduction for respondents giving each of the three categories of reasons for reducing wheat acreage is given in the following table. Table 30 Reasons for Reducing Wheat Acreage Compared With Mean Reduction in Wheat Acreage and Mean Acres of Participation Reasons  Direct Relevance Indirect Relevance No Relevance Mean Acres of Participation 179.07 137.04 61.88 Mean Acres of Reduction 230.81 178.25 113.36 A t-test 2* to determine i f significant differences existed for mean acres of participation and for mean acres of reduction among the three categories of reasons was performed. Table 31 Test of Difference Between Mean Values of Acres of  Participation as Categorized by Reasons for Reducing  Wheat Acreage Categories Compared t-value Degrees of Freedom Direct Relevance and Indirect Relevance 1.065 49 Direct Relevance and No Relevance 4.124* 67 Indirect Relevance and No Relevance 2.840* 64 * significant t-value 21 George Snedecor, S t a t i s t i c a l Methods, Iowa State University Press, 1956, 5th Edition, p. 96 -53-Those farmers who reduced wheat acreage due to reasons not relevant to LIFT had significantly smaller mean acres of participation. Where the LIFT Program in some way influenced wheat acreage reduction i t resulted in larger acreages of participation than where reduction was "accidental". v Table 32 Test of Difference Between Mean Value of Acres of  Reduction as Categorized by Reasons for Reducing  Wheat Acreage Categories Compared t-value Degrees of Freedom Direct Relevance and Indirect Relevance 1.317 49 Direct Relevance and No Relevance 3.852* 67 Indirect Relevance and No Relevance 2.291* 64 * significant t-values The reasons for reducing wheat acreage were significantly related to the extent of the reduction in wheat acreage made by each respondent as shown in the following table. Table 3 3 Reasons for Reducing Wheat Acreage Compared to the  Extent of Reduction in Wheat Acreage Reasons Decrease in Wheat Acreage Direct Relevance Indirect Relevance No Relevance To LIFT to LIFT to LIFT Less than or equal to 1 2 7 acres More than or equal to 1 2 8 acres 1 8 1 3 1 1 3 0 1 2 5 2 4 1 d.f. r 2 2 7 2 4 4 2 9 3 « 2 « 9 . 7 1 5 9 9 The reasons for reducing wheat acreage were significantly related to the extent of participation in the LIFT Program as shown in the following table. Table 3 4 Reasons for Reducing Wheat Acreage Compared to the Extent of Participation Reasons  Acres of Direct Relevance Indirect Relevance No Relevance Participation to LIFT to LIFT to LIFT  1 0 0 acres or less 1 0 1 acres or more 1 3 1 4 1 3 1 1 3 3 5 9 3 4 2 7 2 4 4 2 9 3 d.f. - 2 2 X z 7 . 9 9 6 4 0 -55-In those instances where the LIFT Program had a direct influence on the farmers decision to reduce wheat acreage the amount of reduction tended to be above average for the sample. Conversely where the LIFT Program had no direct influence on the farmers decision to reduce wheat acreage the amount of reduction tended to be below average for the sample. Where reduction in wheat acreage occurred due to reasons not related to the LIFT Program the amount of participation tended to be below average for the sample. CHAPTER V SUMMARY AND CONCLUSIONS A. Summary The LIFT Program was introduced in March of 1970 by the Federal Cabinet and the Canad ian Wheat Board. The purpose of the program was to encourage a reduction in acreage seeded to wheat on the Prairies and at the same time prevent a shift from wheat acreage into other crops. Wheat stocks were estimated by Wheat Board o f f i c i a l s to be about one b i l l i o n bushels. Storage costs were excessive and the surplus put the Wheat Board at a disadvantage as a seller on world markets. It was expected that the LIFT Program would affect individual farmers differently, depending upon their particular circumstances such as stocks of wheat on hand and alternate production p o s s i b i l i t i e s . The objectives of this study of the LIFT Program were: 1. to determine which factors were important for predicting the extent of participation in the LIFT Program, 2. to determine how effective the LIFT Program was in reducing wheat acreage. Data was collected by interviewing a randomly selected sample of prairie farmers. A prepared interview schedule was used and the interviews were conducted in June and July of 1970. Sixty quantitative variables were analysed and means, standard deviations and correlation coefficients determined. Twenty-five qualitative variables were -57-analysed and frequency distributions and chi-square tests made. This analysis constituted the descriptive portion of the thesis and is presented in Appendix B. Participation in the LIFT Program was defined as a decrease in wheat acreage that was matched by an increase in summer fallow and/or forage crops. A hypothetical model was proposed to explain extent of participation. The model was tested using stepwise multiple regression analysis. The following variables were found to be important in predicting Participation in the LIFT Program. Participation was positively influenced by: 1. number of bushels of wheat on hand per cultivated acre 2. age of operator 3. knowledge of the LIFT Program 4. acres of wheat in 1969 5. grade completed by the operator's wife 6. "attitude towards change" score 7. attitude towards the LIFT Program. Participation was influenced negatively by: 1. percentage of summer fallow in the normal crop rotation. These eight variables explained 61.94% of the variation in Participation in the LIFT Program. An analysis of the sources of information about the LIFT Program was performed. Acres.of Participation was found to be signi-ficantly related to information sources used when the sources were categorized on the basis of Method of Dissemination. A proportionately greater number of farmers who obtained information via group methods also had a larger acreage of Participation than did those farmers who obtained information via other methods. Source of information, when categorized according to origin of the information, was significantly related to Acres of Participation. Proportionately more of those farmers who obtained information from Government sources also had larger acreages of Participatidn than did those farmers who obtained information from other sources. It was further determined that obtaining information by group methods and from Government sources was independent of one important determining factor of Participation, stocks of wheat on hand per acre. This indicated a causal relation-ship between information source used and Participation. Reasons for reducing wheat acreage were categorized according to the following scheme; Direct Relevance to the LIFT Program, Indirect Relevance to the LIFT Program, and No Relevance to the LIFT Program. Respondents who reduced wheat acreage due to reasons Directly Relevant to the LIFT Program accounted for 40.809% of wheat acreage reduction and 45.132% of the total Acres of Participation. Respondents who reduced wheat acreage due to reasons Indirectly Relevant to the LIFT Program accounted for 28.014% of the total wheat acreage reduction and 30.701% of the total Acres of Participation. Those respondents who reduced their wheat acreage due to reasons Not Relevant to the LIFT Program accounted for 31.177% of the total reduction in wheat acreage and 24,167% of the total acres of Participation. The mean number of acres of reduction in wheat, where reasons for reduction were Not Relevant to LIFT, was significantly less than the mean acres of reduction where reasons for reduction were Indirectly -59-or Directly Relevant to the LIFT Program. The mean number of Acres of Participation, where reasons for reducing wheat acreage were Not Relevant to LIFT, was significantly less than the mean Acres of Participation where reasons for reduction were Indirectly or Directly Relevant to the LIFT Program. B. Conclusions The study indicated that the policy variables, Knowledge of the LIFT Program and Attitude towards LIFT, were both positively and significantly related to Extent of Participation. Knowledge of the LIFT Program was not significantly related to Bushels of Wheat on hand per acre (r s 0.057); this policy variable was independent of one of the main determining circumstances influencing Participation. It was thus concluded that additional effort in increasing the Knowledge of the LIFT Program would have resulted in increased Participation. For each farmer whose Knowledge of the LIFT Program was raised from the sample mean level of a score of 4.23 to a maximum score of 6.00 an additional 24.7 Acres of Participation would have been obtained. Efforts to create a more favorable attitude towards the program would have resulted in more Participation in the Program. For each farmer converted from a negative to a positive attitude towards the LIFT Program an additional 45.66 Acres of Participation would have been obtained. The analysis of the use of information sources indicates that i f more information had been disseminated by group meetings the extent of Participation could have been increased. It can also be concluded -60-that efforts to increase the dissemination of information from government sources would have resulted in more Participation. The analysis of reasons given for reducing wheat acreage indicates that the LIFT Program did influence, either directly or indirectly, about two thirds of the wheat acreage reduction which occurred in 1970. Thus despite the fact that the Program was disliked by prairie farmers and a combination of several socio-economic factors exerted influence on the farmers decision about his cropping program the LIFT Program did provide an important stimulus to encourage the reduction of wheat acreage in 1970. -61-BIBLIOGRAPHY Abell, Helen C. The Exchange of Farming Information. Ottawa: Canada Department of Agriculture Marketing Service, Economics Division, August, 1953. Olaf F. Larson and Elizabeth R. Dickerson. Communication of Agricultural Information in a South-Central New York County. Ithaca, New York: Cornell University Agricultural Experiment Station, January, 1957. Akinbode, Isaac A. and M. J . Dorling. Farmer Contacts with District  Agriculturists in Three Areas in British Columbia. Vancouver: Department of Agricultural Economics, University of British Columbia, 1969. Alleyne, E. Patrick and Coolie Verner. The Adoption and Rejection of  Innovations by Strawberry Growers in the Lower Fraser Valley. Vancouver: Department of Agricultural Economics, University of British Columbia, 1969. and Coolie Verner. Personal Contacts and the Adoption of Innovations. Vancouver: Department of Agricultural Economics, University of British Columbia, 1969. Bjerring, James and others. UBC TRIP (Triangular Regression Package). Vancouver: The University of British Columbia Computing Center, January, 1968. . UBC MVTAB Multiveriate Contingency Tabulations. Vancouver: The University of British Columbia Computing Center, May 1970. Bohlen, J.M. and G. M. Beal. Dissemination of Farm Market News and Its  Importance in Decision Making. Ames, Iowa: Iowa Agriculture and Home Economics Experiment Station. Iowa State University of Science and Technology. Research Bulletin 553, July, 1967. Bowman, Mary Jean, (ed) Expectations, Uncertainty and Business Behaviour. New York: Social Science Research Council, 1958. Dixon, J . "Uncertainty and Information in Agriculture". Farm Economist. Vol. 11, No. 4, pp. 147-161. Dodds, J . Parry and K. R. Marvin. How do Iowa Farmers Obtain and Use  Market News? Ames, Iowa: Agricultural Experimental Station, Iowa State College Research Bulletin 417. November, 1954. Dorling, M. J . The Okanagan Apple Producer, His Management Attitudes  and Behaviour. Vancouver: University of British Columbia, Depart-ment of Agricultural Economics. -62-Eisgruber, L.M. "Micro- and Macro- analytic Potential of Agricultural Information Systems". Canadian Journal of Agricultural Economics. Vol. 15, No. 2, 1967, pp. 1541-1552. and James Nielson. "Decision-Making Models in Farm Manage-ment". Canadian Journal of Agricultural Economics. Vol. 11, No. 1, pp. 60-70. Farris, Paul L, (ed) Market Structure Research. Ames, Iowa: Iowa State University Press, 1964. Fischer, Sir Ronald A. S t a t i s t i c a l Methods for Research Workers.13th ed. New York: Hofner Publishing Company Inc. Furniss, I.F. "Productivity Trends in Canadian Agriculture 1935-64". Canadian Farm Economics. Vol. 1, A p r i l , 1966. Graholm, E.A.K. "Costs and Returns on Wheat Farms, Central Saskatchewan". Canadian Farm Economics. Vol. 4, No. 5, December 1969. Economics Branch, Canada Department of Agriculture. Johnston, J . Econometric Methods. New York: McGraw H i l l Book Co. Inc., 1963. Kaldor, R. and E.O. Heady. An Exploratory Study of Expectations, Uncertain-ty and Farm Plans in Southern Iowa Agriculture. Ames, Iowa: Agricultural Experiment Station, Iowa State College Research Bulletin 408. April,1954. Kalton, G. Introduction to S t a t i s t i c a l Ideas for Social Scientists. London: Chapman and Hall Ltd., 1966. Knight, Dale A. and Robert W. Greve. Farmer Use and Understanding of Inductive and Deductive Reasoning and Figuring Costs and Returns. Tech. Bull. 107. Kansas Agriculture Experimental Station, March, 1960. Lionberger, Herbert F. Adoption of New Ideas and Practices. Ames, Iowa: The Iowa State University Press, 1960. MacKenzie, J.G. "Economics of Grain-Fallow Rotations and F e r t i l i z e r Use in the Prairie Provinces." Canadian Farm Economics. Vol. 3, No. 3, August, 1968. Canada Department of Agriculture. Marsh, C. Paul and A. Lee Coleman. Communication and the Adoption of Recommended Farm Practices. Some Information From a Study in Washington  County, Kentucky 1950. Lexington: Agricultural Experiment Station, University of Kentucky. Miller, R.T. and others. "Canadian Grains Policy". Canadian Farm Economics. Vol. 2, No. 2, June 1967. . "The Economic Base of the Central Butte Grain-Growing Region of South-Central Saskatchewan". Canadian Farm Economics. Vol.3, No. 3, August, 1968. -63-Nielson, James. "Improved Managerial Processes for Farmers". Journal  of Farm Economics. Vol. 43, No. 5, p. 1251. Richardson, G.B. "Equilibrium, Expectations and Information". The  Economic Journal. Vol. 69, pp. 223-237. Richmond, Samuel B. S t a t i s t i c a l Analysis. 2nd ed. New York: The Ronald Press Co., 1964. Rogers, Everett N. Diffusion of Innovations. New York: The Free Press of Glencoe, 1962. Rust, R.S. "Farm Survey Data Relationships with Managerial A b i l i t y . " Economic Analyst. Vol. XXXIII, A p r i l , 1963 and Vol. XXXIV, February 1964. Economics Division, Canada Department of Agriculture. Simon, Herbert A. "Theories of Decision-Making in Economics and Behavioral . Science." American Economic Review. Vol. 49, June, 1959, pp. 253-283. Stutt, R.A. "Farm Management in Canada". Canadian Farm Economics. Vol. 2, No. 3, August, 1967. Economics Branch, Canada Department of Agriculture. Tintner, Gerhard. Econometrics. New York: John Wiley and Sons, Inc., 1952. Verner, Coolie, Adult Education, Theory and Method. A Conceptical Scheme  for the Identification and Classification of Processes. Washington, D.C: Adult Education Association of the U.S.A., 1962. . Planning and Conducting a Survey. A Report of Procedures in the Conduct of a Cocio-Economic Survey for the Canada Land Inventory. Project No, 16018. Ottawa: Rural Development Branch, Department of Forestry and Rural Development, October, 1967. , and Frank W. Willerd. Adult Education and the Adoption of Innovations by Orchardists in the Okanagan Valley of British Columbia. Vancouver: Department of Agricultural Economics, University of British Columbia, 1966. and Peter M. Cubbels. The Adoption or Rejection of Innovations by Dairy Farm Operators in the Lower Fraser Valley. Agricultural Economics Research Council of Canada, 1967. Warley, T.K. (ed) Agricultural Producers and Their Markets. New York: Augustus M. Kelly Publishers, 1967. -64-APPENDIX A Representativeness of the Sample The representativeness of the sample was tested by comparing age of operator, size of farm, and acres of improved land for the sample against 1966 census data for the regions included in the sample. The regions included in the sample from Alberta were census divisions 4, 7, and 10. The regions included in the sample from Saskatchewan were census divisions 1, 2, 6, 7, 11, 12, and 13. A chi-square analysis was performed to test the hypothesis that no significant difference existed between census data and data obtained from the sample. The formula used to calculate the chi-square values was: where E B expected value a N r^ • sum of the i * - * 1 row in the table cj - sum of the j*"' 1 column in the table N s sum of the value of a l l rows or columns in the table Table 1. Age of Operator Compared by Method of Observation (Census versus sample) Method of Observation Age of Operator Census % Sample % under 25 years 25-34 35-44 45-54 55-59 60-64 65 and over 3.07% 13.71% 24.35% 28.49% 11.49% 8.44% 10.42% 1.85% 12.96% 16.67% 37.04% 11.11% 12.04% 8.33% -65-degrees of freedom s 6 X 2 = 3.751 (not significant at 957. level of significance) Table 2. Total Size of Farm Compared by  Method of Observation Method of Observation Total size of farm Census % Sample % 69 acres or less 1.72% 0.00% 70-239 acres 8.36% 2.78% 240-399 acres 16.23% 6.48% 400-559 acres 15.37% 12.04% 560-759 acres 16.49% 20.37% 760-1119 acres 20.46% 23.15% 1120-1599 acres 11.79% 23.15% 1600-2239 acres 5.33% 9.26% 2240-2879 acres 1.77% 1.85% 2880 or more 2.36% .93% degrees of freedom • 9 X 2 - 15.118 (not significant at 95% level of significance) - 6 6 -Table 3. Number of Improved Acres Compared  by Method of Observation Method of Observation Number of Improved Acres Census 7 . Sample 7 . 6 9 or less 3 . 2 1 7 . 0 0 . 0 0 7 . 7 0 - 2 3 9 acres 1 4 . 5 2 7 . 8 . 3 3 7 . 2 4 0 - 3 9 9 acres 2 1 . 5 6 7 . 1 0 . 1 9 7 o 4 0 0 - 5 5 9 acres 1 8 . 4 9 7 . 2 5 . 9 3 % 5 6 0 - 7 5 9 acres 1 7 . 2 4 7 o 1 5 . 7 4 7 , 7 6 0 - 1 1 1 9 acres 1 5 . 3 7 7 „ 2 2 . 2 2 7 o 1 1 2 0 - 1 5 9 9 acres 6 . 5 4 7 o 1 2 . 9 6 7 . 1 6 0 0 3 . 0 2 7 o 4 . 6 3 7 . degrees of freedom • 7 X 2 « 1 3 . 9 8 6 (not significant at the 9 5 % level of significance) On the basis of the above three tests i t can be concluded that the sample obtained for the study is not significantly different from the population as described by the 1 9 6 6 census. -67-APPENDIX B Descriptive Analysis of Variables Studied List of Tables Table Page 1. Percentage of Summer Fallow in the Usual Crop Rotation 71 2. Percentage of Grain Crops in the Usual Crop Rotation 72 3. Percentage of Forage Crops in the Usual Crop Rotation . . . . . . . 73 4. Bushels of Grain to be Sold as non-Board Feed Grain 75 5. Respondents by Soil Zone 79 6. Mean Values of Acres of Participation by Soil Zone 79 7. Differences Between Mean Values of Acres of Participation by Soil Zone 80 8. Respondents by Soil Zone and Province . . . . 80 9. Mean Value of Acres of Participation by Province . 81 10. Differences Between Mean Values of Acres of Participation by Province 81 11. Respondents by Attitude Toward the LIFT Program 82 12. Acres of Participation and Attitude Toward LIFT 82 13. Reasons for Attitude Toward the LIFT Program . 83 14. Reasons for Not Reducing Wheat Acreages . . . 84 15. Reasons for Reducing Wheat Acreage 85 16. Classification of Reasons for Reducing Wheat Acreage . . . . . 86 -68-Table Page 17. Reasons for Reducing Wheat Acreage Classified by Relevance to the LIFT Program 87 18. Reasons for Not Reducing Wheat Acreage Further 88 19. Reasons for Not Increasing Summer Fallow Acreage 89 20. Reasons for Increasing Summer Fallow Acreage . 89 21. Reasons for Not Increasing Summer Fallow Further 90 22. Reasons for Not Increasing Forage Crop Acreage 91 23. Reasons for Increasing Forage Crop Acreage . . 92 24. Reasons for Not Increasing Forage Crop Acreage Further 93 25. Reasons for Not Growing New Crops 93 26. Reasons for Growing New Crops 95 27. Conversion of Animals to Animal Units . . . . 97 28. Mean Animal Units and Correlation Coefficient with Acres of Participation 98 29. Off-farm earnings 98 30. Gross Farm Income 1969 99 31. Value of Wheat Sold in 1969 100 32. Net Farm Income 1969 101 33. Marital Status of Respondents 102 34. Marital Status of Operator and Acres of Participation 102 35. Post Secondary Education of the Operator . . . 102 36. Post Secondary Education of the Operator and Acres of Participation 102 37. Courses Taken in Agriculture 104 38. Agricultural Courses and Acres of Participation 104 -69-Table Page 39. Other Adult Education Courses Taken by the Operator 105 40. Post Secondary Education of the Operator's Wife 105 41. Post Secondary Education of the Operator's Wife and Acres of Participation 106 42. Main Agricultural Product Sold 106 43. Respondents Reporting Wheat or Beef as the Main Source of Gross Income and Acres of Participation 107 44. Other Agricultural Products Sold 108 45. Enjoyment of Farming 109 46. Acres of Participation and Enjoyment of Farming 109 "47. Social Participation Scores 110 48. Mean Value of Personal Extension Contacts and Correlation Coefficients with Acres of Participation I l l 49. Mean Value of the Impersonal Extension Contacts and Correlation Coefficients with Acres of Participation 112 50. Most Useful Sources of Information about the LIFT Program 114 51. Participation of the Operator's Wife in the Decision About the Cropping Program 115 52. Influence of the Operator's Wife on the Decision About the Cropping" Program . . . . . 115 53. Participation of the Operator's Wife in the Cropping Decision and Acres of Participation 116 54. Influence of the Operator's Wife in the Cropping Decision and Acres of Participation 116 -70-Descriptive Analysis of Variables Studied  The Variables Studied Sixty-one variables were studied. These variables are described in the following section in terms of means and standard deviations for those measured quantitatively and in terms of frequency distributions for those measured qualitatively. Correlation coefficients for the quantitatively measured variables and chi-square coefficients for the qualitatively measured variables in relation to Acres of Participation were also given. The variables studied were categorized under three main headings; 1. Variables of Specific Relevance to the LIFT Program, 2. Socio-Economic Variables, and, 3. Variables of Specific Relevance to Agricultural Extension. A. Variables of Specific Relevance to the LIFT Program 1. (a) Number of bushels of wheat on hand Each respondent was asked to estimate the number of bushels of wheat he had stored on his farm at the time of the interview. No verification of the farmer's answer by inspection of the stored wheat was made. One respondent refused to answer this question. The mean number of bushels of wheat on hand was 6999 bushels (S.D. 7004' bu.). Bushels of wheat on hand was significantly correlated with Acres of Participation (r a 0.56). (b) The number of bushels of wheat on hand per cultivated acre was calculated for each respondent. The mean number of bushels of wheat on hand per cultivated acre was 8.90 bushels per acre and the correlation with the Acres of Participation was 0.37 (significant at the j05 level). 71-2. (a) Number of bushels of storage space Each respondent was asked to estimate how many bushels of covered storage space he would have available for storing the 1970 crop. Covered storage space included regular type grain bins as well as machine sheds, barns, or other buildings which could be used for storage of grain. The mean number of bushels of available storage space was 6622 bushels (S.D. 6143 bu.). The correlation coefficient with Acres of Participation was 0.07 (not significant). (b) The number of bushels of storage space per cultivated acre was calculated for each respondent. The mean value for the sample was 9.79 bushels per acre (S.D. 7.14 bu./acre) and the correlation coefficient with Acres of Participation was 0.31 (significant at .05 level). 3. (a) Percentage of summer fallow in the usual rotation Each farmer interviewed was asked to describe his usual crop rotation in terms of the percentage of land in summer fallow each year. The qualifying term 'usual' was used to exclude the influence of the LIFT Program in the current year. The mean percentage of summer fallow in the usual crop rotation was 39.19% (S.D. 12.64). The frequency distribution of the number and percentage of respondents having different amounts of summer fallow in their normal crop rotation is described in the following table. Table 1. Percentage of Summer Fallow in the Usual Crop  Rotation Percentage of Summer Fallow  Respondents 0.10% 11-20% 21-30% 31-40% 41-507. Number 4 6 16 26 56 Percentage 3.70% 5.56% 14.81% 24.07% 51.85% Percentage of summer fallow in the usual crop rotation was not significantly related to Acres of Participation (r s 0.02). (b) The percentage of grain crops in the normal crop rotation was also determined. The mean percentage value was 55.19% (S.D. 11.88). The frequency distribution of the number and percentage of respondents having different amounts of grain crops in their usual rotations is described below. Crop Rotation Percentage Grain Number Respondents Percentage 0-10% 2 1.85% 11-20% 0 0 21-30% 1 0.93% 31-40% 1 0.93% 41-50% 60 55.56% 51-60% 15 13.89% 61-70% 24 22.22% 71-80% . 4 3.70% 81-90% 0 0 91-100% 1 0.93% Percentage of grain crops in the usual crop rotation was significantly related to Acres of Participation (r • 0.23). (c) The percentage of forage crops in the usual crop rotation was determined from each respondent. The mean value was 5.51% (S.D. 14.53). The frequency distribution of the percentage of forage crops in the usual crop rotation is given below. •73-Table 3. Percentage of Forage Crops in the Usual Crop Rotation. Percentag e Forage Respondents Number Percentage 0-10% 92 85.19% 11-20% 7 6.48% 21-30% 6 5.56% 31-40% 0 0 41-50% 1 0.93% 51-60% 0 0 61-70% 0 0 71-80% 0 0 81-90% 2 1.85% 91-100% 0 0 Percentage of forage crops in the usual crop rotation was significantly related to Acres of Participation (r • 0.21). 4. Knowledge of the LIFT Program Each respondent was asked a series of six selected questions* related to the rules and regulations of the LIFT Program as described in the f i r s t bulletin issued by the Canadian Wheat Board in March, 1970*. A score was calculated for each respondent based on one point for each correct answer given. A score of from 0 to 6 inclusive for each farmer was thus obtained. * See Interview Schedule, page 8. Appendix I * Hon. H.A. Olson and Hon. O.E. Lang, 'Operation L i f t ' Lower Inventory  for Tomorrow, March, 1970. -74-The mean score for knowledge of the LIFT Program was 4.23 (S.D. 1.35). Knowledge of the, LIFT Program was significantly related to Acres of Participation (r • 0.35). 5. Average Yield of Wheat Each respondent was asked to estimate his average yield per acre of wheat over the past five years. The mean yield for the sample was 25.81 bushels per acre (S.D. 7.44 bu./acre). Average wheat yield was not significantly related to Acres of Participation (r •> 0.05). 6. Amount of variation of wheat yield Each respondent was asked to estimate his highest and his lowest yearly average yield of wheat in the past five year period. The difference between the highest yield obtained and the lowest yield obtained by each farmer divided by his five year average yield was the calculated measure of the amount of valiation in wheat yi e l d . The mean value for the amount of variation in wheat yield was 1.02 (S.D. 0.63) and this measure was not significantly related to Acres of Participation. 7. (a) Number of bushels of grain to be fed or sold as Non-Board feed grain. Each respondent was asked to estimate the total number of bushels of wheat, oats, and barley that he expected to feed to livestock in the coming twelve month period. Each respondent was also asked to estimate the number of bushels of wheat, oats, and barley he expected to s e l l as non-Board feed grain in the next twelve month period. The sum of these two estimates was then calculated. The mean value for the sample -75-was 3873 bushels (S.D. 4142 bu.). The amount of grain to be fed or sold as non-Board feed grain was not significantly related to Acres of Participation. (b) The mean value for the expected number of bushels of grain to be fed to livestock was 3324 bushels (S.D. 4163 bu.) and was not significantly related to Acres of Participation (r = 0.06). (c) The mean value for the expected number of bushels of grain to be fed to livestock divided by /the number of cultivated acres in the farm was 5.62 bushels per acre (S.D. 7.51 bu./acre). This value was signi-ficantly related to Acres of Participation (r a 0.27). (d) The mean value for the number of bushels of grain to be sold as non-Board feed grain was 580.2 bushels (S.D. 1809 bu.). A frequency distribution of the number and percentage of respondents expecting to s e l l various quantities of non-Board feed grain is given in the following table. Table 4. Bushels of Grain to be Sold as non-Board Feed Grain Respondents Bushels Number Percentage None 77 71.30% 1-1000 5 4.63% 1001-2000 5 4.63% 2001-3000 3 2.78% 3001-5000 3 2.78% 5001-7500 1 .93% 7501-10000 0 0 10001 1 .93% Maybe some 13 12.04% -76-Thirteen of the respondents did not estimate an amount of grain to be sold as non-Board feed grain but f e l t that they probably would s e l l some grain through this marketing channel. They were recorded under the row in the table headed, "Maybe Some". Thus the table indicates that 71.30% of the respondents did not expect to s e l l any grain as non-Board feed grain and 28.70% did expect to s e l l some non-Board feed grain. The amount of grain to be sold as non-Board feed grain was not significantly related to Acres of Participation (r = 0.01). (e) The mean value of the number of bushels of grain to be sold as non-Board feed grain divided by the number of cultivated acres in the respondents farm was 0.62 bushels per acre (S.D. 1.63 bu./acre) and the correlation coefficient with Acres of Participation was 0.08 (not significant). 8. Acres of wheat in 1969 Each respondent was asked to state the number of acres upon which he had grown wheat in 1969. The mean value for the sample was 267.7 acres (S.D. 202.3 acres). Acres of wheat in 1969 was s i g n i f i -cantly related to Acres of Participation (r s 0.61). 9. Decrease in wheat acreage from 1969 The difference of 1969 wheat average and 1970 wheat average was calculated for each respondent. The mean value for the decrease in wheat average for the sample was 139.4 acres (S.D. 138.5) and was strongly related to Acres of Participation (r a 0.90). -77-10. Acres of summer fallow in 1969 Each respondent was asked to state the number of acres which were summer fallowed in 1969. The mean value was 295.5 acres (S.D. 229.2 acres) and the correlation coefficient with Acres of Participation was 0.33 (significant at .05 level). 11. Increase in summer fallow acreage The difference of 1969 summer fallow acreage and 1970 summer fallow acreage was calculated for each respondent. The mean value of increase in summer fallow acreage for the sample was 97.19 acres (S.D. 151.2 acres) and the correlation coefficient with Acres of Participation indicated a strong relationship (r = 0.93). 12. Acres of forage crops i n 1969 The number of acres of forage crops in 1969 was determined for each respondent. The mean value for the sample was 34.25 acres (S.D. 68.48). The number of acres of forage crops in 1969 was not significantly related to acres of Participation (r • 0.02). 13. Increase in forage crops The difference of 1969 forage crop acreage and 1970 forage crop acreage was calculated for each respondent. The mean value for the sample was 6.11 acres (S.D. 17.33). Increase in forage crop acreage was not significantly related to Acres of Participation (r a 0.11). 14. Number of new crops grown in 1970 From a record of crops grown in 1970 and in 1969, it.was determined for each respondent how many crops were new in 1970; i.e. not grown in 1969. The mean number of new crops per farmer in the sample was 0.41 (S.D. 0.68) and the correlation coefficient with Acres of Participation was 0.07 (not significant). -78-15. Acres of Participation "Acres of Participation" was used as the dependent variable for the multiple regression analysis used in this study. This dependent variable was also used in the correlation analysis. Acres of P a r t i c i -pation was defined as the number of acres of reduction in wheat acreage matched by an increase in summer fallow acreage and/or forage crop acreage increase and/or the number of acres seeded to non-cereals, non-oilseeds (buckwheat, safflower, peas) in 1970. An example of the calculation of Acres of Participation is given below. Crop Acres 1970 Acres 1969 Wheat 300 400 Summer fallow 450 400 Forage crops 0 0 Cereals other than wheat 50 0 Oilseeds 0 0 Non-cereals, non-oilseed 0 0 800 800 Decrease i n wheat acreage = 100 acres Increase in summer fallow acreage s 50 acres Increase in forage crop acreage z 0 acres Acreage of non-oilseeds, non-cereals s 0 Decrease in wheat acreage matched by an increase in summer fallow + increase in forage crops + acreage of non-oilseeds, non-cereals s 50 acres Acres of Participation a 50 acres The mean value of Acres of Participation was 99.19 (S.D. 125.6). -79-16. Soil Zone A str a t i f i e d random sampling technique was used to provide for a number of respondents within each of three selected s o i l zones; Dark Brown Soil Zone, Thin Black Soil Zone, and Black Soil Zone. A frequency distribution of the number and percentage of respondents in each of the s o i l zones is given below. Table 5. Respondents by Soil Zone Soil Zone  Black Soil Thin Black Dark Brown Respondents Zone Zone Zone Total Number 23 14 71 108 Percentage 21.307. 12.967. 65.747. 1007. The mean value of Acres of Participation was calculated for each s o i l zone as shown in the table below. Table 6• Mean Values of Acres of Participation  by Soil Zone Standard Area Mean Deviation N 1. The total surveyed area 99.19 125.6 108 2. The Black Soil Zone 33.26 41.28 23 3. The Thin Black Soil Zone 17.57 23.28 14 4. The Dark Brown Soil Zone 136.6 138.9 71 -80-A comparison of the number of Acres of Participation between s o i l zones is given in the table of t values for significant differences between means*. Table 7. Differences Between Mean Values of Acres  of Participation by Soil Zone degrees of Areas Compared t-value freedom  Black Soil Zone -Thin Black Soil Zone 1.297 35 Black Soil Zone -Dark Brown Soil Zone 3.506* 92 Thin Black Soil Zone -Dark Brown Soil Zone 3.182* 83 * significant at .01 level 17. Province The sample included respondents in the Province of Alberta and in the Province of Saskatchewan. No farmers in the Thin Black Soil Zone or Black Soil Zone were interviewed in the Province of Saskatchewan. A comparison of Acres of Participation between the two provinces was made only for those respondents residing in the Dark Brown Soil Zone. A frequency distribution of the number and percentage of respondents in each Soil Zone and in each province is given below. Table 8. Respondents by Soil Zone and Province Province Black Thin Black Dark Brown Alberta 23 14 23 Saskatchewan 0 0 48 * George W, Snedecor, St a t i s t i c a l Methods, Iowa State University Press, 1956, 5th edition, p. 99. The mean value of Acres of Participation by Province within the Dark Brown Soil Zone is given below. Table 9. Mean Value of Acres of Participation  by Province (Brown Soil Zone) Standard Area Mean Deviation N 1. Alberta 89.26 108.7 23 2. Saskatchewan 159.4 146.9 48 An analysis of the difference between the mean values of Acres of Participation in each of the two provinces is presented in the following table. Table 10. Differences Between Mean Values of Acres of Participation by Province (Dark Brown Soil) Areas compared t-value degree of freedom Alberta - Saskatchewan 2.034* 69 * significant at the .05 level 18. Attitude towards the LIFT Program Each respondent was asked how he f e l t about the LIFT Program. His response was then recorded as strongly opposed, mildly opposed, neutral, mildly in favor, strongly in favor of the LIFT Program. The frequency distribution of the number and percentage of respondents having different attitudes toward the LIFT Program is given in the following table. -82-Table 11. Respondents by Attitude Toward the  LIFT Program Strongly Mildly Mildly Strongly Opposed Opposed Neutral in Favor in Favor Total Number 42 39 17 9 1 108 Percentage 38.89 36.11 15.74 8.33 0.93 100 For the purposes of further analysis by Chi-square, attitude toward the LIFT Program was re-categorized into opposed and neutral or in favor. A bivariate frequency distribution of Acres of P a r t i c i -pation and attitude toward the LIFT Program is given in the following table. Table 12. Acres of Participation and Attitude Toward LIFT Attitude  Acres of Participation Opposed Neutral or In Favor  100 acres or less 57 17 74 101 acres or more 24 10 34 ~8T ~27 108 degrees of freedom s 1 Chi-square s 0.23 (not significant at .05 level) 19. Reasons for attitude toward the LIFT Program This question was not asked of the f i r s t 36 respondents interviewed but i t was asked of the remainder of the sample. Each respondent was asked to give a reason for his attitude toward the LIFT Program. The responses were recorded and later categorized into the general statements as given in the following table. -83-Table 13. Reasons for Attitude toward the LIFT Program Reasons Number of Respondents Percent of total Reasons Given 1. "Impractical rules and regulations" 4 2. "Wheat Board should concen- 10 trate on selling wheat" 3. "The LIFT Program is not helping anyone and is a waste of money" 11 4. "The wheat surplus is not a problem" 9 5. "The LIFT Program is only helping those few large farmers who have been cropping more than 50% of their land each year and now have thus caused the surplus problem." 6 6. "The LIFT Program w i l l upset marketing of grain in the future". 1 7. "LIFT hasn't affected me" 2 8. "There is a need to cut back wheat production" 5 9. "I have been able to obtain benefit from the LIFT Program 3 10. "Operation LIFT is not a satis-factory answer to the current problem" 3 11. "The LIFT Program penalises us by reducing the amount of wheat that the small and/or diversi-fied farmer can s e l l " 10 5.55% 13.88% 15.27% 12.50% 8.33% 1.38% 2.77% 6.94% 4.16% 4.16% 13.88% -84-Table 13 (cont'd.) Reasons Number of Respondents Percent of total Reasons Given 12. "I don't like the compulsion involved in the LIFT Program" 13. "The payments for summer fallowing or seeding forage are not high enough" 14. No response Total 3 36 108 6.94% 4.16% 100 % 20. Reasons for not reducing wheat acreage If the respondent had not reduced his wheat acreage he was asked to give two reasons why he had not done so. Fourteen respondents reported no reduction in wheat acreage and gave the following reasons for not reducing wheat acreage. Table 14. Reasons for not Reducing Wheat Acreage Reasons Number Percentage of Reasons Given 1. "I followed my normal crop rotation" 3 2. "Wheat surplus is not a problem for me" 4 3. "Incentive payments were not high enough" 1 4. "I can feed wheat to livestock" 2 5. "I expect to be able to s e l l some wheat" 2 Total 12" 25.00% 33.33% 8.33% 16.66% 16.66% 100.0% -85-21. Reasons for reducing wheat acreage If the respondent had reduced his wheat acreage he was asked to give two reasons why he had done so. Ninety-four respondents had reduced their wheat acreage. The reasons given by these respondents were grouped as shoxm in the following table. Table 15. Reasons for Reducing Wheat Acreage Reasons Number Percent of reasons 1. "To get more wheat quota" 27 2. "Lack of storage space" 12 3. "Wet spring weather" 16 4. "That's the way the rotation worked out" 5 5. "To improve the land" 2 6. "Lack of labour" 1 7. "A surplus of wheat on hand" 16 8. "Depressed wheat markets" 26 9. "Substituted other crops for wheat" 11 10. "Lack of capital" 1 Total T l 7 23.077% 10.256% 13.675% 4.274% 1.709% 0.855% 13.675% 22.222% 9.402% 0.855% 100.000% A further categorization of the above reasons for reducing wheat acreage was made. In order to present a more generalized picture of the reasons, the classifications; 1. Direct Relevance to the LIFT Program, 2. Indirect Relevance to the LIFT Program, and 3. No Relevance the LIFT Program, were used. The reason "To get more wheat quota" is the only reason given by the respondents which indicates that the -86-LIFT Program had a direct bearing on the decision to reduce wheat acreage. The reasons "Lack of storage space" and "A surplus of wheat on hand", do not indicate that the LIFT Program had a direct influence on the decision to reduce wheat acreage but since the LIFT Program was specially designed for farmers with a surplus stock of wheat, i t can be argued that there was a good chance that farmers giving the above two reasons were in fact influenced by the LIFT Program even though they did not directly say so. The other reasons given by the res-pondents indicate that they would have reduced wheat acreage even i f the LIFT Program had not been in effect. The reclassification of reasons for reducing wheat acreage is summarized below. Table 16. Classification of Reasons for Reducing  Wheat Acreage General Classification Reasons  1. Direct Relevance to the 1. "To get more wheat quota" LIFT Program 2. Indirect Relevance to the 2. "Lack of storage space" LIFT Program 7. "A surplus of wheat on hand"-3. No Direct Relevance to 3. "Wet spring weather" the LIFT Program 4. "That's the way the rotation worked out" 5. "To improve the land" 6. "Lack of labour" 8. "Depressed wheat markets" 9. "Substituted other crops for wheat" 10. "Lack of capital" -87-In reclassifying the reasons given for the reduction of wheat acreage a l l reasons given by one respondent were considered as a unit and the reason most closely relevant to the LIFT Program was given priori t y . For example a respondent had given reasons "Lack of storage space" and "wet spring weather". This would be reclassified as one respondent gave a reason ("Lack of storage space") indirectly related to the LIFT Program. If a respondent gave "Lack of labour" and "To improve the land" as reasons, this would be reclassified as no direct relevance to the LIFT Program. If a respondent gave reasons "A surplus of wheat on hand" and "to get more wheat quota" this would be reclassified as having direct relevance to the LIFT Program. The number of respondents giving reasons that were Directly Relevant to the LIFT Program, Indirectly Relevant and Not Relevant to the LIFT Program is given in the following table. Table 17. Reasons for Reducing Wheat Acreage Classified by Relevance to the LIFT Program. Percentage of Number of Respondents Giving Reasons Respondents Reasons  1. Direct Relevance to the LIFT Program 27 29.032% 2. Indirect Relevance to the LIFT Program 24 25.806% 3. No Relevance to the LIFT Program 42 45.161% Total 93 100.000% 22. Reasons for not reducing wheat acreage further If the respondent had reduced his wheat acreage but had not eliminated wheat in 1970 he was asked to give two reasons why he had -88-not reduced his wheat acreage any further. The reasons given were grouped and are presented in the following table. Table 18. Reasons for Not Reducing Wheat Acreage Further Number of Percentage of Reasons Reasons Total Reasons 1. "Some carryover is needed, surplus not too much of a problem" 15 12.82% 2. "Can use as feed grain 7 5.98%' 3. "Can't summer fallow land two years in succession" 6 5.12% 4. "Wheat is s t i l l profitable" 12 10.25% 5. "Seed was already prepared before the announcement of LIFT Program" 3 2.56% 6. "Incentive payment not enough" 1 0.85% 7. "Expected to be able to s e l l some wheat" 23 19.65% 8. "Bound by land rental agreement" 1 0.85% 9. "Didn't have seed for other crops" 1 0.85% 10. "Hadn't planned on reducing wheat acreage this year, reduction was caused by weather" 9 7.69% Total 78 100.0% 23. Reasons for not reducing summer fallow acreage If the respondent had not increased his summer fallow acreage he was asked to give two reasons why he had not done so. The thirty-one respondents who did not increase their summer fallow acreage gave the following reasons for doing so. -89-Table 19. Reasons for Not Increasing Summer Fallow  Acreage Number of Percentage of Reasons Reasons Reasons Given 1. "I followed my normal crop rotation" 2 5.71% 2. "Surplus is not a problem" 4 11.42% 3. "LIFT incentive payments were not large enough" 4 11.42% 4. "Needed feed grain and straw for livestock" 12 34.28% 5. "Couldn't summer fallow land two years in succession" 15 42.85% 6. "Had summer fallowed additional land last year" 1 2.85% 7. "Substituted other crops for wheat" - 3 8.57% 8. "Bound by land rental agreement" 1 2.85% Total 42 100.0% 24. Reasons for Increasing Summer fallow acreage If the respondent had increased his summer fallow acreage he was asked to give two reasons why he had done so. The seventy-seven respondents who had increased their summer fallow acreage gave the following reasons for doing so. Table 20. Reasons for Increasing Summer Fallow Acreage Number of Percentage of Reasons Reasons Reasons Given 1. "To get more wheat quota" 35 37.23% 2. "Lack of storage space" 6 6.38% 3. "Wet spring weather" 15 15.95% -90-Table 20. (cont'd.) Number of Percentage of Reasons Reasons Reasons Given 4. "That's the way the rotation worked out" 13 13.82% 5. "to improve the land" 11 11.70% 6. "Lack of labour" 1 1.06% 7. "To take advantage of the LIFT incentive payments" 4 4.25% 8. "To reduce wheat acreage 8 8.51% 9. "Machinery breakdown" 1 1.06% Total 94 100 % 25. Reasons for not increasing summer fallow further If the respondent had increased his summer fallow acreage but had not gone to total summer fallow he was asked to give two reasons why he had not increased his summer fallow acreage more than he did. Table 21. Reasons for Not Increasing Summer Fallow  Further Number of Percentage of Reasons Reasons Reasons Given 1. "Need some carryover surplus not a problem" 13 21.31% 2. "Can make use of grain as livestock feed" 13 21.31% 3. "Couldn't summer fallow land two years in succession" 17 27.86% 4. "Wheat is s t i l l profitable" 6 9.83% 5. "Seed was already prepared when the LIFT Program was announced" 1 1.63% -91-Table 21. (cont'd.) Number of Percentage of Reasons Reasons Reasons Given 6. "LIFT incentive payments not large enough" 1 1.63% 7. "Expect to be able to s e l l some wheat" 1 1.63% 8. "Bound by a land rental agreement" 1 1.63% 9. "Lack of capital" 2 3.27% 10. "Seeded other crops" 2 3.27% 11. "Lack of equipment and/or labor" 1 1.63% Total 68 100.0% 26. Reasons for not increasing forage crop acreage If the respondent had not increased his forage crop acreage he was asked to give two reasons why he had not done so. Ninety-one respondents did not increase their forage crop acreage. Their reasons for not increasing forage crop acreage are given in the following table. Table 22. Reasons for Not Increasing Forage  Crop Acreage Reasons Number of Reasons Percentage of Reasons Given 1. "Have enough forage crops" 21 20.38% 2. "No need for forage crops" 29 28.15% 3. "Forage crops not profitable" 15 14.56% 4. "Lack of capital" 3 2.91% 5. "Price of seed too high" 8 7.76% 6. "Couldn't get the seed" 8 7.76% -92-Table 22. (cont'd.) Number of Percentage of Reasons Reasons Reasons Given 7. "Too wet this spring" 9 8.73% 8. "Impractical rules of LIFT Program" 4 3.88% 9. "Will seed some forage this f a l l " 2 1.94% 10. "Not equipped for forage crops" 2 1.94% 11. "Stipulation of the rental » agreement" 1 0.97% Total 102 100.0% 27. Reasons for increasing forage crop acreage If the respondent had increased his forage crop acreage he was asked to give two reasons for doing so. Table 23. Reasons for Increasing Forage  Crop Acreage Number of Percentage of Reasons Reasons Reasons Given 1. "Needed more forage for feed" 11 47.8% 2. "Rotation required new seeding" 7 30.4% 3. "Field location best for forage crops" 1 4.35% 4. "To get wheat quota" 0 0 5. "To take advantage of LIFT incentive" 2 8.7% 6. "Diversifying into hay as a cash crop" 1 4.35% 7. "Could get the seed on over delivery permit" 1 4.35% Total 23 100.0% -93-28. Reasons for not increasing forage crops further If the respondent had increased his forage crop acreage he was asked to give two reasons why he had not increased his forage crop acreage by more than he did. The reasons given for not increasing forage crop acreage further are given in the following table. Table 24. Reasons for Not Increasing Forage Crop Acreage Further Number of Percentage of Reasons Reasons Reasons Given 1. "Will have enough to meet requirements" 5 71.5% 2. "Couldn't get anymore seed" 1 14.3% 3. "Forage crops not profitable" 1 14.3% Total ~7~ 100.0% 29. Reasons for not growing new crops If the respondent had not grown any new crops in 1970 he was asked to give two reasons for not doing so. New crops were defined as crops not grown by the respondent in 1969. Seventy-four respondents did not grow new crops in 1970. Their reasons for not doing so are presented in the following table. To most of those interviewed new crops included rapeseed or flax. Table 25. Reasons for Not Growing New Crops Number of Percentage of Reasons Reasons Reasons Given 1. "Need feed grains" 16 18.82% 2. "Didn't want to change" 8 9.41% 3. "Lack of storage space" 8 9.41% -94-Table 25. (cont'd.) Reasons Number of Reasons Percentage of Reasons Given 4. "Uncertainty about markets for new crops" 7 8.237. 5. "Couldn't get the seed" 2 2.357. 6. "Price of seed too high" 2 2.35% 7. "Didn't have suitable machinery" 4 4.70% 8. "Lack of capital" 4 4.70% 9. "No experience with new crops" 5 5.88% 10. "Expect markets for new crops to decline" 7 8.23% 11 ."Increased other crops instead" 2 2.35% 12. "New crops too risky to grow" 9 10.85% 13. "Had seed prepared before the LIFT Program was announced" 1 1.17% 14. "Was able to take advantage of LIFT" 3 3.52% 15. "Lack of time due to late spring" 5 5.88% 16. "Couldn't get a contract" 1 1.17% 17. "No wheat surplus" 1 1.17% Total 85~ 100.0% 30. Reasons for growing new crops If the respondent had grown new crops in 1970 he was asked to give reasons why he had done so. -95-Table 26. Reasons for Growing New Crops Reasons Number of Percentage of Reasons Reasons Given 1. "Expect to be able to market these crops" 30 58.82% 2. "Can use these crops as livestock feed" 5 9.80% 3. "Could get a contract" 4 7.84% 4. "Could get seed on over delivery" 1 1.96% 5. "Trying to diversify" 7 13.72% 6. "Could get extra wheat quota" 1 1.96% 7. "Had a suitable f i e l d " 2 3.92% Total 50~ 100.0% B. Socio - Economic Variables 1. Age of the operator The age of each respondent was determined from the interview schedule. The mean age of a l l of the farm operators in the sample was 49.06 years (S.D. 12.03 years). Age of the operator was not significantly related to Acres of Participation (r s 0.03). 2. Number of children If the respondent was married he was asked how many children he had. The mean number of children for this sample was 3.36 (S.D. 2.07). The correlation coefficient between number of children and Acres of Participation was 0.04 (not significant). 3. Highest grade in school completed by the operator Each respondent was asked to give the highest grade he had completed in school. The mean number of grades completed in school by the farm operators in this sample was 8.64 grades (S.D. 2.22 grades.). Grade completed in school by the operator was significantly -96-related to Acres of Participation (r • 0.26). 4. Highest grade completed in school by the operator's wife If the respondent was married he was asked to give the number of grades completed in school by his wife. The mean number of grades completed in school by operator's wives in this sample was 9.88 (S.D. 1.96). The correlation coefficient with Acres of Participation was significant (r = 0.33). 5. Number of years farming Each respondent was asked to give the number of years he had been farming on his own. The mean number of years spent in farming by operators in the sample was 25.42 years. Number of years farming was not significantly related to Acres of P a r t i c i -pation (r • 0.01). 6. Total size of the farm The total size of the farm operated by each respondent was determined. The mean total size of farms in the sample was 963.7 acres (S.D. 532.3). Total size of farm was significantly related to Acres of Participation (r • 0.40), 7. Number of cultivated acres The number of cultivated acres on the farm was determined from each respondent. The mean number of acres of cultivated land per farmer was 740.5 acres (S.D. 450.5 acres). The number of cultivated acres on a farm was significantly related to Acres of Participation (r = 0.49). 8. Number of animal units of livestock Each respondent was asked to give the average number of livestock of different kinds (dairy cattle, beef cattle, hogs, -97-sheep, poultry, horses) and classes (mature, yearlings, calves, etc.) he had on his farm for the past year. The number of animal units of each different kind and class of livestock was calculated from the following conversion table and the total number of animal units was derived for each respondent. Table 27. Conversion of Animals to Animal Units* Animals per Animal Unit 1. Dairy cow 0.75 2. Beef cow 1.0 3. Bull 1.0 4. Horse 1.0 5. Dairy hiefer (over 1 yr.) 1.5 6. Beef hiefer (over 1 yr.) 1.5 7. Steer (over 2 years) 1.0 8. Steer ( 1 - 2 years) 1.5 9. Calf (under 1 yr.) 4.0 10. Sows and Boars 3.0 11. Market hogs (100-200 lb.) 5.0 12. Feeder hogs (under 100 lb.) 10.0 13. Sheep 7.0 14. Lambs 14.0 15. Chickens 72.0 16. Turkeys 80.0 * British Columbia Department of Agriculture, Farm Economics Division, "Farm Business, 1967, Annual Report", p. 48. -98-The mean number of animal units per farm in the sample and the correlation coefficient with Acres of Participation are given in the following table. Table 28. Mean Animal Units and Correlation Coefficient  with Acres of Participation  Animals Mean Animal Units Correlation Coefficient 1. Dairy 2.44 (S.D. 7.54) 0.11 2. Beef 34.03 (44.81) 0.08 3. Hogs 4.36 (8.81) 0.05 4. Sheep 0.071 (0.54) 0.09 5. Horses 0.51 (1.35) 0.02 6. Poultry 3.47 (20.29) 0.08 7. A l l Livestock 44.85 (50.58) 0.13 (none of the correlation coefficients are significant) 9. Off-farm earnings in 1969 Each respondent was asked to state the amount of his off-farm earnings during the past year. Ninety-six respondents reported no off-farm earnings, eleven reported off-farm earnings and one did not respond to the question. The frequency distribution of off-farm earnings is given below. Table 29. Off-Farm Earnings Respondents Number Percentage No response 1 .93% None 96 88.89% $100-500 2 1.85% 500-1000 2 1.85% -99-Table 29. (cont'd.) Respondents Number Percentage $1001-1500 4 3.70% 1501-2000 1 .93% 2001-5000 1 .93% 5001-10000 0 0 10000 1 .93% The mean value of off-farm income was $217.7 (S.D. 1063) and the correlation coefficient with Acres of Participation was not significant (r • 0.11). 10. (a) Gross Farm Income 1969 Each respondent was asked to state the amount of his gross farm income for 1969. The responses to this question and to the following two questions were in most cases, based on the respondents' 1969 income tax statement. The mean value of gross farm income for 1969 was $12,820 (S.D. $11,300). The frequency distribution of gross income i s given in the following table. Table 30. Gross Farm Income 1969 Respondents Number Percent No Response 10 9.26% Less than $2500 3 2.78% $2501-5000 18 16.67% 5001-10000 30 27.78% 10001-20000 35 32.41% 20001-30000 5 4.63% 30001-50000 5 4.63% 50001-70000 2 1.85% 70001 0 0 -100-Gross farm income was significantly related to Acres of Participation (r a 0.28), (b) Gross farm income per cultivated acre was calculated for each respondent. The mean value was $19,71 per acre (S.D. $14.94 per acre) . Gross farm income per acre was significantly related to Acres of Participation (r • 0.28). 11. (a) Value of wheat sold in 1969 Each respondent was asked to give the value of wheat he had sold during 1969. The mean value of wheat sold per farm in the sample was $4530 (S.D. $3254). The frequency distribution of the value of wheat sold in 1969 is given in the following .table. Table 31. Value of Wheat Sold in 1969 Respondents ; Number Percentage No Response 10 9.26% Less than 1000 9 8.33% 1001-2000 17 15.74% 2001-3000 16 14.81% 3001-4000 11 10.19% 4001-5000 13 12.04% 5001-7000 12 11.11% 7001-10000 17 15.74% 10001 3 2.78% Value of wheat sold in 1969 was significantly related to Acres of Participation (r a 0.35). -101-(b) The value of wheat sold per cultivated acre was calculated for each respondent. The mean value of wheat sold per cultivated acre was $6.24 per acre (S.D. $3.41/acre). The correlation coefficient with Acres of Participation was not significant (r - 0.10). 12. (a) Net Farm Income Each respondent was asked to give his net farm income for 1969. The mean value was $2055 (S.D. $2739). The frequency dis-tribution of net farm income is given in the following table. Table 32. Net Farm Income 1969 Respondents Number Percentage No Response 12 11.11% 0 or negative 28 25.93% 100-500 5 4.63% 501-1000 12 11.11% 1001-1500 12 11.11% 1501-2000 4 3.70% 2001-5000 26 24.07% 5001-10000 7 6.48% 10001 2 1.85% Net farm income was not significantly related to Acres of Participation (r a 0.001). (b) Net farm income per cultivated acre was also determined for each farm operator. The mean value was $2.94 per acre (S.D. $3.36 per acre). Acres of Participation was not significantly related to net farm income per cultivated acre (r a 0.19). -102-13. Marital status of the operator The marital status of each respondent was determined. The frequency distribution of marital status is given in the following table. Table 33. Marital Status of Respondents Divorced, widowed Respondents Married Single or separated Total Number 92 12 4 108 Percent 85.19% 11.11% 3.70% 100.0% Marital status was compared with Acres of Participation as shown in the table below. Table 34. Marital Status of Operator and Acres of  Participation Marital Status Acres of Participation Married Single*  100 acres or less 60 101 acres or more 32 degrees of freedom • 1 Chi-square a 2.19 Chi probability = 0.135 14. Post secondary education of the operator Each respondent was asked i f he had received any of the following types of education beyond secondary school; some university, university degree, agricultural college, vocational college, or other. For Chi-square analysis this classification was changed to "Yes" i f 14 2 74 34 * Single includes single, and divorced, widowed or separated. -103-the respondent had obtained any of these types of education or "No" i f he had not. The frequency distribution of post-secondary education obtained by the operator is given in the following table, Table 35, Post Secondary Education of the Operator Number Percent Some University 6 5.567. University Degree 1 0.93% Agricultural College 5 4.63% Vocational College 14 12.96% Other 8 7.41% None 73 67.54% No Response .1 0.937. Total 108 100.0% Post-secondary education of the operator was compared with Acres of Participation as shown in the table below. Table 36. Post Secondary Education of the Operator and Acres of Participation Post Secondary Education  Acres of Participation Yes No No Response ,  100 acres or less 19 55 0 74 101 acres or more 15 18 1 34 34 73 1 108 degrees of freedom s 1 Chi-square = 3.25 Chi probability s 0.068 - 1 0 4 -1 5 . Courses taken in agriculture Each respondent was asked i f he had taken any of the following types of courses in agriculture; adult education courses in agriculture, high school courses in agriculture, university courses in agriculture or other types of courses in agriculture. For purposes of Chi-square analysis this classification was changed to "yes" i f the respondent had taken any of these courses and "no" i f he had not. A frequency distribution of the types of agriculture courses taken is given below. Table 3 7 . Courses Taken in Agriculture Percentage Number Adult Education Courses 14 12.967o High School Courses 1 0 . 9 3 % Vocational School Courses 5 4 . 6 3 % University Courses 3 2 . 7 8 % Other 0 0 None 84 7 7 . 7 8 % No Response 1 0 . 9 3 % Total 108 1 0 0 . 0 % Courses taken in agriculture was compared with Acres of Participation as shown in the following table. Table 3 8 . Agricultural Courses and Acres of Participation Agricultural Courses  Acres of Participation Yes No No Response  100 acres or less 13 61 0 101 acres or more 10 23 1 23 84 "T degrees of freedom • 1 Chi-square • 1.50 Chi probability s 0.218 74 34 108 -105-16. Other adult education courses Each respondent was asked i f he had even taken any adult courses in subjects other than agriculture. The frequency distribution of respondents by other adult education taken is given below. Table 39. Other Adult Education Courses Taken  by the Operator Respondents Yes No No Response Total Number 7 100 1 108 Percent 6.48 92.59 0.93 100.0 17. Post secondary education of the farm operator's wife Each respondent was asked what education his wife had obtained beyond secondary school. The frequency distribution of the number of respondents whose wives had obtained various types of post-secondary education i s given below. Table 40. Post Secondary Education of the Operator's Wife Respondents Number Percentage Some University 14 12.96% University Degree 0 0 Agricultural College 9 0 Vocational College 8 7.41% Other 0 0 None 67 62.04% No Response 19 17.59% Total 108 100.0% -106-Post secondary education of the farmer's wife and Acres of Participation were compared as shown in the following table. Table 41. Post Secondary Education of the Operator's Wife and Acres of Participation Post Secondary Education of Wife  Acres of Participation Yes No No Response  100 acres or less 13 46 15 74 101 acres or more 9 21 4 34 22 67 19 108 degrees of freedom s 1 Chi-square - 0.32 Chi probability • 0.579 18. Main agricultural product sold Each respondent was asked to indicate the agricultural product that was his main source of income over the past two years. A frequency distribution of the main sources of gross income is given below. Table 42. Main Agricultural Product Sold Number of Percentage of Product Respondents Respondents 1. Dairy (Milk, cream or butter) 2 1.85% 2. Beef 22 20.37% 3. Sheep 0 0 4. Hogs 8 7.41% 5. Wheat 73 67.59% -107-Table 42. (cont'd.) Number of Percentage of Product Respondents Respondents 6. Coarse Grains 0 0 7. O i l seeds 2 1.857. 8. Forage crops 0 0 9. Other Livestock 1 0.937. 10.Other crops 0 0 Total T08~ 100.07. Those farmers obtaining the most of their gross income from either wheat or beef were compared with respect to Acres of Participation as shown in the following table. Table 43. Respondents Reporting Wheat or Beef as the Main Source of Gross Income and Acres of Participation Main Sources of Income Acres of Participation Beef Wheat Other* 100 acres or less 19 45 10 74 101 acres or more 3 28 .3 34 22 73 13 108 degrees of freedom a 1 Chi-square a 3.64 Chi probability - 0.053 There was a significant relationship between beef or wheat as a main source of gross income and Acres of Participation. Those farmers reporting beef as a main source of gross income tended to participate less in the LIFT Program. * "Other" not included in the Chi-square analysis -108-19. Other agricultural products sold Each respondent was asked to state any other agricultural products he had sold during the past two years. A frequency distribution of the various other products sold is given below. Table 44. Other Agricultural Products Sold Number of Percentage of total Product Respondents time reported  1. Dairy (milk, cream, butter) 10 5.00% 2. Beef 56 28.00% 3. Sheep 1 0.50% 4. Hogs 31 15.50% 5. Wheat 32 16.00% 6. Coarse Grains 52 26.00% 7. O i l Seeds 12 6.00% 8. Forage Crops 0 0 9. Other Livestock 5 2.50% 10 .Other Crops 1 0.50% 200 100.0% 20. Enjoyment of farming Each respondent was asked i f he enjoyed his work as a farmer. A frequency distribution of the degree to which each respondent enjoyed farming is given in the following table. -109-Table 45. Enjoyment of Farming Very Not at Respondents Much Occasionally a l l Total Number 90 17 1 108 Percentage 83.33% 15.74% 0.93% 100.0% Acres of Participation was compared to enjoyment of farming as shown in the following table. Table 46. Acres of Participation and Enjoyment of Farming Enjoyment of Farming  Acres of Participation Yes No 100 acres or less 62 12 74 101 acres or more 28 6 34 "90 18 T08 degrees of freedom - 1 Chi-square s 0.01 Chi probability = 0.884 C. Variables of Specific Relevance to Agricultural Extension 1. Attitude toward change score Each respondent was asked a series of questions* from which was derived an attitude toward change score*. This score indicates the respondent's attitude toward changes in occupation and changes in place of residence and can be taken as an indicator of the respondent's acceptance of change in general. The range of possible scores was from 1 to 7 inclusive. The mean value of attitude toward change score was 3.76 (S.D. 1.78). The correlation coefficient * See appendix page 6, Question #23 * Farmers contact with Dis t r i c t Agriculturalist in three areas in British Columbia Isaac A. Akinbode, and M. J . Dorling -110-between attitude toward change score and Acres of Participation was 0.19 (not significant at the .05 level). 2, Social participation score Each respondent was asked what organizations he had belonged to in the past year, i f he had attended meetings of this organization, made a financial contribution, was a member of a committee or held any executive offices*. From this information a score was calculated* for each respondent. This score indicates the respondent's participation in formal groups or organizations. The mean value for the Social Participation score was 12.09 (S.D. 11.82). A frequency distribution of Social Participation scores is given in the following table. Table 47. Social Participation Scores Respondents Number Percent 0 27 25.00 1-5 13 12.04 6-10 19 17.59 11-15 10 9.26 16-20 13 12.04 21-25 11 10.19 26-30 5 4.63 31-35 5 4.63 35 5 4.63 Total 108" 100.0 Social Participation Score was not significantly related to Acres of Participation (r > 0.01). * See appendix page 6, Question #24 * C. Verner ARDA Socio-Economic Study (Chapin scale) -111-3. Personal extension contact score Each respondent was asked how many times in the past year he had attended meeting or f i e l d days put on by extension personnel, received a v i s i t to his farm by an extension person, visited the extension office, or talked to extension personnel on the telephone*. The Personal Extension contact score was calculated to be equal to the total of the above types of contacts*. A personal contact; is considered to be a contact involving face to face contact between the source and recipient of information were the recipient has an opportunity to cla r i f y his perception of the information by communicating with the source. The mean value of Personal Extension contact score and of each of i t s component parts is given in the table below. Table 48. Mean Value of Personal Extension Contacts and Correlation Coefficients with Acres of Participation Standard Correlation Contact Mean Deviation Coefficient 1. Extension Meetings or f i e l d days attended 0.51 1.20 0.03 2. Vi s i t s by Extension Personnel to Operator's farm 0.15 0.71 0.07 3. Vi s i t s to Extension office by the Operator 1.02 1.88 0.01 4. Telephone calls to the Extension Office 0.44 2.05 0.09 5. Personal Extension Contact Score 2.12 4.14 0.02 * See appendix, page 7, Question #25 (a) - (d) * C. Verner, ARDA Socio-Economic Study of B.C. -112-4. Impersonal extension contact score Impersonal contacts are defined as a situation where there is no face to face contact between the source and recipient of informa-tion and the recipient does not have an opportunity to cl a r i f y his perception of the information by communicating with the source. Each respondent was asked how many times in the past year he had listened to radio or T.V. programs put on by extension personnel, or read bulletins or circulars distributed by extension personnel*. The impersonal extension contact score was calculated for each respondent by summing the scores for each of the above types of contacts based on the following scoring scheme; 1-2 contacts a 1, 13-52 contacts - 2, 53-104 contacts a 3, 105-156 contacts = 4, 157 contacts a 5*. The mean value of the Impersonal Extension Contact Score and each of i t s component parts is given in the table below. Table 49. Mean Value of the Impersonal Extension Contacts  and Correlation Coefficients with Acres of  Participation Standard Correlation Contact Mean Deviation Coefficient 1. Number of Radio and T.V. programs listened to. 28.40 58.47 0.02 2. Number of newspaper articles read. 26.55 23.42 0.01 3. Number of bulletins or newsletter read 3.99 5.23 0.17 4. Impersonal extension contact score 3.17 1.81 0.06 * See appendix page 7, Question #25 (e) - (g) * C, Verner, ARDA Socio-Economic Study of B.C. -113-5. Total extension contact score The total extension contact score was calculated for each respondent by adding the personal and impersonal extension contact score. The mean value of the total Extension contact score was 5.30 (S.D. 4.75). The correlation coefficient with Acres of Parti-cipation was not significant (r a 0.004). 6. Use of formal management techniques score A score was calculated for each respondent based on the following scheme. 1. i f the farmer was able to give a "reasonable" answer ($10.00/acres to $25.00) to the question, "How much does i t cost you per acre to produce wheat (including a l l costs)? score 3 points 2. i f the farmer kept farm records in a farm record book score 1 point 3. i f the farmer had his records analysed to determine returns on his investment and returns to his labour and management score 3 points 4. i f the farmer kept a yearly record of the yields of his various crops score 2 points This score was meant to indicate the extent of the use made of generally accepted management tools. The weighting scheme was used to indicate the sophistication involved in using each item. The lowest possible score was 0 and the highest was 9. The mean value for the Use of Formal Management Techniques Score was 2.09 (S.D. 2.01) and the correlation coefficient with Acres of Participation was not significant (r - 0.02). •114-7. Sources of information about the LIFT Program Each respondent was asked to select from a l i s t of possible sources of information about the LIFT Program those sources of informa-tion he had found to be most useful. Each respondent gave three sources or less. The frequency distribution of the use of the various sources of information by the 108 respondents in the sample is given in the following table. Table 50. Most Useful Sources of Information About  the LIFT Program Source Number of Percent of total Times Reported Sources Reported 1. Farm papers 57 2. The Government leaflets on Operation LIFT 62 3. Radio 16 4. Television 21 5. District Agriculturist 10 6. Elevator Agent 49 7. Neighbours 13 8. Family and friends 8 9. Letter or phone c a l l to Operation LIFT head-quarters 3 10.Other government personnel 0 11.Special Meetings on the LIFT Program 16 12.Farm Organizations 0 13.Salesmen or Dealers 0 14.M.P. or M.L.A. 7 15 .Other sources 0 Total 262 21.75% 23.66% 6.10% 8.01% 3.81% 18.70% 4.96% 3.05% 1.14% 0 6.10% 0 0 2.67% 0 100.0% -115-For a detailed analysis of the relationship between sources of information used and Acres of Participation see Chapter i n . 8. Participation of the operator's wife in the decision about the  cropping program If the operator was married he was asked i f his wife had taken part in the process of deciding what the 1970 cropping program would be. If the operator said that his wife had taken part in the decision-making process he was asked i f he f e l t she had influenced his decision about the cropping program. Frequency distributions of the participation and the influence of the operator's wife are given below. Table 51. Participation of the Operator's Wife in the Decision about the Cropping Program Participation  Respondents Yes No No Response Total Number 35 54 19 108 Percentage 32.41% 50.00% 17.59% 100.0% Table 52. Influence of the Operator's Wife on the Decision About the Cropping Program Influence  Respondents Very Much Some None No Response Total Number 3 21 65 19 108 Percentage 2.78% 19.44% 60.19% 17.59% 100.0% Participation and influence of the operator's wife was compared to Acres of Participation as shown in the following tables. -116-Table 53. Participation of the Operator's Wife in the  Cropping Decision and Acres of Participation  Participation  Acres of Participation Yes No No Response 100 acres or less 21 38 15 74 101 acres or more 14 16 4 34 35 "54 ~19 108 degrees of freedom = 1 Chi-square • 0.61 Chi probability s 0.441 Table 54. Influence of the Operator's Wife in the Cropping Decision and Acres of Participation Influence  Acres of Participation yes No No Response  100 acres or less 12 47 15 74 101 acres or more 12 18 4 34 ~24 ~65 ~19 T08 degrees of freedom = 1 Chi-square a 2.97 Chi probability a 0.081 -117-APPENDIX C Means and 95% Confidence Intervals Variable Table 1. Means and 9570 Confidence Intervals for Selected Variables of Specific Relevance  to the LIFT Program 957» Standard Confidence Mean Deviation Interval 1. (a) Bushels of wheat on hand 6999 bu. (b) Bushels of wheat on hand per cultivated acre 8.90 bu. 2. (a) Bushels of available storage space 6622 bu. (b) Bushels of available storage space per acre 9.79 bu. 3. (a) Percent summer fallow in normal crop rotation 39.197. (b) Percent grain in the usual crop rotation 55.19% (c) Percent forage in the normal crop rotation 4. Knowledge of the LIFT Program (max score 6) 5. Average yield for wheat 6. Amount of variation with respect to wheat yield 7. (a) Total bushels of grain to be fed or sold as feed grain (b) Bushels of grain to be fed 5.51% 4.23% 25.81 bu/acre 1.02 3873 bu. 3324 bu. 7004 8353.2-5644.8 7.46 10.34-7.46 6143 7809.7-5434.3 7.14 11.17-8.41 12.64 41.62-36.76 11.88 57.48-52.90 14.53 8.31-2.71 1.35 4.49-3.97 7.44 27.29-24.33 0.63 1.15-1.89 4142 4705.6-3040.4 4163 4152.5-2495.5 -118-Table 1. (cont'd.) Variable Mean 95% Standard Confidence Deviation Interval 7. (cont'd.) (c) Bushels per acre of grain to be fed (d) Bushels of grain to be sold as non-Board feed (e) Bushels per acre of grain to be sold as non-board feed 8. Acres of wheat in 1969 9. Decrease in wheat acreage from 1969 10. Acres of summer fallow in 1969 11.Increase in summer fallow acreage from 1969 12 .Acres of forage crops in 1969 13. Increase in forage crops from 1969 14. Number of new crops grown in 1970 15. Acres of Participation 5.62 bu/acre 7.51 580.2 bu. 1809 0.62 bu/acre 1.63 267.7 acres 202.3 139.4 acres 138.5 295.5 acres 229.2 97.19 acres 151.2 34.25 acres 68.48 6.11 acres 17.33 0.41 acres 0.68 99.19 acres 125.6 7.12-4.12 949.5- 210.9 0.95-0.29 306.63-228.77 166.1-112.7 339.6- 251.4 126.3-68.1 47.43-21.07 9.44-2.78 0.54-0.28 123.36-75.02 -119-Table 2. Means and 95% Confidence Intervals for Selected Socio-Economic Variables Variable Mean Standard Deviation 95% Confidence Interval 1. Age of operator 49.06 years 12.03 51.37-46.75 2. Number of children 3.36 2.07 3.79-2.93 3. Grade completed by the operator 8.64 2.22 9.07-8.21 4. Grade completed by the operator's wife 9.88 1.96 10.29-9.47 5, Number of years farming 25.42 12.50 27.82-23.02 6. Total size of farm 963.7 acres 532.3 1066.1-861.: 7.(a) Number of cultivated acres 740.5 acres 450.5 827.2-653.8 (b) Number of rented cultivated acres 167.9 acres 269.5 219.8-116.0 8.(a) Total number of animal units 44.85 A.U. 50.58 54.58-35.12 (b) Animal units,Dairy 2.44 A.U. 7.54 3.89-0.99 (c) Animal units,Beef 34.03 A.U. 44.81 42.65-25.41 (d) Animal units,Swine 4.36 A.U. 8.81 6.05-2.67 (e) Animal Units,Sheep 0.071 A.U. 0.54 0.17-0.03 (f) Animal units,Horses 0.51 A.U. 1.35 0.77-0.25 (g) Animal units,Poultry 3.47 A.U. 20.29 7.37-0.43 9. Off farm earnings in 1969 $217.7 1063 423.2-12.17 -120-Table 2. (cont'd.) Variable Mean Standard Deviation 95% Confidence Interval 10. (a) Gross farm income 1969 (b) Gross farm income per cultivated acre, 1969 11. (a) Value of wheat sold 1969 (b) Value of wheat sold per cultivated acre, 1969 12. (a) Net farm income 1969 (b) Net farm income per cultivated acre 1969 $12,820 $19.71/acre $4530 $6 .24/acre $2055 $11,300 15,103-10,536 14.94 3254 3.41 2739 $2.94/acre 3.36 22.73-16.69 5187-3873 6.93-5.55 2614-1496 3.62-2.26 -121-Table 3. Means and 95% Confidence Intervals for Selected Variables of Specific Relevance to  Agricultural Extension Variable Mean 95% Standard Confidence Deviation Interval 1. Attitude towards change score (max.7) 3.76 2. Social participation score 12.09 1.78 11.82 4.10-3.42 14.36-9.82 3.(a) Personal Extension contact score. 2.12 4.14 2.92-1.32 (b) Extension meetings or f i e l d days attended 0.51 (c) Visits by Extension personnel to operator's farm 0.15 1.20 0.71 0.74-0.28 0.29-0.01 (d) Visits to Extension office 1.02 1.88 1.38-0.66 (e) Telephone calls to Extension office 0.44 2.05 0.83-0.05 4.(a) Impersonal Extension contact score 3.17 1.81 3.52-2.82 (b) Total number of Impersonal contacts 58.94 . (c) Extension radio and T.V. programs 28.40 (d) Extension newspaper articles 26.55 66.76 58.47 23.42 71.79-46.09 39.65-17.15 31.06-22.04 (e) Extension bulletins or circular letters 3.99 5.23 5.00-2.98 5.(a) Total Extension contact score 5.30 4.75 6.21-4.39 (b) Total number of a l l extension contacts 61.05 67.21 73.98-48.12 6. Use of Management techniques score (max.9) 2.09 2.01 2.48-1.70 -122-APPENDIX D Chi-Square Values for the Relationship Between  Information Sources Used and Selected Variables  Information Source Classified by: Method Origin Nature Selected Variable X 2 DF chi-prob X 2 DF chi-prob x 2 DF chi-prob 1. Age of operator 2.30 ** 0.68 2.53 0.64 .35 2 0.84 2. Grade completed 1.14 2 0.57 1.23 2 0.55 .86 1 0.36 3. Grade completed by operator's wife 1.20 2 0.55 .44 2 0.80 .75 1 0.39 4. No. cultivated acres in 1970 5.01 2 0.08 2.94 2 0.23 1.13 1 0.29 5. Bu. of wheat on hand 4.13 2 0.12 .55 2 0.76 .50 1 0.49 6. Bu. of wheat on hand per cult, acre 1.33 2 0.52 2.10 2 0.35 .09 1 0.76 7. Bu. of storage space .01 2 0.98 .63 2 0.73 .01 1 0.88 8. Bu.of storage space per cult, acre 2.86 2 0.24 ' .26 2 0.87 2.03 1 0.15 9. Percentage of summer fallow 7.07 2 0.03* 2.59 2 0.27 6.18 1 0.01* 10.Percentage of forage crops 4.38 2 0.11 .86 2 0.66 2.54 1 0.11 11.Total Animal units .83 2 0.67 .99 2 0.62 .00 1 0.95 12.Attitude towards change 1.08 2 0.59 2.24 2 0.33 .60 1 0.44 13.Social P a r t i c i -pation 3.43 2- 0.18 .97 2 0.62 2.94 1 0.08 -123-Method Origin Nature Selected „ chi- ^ chi- 2 " chi-Variable X DF prob X DF prob X DF prob 14.Personal Extension contact score 2.94 2 0.23 4.43 2 0.11 2.42 1 0.12 15.Impersonal Extension contact score 2.37 2 0.31 .95 2 0.63 .32 1 0.58 16. Extension contact score 2.06 2 0.36 2.20 2 0.33 1.62 1 0.20 17. Knowledge of the LIFT Program 6.28 2 0.04* 2.99 2 0.22 .01 1 0.88 18. Average yield of wheat 3.18 2 0.20 3.49 2 0.17 1.28 1 0.26 19. Uncertainty about wheat yield .62 2 0.74 4.55 2 0.10 .35 1 0.56 20. Management score 5.60 2 0.06 1.30 2 0.53 1.04 1 0.31 21. Acres of wheat in 1969 3.92 2 0.14 1.47 2 0.48 .05 1 0.81 22. Gross income 2.27 2 0.32 5.66 2 0.06 1.86 1 0.17 23. Value of wheat sold in past year 6.60 2 0.04* 1.29 2 0.53 .78 1 0.38 24. Net income 1.23 2 0.55* 2.69 2 0.26 .90 1 0.35 25. Acres of Participation 11.19 2 0.004* 7.27 2 0.03* .40 1 0.53 26. Total feed grain to be fed or sold 5.97 2 0.05* .75 2 0.69 .40 1 0.53 27.Soil zone 10.02 ** 0.04 2.44 ** 0.66 2.37 2.: 0.31 28 .Post-secondary education .44 2 0.80 1.22 2 0.55 .04 1 0.82 29.Post-secondary Education of wife ,35 2 0.84 .78 2 0.68 .00 1 0.95 -124-Method Origin Nature  Selected chi- „ chi- 2 chi-Var iable X DF prob X DF prob X DF prob 30 .Agricultural courses taken .93 2 0.63 .46 2 0.80 .64 1 0.43 31.Other adult education courses taken 2.89 ** 0.23 .23 2 0.89 1.87 1 0.17 32.Main Agricultural product sold .93 2 0.63 .49 2 0.79 .03 1 0.84 33 .Attitude towards the LIFT Program .95 2 0.63 5.43 2 0.06 .21 1 0.65 34. Plans to make changes 5.82 2 0.05* i.55 2 0.46 .23 1 0.64 35. Reasons for increasing summer fallow 3.35 2 0.19 6.06 2 0.05* .00 1 0.95 36. Reasons for reducing wheat acreage 7.61 ** 0.27 11.02 ** 0.09 2.19 3 0.54 37. Province (within the brown s o i l zone) 11.17 2 0.004* 3.70 2 0.15 .00 1 0.95 * significant at 95% level ** invalid chi-square -125 APPENDIX E Correlation Matrix Variables 1. Bushels of wheat on hand 2. Bushels of wheat on hand/acre 3. Bushels of available storage space 4. Bushels of available storage space/acre 5. % grain in usual crop rotation 6. % summer fallow in crop rotation 7. % forage crops in crop rotation 8. Change in f e r t i l i z e r expenditure 9. Knowledge of the LIFT Program 10. Average yield of wheat 11. Uncertainty regarding wheat yield 12. Bushels of grain to be fed 13. Bushels of grain to be fed/acre 14. Bushels to be sold as non-Board feed 15. Bushels to be sold as non-Board feed/acre 16. Total fed and non-Board feed sold 17. Acres of wheat in 1969 18. Decrease i n wheat acreage 19. Acres of summer fallow in 1969 20. Increase in summer fallow acreage 21. Acres of forage crops in 1969 22. Number of new crops grown in 1970 23. Increase in forage crops 24. Acres of Participation -126-Variables (cont'd.) 25. Age of operator 26. Number of children 27. Grade completed by operator 28. Grade completed by operator's wife 29. Number of years farming 30. Total size of farm 31. Number of cultivated acres 32. Number of cultivated rented acres 33. Animal units - dairy 34. Animal units - beef 34. Animal units - swine 36. Animal units - sheep 37. Animal units - horses 38. Animal units - poultry 39. Animal units - total 40. Off farm earnings 1969 41. Gross farm income 1969 42. Value of wheat sold in 1969 43. Net farm income 1969 44. Gross income per acre 1969 45. Value of wheat sold per acre 1969 46. Net farm income per acre 1969 47. Attitude towards change score 48. Social participation score 49. Extension meetings or f i e l d days -127-Variables (cont'd.) 50. Farm v i s i t s by extension personnel 51. Visits to the extension office 52. Telephone calls to extension office 53. Personal extension contact score 54. Extension radio or T.V. programs 55. Extension newspaper articles 56. Extension bulletins or circulars 57. Total impersonal extension contacts 58. Impersonal extension contact score 59. Total of a l l extension contacts 60. Total extension contact score 61. 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0 . 0 0 2 0 .131 0 . 0 2 1 0 . 1 2 0 - 0 . 0 1 7 0 . 1 2 7 - 0 . 1 1 3 - 0 . 0 4 2 - 0 . 0 8 0 0 . 0 9 5 - 0 . 0 8 7 - 0 . 0 8 4 0 . 0 1 2 - 0 . 1 1 4 0 . 0 4 4 0 . 0 4 4 0 . 2 1 9 - 0 . 1 1 0 0 . 0 4 3 - 0 . 1 0 2 0 . 1 0 8 - 0 . 1 0 3 0 . 0 3 3 0 . 0 4 6 - 0 . 0 3 6 0 . 1 3 0 - 0 . 0 4 3 2 1 . 2 2 . 2 3 . 2 4 . 3 0 . 3 1 . 3 8 . 3 9 . 1 .000 - 0 . 0 9 3 1 .000 - 0 . 0 6 4 0 . 0 7 2 - 0 . 0 2 1 0 . 0 6 8 0 . 0 2 9 - 0 . 0 4 8 0 . 0 6 0 0 . 0 3 7 0 . 2 4 5 - 0 . 0 1 3 0 .011 0 . 3 5 5 - 0 . 0 4 7 - 0 . 1 5 8 0 . 0 4 2 0 . 1 0 5 1 .000 0 . 1 0 8 - 0 . 2 3 6 0 . 0 0 5 0 . 1 3 5 0 . 0 5 9 0 . 1 4 0 0 . 0 6 5 - 0 . 0 8 1 - 0 . 2 5 3 0 . 2 5 8 0 . 0 3 3 1 .000 - 0 . 0 2 8 - 0 . 0 4 0 0 . 2 5 9 0 . 3 2 6 0 . 0 0 7 0 . 3 9 7 1 .000 0 . 0 4 9 1 .000 - 0 . 4 8 2 - 0 . 0 1 4 1 .000 - 0 . 3 9 2 - 0 . 1 2 2 0 . 5 9 4 1 .000 0 . S 5 0 0 . 0 8 7 - 0 . 4 0 3 - 0 . 3 2 9 1.000 - 0 . 2 7 2 - 0 . 0 7 5 0 . 4 1 9 0 . 3 7 0 - 0 . 1 7 3 1 .000 0 . 0 7 7 0 . 3 O 4 - 0 . 0 4 5 0 . 4 9 2 - 0 . 3 1 1 - 0 . 0 2 7 0 . 3 8 7 0 . 3 4 9 - 0 . 1 9 0 0 . 8 7 3 0 . 1 6 0 0 . 0 0 3 - 0 . 1 4 6 0 . 0 0 9 0 . 0 0 9 0 . 1 5 4 0 . 3 1 8 - 0 . 1 0 7 - 0 . 0 7 9 - 0 . 3 2 3 - 0 . 0 4 4 0 . 1 9 6 0 . 1 7 1 - 0 . 2 5 2 0 .501 -0 .041 0 . 0 6 5 - 0 . 0 8 4 0 . 0 0 6 - 0 . 1 2 1 - 0 . 0 9 8 - 0 . 2 4 7 0 . 0 6 6 0 . 2 3 1 0 . 1 9 5 - 0 . 1 8 5 0 . 3 7 0 - 0 . 1 5 9 - 0 . 0 6 6 - 0 . 0 4 6 - 0 . 1 9 4 0 . 1 5 9 0 . 0 3 1 - 0 . 0 0 1 - 0 . 1 4 9 - 0 . 0 6 8 0 . 0 6 6 - 0 . 0 7 9 - 0 . 0 3 6 - 0 . 0 8 9 0 . 2 0 5 - 0 . 0 9 5 0 . 0 0 2 - 0 . 0 2 2 0 . 0 3 7 0 . 1 2 1 0 . 0 0 4 - 0 . 0 3 5 0 . 0 6 9 - 0 . 0 8 0 0 . 1 4 7 - 0 . 1 0 3 - 0 . 0 3 2 - 0 . 0 4 6 0 .161 0 . 0 7 9 0 . 0 2 3 - 0 . 0 9 9 - 0 . 0 4 4 - 0 . 0 7 7 -0 .161 0 . 0 6 9 - 0 . 0 1 3 - 0 . 0 8 8 - 0 . 1 3 4 - 0 . 1 2 7 0 . 3 0 5 - 0 . 0 8 5 0 . 1 0 7 - 0 . 1 2 6 - 0 . 0 6 4 - 0 . 0 5 4 0 . 1 3 7 - 0 . 1 0 9 - 0 . 3 1 9 0 . 1 4 2 0 . 2 0 0 0 . 1 0 6 - 0 . 2 5 6 0 . 2 5 2 - 0 . 1 4 4 0 . 0 0 8 0 . 1 7 2 0 . 0 6 8 - 0 . 1 9 6 - 0 . 0 6 7 1 .000 0 . 6 0 7 1.000 - 0 . 1 4 5 - 0 . 0 7 9 1 .000 0 . 1 4 7 - 0 . 0 1 8 0 . 0 1 8 1 .000 - 0 . 0 1 0 - 0 . 0 2 8 0 . 0 1 8 - 0 . 0 3 9 1.000 - 0 . 0 6 9 - 0 . 0 5 5 0 . 1 3 6 - 0 . 0 5 6 - 0 . 0 3 6 1 .000 - 0 . 0 7 6 - 0 . 0 8 5 0 . 0 0 9 0 . 2 7 1 0 . 0 6 7 - 0 . 0 5 0 1 .000 - 0 . 0 8 5 0 .051 - 0 . 0 2 4 0 . 0 0 1 - 0 . 0 1 4 - 0 . 0 1 4 - 0 . 0 5 3 1 .000 0 . 0 7 0 - 0 . 0 1 5 0 . 1 6 0 01889 0 . 1 3 9 - 0 . 0 3 2 0 . 2 5 7 0 . 3 9 4 1 .000 - 0 . 0 8 7 - 0 . 0 7 3 - 0 . 0 0 2 - 0 . 0 3 7 - 0 . 0 2 1 - 0 . 0 2 7 - 0 . 0 0 8 0 . 0 1 6 - 0 . 0 3 1 I I-" Co (-< I 1.000 4 8 . 4 9 . 5 0 . 5 1 . 5 2 . 5 3 . 6 0 . 6 1 . 0 . 1 0 9 0 . 1 5 6 0 . 0 7 6 0 . 0 6 2 - 0 . 2 7 4 0 . 0 6 4 0 . 2 5 7 0 . 1 9 8 - 0 . 0 7 2 0 . 2 2 4 - 0 . 0 4 3 0 . 3 5 5 - 0 . 0 2 3 - 0 . 1 5 3 0 . 3 0 1 0 . 2 2 6 0 . 1 7 2 0 . 1 4 7 0 . 0 6 3 - 0 . 0 0 1 - 0 . 1 2 9 - 0 . 0 2 8 0 . 1 8 0 0 . 0 9 3 0 . 0 2 3 - 0 . 0 5 4 0 . 0 5 9 - 0 . 2 8 3 - 0 . 2 1 2 0 . 1 3 5 0 . 0 7 3 - 0 . 0 0 6 - 0 . 2 8 0 0 . 1 4 5 - 0 . 0 1 1 0 . 1 2 2 - 0 . 0 2 8 0 . 0 5 4 0 . 0 3 0 0 . 0 1 8 0 . 1 1 0 0 . 1 9 4 0 . 1 1 0 0 . 1 7 3 0 . 2 5 2 0 . 1 7 3 0 . 1 1 3 0 . 0 1 2 0 . 0 5 4 0 . 0 4 0 - 0 . 1 5 6 - 0 . 0 6 0 - 0 . 1 3 8 0 . 0 0 1 - 0 . 0 5 2 - 0 . 0 3 4 0 . 2 1 4 0 . 0 0 9 0 .081 0 . 0 6 4 -0 .101 0 . 1 5 4 0 . 2 4 7 0 . 0 0 5 - 0 . 0 9 0 - 0 . 0 1 7 0 . 0 0 9 0 .101 - 0 . 1 1 2 - 0 . 0 0 2 - 0 . 0 5 9 0 . 0 0 4 - 0 . 0 4 3 0 . 0 9 0 0 . 1 0 2 0 . 0 3 3 0 . 0 9 9 0 . 1 3 6 - 0 . 1 8 6 - 0 . 0 5 3 0 . 1 9 3 - 0 . 0 0 8 0 . 0 3 3 0 . 0 6 6 0 . 0 0 9 - 0 . 0 9 4 - 0 . 0 2 1 - 0 . 0 3 4 - 0 . 0 2 5 - 0 . 0 2 1 - 0 . 0 0 9 0 . 0 0 4 - 0 . 0 1 6 - 0 . 2 4 0 - 0 . 0 1 6 0 . 0 9 5 0 . 0 9 7 0 . 1 0 4 0 . 0 4 4 - 0 . 4 1 8 - 0 . 0 3 4 0 . 2 8 3 0 . 2 1 5 - 0 . 1 0 7 0 . 0 4 4 - 0 . 0 2 3 - 0 . 1 1 9 - 0 . 0 5 9 - 0 . 0 7 4 0 . 1 6 0 0 . 0 0 6 0 . 0 8 4 0 . 0 6 4 0 . 0 5 2 0 . 1 4 2 0 . 1 3 0 0 . 1 2 0 0 .141 - 0 . 0 0 7 0 . 0 5 7 0 . 1 0 2 0 . 1 3 6 - 0 . 0 2 8 - 0 . 2 2 4 - 0 . 1 4 6 - 0 . 0 7 6 0 . 0 5 9 - 0 . 0 8 6 - 0 . 0 2 2 0 . 0 0 4 0 . 1 5 5 - 0 . 0 4 1 0 . 0 4 4 - 0 . 0 1 0 - 0 . 0 2 3 - 0 . 0 1 9 0 . 0 5 4 - 0 . 0 6 5 0 . 0 9 4 - 0 . 0 8 4 0 . 0 6 0 0 . 0 0 4 0 . 0 6 2 0 . 0 4 1 0 . 2 1 0 - 0 . 1 9 3 0 . 0 2 3 - 0 . 0 1 0 - 0 . 1 8 8 0 . 0 8 9 0 .041 - 0 . 3 9 3 - 0 . 0 8 6 0 . 0 8 9 0 . 2 0 2 0 . 0 4 9 0 . 1 0 3 0 . 0 7 7 - 0 . 0 0 1 - 0 . 0 8 2 - 0 . 0 8 3 0 . 0 3 8 0 . 0 5 3 0 . 2 4 6 0 . 0 7 0 0 . 1 3 4 0 . 1 7 8 0 . 1 4 0 0 . 1 5 7 - 0 . 0 3 3 0 .171 0 . 0 3 7 0 . 1 5 3 0 . 1 7 5 0 . 1 6 3 0 . 1 7 2 0 . 0 3 3 -0 .191 0 . 4 4 5 0 . 3 2 4 - 0 . 1 5 1 - 0 . 1 4 8 0 . 1 4 7 0 . 1 0 9 - 0 . 0 3 4 0 . 1 3 9 0 . 0 8 5 0 .121 0 . 2 0 0 - 0 . 0 3 5 - 0 . 0 4 8 0 . 1 1 3 0 . 0 0 3 -0 .001 0 . 1 2 4 0 . 0 1 2 0 . 0 7 6 0 . 0 1 9 0 . 1 2 9 0 . 1 6 9 31 32 0 . 4 1 1 0 . 2 1 2 0 . 6 3 8 0 . 2 9 8 0 . 2 6 0 0 . 0 6 1 - 0 . 2 2 7 - 0 . 1 2 6 - 0 . 0 1 4 - 0 . 0 8 8 - 0 . 0 8 9 - 0 . 1 2 3 0 . 0 5 5 - O . 0 7 3 0 . 0 1 0 - 0 . 1 7 3 0 . 1 8 3 0 . 2 2 8 0 .181 0 . 1 2 8 0 . 1 6 6 0 . C 2 9 - 0 . 0 3 2 - 0 . 0 2 5 0 . 1 4 4 0 . 0 8 9 - 0 . 0 5 6 - 0 . 1 4 8 - 0 . 0 0 9 - 0 . 0 6 5 0 . 1 3 5 0 . 0 3 0 - 0 . 0 4 2 - 0 . 1 5 0 0 . 0 1 3 - 0 . 0 9 9 - 0 . 0 3 3 - 0 . 1 4 4 0 . 1 3 3 0 . 0 3 8 0 . 1 3 3 0 . 1 3 6 33 34 0 . 0 3 5 0 . 6 2 6 - 0 . 2 2 5 - 0 . 0 3 5 0 . 0 4 3 0 . 5 8 4 0 . 1 2 2 0 . 4 6 7 - 0 . 1 3 2 - 0 . 2 2 4 0 . 1 1 1 0 . 5 0 2 0 . C 9 6 0 . 1 6 8 0 . 0 1 2 0 . 2 8 0 0 . 0 2 7 0 . 0 5 2 - 0 . 0 5 4 0 . 1 8 1 - 0 . 0 0 9 0 . 2 1 0 0 . 0 0 6 0 . 3 1 5 - 0 . 0 0 3 0 . 2 9 7 - 0 . C 4 0 0 . 1 0 6 0 . 2 3 7 0 . 0 2 9 0 . 1 0 7 0 . 0 1 6 0 . 0 5 7 0 . 1 0 4 0 .151 0 . 1 6 8 0 . 0 5 6 0 .121 0 . C 5 4 0 . 3 2 5 - 0 . 0 6 3 0 . 2 2 5 35 36 0 . 1 1 0 - O . 0 2 6 - 0 . 1 2 3 - 0 . 0 9 2 - 0 . 0 1 9 - 0 . 0 4 5 0 . 2 2 0 0 . 0 1 7 - 0 . 1 5 9 -0 .C81 - 0 . 0 1 3 -0 .C31 0 . 0 9 5 - 0 . 0 7 9 0 . 1 3 2 - 0 . 0 1 2 0 . 0 6 7 - 0 . 0 5 6 0 . 0 6 9 - 0 . 0 2 8 - 0 . 0 0 3 0 . C 2 0 - 0 . C 5 7 - 0 . 0 2 9 0 . 0 0 2 - 0 . C 2 6 - 0 . 0 4 5 - 0 . C 4 2 0 . 0 5 0 0 .041 0 . 2 0 7 0 . C 9 6 - 0 . 0 0 6 - C . 0 1 5 0 . 0 6 4 0 . 0 3 5 - 0 . 0 0 6 - 0 . 0 1 6 0 . 0 2 5 - 0 . 0 1 0 0 . 1 1 4 - 0 . 0 9 5 37 38 0 . 0 0 9 0 . 4 9 9 - 0 . 0 6 8 - 0 . 0 0 2 0 . 0 7 3 0 . 1 2 1 0 . 0 0 1 0 . 4 2 2 -0 .131 - 0 . 0 0 9 0 . 0 6 8 0 . 1 0 6 - 0 . C 3 0 0 . 0 3 2 0 . 1 6 3 - 0 . 0 1 5 - 0 . 0 9 2 0 . 2 5 1 - 0 . C 6 0 0 .071 - 0 . C 7 7 0 . 0 3 4 - 0 . C 5 6 O. J 19 - 0 . 1 0 0 0 . 1 5 9 0 . 1 6 3 - 0 . 0 7 0 0 . 1 2 6 - 0 . 0 2 1 0 . 1 8 3 - 0 . 0 6 6 0 . 2 0 1 - 0 . 0 7 4 0 . 2 5 2 - 0 . 1 2 1 0 . 1 9 4 - 0 . 0 6 3 0 . 0 0 8 0 . 0 9 2 - 0 . C 1 1 - 0 . C 0 4 39 40 0 . 7 4 7 - 0 . 0 6 7 - 0 . 0 9 1 0 . 0 6 6 0 . 5 6 9 - 0 . 0 7 1 0 . 6 1 3 0 . 0 2 8 - 0 . 2 5 7 0 . 3 3 9 0 . 5 0 0 - 0 . C 4 3 0 .191 0 . 1 4 3 0 . 2 7 1 0 . 1 6 0 0 . 1 5 9 - 0 . 0 8 8 0 . 1 9 1 - 0 . C 4 4 0 . 1 9 6 0 . 1 3 8 0 . 3 1 6 0 . C 5 5 0 . 3 2 4 0 . 0 5 7 0 . 0 5 6 - 0 . 0 3 0 0 . 0 6 ^ 0 . 0 2 0 0 . 0 4 6 - 0 . 1 0 6 0 . 0 7 6 - 0 . 0 2 8 0 .141 - 0 . 1 2 1 0 . 0 9 4 - 0 . C 2 4 0 . 3 3 8 0 . C 0 4 0 . 2 0 7 0 . 2 2 4 0 .290 1.000 0 . 6 9 5 0 .351 0 .691 -0 .149 0 .024 0 .666 0 . 4 3 5 1.C00 0 .154 - 0 . C 1 9 1.C00 0 . 5 2 7 0.C77 0 .838 0 . 5 8 9 0 . 1 4 4 1.000 0 . 1 2 9 O.C23 0 .C60 0 . 1 2 6 0 . 0 3 9 0 .072 1.000 0 .168 0 .C69 0 .085 0 . 0 7 3 -0 .022 0 .058 0 .307 l .COO 0 .357 0 .043 0 .063 0 .205 - 0 . 0 8 3 0 .029 0 .045 0 .212 l .OCO 0 . 4 8 3 0 .089 0 .527 0 .296 - 0 . 0 2 5 0 .338 -0 .090 0 .C07 0 .317 1.000 0 .462 0 .165 0 .448 0 . 3 1 5 0 .075 0 .338 0 .097 0 .183 0 .322 0 .602 0.291 0.CO8 0 .259 0 .359 0 . 0 6 3 0 .364 0 .066 0 .C57 0 .241 0.354 0 .542 0 .106 0 .442 0 .432 0 . 0 3 7 0 .402 0 .C74 0 .174 0 .610 0.711 -0 .027 0.C24 0 .068 - 0 . 0 2 7 -0 .007 0 .138 0 .030 -0 .045 -0 .029 -0.081 0 .143 0.C68 0.102 0 .111 - 0 . C 0 5 0.C8O 0 . 1 0 9 0 .217 0 .C82 0 .126 0 . 0 8 5 0.C61 0 .173 - 0 . 0 0 6 - 0 . 0 5 8 0.191 0 .C51 0.C91 0 . 1 3 7 0.031 0 .031 0 .049 0 . 1 0 7 0 .013 -0 .012 0 .164 0 .069 0 .044 0 .014 -0 .C24 0 .121 -0 .C20 0 .164 0 .001 - 0 . 1 3 2 0 .197 0 .129 0 .221 0 . 0 5 5 0 .068 0 .064 0.C55 0 .134 0 .040 - 0 . C 1 0 0 .1 0 . C 7 3 0 .054 0.051 0 .020 0 .090 0 .463 0 .387 - 0 . 0 1 5 0 .434 0 . 1 1 3 0 .236 0 .554 0 .662 -0.C01 0 . 0 5 9 0 .088 -0 .024 - 0 . 0 0 5 0 .140 0 .222 0 .340 0 .056 0 .216 l.COO 0 .757 0 .723 1.000 LO I -0 .C34 0 .C87 0 .005 l .COO 0 .154 0 .148 0 .188 0 .146 1.000 0 .062 0 .013 0 .079 0 .006 0 .235 l .COO 0.C29 0 .129 0 .077 0 .928 0 .497 0 .166 1.000 0 .040 0.141 0 .116 0 .557 0 .624 0 .498 0 .746 l .COO 0 .076 0 .173 0 .133 0.922 0 .506 0 .170 0.998 0 .748 l .COO 0 .687 0 .686 0 .925 0 .216 0 .404 0 .260 0.352 0 .483 0 .406 1.000 0 .225 0 .095 0 .257 0 .046 0 .016 -0 .085 0 .040 - 0 . C 0 7 0 .C55 0 .221 l .COO -134-APPENDIX F Multiple Regression Analysis of 60 Quantitative and  14 Qualitative Variables The stepwise multiple regression routine was used to determine which of 60 quantitative and 14 qualitative variables were s t a t i s t i c a l l y significant in jointly explaining the variation in Acres of Participation. The variables used in this routine are listed in Table 58. Table 1. . Quantitative and Qualitative Variables 1. Age of operator ...2. No. of children 3. Grade 4. Grade - wife 5. Yrs. farming 6. Size of farm 7. No. cult, acres 8. No. rented acres 9. Bu. wht. OH. 10. Bu. wht. OH/acre 11. Bu, storage space 12. Bu. storage space/acre 13. % grain 14. % s.f. 15. 7o forage 16. A.U. dairy 17. A.U. beef 18. A.U. swine 19. A.U. sheep -135" Table 15. (cont'd.) 20. A.U. horses 21. A.U. poultry 22. A.U. Total 23. Attitude towards change score 24. Social participation score 25. No, f i e l d days and meetings 26. No. of F.V. by D.A. 27. No. of O.V. to D.A. 28. No. of ph. calls to D.A. 29. Personal Ext. score 30. No. of Ext. Radio or T.V. programs 31. No. Ext. newspaper articles read 32. No. of Ext. Bulletins or circulars 33. Total Impersonal Ext. contents 34. Impersonal Ext. content score 35. Total No. Ext. contents 36. Total Ext. content score 37. Knowledge of LIFT Program 38. Ave. Wht. yield 39. Amount of variation 40. Bu. of grain to be fed 41. Bu. of grain to be fed/acre 42. Bu. of grain to be sold n.b, 43. Bu. of grain to obe sold n.b./acre 44. Acres wht. 1969 -136-Table 1 ( c o n t ' d . ) 45. Acres of forage 1969 (est.) 46. Acres of S.F. 1969 47. Decrease in wht. acreage 48. Increase in s.f. acreage 49. Increase in forage acreage 50. No. of new crops 51. Management techniques score 52. Off-farm earnings 53. Gross income 1969 54. Value of wht. sold 1969 55. Net income 1969 56. Gross/acre 1969 57. $ wht./acre 1969 58. Net/acre 1969 59. Attitude towards the program 60. Acres of participation 61. Marital status 62. Post Secondary Education 63. Courses in Agriculture 64. Other A.E. courses 65. Post Secondary Education of the wife 66. Occurrence of wet spring weather 67. Knowledge of costs of production 68. Keeping farm records -137.-Table 1 (cont'd.) 69. Analysis of records 70. Record of crop yields 71. Plans to make changes 72. Participation of operator's wife 73. Influence of operator's wife 74. Total bushels to be fed or sold as n.b. feed. The following table gives the s t a t i s t i c a l l y significant (.05 level) variables which jointly explain Acres of Participation. Table I'D. Stepwise Regression Analysis of 60 Quantitative  and 14 Qualitative Variables F-prob Std. Error of Y Variable s 0.7397 s 0.0000 = 67.4927 Coefficient Std. Error F-ratio F-prob Constant Grade completed by operator's wife No. of cult acres Bu. of wheat on hand Bu. of storage space per acre Animal units of beef No. of Extension newspaper articles Bushels of grain to be sold as non-Board feed grain Acres of wheat in 1969 Acres of s.f. in 1969 Attitude towards the LIFT Program -101.2450 14.1828 0.2911 0.00686 - 2.7749 - 0.5820 - 0.8876 - 0.0090 0.2959 - 0.7275 34.5201 36.8569 3.9309 0.0546 0.00133 1.0811 0.1963 0.3119 0.0041 0.0873 0.0823 16.2556 13.0181 28.3874 26.6406 0.0006 0.0000 0.0000 6.5874 0.0115 8.7933 0.0039 8.0968 0.0055 4.7981 11.4804 78.1580 4.5096 0.0294 0.0012 0.0000 0.0344 -137-The multicolinearity in the previous regression equation is indicated in the following table of simple correlation coefficients. Table 3 J . Multicolinearity in Explanation of Extent  of Participation 1 2 3 4 5 6 7 8 9 1. Grade of wife 1 2. No. cult.acres .35 1 3. Bu.wht. on hand .21 .57 1 4. Bu.storage/acre -.07 -.20 -.39 1 5. A.U. beef .20 .15 -.06 -.03 1 6. No. Extension Newspaper articles .25 -.01 -.01 .09 .03 1 7. Bu. of grain to be sold non-Board .09 .35 .09 -.02 -.09 -.03 1 8. Acres of wht./69 .29 .88 .61 -.30 -.12 -.05 .31 1 9. Acres of s.f./69 .31 .91 .62 -.27 -.01 -.11 .35 .84 1 (no. of observations s 108) r - ,19 (significant at .05 level) -138-APPENDIX G Stepwise Regression Analysis of the 16 Variables Included  in Both the Net Cash Income Maximizing Model and the  Extension of the Net Cash Income Maximizing Model;  Data in Log. Form The following 16 variables were converted into Natural Log form and put into a Stepwise Regression Routine. 1. Age of operator 2. Grade of operator 3. Grade of operator's wife 4. Bushels of wheat on hand 5. Bushels of storage space 6. Percentage summer fallow 7. Attitude towards change 8. Social Participation socre 9. Total extension contact score 10. Knowledge of the LIFT Program 11. Average wheat yield 12. Amount of variation in wheat yield 13. Acres of wheat 1969 14. Number of new crops 15. Attitude towards the LIFT Program 16. Total bushels of grain to be fed or sold as non-Board feed grain. -139-Table 11. Results of the Stepwise Regression Using Data in Log Form R 2 s 0.3284 F-probability = 0.0000 Std. error Y s 1.8574 Variable Coefficient Std. Error F-ratio F-probability Constant -2.8953 0.8918 Knowledge of the LIFT Program 1.3653 0.4525 9.1034 0.0034 Acres of wheat in 1969 0.8091 0.1500 29.1080 0.0000 The purpose of attempting a stepwise regression analysis with the data in logrithmic form was to determine i f the hypothesized relationships between the independent variables and Acres of Participation tended to be nonlinear. If the R 2 value of the regression equation of the data in log form was greater than the R value for the regression equation of number values i t could be concluded that the relationships between the independent variables and the dependent variable were more nonlinear than linear. WHEAT REDUCTION PROGRAM By now you will have heard about the federal govern-ment's wheat inventory reduction program for 1970. You probably have a great many questions about the program. This is an attempt to answer some of them. The three most frequently asked questions are: I Why was a program such as this necessary? , II What is it trying to accomplish? Ill How can I make best use of it? 1. WHY WAS A REDUCTION PROGRAM NECESSARY? On July 31, 1970, we will begin a new wheat crop year. At that time there will be almost one billion bushels of wheat in storage. This is enough to meet our normal wheat needs for almost two years. If farmers in 1970 were to har-vest the size of crop they have been harvesting in recent times, the storage stocks would grow way over the billion bushel figure. The load in the marketing pipeline is such that it is difficult to get the right grades in the right place at the right time. It also means that storage and transportation facilities are not able to handle other crops as efficiently as they should. If the government had not introduced the wheat inven-tory reduction program, where would this have left the wheat farmer? You probably would have done one of two things. You would probably have continued to grow wheat or you would have switched to growing another crop. Either way, serious problems would have developed. Growing more wheat would simply have added more to the huge stockpile — a stockpile that costs money to store and which would never be needed to meet market demands. , In the three prairie provinces there is almost as much land normally sown to wheat as to all other crops com-bined. Any wholesale shift to other crops could spell a disastrous drop in price and yery large carryovers. A third alternative, of course, would'tea for farmers to voluntarily cut wheat acreage! while not s^ Stettfejg to other crops. On their own in 18S9, producers reduced wheat plant-ings fay five million acres, however, the. financial position of most prairie grain growers makes it quite unrealistic to expect thenv to cut wheat acreage further without some outside help: Reduction in surplus, wheat stocks is one method of strengthening our bargaining position with foreign buyers; certainly our current stock position places us in a weakened bargaining position with ftis buyers. The iead taken by Canada should spur other wheat producing countries to similar action which in turn will stabilize the world wheat economy. 2. V5JHAT DOES THE'WHEAT INVENTORY RI0UCT8ON PROGRAM HOPE TO ACCOMPLISH ? The aim of the program is to cut the amount of wheat in storage by half. There are two ways to reduce storage, of course. One way is to sell more wheat. The other is to plant less. Every effort is being made to increase export sales. Increased food aid and more attractive credit have helped the Canadian Wheat Board to make export sales that will reach 375,000,000 bushels of wheat this crop year. That's more than any year, except one, in the history of the Board from 1943 to the year of the first major Russian purchase in 1963. Market forecasts indicate that we will sell the wheat production from about 20 million acres a year. The reduc-tion program is intended to get rid pi the backlog so we can return to normal as quickly as possible. The program is designed to wipe out our wheat surplus in one year — if farmers back the program to its fullest We could then return to normal production next year. An important feature of the.program is that it can re-duce wheat surplus without encouraging farmers to switch to other crops. This is of benefit to all farmers in Canada — not just the western wheat producer. The decision on what you are going to plant on your farm is, of course, up to you. However, we urge all wheat growers to examine thsi? position very carefully before seeding $jeir< crops this year. If you have significant  amounts-of "^ unsold wheat on hand-now, it is almost cer- tainly to your advantage to seed'no wheatJfoisysar and to  fallow- your land insteadT T, • : . . . 3. HOW CAN YOU USE THE PROGRAM TO BEST ADVANTAGE? The details of the program are set out for you else-where on this leaflet. There are, however, two general points to remember: i) Wheat acreage reduction payments will be made only if summerfallow or perennial forage acreage is increased. ii) Wheat quotas will bebased entirely on summer-fallow or increase in forage acreage. THE LOWER INVENTORY FOR TOMORROW PROGRAM General » Summerfallow includes any land held out of pro-duction in 1970 if in 1969 the land was cultivated but not in perennial forage. o Provisions will be made in the programs for farmers wishing to seed cover crops on summerfallow which might otherwise be subject to erosion. Details will be announced shortly. 0 No producer may receive payments for more than 1,000 acres of reduction in wheat acreage. « This program applies to all wheat except Soft White Spring Wheat. o The program will be backed up by a full on-the-farm inspection system to prevent artificial division of farm units and other abuses that might occur. Wheat Reduction Payments A payment will be made to every 1970 permit book holder who this year reduces total acres seeded to wheat from that stated in his 1969 permit book. Total acres eli-gible for payment for any producer may not exceed, the total by which he increases summerfallow, plus the' net increase in acres of perennial forage. Putting it another way: you will receive your full payment only if you increase the sum of your 1970 summer-fallow and perennial forage acreage by an amount equal to that removed from wheat. For example, if last year you had 400 acres in wheat, 200 acres in summerfallow and 200 acres in perennial for-age, you must have 800 acres in summerfallow and/or perennial forage (of which 200 acres must be perennial forage) this year to get payment on your full 400 acres taken out of wheat. If, in this example, you were to plant the 400 acres to barley, you would receive no acreage payment at all. You will receive $6.00 for each acre entitled to the reduction payment. Part of the payment will be sent to you before the end of July, with the balance in the fall. You may choose to seed the acreage you have taken out of wheat to a perennial forage this year. If you do, you will receive the $6.00 reduction payment plus an additional _ $4.00 for each acre by which your 1970 forage acreage ex-' ceeds your 1969 acreage, provided the acreage remains in forage until the land is inspected in the mid-summer of 1971. The extra $4.00 payment will be made after this inspection. For example, if you had 200 acres in wheat and 200 acres in perennial forage last year, you will receive a total of $2,000 if you put the wheat acreage into perennial forage this year, provided you leave the acreage that was in per-ennial forage last year untouched. If you were to break up all the land that you had in perennial forage last year, even for summerfallow, you would receive no payment at all — even though you had planted 200 acres of new perennial forage. A maximum of 2,000,000 acres has been set to qualify for payments on additional perennial forage, but it is ex-pected that this will be more than sufficient to handle all farmers wishing to participate. Special Provisions Some producers voluntarily got out of wheat last year. ' To provide these farmers with assistance under the pro-gram, two special provisions have been added. 1. If you planted less than 100 acres of wheat in 1969, according to your permit book, and plant no wheat in 1970, you may use your 1968 quota book up to 100 acres as the basis for comparison with 1970 for payments under the wheat reduction program. In such cases, the 1968 wheat acreage used to calculate the payment shall not exceed , 100 acres. 2. If, according to your 1969 permit book, you had more than half your specified land in summerfallow last year, you may treat the amount over half as if it had been seeded to wheat in 1969 for reduction payment purposes. For example if you have a total of 600 specified acres and you fallowed 600 acres, you may count, for payment pur-poses, 200 acres of the summerfallow as if they had been seeded to wheat. Grain Delivery Quotas ° Acres qualified for wheat delivery quotas in 1970 will be the total of 1970 summerfallow and the increase in perennial forage acreage in 1970 over 1959. In addition, 25 per cent of the summerfallow stated in the 1969 permit book may be claimed for quota purposes this year. For example, if a farmer has 1,000 acres in summerfallow this year and had 800 acres in summerfallow last year, he has 1,000 acres plus 200 acres from last year eligible for quota. This gives him a total of 1,200 acres qualified for 1970 quota. o Permit book holders in 1970 will receive wheat de-livery quotas of eight bushels for each acre qualified for wheat quota. ° The eight bushel quota will apply so long as quali-fied acreage does not exceed 53 million acres. At this level wheat deliveries in the 1970-71 crop year would be about 425 million bushels. This was the total acreage in wheat and summerfallow in 1969 and therefore is unlikely to be exceeded under the new program. ° If qualified acreage is less than 47 million acres then the quota may be raised to nine bushels per qualified acre. o If the demand for durum or specific grades of wheat requires additional deliveries, special quotas would be opened on the basis of acreage qualified for wheat quota. o There will be no unit quotas in the 1970 quota system. ° Acres seeded to wheat in 1970 will not qualify for quota. ° Quotas for oats, barley, soft spring wheat, and other crops to which delivery quotas apply, will be based on the acres seeded to each crop as stated in the producers' 1970 permit book. o Summerfallow that comes from working up old for-, age stands or land not cultivated in 1969-will not count as summerfallow for the purposes of this program. o A producer may if he wishes allocate any or all of his acres qualified for wheat quota to any other crop — in which case the entitlement to wheat quota would be re-duced accordingly. Here are a few examples of how the acreage reduction payment and wheat quota system would work in some individual cases: Example 1 Size of farm: 1,000 acres Allocation of crops in 1969 permit book: Wheat: 400 acres Summerfallow: 400 acres Barley: 200 acres Wheat on hand: 9,000 bushels Allocation of crops in 1970 permit book: Wheat 0 acres Summerfallow: 1,000 acres Barley 0 acres Acreage reduction payment ($6.00 x 400 acres) = $2,400 Wheat quota entitlement: 1,000 acres for 1970 summerfallow plus 100 acres from 1969 summerfallow=1100 acres x 8 bushel quota =8,800 bushel wheat quota This farmer will receive a direct reduction payment of $2,400 plus entitlement to deliver 8,800 bushels. He will thus be able to dispose of the wheat carried over on his farm. Example 2 Size of farm: 1,000 acres Allocation of crops in 1969 permit book: Wheat: 400 acres Summerfallow: 400 acres Barley: 200 acres Wheat on hand: 9.000 bushels Allocation of crops in 1970 permit book: Wheat 400 acres Summerfallow: 400 acres Barley: 200 acres Acreage reduction payment $0.00 Wheat quota entitlement: 400 acres for 1970 summerfallow plus 100 acres for 1969= 500 acres x 8 bushels for a total wheat quota of 4,000 bushels This farmer will receive no acreage reduction payment and a 4,000 bushel wheat quota which means he could deliver less than half this year's crop, and dispose of none of his surplus. He would receive a barley quota based on his acreage in that crop. Example 3 Size of farm: 400 acres Allocation of crops in 1969 permit book: Wheat: 200 acres Perennial Forage: 100 acres Summerfallow: 100 acres Wheat on hand: 3,000 bushels Allocation of crops in 1970 permit book: Wheat: 0 acres Perennial Forage: 200 acres Summerfallow: 200 acres Acreage reduction payment 200 acres x $6.00= $1,200.00 plus 100 acres of new perennial forage at $4.00=$400.00 Total payment = $1,600 Wheat quota entitlement: 300 acres for 1970 summerfallow and new forage plus 25 for 1969 summerfallow= 325 acres x 8 bushels=2,600 bushels. This farmer would receive total payments of $1,600 plus a total wheat quota of 2,600 enabling him to dispose of almost all his wheat. Example 4 Size of farm: 400 acres Allocation of crops in 1969 permit book: Wheat: 200 acres Perennial Forage: 100 acres Summerfallow: 100 acres Wheat on hand: 3,000 bushels Allocation of crops in 1970 permit book: Wheat: 0 acres Perennial Forage: 0 acres Rapeseed: 300 acres Summerfallow: 100 acres Acreage reduction payment=$0.00 Wheat quota entitlement: no entitlement on 1970 allocation; 25 acre entitlement from 1969 summerfallow for total quota of (25 x 8) = 200 bushels This farmer lost his acreage reduction payment because the wheat reduction was not accompanied by any rise in summerfallow or perennial forage acreage. Reduction in perennial forage acreage in 1970 was deducted from sum-merfallow acreage for quota entitlement. Example 5 Size of farm.- 600 acres Allocation of crops in 1969 permit book: Wheat: 200 acres Summerfallow: 200 acres Barley: 200 acres Wheat on hand: none (hailed out in 1969) Allocation of crops in 1970 permit book: Wheat: 162 acres Summerfallow: 438 acres Acreage reduction payment: 38 x $6.00=$228.00 Wheat quota entitlement: 438 acres for 1970 summerfallow and 50 acres for last year's summerfallow=488 acres x 8 bushels = 3904 total bushels quota. Given a yield of 24 bushels per acre he will be able to dis-pose of all his 1970 wheat production. A higher expected yield would require less acres seeded to wheat and more in summerfallow to ensure disposal of the anticipated crop. A lower expected yield would permit more wheat acres and less summerfallow. Enquiries should be directed to: "OPERATION LIFT"-500 FINANCIAL BUILDING REGINA, SASK. Phone 522-2637 OPERATION LIFT Lower Inventory For Tomorrow Seeding time is just about here. The big question this year is, "Should I plant any wheat?" Our answer is a definite "NO" in most instances has of course the final decision is up to you. Look at it this way: » you will receive a $6.00 payment for every 1969 wheat acre taken out of production in 1970. provided this reduction is reflected in increased summer*-.Mow or peren-nial forage acreage. . • you will receive a wheat quota of eight bushels for ,i>acn acre of 1970 summerfallow and additional perennial .forage, plus 25 per cent of your 1969 summerfallow acreage. • even if you don't have wheat on hand you can use your wheat quota to deliver oats, barley, rye, rapeseed or flax. This is a golden opportunity to reduce the stocks of grain that have been piling up on your farm. Remember — Wheat quotas will be earned on summi"'allow and additional perennial forage acreage, plus 25 per cent of ysur 1969 surnmerfallow. Land sown to wheat will cost you wheat quota. You'will not be able to deliver wheat on barley or oat quotas. If you reduce your perennial forage acreage from that shown in your 1969-70 permit book, the amount of reduc-tion will be subtracted from your summerfallow and new forage acreage. . There will be no unit quotas for the 1970-71 crop year We urge you to talk over your crop plans with you' provincial extension people, with your elevator agent, or write or telephone the Operation LIFT office in Regina. Double-checking your plans may save you money. • Since the firef Operation LIFT pamphlet was mailed to you a number of questions have been asked about the Wheat Inventory Reduction Program. Following are the ones most often asked: QUESTIONS AND ANSWERS General 1. Q: The Wheat Inventory Reduction Program encour-ages farmers to take land out of production. At , the same time, new lands are being broken in . . some areas. Is anything being done to correct this contradiction? ., A: Lands cultivated in 1970 for the first time will not be eligible under the Program. So there will be no incentive to break new land in 1970. Lands must have been included as cultivated acreage in the 1959-70 permit book to be included in this Program. 2. Q: How does this program affect Registered'Seed Growers? A Registered Seed Growers w i l l be treated the same as other growers. 3. , Q: If Primers t.i->* full advanU. of the Wheat In-ve; Sory Red., (ion *-'ograv -his year and grow litt»« or n o w» -it, v. ; Canao.o have enough wheat of every grade to meet export demands? A: On July 31, 1970, we will have almost one billion bushels of wheat in storago. That's enough to meet our normal wheat: neert, for almost two years. Canada's largest surplus is or No. 3 and No. 4 hard red spring wheats, the grades most popular with foreign buyers. It is possible - but not likely — that we could deplete our stocks of some of the less popular grades. However, this i* J possibility any yea: There is always a v.iiiatio;. In quality from une cr^ -p to another. 4. Q: /vnat steps have been taken to prevent dis-honesty'' A ' Then- will be a farm-to-farm inspection r - f a m and offenders will be penalized, inspection will include measuring fields. 5. Q; He-.-, does the Wheat Inventory Reduction. Pro-gram apply to land that is rented? A: The Program is tied strictly U the holdc of the Canadian Wheat Board permit book. If the tenant holds the permit book, he will receive any bene-fits under the Program. (Landlords and tenants can of course make arrangements between themselves.) 6. Q: How do producers enroll in this Program? A: You will receive application forms by mail. Copies will also be available from elevator agents. Application for wheat reduction pay-ments must be made at the same time as you apply for your 1970-71 Wheat Board permit book. The two applications must be forwarded together. 7. Q: What is the deadline for making application for Wheat Reduction payments? To ensure consideration, applications for pay-ments must be received before July 15, 1970. The sooner you send in your application the sooner you will receive your interim payment. 13. 8. Q: Is Pitic considered as wheat under the reduction program? A: Yes. 14. , 9. Q: Can I work up old forage stands and have this acreage qualify as summerfallow? A: The program is based on summerfallow and additions to perennial forage. A reduction of Qu perennial forage would be deducted from your 1 C. perennial forage and summerfallow total. , Cover Crops 10. Q: Can I seed a cover crop on my summerfallow to prevent soil drifting and still have the land con-sidered as summerfallow for the $6.00 reduction payment and for a wheat quota? A: Yes, you can sow any crop you like after July 15, 1970. Also you may sow oats lightly as a cover crop before July 15, but to receive payment you 15 must cut the oats down, turn it under, or graze it off before July 15. No payment will be made to a permit holder who seeds an oat cover crop before July 15 until he provides the Director of 17, J*, PFAA with a document signed by a Commissioner <t of Oaths attesting to the fact that the Commis-•"J1 sioner personally has inspected the fields in question and that the oat crops have been dealt with in such a manner as to render threshing of the crop impossible. 11. Q: With vast areas under summerfallow, how do we prevent soil erosion? A: Research has provided many management answers to prevent a recurrence of the wide-spread soil erosion of the Thirties. These include chemical summerfallow, trash cover, shelterbelts and strip cropping. In addition, the Wheat Inven-tory Reduction Program allows farmers to plant cover crops where it is considered essential to 18. do so. (See previous answer.) 12. Q: Can sunflowers or corn be sown this spring in widely spaced rows and qualify as summerfallow under this Program? A: No. Q: Is sweet clover included as a perennial forage? A: Yes, for the purposes of this Program. Q: What is considered perenniai forage in the Wheat Inventory Reduction Program? A: All clovers, trefoil, alfalfa, sainfoin and perennial grasses. Q: It we grow feed grains which will be fed to live-stock, can we allocate this acreage tu wheat delivery? A: No. Quotas for oats, barley, and other crops to which delivery quotas apply, will be based on the acres seeded to each crop as stated in the pro-ducers' 1970 permit book. However, the wheat quota may be.assigned to one of these other crops if the producer prefers. Q: Is Durum acreage considered to be wheat acreage? A: Yes. Q: Flax and Durum usually have separate quotas. Will there continue to be separate quotas on these crops? A: There will be a separate quota on flax, based on the acreage seeded to flax this crop year. Durum quota will fall under the general wheat quota, which is based on summerfallow and increase in perennial forage, plus 25 per cent of your 1969 summerfallow. If the market requires extra deliveries of Durum during the year, the Canadian Wheat Board might establish a special quota for Durum. But remember this special quota would NOT be based on seeded acreage, but on the same acreage (summerfallow and perennial forage) as the general wheat quota. Q: If a man quits farming, what quota does he receive? A; If the man has been a holder of a permit book, he should apply to the Canadian Wheat Board for special consideration. 19. Q: Can I count land that was in grass last year in determining my 1970-71 wheat delivery quota base? •A: Yes, but only if it appears in the 1970-71 permit book for the first time. For example, farmprs may have sown barley as a nurse crop with forage last year. This land could have been listed in last year's permit book as barley acreage. There-fore, this year would be the first time it would appear in his permit book as forage acreage and can be claimed as new grass acreage for the purposes of calculating wheat quota. However, only perennial forage sown in 1970 will be eligible for the $4-an-acre extra payment for increased perennial forage acreage. Nurse Crop 20. Q: Can I plant a nurse crop with my spring forage seeding? A: Yes, but only oats. And the oats must be removed before July 15, 1970. The same restrictions apply as to oats sown as a cover crop. (See answer to question No. 10.) Any nurse crop may be seeded ( after July 15. if- 21. Q: Does the Wheat Inventory Reduction Program <-' include adoption of the new quota system recom-1 mended by the special committee studying quotas? A: The quota system adopted for this year only by the Wheat Inventory Reduction Program bears some resemblance to some of the recommenda-tions of the special committee which studied quotas. This, however, is a coincidence. The 1970-71 quota system is NOT the system recom-mended by the special committee studying quotas. The committee report is still under study. 22. Q: A: 23. Q: A: Fall Rye 24. Q: Some people claim the Program discriminates against those who diverted land out of produc-tion last year and into perennial forage or summerfallow. What steps has the federal government taken to alleviate discrimination? 1. if a farmer summerfallowed more than half of his specified acreage last year, he can claim the summerfallow acreage in excess of half for the $6-an-acre payment this year, provid-ing it is held out of production again this year. In addition he can use this excesv acreage in calculating his wheat quota delivery base. 2. In addition, ai; J jKmprs will be able to clami 25 per cent of last year's summeriailoA as part of their wheat quota delivery base for 1970-71. 3. F i v farmers who had less than 100 acres needed to.wheat last year, provision has been made to allow a farmer who seeds no wheat in 1970 to choose either his 1968 or 1969 wheat acreage for comparison with 1970 acreages in determining the wheat acreage reduction pay-ment to which he is entitled. In such cases the payment shall not apply to more than 100 acres. This provision applies to payments only. 1968 acreages can not be used for purposes of estaMishine ; " r>7i wheat quotas. What about the farmer who w e m out of wheat in 1968 or before? What does he get from the program? He will EP! a very important benefit. If this pro-gram had not been introduced, wheat growers would hav« switched this year to other crops, depressing the market for -hese commodities, (-or instance, if you are now growing rapeseed, you know that this program will discourage a wholesale switch to thii' crop which would ruin your market. If a farmer plants rye this fall on land which was removed from wheat and which he summer-fallows this summer, will he receive the $6-an-acre payment for diverting land into summer-fallow? Yes, provided the rye crop is seeded after July 15, 1970. 25. Q: A: 26. Q: A: 27 Q: ? A: - i t 28. Q: A: Can the rye crop seeded this fall be harvested as grain in 1971? Yes. The farmer will still qualify for the $6-an-acre payment this year provided it is associated with a corresponding reduction in wheat acreage, and can also count the acreage as 1970 summerfallow when he is calculating his wheat quota. Is winter wheat or fall rye acreage seeded in 1969 considered to be acreage in wheat in 1970 for purposes of the Wheat Inventory Reduction Program? Yes. Winter wheat and fall rye crops will, for purposes of this Program, be considered to have been seeded in the calendar year in which they are harvested. Can I divert land from barley stubble into sum-merfallow and have the additional summerfallow qualify for the Wheat Inventory Reduction Pro-gram? Yes. It does not matter what specific acres you summerfallow, provided there is a correspond-ing reduction in wheat acreage. Acreage figures for payment are calculated by comparing 1969 wheat and summerfallow acreage to 1970 wheat and summerfallow (or increased perennial for-age) acreages. Can farmers plant barley, for use as silage, and still count the acreage as summerfallow for both the $6-an-acre payment and the wheat quota? Barley planted on summerfallow acreage after July 15, 1970' and not threshed is eligible for the $6-an-acre payment. It may be harvested as silage. 29. Q: Will annual forages qualify for the $10-an-acre payment for land diverted to forage production? A: No. Only land diverted to perennial forages will count for this $10-an-acre payment. 30. Q: How will wheat quotas he set next year? A: This has not been decided as yet. Enquiries should be directed to: "OPERATION LIFT" 500 FINANCIAL BUILDING REGINA, SASK. Phone 522-2637 IMPORTANT FACTS TO KNOW • The Canadian grains, industry is faced with a wheat surplus that will amount to almost one billion bushels at the end of July — an inventory large enough to meet normal demand for almost two years. While every avenue to increased sales and utiliza-tion is being explored, the hard fact is that the only effective approach to significantly cut back Canada's wheat inventory is by reducing produc-tion. This is the same approach many major industries take when they are faced with huge inventories — an approach that makes sound economic sense. This is the avenue the federal government has chosen to promote through the Wheat Inventory Reduction Program. The federal government is uilering you and the entire indus-try a program that helps you to help yourself. To make it work, the program is being applied to every grain producer in western Canada. It would be foolish to reduce wheat production and, at the same time, to produce huge surpluses of other grains. That would merely transfer the problem from one crop to another. The solution, then, lies in summerfallowing more land this year. The federal government is offering to provide some financial help for those who co-operate in keeping the wheat surplus within reasonable > bounds. That's what the $6-an-acre wheat acre-. age reduction payments are for. And, if you permanently retire land from cereals and oilseeds production by putting it into perennial forage, there's a $4-an-acre bonus. You have already been supplied with details concerning this part of the Wheat Inventory Reduction Program. If you have any further questions, you can contact Operation LIFT at 500 Financial Building. Regina. There will be absolutely no wheat quota on acres seeded to wheat this year. Entitlement to deliver wheat will be based on acreage of summerfallow, any increase in perennial forage, and on acres seeded this year to crops other than cereals, oilseeds and forage. There will be a wheat delivery quota of eight bushels for each acre you summerfallow. In other words, there will be no specified acre-age quota for wheat in the 1970-71 crop year. Delivery quotas for other cereals and oilseeds will be based on the acreages y ; i .vtually seed to these other crops. In other words, if you plant 400 acres of rye this year, your rye delivery quota will be based on those 400 acres. If a surplus of these other grains is produced this year, the delivery quotas will obviously be small. This is the risk that farmers who expand production of such crops this year will be taking. However, you may assign your wheat delivery quota to other grains when you apply for your 1970-71 permit book. You can provide yourself with an outlet for your grain this year by making sure you have enough land in summerfallow to use as a base to deliver your grain. In other words, if you have 4000 bushels of wheat to sell, you can be assured of a market for that wheat by summerfallowing about 500 acres of land this year. Since you received the second bulletin about Operation LIFT, the wheat delivery quota base has been extended to include land seeded to crops other than cereals (wheat, oats, barley, rye), oilseeds (rape, flax, mustard, safflower and sunflower) and perennial forages. This weans that crops such as potatoes, peas, buclrwh^ijt, sugar beets, com and vegetables can be Counted as part of the acreage base for the wheat de-livery quota. However, these acres do not qualify for the $6 per acre reduction payment. In addition, regulations governing perennial forage have been clarified. You will receive $10-an-acre for a net increase in perennial forage — $6 this year and.the extra $4 in 1971, provided this increased, acreage is associated with a reduction in wheat acreage. You also re-ceive wheat delivery quota privileges for; any net increase in perennial forage. To calculate your net increase in perennial forage, compare your total perennial forage acreage at the end of this yes* with the total ••you ..stated in your 1969-70 permit book. But remember, you cannot get paid on more than your reduction in wheat acreage. New perennial forage may be seeded either this spring or fall. Be as accurate as possible when you are filling out forms for your wheat acreage reduction pay-ments and when you list acreages in your 1970-71 permit book. There will be a full inspection program. The Canada Department of Agriculture has joined the Department of Energy, Mines and Resources in an aerial survey of the Prairie Provinces. The Department of Energy, Mines and Resources was planning this survey before Operation LIFT was announced. Because the aerial photographs can be used for inspection of Operation LIFT, the two departments have decided to combine operations. i The : Canadian Wheat Board has changed its permit book issuing procedure this spring. Applications for permit books will be available from elevator managers by June 1 but the actual permit books will be held in the Board office and not issued until applications have been re-ceived and processed. An application filed with the Board as soon as seeding is completed will assure the availability of a permit book in time for the commencement of the 1970-71 crop year. It is important to note that from 10 days to two weeks will be required to process a permit appli- J cation before a permit book can be issued. j In the past, it was possible to apply for a ! Canadian Wheat Board permit book any time j after they became available in the country and \ throughout the crop year in which the permit j book would be used. This Will not be so during the 1970-71 crop year. APPLICATION FOR A DELIVERY PERMIT BOOK MUST BE MADE AND IN THE HANDS OF YOUR ELEVATOR MANAGER, BY JULY 15, 1970. Those farmers who wish to receive interim pay-ments for their wheat acreage reduction must complete a permit book application and an "Operation LIFT" application form before June 20. The deadline for applications is July 15. Growing more wheat this year will simply add more to the huge stockpile — a stockpile that costs money to store and which would not be needed to meet market demands. On the other •i-md, huge increases in other crops will merely transfer the wheat surplus problem to these other crops. Before you seed this year, we urge you to study your situation carefully. Take full account of the acreage reduction payments you could earn and study the benefits you can achieve by increasing your wheat delivery quota under the provisions of the Wheat Inventory Reduction Program. -151-APPENDIX I INTERVIEW SCHEDULE A Study of Farmer Response to the LIFT Program University of British Columbia Department of Agricultural Economics Do you operate land in township START DATA CARD NO. 1 Respondent's Name Respondent's Number Soil Zone Card No. range col. 1, 3 4 5 Hello! I am a graduate student from the University of British Columbia. I am doing a study of the way farmers have responded to the LIFT Program. I would like to ask you to please answer some questions about yourself, your farm and how you have adjusted your farming operations in response to the LIFT Program. A l l information w i l l be kept strictly confidential. I would first like to ask you some questions about yourself and your farm. col. 1. What is your age ? 2. col. 2. What is your marital status ? a. Married b. Single c. Widowed, separated, divorced 8 3. How many children do you have ? 9,10 4. What was the highest grade you completed in school? 11,12 What education have you had after secondary school? a. Some University b. University Degree 13 c. Agriculture College 14 d. Vocational College 5. Have you taken any courses in agriculture? a. Adult Education Courses in Agriculture b. High School Courses in Agriculture 15 c. Vocational School Courses in Agriculture 16 d. University Courses in Agriculture 6. Have you taken any adult education courses in other subjects? 1. Yes 2. No 17 7. What was the highest grade completed in school by your wife ? 18,19 What education has your wife had after secondary school? a. Some University b. University Degree c. Agriculture College 20 d. Vocational College 21 8. How many years have you been farming? 22,23 3. col. 9. How many years have you been on your present farm? 24,25 10. Where were you born ? a. British Isles b. Germany c. Denmark, Norway, Sweden d. Netherlands e. France f. Eastern Europe g. Italy h. Alberta i . Another Province in Canada j. Another Prairie Province k. U.S.A. 1. Other m. Not stated 26 11. When did you immigrate to Canada (how many years ago)? 27,28 12. What is the total size of your farm in acres? i . 1970 29,33 i i . 1969 34,38 13. How many cultivated acres do you operate ? i . 1970 39,43 i i . 1969 44,48 14. How many cultivated acres do you rent or lease? i . 1970 49,53 i i . 1969 54,58 15. How many bushels of wheat do you have on hand now ? 59,63 16. How many bushels of covered storage space do you expect to have available at harvest time this year? 64,68 4. col. 17. What is your usual crop rotation ? % grain 69, 70 % summerfallow 71,72 % forage crops 73,74 18. How much labour did you hire for your farming operation in 1969 ?_ (months) 75,76 START DATA CARD NO. 2 Re spondent' s Number 1,3 Soil Zone 4 Card No. 5 19. What is your principal agricultural product sold (that is the product from which you obtained the largest gross revenue)? 6 What other agricultural products do you sell? 7 8 9 10 11 1. dairy (milk, cream or butter) 2. beef 3. sheep 4. hogs 5. wheat 6. coarse grains 7. oil seeds 8. forage crops 9. other livestock a. other crops 5. col. 20. What would you estimate to be the present market value of this farm? (Everything included) 12,17 21. How much did you spend on fertilizer for this year's crop? 18,22 How much did you spend on fertilizer for last year's crop? 23,27 22. What was the average number of animals on your farm for the past year ? DAIRY ANIMALS cows heifers calves bulls Total animal units, dairy stock 28,30 BEEF ANIMALS cows heifers yearlings calves bulls Total animal units, beef stock 31, 34 SWINE Over 100 lbs. Under 100 lbs. Total animal units, swine 35,39 SHEEP 40,44 HORSES 45,46 POULTRY 47,52 TOTAL ANIMAL UNITS 53, 57 6. 23. I will now read six statements about changes that could occur in your future. Please say whether you agree or disagree with each statement. Agree Undecided Disagree I would not mind leaving here in order to make a substantial advance in my occupation 1 0 I do not want any new job which involves more responsibility. 0 1 I would not leave this area under any circumstances. 0 1 Learning a new routine would be very difficult for me. 0 1 I would find it very difficult to go to school to learn new ski l l s . 0 1 I have no desire to learn a new trade. 0 0 TOTAL SCORE col. add 1 +1 SCALE SCORE 58 24. Would you please try to recall the names of all the organizations that you have belonged to in the past year-. Name of Financial Member of Offices Organization Attendance Contribution Committee Held Total (Xi) (X2) (X3) (X4) (X5) col. TOTAL SCORE 59, 60 7. col. 25. How many contacts of the kinds named below have you had in the previous year with the District Agriculturist or other agricultural extension personnel? a. Attended meetings or field days 61 b. Farm visits by extension personnel 62 c. Office visits to extension personnel 63 d. Telephone conversations with extension personnel 64 SUB-TOTAL 65,66 e. Listened to radio or television programs given by extension personnel 67 f. Read newspaper articles written by extension personnel 68 g. Read mailed circular letters or bulletins sent by extension personnel 69 SUB-TOTAL 70 TOTAL NO. OF CONTACTS 71 TOTAL WEIGHTED SCORE 72 26. Do you enjoy your work as a farmer? 1. Yes, very much. 2. Occasionally. 3. Not at a l l . 73 The next series of questions w i l l be about the LIFT Program. 27. How do you feel about the LIFT Program? 1. strongly opposed. 2. mildly opposed. 3. neutral. 4. mildly in favour. 5. strongly in favour. 74 8. col. 28. I would like to find out if the information about the LIFT Program was adequate. The following statements are about the LIFT Program. Please state whether you agree, disagree, or don't know in response to each. i . The wheat delivery quota for the crop year beginning August 1, 1970 wi l l be based on the total number of cultivated acres as stated in your 1970-71 permit book. 1. agree 2. disagree 3. don't know 75 i i . Wheat acreage reduction payments w i l l be made to those farmers who reduce total acres seeded to wheat and increase their summerfallow and/or forage crop acreage by that amount. 1. agree 2. disagree 3. don't know 76 i i i . A producer may receive payments for up to 2, 000 acres of reduction in wheat acreage. 1. agree 2. disagree 3. don't know 77 iv. The unit quota for wheat this year w i l l be 400 bushels. 1. agree 2. disagree 3. don't know 78 v. Summerfallow that comes from working up old forage stands or land not cultivated in 1969 w i l l not be counted as summerfallow for the purposes of the LIFT Program. 1. agree 2. disagree 3 don't know 79 v i . A producer may allocate any of his acreage qualified for wheat quota to any other crop. 1. agree 2. disagree 3. don't know ' 80 9. START DATA CARD NO. 3 col. Respondent's Number 1,3 Soil Zone 4 Data Card No. 5 29. What sources have you found most useful in obtaining information about the LIFT Program ? (show card with list of sources) a. Most Useful 6 b. Second Most Useful 7 c. Third Most Useful 8 The next series of questions w i l l be about your expectations for crop yields, prices, and quotas. 30. a. In the last 5 years what has been your average yield per acre for each of these crops? b. Over the past 5 years what has been your highest yield for each of these crops ? c. Over the past 5 years what has been your lowest yield for each of these crops ? CROP HIGHEST LOWEST AVERAGE Wheat 9,10 11,12 13,14 Oats 15,16 17,18 19,20 Barley 21,22 23,24 25,26 Flax 27,28 29,30 31,32 Rape 33,34 35,36 37,38 31. a. What do you expect to be the most probable Wheat Board final price per bushel for each of these crops during the 1970-71 crop year? 10. col. b. What do you expect to be the highest the Wheat Board final price per bushel is likely to go for each of these crops during the 1970-71 crop year ? c. What do you expect to be the lowest the Wheat Board final price per bushel is likely to go for each of these crops during the 1970-71 crop year? CROP HIGHEST LOWEST MOST PROBABLE Wheat #2 Nor. 39,41 42,44 45,47 Oats 3 CW 48,49 50,51 52,53 Barley 3 CW 54,56 57,59 60,62 Flax 3 CW 63,65 66,68 69,71 Rape 1CW 72,74 75,77 78,80 START DATA CARD NO. 4 Respondent's Number 1,3 Soil Zone 4 Data Card No. 5 32. a. What do you expect to be the most probable Wheat Board quota for each of these crops for the 1970-71 crop year? b. What do you expect to be the highest likely quota for each of these crops for the 1970-71 crop year? c. What do you expect to be the lowest likely quota for each of these crops for the 1970-71 crop year^?(in bushels) 11 col. CROP Wheat Oats Barley Flax Rape 33. a HIGHEST LOWEST MOST PROBABLE 6,7 8,9 10,11 per eligible acre 12,13 14,15 16,17 per acre seeded to Oats 18,19 20,21 22,23 per acre seeded to Barley 24,25 26,27 28,29 per acre seeded to Flax 30,31 32,33 34,35 per acre seeded to Rape How many bushels of each of these different kinds of grain do you expect to feed to livestock during the 1970-71 crop year? GRAIN Wheat Oats Barley AMOUNT 36,40 41,45 46,50 How many bushels of each of these different kinds of grain do you expect to sell as non-board feed grain during the 1970-71 crop year? GRAIN Wheat Oats Barley AMOUNT 51,55 56,60 61,65 START DATA CARD NO. 5 Respondent's Number Soil Zone Data Card No. 1,3 4 5 34. a. What do you expect to be the most probable price per bushel for non-board feed grain during the 1970-71 crop year ? 12. b. What do you expect to be the highest that the non-board feed grain prices per bushel is likely to go during the 1970-71 crop year? c. What do you expect to be the lowest that the non-board feed grain price per bushel is likely to go during the 1970-71 crop year? CROP HIGHEST LOWEST MOST PROBABLE Wheat 6, 8 9,11 12,14 Oats 15,17 18,20 21,23 Barley 24,26 27,29 30,32 The next few questions w i l l be about what crops you seeded this year. 35. How many acres of each of the different crops did you have in 1970 and in 1969 ? CROP ACRES - 1970 ACRES - 1969 Wheat 33,37 38,42 Oats 43,47 48,52 Barley 53,57 58,62 Soft Spring Wheat 63,67 68,72 START DATA CARD NO. 6 col. Respondent's Number 1,3 Soil Zone 4 Data Card No. 5 13. col. Rye 6,10 Rape 16,20 Mustard 26,30 Flax 36,40 Forage crops (newly seeded) 46,50 Forage crops (established) 56,60 Summerfallow 66,70 11,15 21,25 31,35 41,45 51,55 61,65 71,75 START DATA CARD NO. 7 Respondent's Number — Soil Zone Data Card No. 36. 1970 6,10 Other crops Calculate (sa) decrease in wheat acreage (b) increase in summerfallow acreage increase in forage crop acreage (c) number of new crops (crops not grown in 1969) 11,15 If there was no reduction in wheat acreage: What was the main reason(s) you did not reduce your wheat acreage ? 1969 1,3 4 16,20 21,25 26,30 31 32 33 34 35 14. B. If there was a reduction in wheat acreage: col. What was the main reason(s) you did reduce your wheat acreage ? 36 37 38 39 i i . What was the main reason(s) you did not reduce your wheat acreage further? 40 41 42 43 37. A. If there was no increase in summerfallow acreage: What was the main reason(s) you did not increase your summerfallow acreage ? 44 45 46 47 B. If there was an increase in summerfallow acreage: i . What was the main reason(s) you did.increase your summerfallow acreage ? 48 49 50 51 i i . What was the main reason(s you did not increase your summerfallow acreage further ? 52 53 54 55 15. 38. A. If there was no increase in forage crop agreage: What was the main reason(s) you did not increase your forage crop acreage? 56 57 58 59 B. If there was an increase in forage crop acreage: i . What was the main reason(s) you did increase your forage crop acreage? 60 61 62 63 i i . What was the main reason(s) you did not increase your forage crop acreage further 64 65 66 67 39. A. If no new crops were grown: What were the main reason(s) you did not grow any new crops ? 68 69 B If new crops were grown: What were the main reason(s) you did grow new crops this year ? 70 71 16. 40. Do you know what it costs you per acre to produce wheat?(all costs included) 1. Yes 2. No 72 If yes (a) How much does it cost ? $/acre 73,74 (b) Where did you get this information ? 1. calculated from own records 2. Read it in a bulletin or research report 3. Read it in a farm magazine 4. Other sources (specify) 75 41. Do you keep farm records in a farm account book? 1. Yes 2. No 76 If Yes, do you have your records analysed to find out your return to labour and investment? 1. Yes 2. No 77 If Yes, who does this analysis ? 1. Economics Division (Farm Business Analysis) 2. F. C. C. or the Bank 3. Does own 78 42. Do you f i l l out your own income tax report or do you have an accountant f i l l it out ? 1. F i l l s out own 2. Filled out by an accountant. 79 43. Do you keep a written record of your crop yields ? 1. Yes 2. No 80 17. START DATA CARD NO. 8 Respondent's Number 1,3 Soil Zone 4 Data Card No. 5 44 Do you have any definite plans to make any changes in your farming operations in the next few years ? 1. Yes 2. No 6 If Yes, what changes If no, why not? 9 10 45. Did your wife take part in the process of deciding what the cropping program would be for this year? 1. Yes 2. No. 11 If Yes, would you say that she influenced your decision about the cropping program ? 1. very much 2. some 3. not at all 12 46. Would you consider 1969 a typical year, or was it better or poorer than average with respect to net farm income ? 1. typical 2. better than average 3. poorer than average 4. not farming previous to 1969 13 47. How many months did you spend working off your farm last year? 14,15 18 48. What were your earnings from off-farm employment last year? 16,21 49. What was the gross value of sales of all your agricultural operations last year? 22,27 50. What was the gross value of the wheat you sole-last year? 28,33 51. What was your net income from farming last year? (gross income less cash expenses) 34,39 

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