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This is to certify that the thesis entitled IMPACT OF LARGER EQUIPMENT 0N MICHIGAN CASH CROP FARMS presented by Philip Larry Greenburg has been accepted towards fulfillment of the requirements for M.S. degree in Agricultural Economics Major professor Date October 10, 1980 0-7639 - o “1::‘\‘%\\ “p (11!” _ ‘* mutt .‘ w“ mum STATE UNIVERSITY ' 1 OVERDUE FINES: 25¢ per day per item RETURNIN L IIRARV MATERIALS: Place in book return to remve charge from circulation records IMPACT OF LARGER EQUIPMENT ON MICHIGAN CASH CROP FARMS By Philip Larry Greenburg A THESIS Submitted to Michigan State University in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE Department of Agricultural Economics ABSTRACT IMPACT OF LARGER EQUIPMENT ON MICHIGAN CASH CROP FARMS By Philip Larry Greenburg During the twentieth century, one of the biggest changes in agriculture has been increased mechanization. Agriculture has changed from the use of horses as the major source of power to almost complete use of tractors. In recent years, this size of farm tractors has followed an upward trend. From l973 to 1976 the retail sales of tractors with a P.T.0. horsepower of l40 or greater increased by 58.5%. At the same time, tractors less than l40 horsepower had decreased retail sales by 36.5%. Along with the shift to larger tractors there has been‘ an associated shift to larger tillage, planting and harvesting equipment. The purpose of this study was to investigate the reasons for the movement to large machinery systems and calculate if large machinery systems are causing Michigan farmers to be overmechanized. By studying the factors which encourage the trend to large machinery systems, a better historical understanding of changes in agriculture can be developed. If those factors continue to be important in the decision making process, future equipment needs can be predicted. If the observed trend is in effect beneficial or detrimental to the farm operation, this will be a valuable insight into the financial management changes in agriculture. ACKNOWLEDGEMENTS The author wishes to thank Dr. Stephen Harsh who served as major professor'on this thesis. It was only through his help, advice and counsel that this project was possible. Dr. John Brake and Dr. F.w. Bakker-Arkema, both of whom were very supportive and made valuable contributions, were the other members of the thesis committee. The author also wishes to thank Linda Wilkes, who typed the first draft and Kim Payne and Sandy Casselberry, who typed the final draft. The Department of Agricultural Economics was very supportive, and without their assistance this study would have been impossible. Throughout the study my family has been very understanding and supportive. My wife Lisa helped during the writing by proofreading, having a sympathetic ear and an encouraging word. ii TABLE OF CONTENTS Page LIST OF TABLES ..................................................... iv LIST OF FIGURES .................................................... vi LIST OF APPENDICES ................................................. vii CHAPTER I Introduction ........................................... l Endnotes ............................................... 5 CHAPTER II Theory of Equipment Size and Research Methodology ...... 6 Economics of Machinery Size ............................ 6 Theory of Equipment Decision Making .................... 19 Methodology ............................................ 20 Data Collection Techniques ............................. 24 Endnotes ............................................... 26 CHAPTER III Analysis of Data ....................................... 27 Characteristics of Farms in Survey ..................... 27 Analysis of Factors Affecting the Decision ............. 33 Comparative Economics of Different Size Machinery Systems .............................................. 37 Endnotes ............................................... 44 CHAPTER IV Conclusions ............................................ 45 APPENDICES ......................................................... 43 BIBLIOGRAPHY ....................................................... 73 iii LIST OF TABLES Table Page 1-1 Number of Employees on Michigan Farms with Sales over $2,500 per Year in 1969 and 1974 ........................... 1 1-2 Estimated Market Value of all Machinery and Equipment on Michigan Farms 1969 and 1974 .................. . ......... 2 1-3 Michigan Retail Sales of Farm Wheel Tractors, 1973-1976.... 3 1-4 Percent Michigan Retail Sales of Farm Wheel Tractors, 1973-1976 .................................................. 4 2-1 Five Year Average Corn Yield Related to Different Planting Dates in Central Michigan 1970-1974 ............... 7 2-2 Relative Corn Yield and Percent Moisture with Different Harvest Dates in Michigan .................................. 8 2-3 Relative Corn Yield Loss in Michigan with Different Planting and Harvesting Dates .............................. 9 3-1 Selected Factors Related to Size of Acreage Farmed on 56 Farms, Thumb Area of Michigan, 1977 ........................ 28 3-2 Average Values of Tractor Size and Number by Acreage on 56 Farms in the Thumb Region of Michigan, 1977 ............. 29 3-3 Selected Factors Related to Size of Tractor Purchased on 56 Farms, Thumb Area of Michigan, 1977 .................. 31 3-4 Machinery and Labor Systems on Representative Farm for the Small Group of Farms ....................................... 38 3-5 Work Capacity on Representative Farm for the Small Group of Farms by Equipment Size ........................ . ........ 39 3-6 Returns Over Variable Costs on Four Representative Farms with Different Sizes of Equipment .......................... 40 3-7 Total Annual Fixed Costs for Different Equipment Sizes on the Representative Farms ................................... 41 3-8 Total Annual Labor Costs for Different Equipment Sizes on the Representative Farms ................................... 41 iv Page Net Return Per Acre Over Fixed and Variable Costs for the Different Equipment Sizes on the Representative Farms ....................... . ............................. 42 LIST OF FIGURES Figure Page 2-1 Fixed Costs with Increasing Production ..................... 10 2-2 Variable Costs with Increasing Production .................. 10 2-3 Total Cost with Increasing Production ...................... 11 2-4 Average Costs Per Unit with Increasing Production .......... 11 2-5 Average Total Cost and Economic Loss with Increasing Production ................................................. 13 2-6 Average Total Cost for Small and Large Equipment ........... 14 2-7 Average Total Cost and Economic Loss for Small and Large Equipment ............................................ 15 2-8 Isoproduct Curve of Labor and Equipment with Constant Production ................................................. 16 2-9 Isocost Curves of Labor and Equipment with Constant Cost... 17 2-10 Isoproduct Curves and Isocost Curves for Two Different Levels of Production ....................................... 18 2-11 Expansion Path on the Least Cost Combination of Inputs at Different Production Levels ............................. 19 vi LIST OF APPENDICES Appendix Page A Field Questionnaire ..................................... 48 B Cropping Program of Representative Farms ................ 51 C Machinery and Labor Systems for Representative Farms.... 52 D Field Work Speed on Representative Farms by Different Equipment Systems ....................................... 56 E Results of Linear Programming Analysis of Representative Farms ................................................... 58 F Input Form for TELPLAN Program Number 18 (Crop Farm Planning Guide - a TELPLAN Program) ..................... 61 Vii CHAPTER I INTRODUCTION "Since 1900, one of the biggest changes in American agriculture has been the mechanizing of farm operations."1 Mechanization has allowed the 1977 average farm size to grow to about 393 acres from 348 acres in 1966.2 Through the use of equipment, farmers have been able to increase the size of their operations and improve labor efficiency. By 1976, there were approximately 154.5 thousand men and women 3 employed in Michigan agriculture. In 1967, the agricultural sector employed 305.5 thousand people in Michigan. Over the same ten year 4 The period, the amount of land in agriculture only declined by 4%. reduction of 151 thousand workers in ten years represents a 49% decrease. As employee numbers were declining, the pattern of employment has shifted from seasonal workers to more full time workers (Table 1). Table'l-1.Number of Employees on Michigan Farms with Sales over $2,500 per Year in 1969 and 1974 Length of Year Employment 1969 1974 More than ,, 150 days 9,879 12,273 Less than 150 days 176,547 127,602 Source: 1974 Census of Agriculture, U.S. Department of Commerce, Bureau of the Census, Vol. 1, part 22, pp. 1-16. With a declining labor force and an increasing average farm size, a substitution effect between labor and equipment has allowed a farmer to decrease his labor requirements and increase the number of acres farmed. The change from seasonal to full time workers has also decreased the number of workers needed.5 In this shift to higher mechanization of farms, (Table 2) it is desirable that a proper mix between machinery, labor and other resources be maintained. Otherwise, farmers having too much or not enough machinery resources in relationship to other resources will be at'a competitive disadvantage. In recent years, there has been an accelerated trend to larger sized machinery systems. The core of these large machinery systems is the high horsepower tractor, many of which are four wheel drive (Table 3). Table 1-2.Estimated Market Value of all Machinery and Equipment on Michigan Farms 1969 and 1974 Year 1969 1974 Number of farms 76,060 61,877 Estimated market value (million $) $716 $1,313 Source: 1974 Census of Agriculture, U.S. Department of Commerce, Bureau othhe Census, Vol. 1, part 22, pp. 1-4. Table 1-3.Michigan Retail Sales of Farm Wheel Tractors, l973-1976a P.T.0. Year of Sale Horsepower 1973 1974 1975’ 1976 ------------------ number------------------- <60 1649 1513 1166 1113 60-99 1567 1377 1258 1227 100-139 1214 1210 1090 1105 140-169 228 314 371 257 1703_ 88 121 191 244 Source: Adapted from "Retail Sales of Farm Wheel Tractors by Horsepower (in units)," Implement and Tractor, Intertec Publishing Corp., Vol. 92, no. 10, pp. 28, 29; vol. 91, no. 10, pp. 28, 29; vol. 90, no. 10, p. 10; vol. 89, no. 23, p. 30. aTwo assumptions were made in compiling the data. The first was that all two wheel tractors had a P.T.O. horsepower rating less than 170. The second assumption was that all four wheel tractors were rated above 140 horsepower. These assumptions were necessary because the original data were divided between two wheel and four wheel tractors. From 1973 to 1976, yearly tractor sales have decreased by about 17%. When the data presented in Table 3 are stated in percentages, the retail sale decrease was not uniform for all classes (Table 4). While the retail sales of tractors with a P.T.0. horsepower less than 140 decreased by 36.5%, the sales of tractors rated 140 h.p. and greater increased by 58.5%. Therefore the trend to larger tractors is also evident in Michigan. Along with the shift to larger tractors, related equipment must be changed to take advantage of the increased tractor size. Planter, plow and other field equipment must be matched with the work capacity of the tractors. It would not be economical to use a 200 horsepower tractor to pull a 4 bottom plow. The rate of work would be much less than expected for a 200 horsepower tractor. Therefore, the shift to larger tractors has caused an associated shift to larger tillage, plant- ing and harvesting equipment. Table1-4. Percent Michigan Retail Sales of Farm Wheel Tractors, 1973-1976 P.T.0. Year of Sale horsepower 1973 1974 1975 1976 <60 100% 91.8% 70.7% 67.5% 60-99 100 87.9 80.3 78.3 100-139 100 99.7 89.8 91.0 140-169 100 137.7 162.7 112.7 170: 100 137.5 217.0 277.3 Source: Implement and Tractor, 9p, git, The question that needs to be addressed is whether Michigan farmers, in their movement to large machinery systems, are becoming overmechanized, therefore, at a comparative disadvantage. 0r conversely, whether they have been undermechanized and are now at a more competitive advantage. The objectives of this study are: 1. To study the economic advantage or disadvantage of equipment size for different sized Michigan farming operations. In particular, has the trend to large tractors and related equipment improved the profitability of Michigan farms. 2. To determine the economic and non-economic factors which influence farmers' decisions in selecting the size of tractor purchased. ENDNOTES 1Earl 0. Heady and Harold R. Jensen, Farm Management Economics, Prentice-Hall, New York, 1954, p. 374. ZUSDA, "U.S. Farms: Still Disappearing," ggriculture Situation, March 1977, p. 11. 3Michigan Department of Labor, "Michigan Agricultural Labor in PerspectiveJ'The Michigan Farm Worker, Vol. 1, no. 1, p. 2. 4 USDA, 92, £15,, p. 11. 5Michigan Department of Labor, op. cit., p. 11. CHAPTER II THEORY OF EQUIPMENT SIZE AND RESEARCH METHODOLOGY There are two basic problems to be addressed in this study. The first problem is gaining a better understanding of factors which caused farm managers to purchase larger equipment. The second problem is evaluating the economic advantages or disadvantages of different size groups of equipment. By studying the factors which encouraged the trend to large machin- ery systems, a better historical understanding of changes in agriculture can be developed. If those factors continue to be important in the decision making process, future equipment needs can be predicted. In addressing the second problem, it is important to determine if the observed trend is in effect beneficial or detrimental to the farm operation. The answer to this problem will give insight into the financial management changes in agriculture. There are probably many reasons for buying larger tractors. These reasons should reflect the size, work capacity and financial situation of the operation. When a fanner purchases a large tractor, it should be because a smaller tractor is unable to complete the tasks involved within the expected time constraints. There are also financial tax advantages for making the purchase. Tax advantages include increased depreciation and more investment tax credit. Economics of Machinery Size Many of the perceived needs for large equipment cannot be econom- ically justified. On the other hand, farmers who are trying to use 6 a minimal amount of equipment might be at an economic disadvantage in the planting or harvesting seasons. The timeliness of farm operations is very important to production. Not planting or harvesting at the optimum time can reduce yield. Plant- ing date affects expected yield. Corn that is planted in the middle of May will only yield 80% of its potential (Table 5). A later planting date will reduce the yield potential by limiting the growing season and the number of heat degree days. TableZLJ. Five Year Average Corn Yield Related to Different Planting Dates in Central Michigan 1970 through 1974. Average Average Bushels per planting % moisture acre at 15.5% date at harvest moisture April 21 26 102 May 3 28 96 May 13 31 83 May 23 34 78 June 2 39 64 June 11 43 72 Source: Michigan Corn Production Series, Department of Crops and Soil Science, Michigan State University, East Lansing, Michigan, 1976. Table 6 shows the results of corn planted at the same time but harvested during different periods. There is a yield reduction of 12% between the different harvest times. A late harvest will have a lower yield because of stalk lodging. Table 2-2,Relative Corn Yield and Percent Moisture with Different Harvest Dates in Michigan. Relative yields Harvest % moisture per acre Period at harvest at 15.5% moisture Sept. 27-Oct. 3 28 90 Oct. 4-Oct. 10 28 100 Oct. ll-Oct. 17 26 99 Oct. 18-Nov. 7 23 98 Nov. 8-Nov. 28 21 88 Source: User's Guide For Corn, Soybean Farm Planning Guide, Department of Agricultural Economics, Corn-Soybeans Planning Guide, Program No. l8,Form 1, January, 1973. Table 7, which is a combination of Tables 5 and 6, shows that a low work capacity causes a 49.3% reduction in yield. If land potential were 120 bushels per acre, a delayed planting and harvesting schedule would result in an estimated yield of 61 bushels. With a market value of $2.00 per bushel, the crop loss of 59 bushels would reduce gross income by $118.00 an acre. A farm operation that does not have adequate machinery and labor is at a serious disadvantage. As shown by tables 5, 6, and 7, there is a reduction in yield because of untimely operations. Table 2-2,Relative Corn Yield and Percent Moisture with Different Harvest Dates in Michigan. Relative yields Harvest % moisture per acre Period at harvest at 15.5% moisture Sept. 27-Oct. 3 28 90 Oct. 4-Oct. 10 28 100 Oct. ll-Oct. 17 26 99 Oct. l8-Nov. 7 23 98 Nov. 8-Nov. 28 21 88 Source: User's Guide For Corn, Soybean Farm Planning Guide, Department of Agricultural Economics, Corn-Soybeans Planning Guide, Program No. 18,Form 1, January, 1973. Table 7, which is a combination of Tables 5 and 6, shows that a low work capacity causes a 49.3% reduction in yield. If land potential were 120 bushels per acre, a delayed planting and harvesting schedule would result in an estimated yield of 61 bushels. With a market value of $2.00 per bushel, the crop loss of 59 bushels would reduce gross income by $118.00 an acre. A farm operation that does not have adequate machinery and labor is at a serious disadvantage. As shown by tables 5, 6, and 7, there is a reduction in yield because of untimely operations. Table 2-3,Relative Corn Yield Loss in Michigan with Different Planting and Harvesting Dates. Harvest date Planting Sept. 27 Oct. 4 Oct. 11 Oct. 18* Nov. 8 date Oct. 3 Oct. 10 Oct. 17 Nov. 7 Nov. 28 April 21 10.0% 0.0% 1.0% 2.0% 12.0% May 3 15.9 5.9 6.9 7.9 17.9 May 13 28.6 18.6 19.6 20.6 30.6 May 23 33.5 23.5 24.5 25.5 35.5 June 2 47.2 37.3 38.3 39.3 49.3 June 11 39.4 29.4 30.4 31.4 41.4 How much equipment a farm should have is as difficult to know as predicting the weather. Given ideal conditions,it is possible to maximize profits with small equipment. During a wet or poor growing year, larger equipment would be necessary for maximum profit. There are costs to having and operating farm machinery which should be considered in determining the proper equipment size. Large equip- ment can help achieve maximum yield, but ownership and operating costs might more than offset the increased yield. Ownership costs are fixed costs which do not vary with production. These costs include depreciation, interest, or opportunity cost on capital invested and insurance. Total fixed costs do not change with production, but the cost per unit decreases as more units are produced. 10 Total fixed cost fixeg_cost per unit production Figure 2-1. Fixed Costs with Increasing Production. Operating costs are variable costs of production. Variable costs consist of repairs, fuel, oil, grease and other inputs that change with production. Total variable cost increases as production increases. Some of the costs, such as repairs, increase at an increasing rate as pro- duction increases. $ Total variable cost Variable cost per unit 0 production Figure 2-2. Variable Costs with Increasing Production- 11 Graphically, fixed costs and variable costs can be combined to show total costs and average cost. $ Total cost Total variable cost total fixed cost production Figure 2-3. Total Cost with Increasing Production. $/unit Average total cost fixed cost Average fixed cost production Figure 2-4. Average Costs Per Unit with Increasing Production. The ideal size of equipment used on a farming operation is the one that maximizes returns. The exact size of equipment might be different for each farm based on: 12 (1) The availability of labor. (2) The amount of work to be done in the critical crop operations. (3) The number of working days that have satisfactory weather for field work during the critical periods. If the available labor force is small, larger equipment might be required to complete field work in the time constraints. More workers extend the number of hours worked per day and thus reduce equipment needs. Limited labor supply, large amounts of work to be done, or weather conditions that restrict field work are factors which reduce the ability to finish the planting or harvesting during the ideal time period. Table 7 shows the potential yield reduction associated with untimely cropping operations. Because of the severe penalties, it is desirable to have equipment which reduces yield loss. Point A in Figure 2-5 is the location where economic losses due to untimely field operations begin. Any production to the right of point A has increasingly high economic loss. Speeding up the work rate or having more favorable weather conditions will shift point A to the right. 13 i : --average total cost plus ' economic loss --average total cost ; / [I / l // x/i/--economic loss from ,",/ untimely operations / I / l o x’ T A production Figure 2-5. Average Total Cost and Economic Loss with Increasing Production. Source: Managing the Farm Firm, S.B. Harsh, L.J. Connor, G.D. Schwab, In publication process, Prentice-Hall, New York, 1981. Assuming that labor and equipment are being used at their capacity and normal weather conditions are expected, the way to expand pro- duction and minimize economic loss from untimely field work is to increase the size of equipment. Larger equipment can increase the productivity of labor. This allows more acres to be covered per hour with the same labor force. Total ownership costs and operating costs will increase with larger equipment. Higher equipment cost will increase annual depreciation, interest, or opportunity cost, insurance and repairs. Therefore, the curves shown in figures 2-4 and 2-5 will shift to the right as large equipment is acquired. l4 $/u --average total cost small equipment --average total cost large equipment production Figure 2-6. Average Total Cost for Small and Large Equipment. Figure 2-6 shows the shift of the average total cost curve to the right when larger equipment is used. Figure 2-7 illustrates the average total cost curves with the economic loss curves added for 2 sizes of equipment. Point 8 is the threshold level where it is more pro- fitable to change equipment size. 15 $/u ( ) average total loss ( ------ ) average economic loss from untimely field operations ( ------ ) average total cost + average economic loss 1 I I 8 acres Figure 2-7. Average Total Cost and Economic Loss for Small and Large Equipment. Source: Managing the Farm Firm, S.B. Harsh, L.J. Connor, G.D. Schwab, In publication process, Prentice-Hall, New York, 1981. Any farm size smaller than point 8 could maximize net income by using small equipment. Farms larger than B would benefit from using large equipment. In the short run, there could be farms that are using the wrong sized equipment because of good economic reasons. A farm with fewer acres than point 8 might have large equipment to expand to operations larger than B. One input can often be substituted for another and the same level of production maintained. Between labor and equipment there are several different combinations which can produce the same amount. This is referred to as the substitution effect and is a physical relationship between inputs. Figure 2-8 illustrates the various possible combinations 16 of two inputs (labor and equipment) to achieve a certain level of production. Labor -Isoproduct curve Equipment Figure 2-8. Isoproduct Curve of Labor and Equipment. The different possible combinations of inputs which achieve a constant level of production defines an isoproduct curve. The least cost combination of inputs at any production level is determined by the price relationships of the inputs. An isocost line_ then,is a series of combinations of the two inputs which have constant total cost. Any point on line L3, E3 has the same total cost. 17 Labor L2 -Isocost curves 0 \ E1 E2 E3 Equipment Figure 2-9. Isocost Curves of Labor and Equipment. Figures 2-8 and 2-9 can be combined to find the least cost com- bination of inputs at a production level. The point where the isoproduct curve and isocost curve are tangent is the least cost combination. In figure 2-10, point A is the point of tangency to achieve output level 0. This means that L1 of labor and E1 of equipment would be the least cost combination to product at quantity 0]. If more production is re- quired, a higher isoproduct curve (eq. 02) needs to be used. Increased production requires more inputs so a higher isocost curve is needed to find the least cost combination at 02 production. 18 Labor Equipment Figure 2-10. Isoproduct Curves and Isocost Curves for Two Different Levels of Production. Points A and B in figure 2-10 are the least cost combinations at production levels 01 and 02' For any level of production the least cost combination can be found at the point of tangency of the iso- cost and isoproduct curves. Figure 2-11 shows least cost points for several different levels of production. 19 Labor - Expansion path Equipment Figure 2-11. Expansion Path on the Least Cost Combination of Inputs at Different Production Levels. The expansion path in figure 2-11 is a curve which connects each of the least cost points. This path is the combination of inputs which will minimize labor and equipment costs at any level of production. If a farm is not on the expansion path, then it is not using the most pro- fitable combination of inputs to maximize profit. In the short run, it is possible that a farm would not be on the expansion path because of the way resources are purchased. In the long run, to be efficient, a farm should be on the expansion path to minimize total cost. Theory of Equipment Decision Making The decision making process of buying farm tractors and related machinery is an involved process. There are many factors which are used to determine the size of tractor to purchase. The purchased tractor must help satisfy the power needs of the farm operation and be 20 compatible with existing equipment. Existing equipment requiring a certain type of hitch or hydraulic system can limit the number of tractor options. Jones1 and Lambert2 conducted studies which compared farmers' intentions to buy tractors with actual purchases. They interviewed farmers regarding their intentions to purchase and subsequently determined if their intentions were realized. In both cases the best predictors of a purchase were the farmer's initial intentions. Some of the other fac- tors considered in their studies included tillable acreage farmed, current dis- posable income and the change in disposable income. Methodology, Two different models are needed to meet the objectives of this study. A linear regression model can be used to test the importance of several variables on the decision making process. A linear programming model can be used to evaluate the economics of different sizes of equipment on different sizes of farms. TELPLAN program number 18 is a computerized program which calculates the yield and subsequent return above variable cost. The objective of using this linear programming model is to see if there is a difference in returns over variable cost of one size of equipment over another. An input sheet for TELPLAN 18 is in Appendix F. The TELPLAN system is a series of computer programs developed for educational purposes in either the classroom or for extension work.3 These computer programs were developed by many people who were interested in the educational uses of computers. Programs are available in the following areas: capital investment and planning, crops and soils, dairy, family living, financial management, horticulture and forestry, 21 and livestock. There are over eighty different programs on the TELPLAN system. TELPLAN program number 18 is a crop planning guide. The program considers the trade-offs between the amount of corn and soybeans to plant given prices, machinery system and labor force. A projected budget is printed for the best combinations of corn and soybeans. The budget includes yield, income and expenses and constraints on limiting resources. From data collected by interviewing farmers, the number of tillable acres can be used to divide the farms into size groups. Within each group the total tractor horsepower of each farm can be calculated and ranked from smallest to largest. Then, three different sizes of equipment and labor can be estimated as being characteristic of the smallest 25%, medium 50%, and the largest 25% of each class. TELPLAN program number 18 can be run three times for each of the different size classes to generate returns to each of the three equipment and labor classifications. TELPLAN program number 18 is designed to determine the most pro- fitable combination of corn, soybeans and other crops given expected yields, production costs, prices, equipment, work capacity and labor. The major change in the original program was to convert the soybeans option to a navy beans option. The necessary changes involved limiting the planting and harvesting seasons to reflect normal operations of navy bean production. Navy beans should not be planted before the last week of May and must be harvested by the first week of November. The percentage of time available for field work for different time periods was taken from another study done for Lenawee, Monroe and 22 Livingston counties of eastern Michigan.4 The linear programming model will compute returns above variable cost for the small, medium and large types of equipment in each group of farms. Returns above variable costs will be reduced by fixed costs so that the results can be comparable between equipment groups. A linear regression model can be used to test the importance of several variables on the decision making process. The regression model should consider measures of the size of operation and working capacity. The only exception is a dummy variable to reflect the 1975 change in investment tax credit from 7% to 10%. These types of variables should be considered because they are important in determining which size of equipment to purchase. The following linear regression model was hypothesized to determine the predictability of tractor size purchases: Size of tractor = f(size of tractor traded in, tillable acres farmed, purchased horsepower of existing tractors, returns above variable costs, farm labor, percentage of favorable work days during the spring, investment tax credit). The hypothesis used in building this model was that the purchase of the tractor is influenced by the amount of work to be done, the farm's resources in labor and machinery, disposable income and the investment tax credit allowed. The model used the number of tillable acres after the purchase to reflect the amount of work to be done. Because a tractor is a capital investment which will be used for several years, the number of tillable acres after the purchase was used instead of the number of tillable acres before the purchase. The calculated regression coefficient should be positive because larger farms should have a need for large tractors to provide the necessary working capacity. 23 Another variable is the estimated favorable field work days in the spring. This variable showed how much time the farmer felt was available for his planting operations. The regression coefficient should be negative because a farmer who thought that he had more days to plant in the spring might be less likely to buy a large tractor than a farmer who felt that he had limited time to do his spring work. Variables which indicate the farm's work capacity are drawbar horsepower of trade-in, horsepower of tractors available for field work and adult equivalents of farm labor. Drawbar horsepower of the trade- in was used because most purchases are to replace a worn-out or an out-dated model. Since most farmers who purchase tractors are expanding instead of decreasing their size of operation, the regression coefficient should be positive. The horsepower of tractors available for field work and labor in adult equivalents are both measures of work capacity of the farm. The regression coefficient should be negative for both of these variables because small tractor horsepower and few adult labor equivalents would suggest the need for a large tractor, and a large amount of existing horsepower and several workers would in- dicate that a large tractor might not be needed. Estimated returns above variable costs were used to indicate the amount of money available for a tractor purchase. This variable should have a positive sign on the regression coefficient because a farmer would be willing to invest more in a larger tractor if his income from the previous crop year had been good than if it had been a low income year. It was decided that this variable needed to be estimated because of the difficulty of obtaining this information from farmers. Income estimation is to be accomplished by using yearly variable cost of 10 production budgets, average yearly price and average yield for Saginaw 24 Valley cash crop farms.6 For each year and commodity, the return above variable cost per acre was calculated and multiplied by each farmer's reported acreage of each commodity to compute an estimated return above variable cost. The variable which represented the change in investment tax credit was coded so the years before 1975 were set equal to zero and purchases in 1975 and 1976 were given the value one. When the investment tax credit changed from 7% to 10% after 1974, this was an incentive for more investment. The regression coefficient should be positive because of increased advantage of purchasing large tractors when the investment tax credit rate increased. The linear regression model can be used to estimate the relationships between each of the independent variables and the size of tractor pur- chased. From the results of this analysis, the impact of each of the independent variables on the size of tractor purchased can be determined. Data Collection Techniques The approach used in this study was first to collect data which could be used to determine factors important in the decision making process, and second to analyze the comparative advantage»or disadvantage of different sizes of equipment. To make the study manageable and the sample data comparable, Huron and Tuscola counties in Michigan were selected as the study area. This area has had a large increase in use of large tractors. It is an important agricultural area. Most of the farms in this area are comparable because production is mainly cash crops of corn, edible beans, sugar beets and small grains. Data collection began by first contacting several Cooperative Extension agents in the study area for their insights regarding the trend towards purchasing larger tractors. From the agents a list 25 of tractor dealers was compiled. Later several of the dealers were contacted for their opinions on the present trend and possible changes in the near future. The next step was to collect a list of farmers who had purchased a tractor within the last six years from the dealers. Farmers on the list were then contacted to complete a questionnaire. The questionnaire contained questions about the size and type of operation, tractor purchased, other tractors used for field work, labor force and questions about the reasons for a tractor purchase (Appendix A). The method of selecting farmers to interview was not a random selection. The list of farmers was from dealers and did not include a complete list of all farmers who had purchased a tractor. Also attempts were made to get an equal mix of large and small tractors. A questionnaire was administered to the farmers as they appeared on the list. Some of the questionnaires were not used because of incomplete data or because the operation was not a cash crop farm. When a ques- tionnaire was rejected, another farmer was selected from the list. Fifty-six questionnaires were used in the data analysis. ENDNOTES 1A.R. Jones, Factors Affecting Tractor Purchases and Expenditures, MS Thesis, Department of Agricultural Economics, MSU, 1966. 2L.D. Lambert, The Relationship of Intentions to Buy and Subsequent Purchase of Farm Machinery, MS Thesis, Department of Agricultural Economics, MSU, 1964. 35.8. Harsh, A Progress Report on TELPLAN Activities, Department of Agricultural Economics, Michigan State University, 1979. 4R.A. Hinton, User's Guide For Corn, Soybean Farm Planning Guide, form l, 1973. 5w. Knoblauch, s. Nott, G. Schwab, s. Harsh, J. Black, Michigan Farm Enterprise Budgets, Agricultural Economics Report, Department of Agricultural Economics, MSU, No. 295, 1972, 73, 74, 75, 76. 6 “TELFARM”, yearly summary for the Saginaw Valley, (unpublished), I971, 72, 73, 74, 75, 76. 26 CHAPTER III ANALYSIS OF DATA The procedure employed to analyze the data was first to compile the data into tables which could help identify similarities and differences. Later the regression model was tested, and finally the linear programming model was used to compare the economic advantage or disadvantage of different equipment sizes. Characteristics of Farms in Survey The range of farms in the sample was from a low of 300 tillable acres to a high of 2,850 tillable acres. The data were grouped by tillable acreage from 300 to 599 acres, 600 to 999 acres, 1,000 to 1,299 acres and 1,300 or more acres. The size groupings had a fairly even distribution of observations. Both the first and second classes had 16 observations, the third class had 13 observations and the last class had 11 observations. Table 3-1 shows the average values and standard deviations of several variables within each of the tillable acreage class groupings. From Table 3-1, several observations can be made about the similarities and contrasts between groups. The drawbar horsepower of the tractor bought, total drawbar horsepower of other tractors, farm labor and the change in total average horsepower all increase with tillable acreage. This trend is consistent with the regression hypothesis that larger farms need more equipment and labor. 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N QNG‘U‘IOW >< ll 4 estimated returns above variable costs in dollars X5 = farm labor in yearly adult equivalents (1 adult equivalent = 3,000 hours of labor) X7 = investment tax credit dummy variable 0 1 purchases in 1971, '72, '73 and '74 purchases in 1975 and '76 X = tillable acres divided by the horsepower of tractors available for field work excluding the purchased tractor X = farmer's estimation of favorable field days in the spring divided by the number of tillable acres 36 B B1 . . . B9 = regression coefficients of constant term and 0 independent variables E = error term The new variable, tillable acres per horsepower of tractors available for field work excluding the purchased tractor, should have a positive regression coefficient. A farmer who has more acres per horsepower would need to increase his tractor power by purchasing a large tractor. The opposite should be true of a farmer who has a small ratio of acres to tractor horsepower. The regression coefficient on the number of favorable field days per tillable acre should have a negative sign. A farmer who estimates he has more time per acre would be less likely to purchase a large tractor than a farmer with less time per acre. The estimated regression coefficients were: (4) Y = 109.3 + .360(X]) + .OOOl(X4) - 4.375(X5) + 33.664(X7) (3.488)* (4.205)* (2.236)* (-.949) (2.670)* + 2.510(x8) - .684(X9) (.441) (-.879) R2 = .485 F statistic (6,49) = 7.694 *These coefficients were significantly different from zero at the 90% confidence level. In the revised model, each of the estimated coefficients had the correct sign to agree with the regreSsion hypothesis. According to the results, when a farmer buys a tractor it will have more horsepower than the trade-in. The amount of disposable income and government incentives also have a positive effect on the size of tractor purchased. When farm income is up, farmers tend to purchase larger tractors. The 37 other variables had a hypothesized coefficient sign, but they were not significantly different from zero at the 90% confidence level. The decision to accept or reject the results of the model was based on the calculated F statistic and the table value for rejecting or accepting the F test. The table value for F(.90,6,49) = 1.91. The calculated F value was 7.69 so one or more of the coefficients is significantly different than zero. The R2 value was 48.5 percent. This means that 48.5% of the variation in the dependent variable is explained by the independent variables. Equation 4 was preferred to equation 3 even though the R2 value is slightly less. The reasons for preferring the results of the re- formulated model were that more independent variables were significant and all of the coefficient signs were the same as hypothesized. Comparative Economics of Different Size Machinery Systems Before the linear programming model could be run, several field work rates were calculated for each type of equipment. In each farm size group, the farms were grouped by total tractor horsepower. These three different groups of equipment were based on 25% of the farms with the largest total tractor horsepower, and the middle 50% of the farms with average total horsepower. The four farms that were in the small equipment group of the 300 to 599 tillable acres group had an average of 165.8 total tractor horsepower, 2.25 tractors and 1.55 adult equivalents. The average size of tractor purchased was 92.4 horsepower. A representative farm which represents each size group was developed by the researcher and is tabulated in Table 3-4. 38 Table 3-4. Machinery and Labor Systems on Representative Farms for the Small Group of Farms. Machinery and Labor System Small Medium_ Large Tractor 94 HP 108 HP 135 HP 71 HP 74 HP 86 HP 55 HP 74 HP 32 HP 42 HP 27 HP Tillage 5-16" plow 5-16" plow 7-16" plow 18' f. cult 18' f. cult 4-16" plow 20' f. cult Plant 8 r. planter 8 r. planter 8 r. planter 14' drill 14' drill 14' drill Harvest 3 r. beet 3 r. beet 4 r. beet combine combine combine Labor 1.55 adult eq. 1.75 adult eq. 2.38 adult eq. Because the interest is in the effect of different sizes of tractors, all equipment combinations have the same combine. The size of a combine is not determined by tractor size. After selecting the above equipment, their work capacity was calculated based on a study by White.1 39 Table 3-5. Work capacity on Representative Farm for the Small Group of Farms by Equipment Size. Equipment System Operation Small Medium Large Plowing 2.72 acres/hr. 2.90 acres/hr. 2.99 acres/hr. Plant corn 3.10 " " 3.10 " " 3.29 " " Plant navy beans 3.20 " " 3.20 " " 3.43 " " Plant sugar beets 2.90 " " 2.90 " " 3.14 " " Drill wheat 2.96 " " 2.96 " " 3.14 " " Drill oats or barley 2.78 " " 2.78 " " 2.94 " " Harvest sugar beets 4.50 " " 4.50 " " 6.00 " " Harvest corn 3.70 " " 3.70 " " 3.70 " " Harvest navy beans 5.00 " " 5.00 " " 5 OO " " Using TELPLAN program 18, the above equipment was used on an identical representative farm which is the average of all farms in the smallest class of tillable acres. This hypothetical farm, for all sizes of machinery systems, produced: Corn 133 acres Navy beans 144 " Sugar beets 42 " Wheat 53 " Barley 8 " Oats 6 " The above method of selecting low, medium and high sets of equipment and labor was used for each of the land size classes in Table 8 (appendix B). The work coefficients were also calculated the same way. A list of the labor, equipment and rate of work of each set of equipment is in appendixes C and D. From the linear programming model, the following data were calculated on three different sizes of equipment in each of four different sizes of the representative farms. A more complete listing of the results is in the appendix E. 40 Table 3-6. Returns Over Variable Costs on Four Representative Farms with Different Sizes of Equipment.* Representative Equipment Size Farm Size (Tillable Acreage) Small Medium Large 386 acres $37,736 $37,873 $38,981 699 acres 59,115 60,122 60,467 982 acres 78,712 88,321 91,364 1860 acres 84,229 88,691 90,974 *Variable costs include a land charge for property tax and land rent. Property tax was estimated to be $24.80 per acre. (31 mil at $800 per acre). The median cash rental rate of $50.00 per acre was used. Before an analysis could be performed on the comparative advantage or disadvantage of the different equipment sizes, the data was adjusted for fixed costs and labor costs. Fixed cost on equipment consisted of depreciation, interest and insurance. Depreciation was estimated by using the straight line method with a varying years of life depending on the type of equipment and a 10% salvage value. The average retail price for each piece of equipment was taken from the Official Guide Tractors and Farm Equipment.2 Where data were not available, local dealers gave an estimated average retail price. Both interest and insurance were based on the average value. They were calculated as a percentage of the average value. Interest was 7% and insurance was 1%. An interest rate of 7% was used because at the time of the survey. Spring, 1977, this was the approximate rate of opportunity cost. 41 Table 3-7. Total Annual Fixed Costs for Different Equipment Sizes on the Representative Farms. Representative Equipment Size Farm Size (Tillable Acreage) Small Medium Large 386 acres $10,469 $11,771 $15,996 699 acres 14,122 14,432 10,758 982 acres 18,326 23,628 25,672 1860 acres 25,005 29,525 31,662 The labor costs were estimated by taking the field time for each operation times the number of men needed times the wage rate of $3.50. The median wage rate from the results of the applied questionnaire was $3.50. Table 3-8. Total Annual Labor Costs for Different Equipment Sizes on the Representative Farms. Representative Equipment Size Farm Size (Tillable Acreage) Small Medium Large 386 acres $ 1,989 $ 1,933 $ 1,872 699 acres 3,399 3,316 3,161 982 acres 3,950 3,721 3,476 1860 acres 7,249 7,084 6,895 After adjusting for fixed costs and labor costs, the total farm net returns were divided by the number of acres. The net return per acre was used to compare the economic advantage or disadvantage of 42 different equipment sizes. Within each size group, the difference observed in net return per acre reflects the timeliness in the cropping system. Timeliness was determined based on the available work force and equipment work capacity. Some caution should be used when net return per acre is compared between size groups. The crop mix is slightly different for each size of farm and could account for differences. The mix of rented and owned land would result in different variable costs per acre. Table 3-9. Net Return Per Acre Over Fixed and Variable Costs for the different Equipment Sizes on the Representative Farms. Representative Equipment Size Farm Size (Tillable Acreage) Small Medium Large 386 acres $65.49 $62.61 $55.73 699 acres 59.51 60.62 53.42 982 acres 57.47 62.09 63.39 1860 acres 27.94 26.93 28.18 Table 3-6 shows that as equipment size increases, the returns above variable costs also increases. This was true for every farm size. Additional equipment made the farm operation more likely to complete its work on time. Net return per acre in Table 3-9 varies for the different farm sizes. In the first size farm, the smallest equipment was the most profitable. The medium equipment was the most profitable in the second farm size and the large equipment showed more profitlnithe last two farms. From Table 3-9, the results indicate that many farms are under 43 equipped or over equipped. Where the operation is in a state of change, this could be a short run problem. However, if this is not corrected in the long run, the operation will be at a financial disadvantage. The net return per acre between different sizes of the representative farms shows the different economies of size. As the number of tillable acres increases, the net return per acre decreases. At the same time, total farm returns above variable costs increase. ENDNOTES 1Robert G. White, Effect of Speed on Power Requirements for Selected Farming Operations, Agricultural Engineering Facts, Michigan State University, No. 41, file 18.4, 1975. 2National Farm and Power Equipment Dealers Association, Official Guide Tractors and Farm Equipment, Lansing, Michigan, 1971, '72, '73, '74, '75, T76. 44 CHAPTER IV CONCLUSIONS The trend in tractor purchases has been to larger tractors. Between 1973 and 1976, tractors of 170 drawbar horsepower or more had increased sales of 277.3% in Michigan. During the same period, the sales of tractors with less than 100 horsepower decreased to 72.8% of their 1973 sales. In the analysis of factors affecting tractor purchases, a linear regression model showed that tractor purchases were affected by net farm income, government tax incentives and the size of the tractor traded. The other variables in the model (tillable acres per tractor horsepower, farm labor and farmers' estimation of favorable field work days in the spring divided by the number of tillable acres) had correct coefficient signs but were not significantly different from zero at the 90% confidence level. The model indicates that the observed trend to larger tractors was because there were favorable returns to investments in agriculture and government incentives for machinery investment. The farmers' decisions were influenced by the size of tractor to be traded in. The regression model coefficient was positive, showing a trend to trade for larger tractors. The average tractor purchased is twice the size of the trade-in. Reasons for trading to larger tractors are timeliness factors during the planting or harvesting season or adoption of a cropping system which requires more horsepower. In 1975, the investment tax credit was changed from 7% to 10%. Investment tax credit is a government incentive for investment. The 45 46 The credit is a percentage of the investment cost which can be used to offset federal income tax due. The regression coefficient showed that there is a positive correlation between larger tractor purchases and the investment tax credit change. When the investment tax credit rate changed from 7% to 10%, there was an increase in the size of tractor purchased. Another important variable in the decision process is net farm income. When net farm income increased, there was also an increase in the size of tractor purchased. A high net income facilitates financing and also induces a purchase to decrease tax liabilities. The size of the tractor that a farmer purchases was determined by the tractor to be traded in, government tax incentives and net farm income. As long as tax incentives continue, and net farm income is high, the trend to large tractors should continue as long as they can be used on sufficient acreage to make them economical. Depending on the severity of the change, a reduction in net farm income or government incentives would slow down or reverse the trend. In the trend to larger tractors it is desirable to maintain a proper mix between machinery, labor and other resources. Farms that have too much or not enough machinery resources in relation to other resources will be at a competitive disadvantage. The estimated net returns per acre were calculated from theiresults of the linear programming model for the different equipment sizes. Within each size of farm there is a difference between returns per acre with the type of equipment used. The smallest farm size had net return per acre which varied as much as $10 depending on the size of the equipment system. Each of the four farm sizes had a difference 47 in net returns per acre with different sizes of machinery. While net return per acre decreased with farm size, total farm returns increased. The largest representative farm had an estimated average return above variable costs of $87,298. The smallest representative farm had an estimated average return of $26,863. Even though net return per acre varied within each farm size, there was not a trend to suggest that one equipment size was at an advantage or disadvantage among all farm sizes. The smallest farm had the highest return with the smallest equipment. The two largest farms had the highest net returns with the largest machinery system. Only the second farm size had a higher net return with the medium type of equipment. The trend to larger equipment has not put farmers at an economic disadvantage. If large equipment put farms at an economic disadvantage, net profit per acre would have shown large equipment to be the least profitable in all farm sizes. From the results of the questionnarie data, it can be concluded that there are several farms which are not on the expansion path. The data used in this study shows the smaller farms usually have too much equipment and large farms are underequipped. To maintain the proper mix of machinery, labor and other inputs, farmers should be on the expansion path. If the situation persists where farmers do not have the proper resource mix, they will have a financial handicap. APPENDICES APPENDIX A Field Questionnaire Name: Phone: Address: Tractor Purchases and On Hand: Date of Principal Model Purchase Model Tractor hrs./yr. Use Traded (Purchased) (Owned) (Purchased) (Owned) What options were on the tractor purchased and what extra equipment was needed? 1. 2. Is your equipment used on a partnership basis? Why did you select the model purchased? (Rank by importance) Replace worn out model Needed more power, why Only model available then Goes with other equipment Special features Other reasons (see comments) Hf—‘flflI—ll-‘I L—JI—JL—lL—Jl—JL—J What influenced the timing of your purchase? (Rank by importance) [ Reduce taxes When dealer received it Problem with other tractors Easier to get financing at this time Cash flow Other reasons (see comments) flflHI—II—‘I l—ll—JI—JI—JL—fl—l Are rented, leased or custom hire tractors available? Cost? Terms? 48 49 Have you ever rented, leased or used custom hire tractors? When? Do you have a brand preference in your tractor purchases? Why? [ 1 Dealer service [ ] Have always been satisfied with brand [ ] Convenient location [ ] Other reasons (see comments) Acreage in Tillable Crops: Year Before Year of Crop Purchase Owned Rented Purchase Owned Rented l. 2. 3. 4. 5. l. 2. 3. 4. 5. If you are using rented land, what are the terms? When are your most critical time requirements? Last year, when did you start and finish planting corn? Harvesting corn? Given favorable weather, how many working days are needed to: Prepare land Plant Harvest l. 2. 3. 4. 5. DWNd 50 In an average year, how many favorable work days do you have to: Prepare and Plant Harvest U'l-PWN-d Farm Labor: Time available for field work; family and hired; (including owned) before and after purchase: During your critical time commitments, is it possible for you to hire extra help? How many hours per day? Cost? Age of operators Number of years in farming APPENDIX B Cropping Program of Representative Farms APPENDIX B Table B-1. Cr0pping Program of Representative Farms Farm Size Small Medium Large Extra Large Corn 133 acr. 252 acr. 401 acr. 951 acr. Navy beans 144 acr. 206 acr. 269 acr. 495 acr. Sugar beets 42 acr. 109 acr. 168 acr. 101 acr. Wheat 53 acr. 96 acr. 117 acr. 193 acr. Barley 8 acr. l4 acr. 8 acr. 105 acr. Oats 6 acr. 22 acr. l9 acr. 15 acr. 51 APPENDIX C Machinery and Labor Systems for Representative Farms 52 Table C-l. Machinery and Labor Systems on 386 Tillable Acre Representative Farm Size Machinery System Small Medium Large Tractor 94 HP 108 HP 135 HP 71 HP 74 HP 86 HP 55 HP 74 HP 32 HP 42 HP 27 HP Tillage 5-16" plow 5-16" plow 7-16" plow 18' f. cult. 18' f. cult. 4-16" plow 20' f. cult. Plant 8 r. planter 8 r. planter 8 r. planter 14' drill 14' drill 14' drill Harvest 3 r. beet 3 r. beet 4 r. beet combine combine combine Labor 1.55 adult eq. 1.75 adult eq. 2.38 adult eq. 53 Table C-2. Machinery and Labor Systems on 699 Tillable Acre Representative Farm Size Machinery System Small Medium Large Tractor 126 HP 126 HP 135 HP 108 HP 104 HP 113 HP 32 HP 84 HP 108 HP 55 HP 85 HP 45 HP Tillage 6-16" plow 6-16" plow 7-16" plow 5-16" plow 5-16" plow 6-16" plow 20‘ f. cult. 20' f. cult. 5-16" plow 24' f. cult. Plant 12 r. planter 12 r. planter 12 r. planter 14' drill 14' drill 14' drill Harvest 4 r. beet 4 r. beet 4 r. beet combine combine combine Labor 3.0 adult eq. 2.5 adult eq. 3.75 adult eq. 54 Table C-3. Machinery and Labor Systems on 982 Tillable Acre Representative Farm Size Machinery System Small Medium Large Tractor 155 HP 181 HP 194 HP 113 HP 132 HP 135 HP 86 HP 68 HP 108 HP 33 HP 74 HP 55 HP Tillage 8-16" plow 9-16" plow 10-16"plow 6-16" plow 7-16" plow 7-16" plow 36' f. cult. 38' f. cult. 38' f. cult. Plant 12 r. planter 12 r. planter 12 r. planter 14' drill 14' drill 14' drill Harvest 4 r. beet 6 r. beet 6 r. beet combine combine combine Labor 2.33 adult eq. 2.86 adult eq. 2.66 adult eq. 55 Table C-4. Machinery and Labor Systems on 1860 Tillable Acre Representative Farm Size Machinery System Small Medium Large Tractor 181 HP 202 HP 227 HP 135 HP 160 HP 194 HP 108 HP 108 HP 135 HP 42 HP 94 HP 64 HP 33 HP 47 HP Tillage 9-16" plow 10-16" plow 12-16" plow 7-16" plow 8-16" plow 10-16" plow 38' f. cult. 38' f. cult. 7-16" plow 40' f. cult. Plant 12 r. planter 12 r. planter 12 r. planter 14' drill 14' drill 14' drill Harvest 6 r. beet 6 r. beet 6 r. beet combine combine combine Labor 3.17 adult eq. 3.3 adult eq. 3.17 adult eq. APPENDIX 0 Field Work Speed on Representative Farms by Different Equipment Systems 56 Table D-l. Field Work Speed on 386 Tillable Acre Representative Farm with Different Equipment Systems Equipment System Operation Small Medium Large Plowing 2.72 acr./hr. 2.90 acr./hr. 2.99 acr./hr. Plant corn 3.10 acr./hr. 3.10 acr./hr. 3.29 acr./hr. Plant navy beans 3.20 acr./hr. 3.20 acr./hr. 3.43 acr./hr. Plant sugar beets 2.90 acr./hr. 2.90 acr./hr. 3.14 acr./hr. Drill wheat 2.96 acr./hr. 2.96 acr./hr. 3.14 acr./hr. Drill oats or barley 2.78 acr./hr. 2.78 acr./hr. 2.94 acr./hr. Harvest sugar beets 4.50 acr./hr. 4.50 acr./hr. 6.00 acr./hr. Harvest corn 3.70 acr./hr. 3.70 acr./hr. 3.70 acr./hr. Harvest navy beans 5.00 acr./hr. 5.00 acr./hr. 5.00 acr./hr. Table D-2. Field Work Speed on 699 Tillable Acre Representative Farm with Different Equipment Systems Equipment System Operation Small Medium Large Plowing 2.99 acr./hr. 2.99 acr./hr. 3.29 acr./hr. Plant corn 3.29 acr./hr. 3.29 acr./hr. 3.69 acr./hr. Plant navy beans 3.43 acr./hr. 3.43 acr./hr. 3.86 acr./hr. Plant sugar beets 3.13 acr./hr. 3.13 acr./hr. 3.50 acr./hr. Drill wheat 3.14 acr./hr. 3.14 acr./hr. 3.46 acr./hr. Drill oats or barley 2.94 acr./hr. 2.94 acr./hr. 3.26 acr./hr. Harvest sugar beets 6.00 acr./hr. 6.00 acr./hr. 6.00 acr./hr. Harvest corn 3.70 acr./hr. 3.70 acr./hr. 3.70 acr./hr. Harvest navy beans 5.00 acr./hr. 5.00 acr./hr. 5.00 acr./hr. 57 Table D-3. Field Work Speed on 982 Tillable Acre Representative Farm with Different Equipment Systems Equipment System Operation Small Medium Large Plowing 3.81 acr./hr. 4.35 acr./hr. 4.62 acr./hr. Plant corn 4.60 acr./hr. 4.75 acr./hr. 4.75 acr./hr. Plant navy beans 4.90 acr./hr. 5.03 acr./hr. 5.03 acr./hr. Plant sugar beets 4.30 acr./hr. 4.43 acr./hr. 4.43 acr./hr. Drill wheat 4.17 acr./hr. 4.25 acr./hr. 4.25 acr./hr. Drill oats or barley 3.96 acr./hr. 4.10 acr./hr. 4.10 acr./hr. Harvest sugar beets 6.00 acr./hr. 9.00 acr./hr. 9.00 acr./hr. Harvest corn 3.70 acr./hr. 3.70 acr./hr. 3.70 acr./hr. Harvest navy beans 5.00 acr./hr. 5.00 acr./hr. 5.00 acr./hr. Table D-4. Field Work Speed on 1860 Tillable Acre Representative Farm with Different Equipment Systems Equipment System Operation Small Medium Large Plowing 4.35 acr./hr. 4.90 acr./hr. 5.25 acr./hr. Plant corn 4.75 acr./hr. 4.75 acr./hr. 4.87 acr./hr. Plant navy beans 5.03 acr./hr. 5.03 acr./hr. 5.17 acr./hr. Plant sugar beets 4.43 acr./hr. 4.43 acr./hr. 4.54 acr./hr. Drill wheat 4.25 acr./hr. 4.25 acr./hr. 4.34 acr./hr. Drill oats or barley 4.10 acr./hr. 4.10 acr./hr. 4.15 acr./hr. Harvest sugar beets 9.00 acr./hr. 9.00 acr./hr. 9.00 acr./hr. Harvest corn 3.70 acr./hr. 3.70 acr./hr. 3.70 acr./hr. Harvest navy beans 5.00 acr./hr. 5.00 acr./hr. 5.00 acr./hr. APPENDIX E Results of Linear Programming Analysis of Representative Farms 58 Table E-l. Results of the Linear Programming Analysis on 386 Tillable Acre Representative Farm with Different Equipment Sizes Equipment Size Item Small Medium Large Return above $37,736 $37,873 $38,981 variable cost Corn yield 98 bu/acre 98 bu/acre 98 bu/acre Navy bean yield Scarce resources: Planting time June 4-June 11 17.3 cwt/acre $104.54/hr. 17.3 cwt/acre $107.81/hr. 17.5 cwt/acre $111.08/hr. Table E-2. Results of the Linear Programming Analysis on 699 Tillable Acre Representative Farm with Different Equipment Sizes Equipment Size Item Small Medium Large Return above variable cost $59,115 $60,122 $60,468 Corn yield Navy bean yield Scarce resources: 91.8 bu/acre 17.2 cwt/acre 92.4 bu/acre 17.3 cwt/acre 96.8 bu/acre 17.4 cwt/acre 59 Table E-3. Results of the Linear Programming Analysis on 982 Tillable Acre Representative Farm with Different Equipment Sizes Item Equipment Size Small Medium Large Return above variable cost Corn yield Navy bean yield Scarce resources: Planting time April 25-May 10 June 4-June 11 $78,712 $88,321 92.8 bu/acre 97 bu/acre l7 cwt/acre 17.8 cwt/acre $67.90/hr. $160.08/hr. $69.98/hr. $179.85/hr. $91,384 98.3 bu/acre 18.3 cwt/acre $230.21/hr. Table E-4. 60 Results of the Linear Programming Analysis on 1860 Tillable Acre Representative Farm with Different Equipment Sizes Item Equipment Size Small Medium Large Return above variable cost Corn yield Navy bean yield Scarce resources: Land preparation Sept. 27-0ct. 17 Oct. 18-Nov. 7 Nov. 8-Nov. 28 Apr. l-Apr. 24 Apr. 25-May 10 May 11-May 18 May 19-May 26 May 27-June 3 June 4-June 11 Planting time Apr. 25-May 10 May ll-May 18 May 19-May 26 May 27-June 3 June 4-June 11 $84,229 87.8 bu/acre 17.1 cwt/acre $44. $44. $44. $44. $255. $184. $114. $44. $44. $255. $184. $114. $44. $181. OO/hr. OO/hr. OO/hr. OO/hr. 06/hr. 21/hr. 51/hr. OO/hr. OO/hr. O6/hr. 21/hr. 51/hr. OO/hr. 50/hr. $86,691 88.3 bu/acre 17.1 cwt/acre $211. $140. 70. $211. $140. $70. $181. O6/hr. 21/hr. 51/hr. O6/hr. 21/hr. 51/hr. 50/hr. $90,974 90.2 bu/acre 17.2 cwt/acre $143.47/hr. $71.15/hr. $187.04/hr. APPENDIX F Input Form for TELPLAN Program Number 18 (Crop Farm Planning Guide a TELPLAN Program) CROP FARM PLANNING GUIDE A TELPLAN PROGRAM* NAME ADDRESS Program: 18 Form: 3 System: ‘ L H-T : Data FiIE—Ro: PHONE DATE RUN BUDGET ANALYSIS Problem: To determine the most profitable mix. corn, soybean. and other crap acreages given expected prices, yields, production costs. machinery performance. field time, and land available. Too, the program can be used to explore the machinery requirements for alternative land and labor bases. ”3111‘ LINE FIRST ' .110. ANALYSIS SECTION I. CROP BUDGETS AND TILLABLE‘ACREAGE AVAILABLE: I Tillable Acres 01. 1 1 a. Owned ""i-" b. Rented 2 Corn Budget (Owned Land) 02. a. Expected corn vield (bu. 0 15.5% moisture) When planted during the period April 26-May 10 and har- vested during the period October 4-10. b. Expected variable cost (Slacre) excluding drying costs. c. Expected drvine costs (¢/bu.) for drying corn down one point. 3 Corn Budget (Rented Land) 03. a. Expected yield. If share-rented, enter your share. b. Expected variable costs. If share-rented. enter your share. b 4 Soybean Budget (Owned Land) 09- | . r a. Expected yield when planted "T — ""'"E°‘ during the period hay 19-26 and harvested during the period September 27-October 3. b. Expected variable cost. 5 Soybean Budget (Rented Land) 05. 'a. Expected vield. It share-rented. enter your snare. b. Expected variable costs. It share-rented. enter your share. |_7~4__?m. SECTION II. LAND PREPARATION, PLASTIXG, AND POST LANTISG OPERATIONS: 6 Land Preparation a. Fall land (acres prepared/hour) b. Spring land (acres prepared/hour) c. I! yield on spring prepared ground is different than the yield on f 11 prepared ground. enter the estimated percentage at {all yield. 1 ADJUSTED 1—-;-1--.,— -— 1 1 1—7-—1-—1;-—1 1 1—-,--—1—-1,--—1 05- 1-1--|--5---|—-;-I |--;°-j|--5'-|--;—! i . Dari: program developed as 8 cooperative effort bv J. Rov Black and Stephen B. Marsh. Michigan State University; Duane Ericksr: and Royce Hinton, University 0! Illinois: Iright, Ohio State University. 61 and Ailau Lines and Paul 62 LINE FIRST , ADJUSTED .1102 ANALISIS ANALYSIS 7 'EIricres planted/hour 07. "7 °— l"? ""l I“? '- l"? "I b. Acres harvested/hour 8 Soybean 03- a. Acres planted/hour l-7'—I—D°_I-?-I l_T°—l-D '— I..-- b. Acres harvested/hour c. Estimate what percentage a typical harvesting day {or corn can be used in harvesting soybeans SECTION III. TIME AVAILABLE FOR FIELD OPERATIONS: (If you want to enter individualized time availability. enter "0" in line 09 and complete lines 10 through 16. Otherwise, complete line 09 and proceed to line 17.) 9 Machine-Man Equivalent Availability 09. 1 . a. Fall land preparation -' ‘- D. Spring land preparation c. Planting d. Harvesting 10 Fall Land Preparation (Hours/Period) 10. |______{__ a. Sept. 27-Oct. 17 (21 days) '5- Days xhrs/dayw % D. Oct. 18- Nov. 7 (21 days) Days xhrs/day Fa c. Nov. E-Dec. 12 (35 da,s) Days___ xhrs/day 2'6 11 Spring Land Preparation (Hours/Period) 11. April 1-April 24 (24 days) Days I: hrs/day D. ApriI ES-Way 10 (16 days)? Days xhrs/day c. lay ll-uay 18 (8 days) Days x hrs/day '5 1——-1—~,-—1--c--1 l--;--—l-—~5-I-—-l C 12 (Spring Land Preparation Continued) 12. a. May 19-Way 26 (8 days) Days x hrs/day 83 D. May 27-June 3 (8 day 3) Days 7: hrs/day ‘5 c. June 4-3une 11 (8 da,s) Days 8 hrs/day '5 13 Planting (Hours/Period) a. April 25-" .ay 10 (16 days) Days ths/day c D.May11I-Hay 18 (3 days) Days x hrs/dav__ c. May115-Hay 26 (8 days) Days xhrs/day 13'1—7—1—3-1-3—1 1-7—1-3-1—3- “Q 51! 14 (Planting Continued) 10. a. May 27-June 3 (8 days) Days xhrs/day D. June I-Dune 11 (6 days) Days x hrs/day c. June 12-3une 19 (8 days) Days 7: hrs/day 2’8 I—-;--l---g-l---c—-I l--;--I-—-5---|---;-l a I. 3.1 15 Harvest (Hours/Period) 15. __ _ _ _____ ____ _ __ ____ a.Sept.27-.Oct3(7days) la""5lcI I a '6' c Days xhrs/day S D. Oct. K-Oct. 10 (7 da,s) Days xhrs/ day” % c. Oct. Ii-Oct. 17 (7 days) Days xhrs/day ‘3 63 LINE FIRST ' ADJUSTED . .flfli AflALISlS ANALISJS 16 (Harvest Continued) ' 16. I I I I a. Oct. 18-Nov. 7 (21 days) ‘71" “‘8" "7‘4"?" Days x hrs/day x % b. Nov. -Nov. 28 (21 days) Days x hrs/day x 5 SECTION IV. TRADE—OFFS BETWEEN FIELD OPERATIOXS: 17 Trade-offs between spring land prepa- 17. I I I I I I I__I__I__I__I ration planting and the planting opera- 1 '5 ? -d' '3 a b c d e' tion would occur in (O - no; 1 - yes) a. Apr. ZS-nay 10 b. May 11-May 18 c. May 19-May 26 d. May 27-June 3 e. June 4-June 11 18 Trade-offs between harvest and fall 18. I I I I I I I I I__I__I__I land preparation would occur in 7; 15 75 71 73 1f '5 c d e (O - no; 1 - yes): a. Sept. 27-Oct. 3 b. Oct. 4-Oct. 10 c. Oct. 11-Oct. 17 d. Oct. 18-Nov. 7 e. Nov. B-Nov. 28 SECTION V. CUSTOM HIRE FIELD WORK: 19 Enter "1" it you are interested in 19. I__I I__I__I I__I__I__I__I custom hiring to replace or supplement a '5 c d a b c d self-performed field operations; otherwise, enter ”0" a. Fall preparation b. Spring preparation c. Soybean harvest d. Corn harvest 20 FIJI Preparation ' 20. |____ |__ ._ |____ I___ '-| a. Maximum number of acres a b I b b. Net rate (custom rate 5 /A - q variable cost of own talI prepara- tion S /A) 21 Spring Preparation (maximum acres 21. I____ I_____I I____ I____ available/period) a b a b a. Apr. 1-May 10 D. May 11-May 18 22 Spring Preparation 22. |-—--|——'— I_______ |——’-’ a. May 19-May 26 - ' a b D b. Net rate (custom rate 8 /A - variable cost of own fall prepara- tion 8 IA) 23 Soybean Harvest (maximum acres 23. I______I______I______I I______I__ __I______ available/period) a b c ‘5 . Sept. 27-Oct. 3 (7 days) D. Oct. 4-Oct. 10 (7 days) c. Oct. 11-Oct. 17 (7 days) 24 (Soybean Harvest Continued) 2Q. |-—-|——°-I I___I_ '—l a. Oct. 18-30v. 7 (21 days) a b a "D b. Net rate (custom rate 5 IA - S [A + (-) loss (gain) associated with custom harvest) 64 [IUE FIRST .10... ANALISJS 25' |-1;-|-'1;-'l-'1;‘-| ADJUSTED ANALYSIS. 25 Corn Harvest (maximum acres available/period) l-1r-l-15-l —'2? “‘1 a. Sept. 27-0ct. 3 (7 days) D. Oct. d-Oct. 10 (7 days) c. Oct. ll-Oct. 17 (7 days) 26 (Corn Harvest Continued) a. Oct. lS-Nov. 7 (21 days) D. Nov. B-Nov. 28 (21 days) c. Net rate (custom rate 5 /A - variable cost of own harvest 3 [A + (-) loss (gain) asso- cIatea with custom harvest) Zfil-r- |-1;-|-15'-|--7;-I l--5--l-—c--| SECTION VI. ALTERNATIVE CROP IEIFORHATION’: 27. 27 ALTERNATIVE CFC? 1 (if no more. enter "0” and proceed to line 57) l'-'-1;‘“-I'5'LE'l-1I-| l'-'-“;'"-'l1;|1§I'-1f-7 a. Net return per acre ( yield/A 3 price - - variable cost 5 IA) D. Land type (0 - no land used; 1 - owned; 2 - rented; 3 - either) o. Acreage restrictionu d. lumber of acres related to re- striction Competition by time periods (when no more competition. enter "0" and proceed to next crop) 28 a. Period of competition code"‘ 28. 30 31 b. c. d. a. b. o. d. a. b. c. d. Hours per Period of Hours per Period of Hours per Period of Hours per Period of Hours per Period of aburs per Period of Hours per Period of Hours per period per acre competition code"‘ period per acre competition code“‘ period per acre competition code“‘ period per acre competition code... period per acre competition code"' period per acre competition code"‘ period per acre competition code“‘ period per acre 29- 30. 31- l1rl-'15-'I-fif'|-"1I-'lI1:1-"15-l-flf-|-'13- l-;I--1;—l—c—l---;-l|1l--1;-l-5-I-q- |1|'-"5'- I17 I- '1-||1|-° '1 b I c F;W-'~5-l-1g-l-‘1{-lLi'F-““5"-I-1;-|-'1;- none; 1 - maximum acres; 2 - actual acres; 3 - minimum acres land preparation (April 1-April 24); 2 - land preparation/planting (April 25-May 10); land preparation/planting (nay 11-uay 18); 4 - land preparation/planting (May 19~nay 26); land preparation/planting (nay 27-June 3); 6 - land preparation/planting (June 4-June 11); planting (June 12-June 19); a I harvest/land preparation (September 27-October 3); harvest/land preparation (October 4-0ctober 10); 10 - harvest/land preparation (October 11- October 17); 11 - harvest/land preparation (October 18-November 7); 12 - harvest/land prepa— ration (November B-November 28). OQOUHO IIIII 32 ALTERNATIVE CROP 2 (if no more. enter ”0” and proceed to line 57) a. Net return per acre ( yield/A x price - - variable cost 5 IA) b. Land type (0 - no land used; 1 - owned; 2 - rented; 3 - either) c. Acreage restriction" d. Dumber of acres related to re- striction 65 LINE FIRST ADJUSTED .NQi ANALYSIS. ANALYSIS 32-; l—--,;--l-g|;I—q--I I——-;°-l-5|;l—-d-- Competition by time periods (when no more competition, enter "0" and proceed to next crop) 33 34 35 36 37 Period of Hours per Period of Hours per Period of Hours per Period of Hours per Period of Hours per Period of Hours per Period of Hours per Period of Hours per competition code"' period per acre competition code"' period per acre competition code"‘ period per acre competition code"‘ period per acre competition code"' period per acre competition code"‘ period per acre competition code"' period per acre competition code"' period per acre ALTERNATIVE CROP 3 (if no more. enter “0” Net return per acre ( b. C. d. x price and proceed to line 57) yield/A variable cost 3 73) Land type owned; 2 - rented; 3 - either) (0 - no land used; Acreage restr1ction“ Number of acres related to re— atriction 33‘ I7I—-;-l—c—l—'i-l|.l-"5- -c-=-°7: 3‘“ l-gl—T-|—¢-|-'1—||7‘-"5"-c‘""3 35- lél_,__I__|_.__||_1_.__l_._ _._ 36' l-;|-'3-l-c—|-"a-”Tl-"5‘"?""d' 37. !——-;°—I-51-;|--3—I |——-;--I-5I?!-—g- '0 Competition by time periods (when no more competition. enter "0" and proceed to next crop) 38 39 40 41 a. c2 ‘0 H. b. c. A d U a. D. O. d. a. b. c. d. Period of Hours per Period of Hours per Period of Hours per Period of Hours per Period of Hours per Period of Hours per Period of Hours per Period of Hours per competition code"' period per acre competition code"' period per acre competition code"‘ period per acre competition code“' period per acre competition code"' period per acre competition code"' period per acre competition code"° period per acre competition code"' period per acre 38. !-;"-‘“g""757""71""WI!"'13-'|-1?-!-.7I 39.- I? b c d if b '75- 40~ l—|--——l——|—-——Il—|-°-—|——|--— a b c d a b c d «1. |-;|—-1,-—l—c—l—"a—H-a-l—us-l-c— _.3 See explanation of footnote on Page 4. See explanation of footnote on Page 4. 42 ALTERNATIVE CPO? 4 (if no more. enter ”0” and proceed to line 57) a. Net return per acre ( x price - - variable cost 5 IA) b. Land type (0 - no land used; 1 - Owned; 2 - rented; 3 - either) c. Acreage restriction-‘ d. Number of acres related to re- Striction - LINE _flfli yield/A FIRST ADJUSTED ANALXSLS AHALXSLS "2' |*——. '— '15 "a “‘3" "—7 "' '1; “a 3‘1 Competition by time periods (when no more competition. enter "0" and proceed to next crop) 43 44 45 46 47 Period of Hours per Period of Hours per Period of Hours per Period of Hours per Period of Hours per Period of Hours per Period of Hours per Period of Hours per competition code"' period per acre competition code"' period per acre competition code“‘ period per acre competition code"‘ period per acre competition code"' period per acre competition code"' period per acre competition code"' period per acre competition code"' period per acre ALTERNATIVE cnop 5 (1: no more. enter '0” and proceed to line 57) Net return per acre ( yield/A x price - - variable cost 5 IA) b. c. d. Land type (0 - no land used; 1 - owned; 2 - rented; 3 . either) Acreage restriction“ Number of acres related to re-' striction .“3' I;I—'-5-I—c—I—-q—II7I---g—l——?-°— m" l?"'t-i-c—'-°a—'|r —"5_i-c_{_°—c “5' I;I—-;—I—c—I—-;—II; —-;-—I—c— —-; “5' I;I—o;—I—c—I—-;—II;I—-;—I—c— -'-; II7. '———r‘—'t'z'-a—' '--'r°-!15"53—a‘ Competition by time periods (when no more competition, enter "0" and proceed to next crop) 48 49 50 51 a. b. c. d. a. b. c. d. a. b. c. ‘0 Period of Hours per Period of Hours per Period of Hours per Period of Hours per Period of Hours per Period of Hours per Period of Hours per Period of Hours per competition code“* period per acre competition code"' period per acre competition code"' period per acre competition code"' period per acre competition code"' period per acre competition code"° period per acre competition code"‘ period per acre competition code“' period per acre us. I 1;|-'-3‘-l'-5-|-'1§-'|I1;|-'~5-l-fig-?-"a I; I- -;— l—c— I—-;— I I; I—-;— I-c— :— .; I— I— -—— I-- l— -—— I I— I—-;-— I—— z— -- b c d a 51. I ; I— o;— l—c— I- ~;— I I; I—-;— l-c- I— -; See explanation of footnote on Page 4. See explanation of footnote on Page 4. 67 -' ' "LINE FIRST ADJUSTED JILL ANALISLS AIIALISLS 52 ALTERVATTVE Prop 6 (1: no more, 52. enter "0" and proceed to line 57) I__T°-I'El?l-_d-‘ l-"mTu—l'El-E [—71-— a. Net return per acre ( yield/A x price - - variable cost 3 IA) b. Land type (0 e no land used; 1 - owned; 2 - rented; 3 = either) Acreage restriction"I Number of acres related to re- striction D-O Competition by time periods (when no more competition. enter "0" and proceed to next crop) 53 Period of competition code"' 53. I;I--;—I-—c—I—-;-II;I—-;— —-c—I-—-;- GOG” noon- O-OO" Hours per Period of Hours per Period of Hours per Period of Hours per Period of Hours per Period of Hours per . Period of Hours per Period of Hours per period per acre competition code‘u period per acre competition code“' period per acre competition code‘*‘ period per acre competition code‘*‘ period per acre competition code"* period per acre competition code"' period per acre competition code"' period per acre 5‘!- 55- 55- |-;l—°-5—I—c—I---3—Il-;l— I; |—- -;-—- l—é— I— ~;— I I; l— I; I—-;- I-c- I— -;— I I; I- -:.—-I—.—- I— -—.-—I—.—I-— °‘5"l'7§'i-' SECTION VII. OPTION T0 RESTRICT CERTAIN PRODUCTION ALTERNATIVES: (Enter ”0". aiter you have entered the last reStriction) RES.‘ RES.f RESTRICTION RES.‘ RES.H RESTRICTICH RESTRICTION CODE' TYPE AMOUNT CODE' TYPE' AMOUNT 57- 57° ITI—b—I——c——II71—b—l—-—— 58 58-I—I——I—-——II—I-—I————— 59 59'!-|———l————ll—I—-—I-—-——- 6°~ 60-I—I——I---—-——II—I——I———-— 61- 61-I—-I—-—I—-————-II—I----I-—-——--- 62- 52-I—I——-I-—--——-II—I—-——I-——--— 63- 53'l—l——I———-—Il—l—-—l———-— 64- M'I—I—-—I—-——-—II—I-——I———— 65- 55-I—I——-I——-—II—I——I—-—-—— 66- 66-I—I——-—I-———-——II-—I—-—I———-— 67- 57-I—I——I———-—II—I—-—I-——— 68. 68, " See explanation of footnote on Page 4. at. See explanation of footnote on Page 4. f RESTRICTION CODES: l is maximum (1); 2 is equal to (-); 3 is minimum (1). if RESTRICTIOX TYPES: CORN: l - total acres; 2 - owned acres; 3 - rented acres; 4 - owned acres planted between April ZS-Hay 10; 5 - rented acres planted between April 25-May 10; 6.- acres harvested between September 27-Octobcr 10; 7 - owned acres harvested between September :7— Octobor 10; S - rented acres harvested between September 27-0ctober 10. BEASS: ll - total ac: l2 - ownvd acrvw. 13 ' rented qu“S. 14 - acrwu plantvd between Hay lO-Ua7_ITT AITTTVI’YV? CROP FYTFUP"Y¢[§: 21 - acres of alternative crop 1; 22 I acres of alternative chS'ET'fI‘Z‘e: fur up I.“ H I‘rup‘h 69 7O 71 68 LINE FIRST ADJUSTED JD... ANALISJS ANALISJS Storage available for corn and soybeans 69- (1.000 bu.) Corn. S/Bu. (15.5% moisture) 70. a. O harvest b. 9 spring I-—;--I |--5—-—l |—-r—l-°5—-—I l-—--;——l—-5——l soybeans I S/BU¢ 71. l——._—|—- O——- l——O—_I——O-—-—— a. Q harvest a b a b b. 9 spring SECTIOH IX. OPTIOX TO 3:3"37 YIELD AFSCVPTIONS OF AXALYSIS' (If you accept too as: men radiations, Table 3, enter ”100”; otherwise, enter a yield reduction 5 factor where "O" implie 72 73 no reduction while "200” implies twice the assumed reduction). Corn Yield Reductions 72. |__ I __| |____._|__ ..| a. Owned land 7" ‘T a '5 b. Rented land Soybean Yield Reductions 73. I"'-'-I a a. Owned land b. Rented land —;—I I—;—I-;—I SECTION x. option to ADJUST ornra ASSUMPTIONS or ANALYSIST” ASSUMPTIOH ASSUMPTIOH ASSUMPTION ASSUMPTION ASSUMPTIOH VALUE cont VALUE CODE 74. 7Q. |---1;°--|-“17 -' II'---1[°--I'-'17 -I 75. 75- |----'--|- _. -| |----'--I- __ -—I :6. 76- |____.__|_ _ -| |—-—-°--|— _._ —i ‘ 77' |----°--|-‘- -| |----'--l- - -3 78. 78- |________.____|__ __ __.||.__..__......|__ --'--l 79. 79- l——--'——l—-—| |———--——|——-3 so. 80. [_-__.__|_ _ -—| |————-——[— — —-i 81. 81- I----::--|- __ ..| |----°--|- __ .., 82. 82- |—----——|— _ —| I-——-—°--l-- _. —! an. 83. |____.___|_ _ -l |----°--l- _ —l 84. 814- |____.__|_.__| |____.._._I____, 85. 85- |________.___. _ ‘-'-—| |-------l- __ __' 86. 86- l-------|r- __ __| |-------|- __ __3 87. 87- |___.___..____|__ __ __| |_.___.__.__._|_. ._ __I 88. 88- l-—--'--|———I I————---—l-———! 89. 89- |________.____|__.__ __| |__..____._.__|__ -—-——l 90. 90. [_.______.___.|__.__ __4 l----° --I -'- -—I 91.‘ 91- |-—------|-— __ __| l---—-°--|- __ ——I 92. 92- l-------|- _. __| |-—--—----|-— __ _.j 93. 93- |_____.___|_ _ —| l—-——---—l— _._. --| 94. 94- I----°-’l—-—l |..———-——|—-———-l 95. 95 l--———'-—I———I |____.__|___._l irt See User's Manual for explanation. 69 LINE FIRST _NQ... ANALYSIS SECTION-XI. ADDITIONAL INFORMATION: 96 97 98 State And Regional Codes 96o |-'-I I a. State code a '5 b. Region code Plan (enter “1" if desired, 97- I"I I-'| I"I "0" otherwise) a .5 c 3 e a. Summary b. Details on custom hire c. Details on corn planting and harvest scheduling d. Details on soybean planting and harvest scheduling e. Details on land preparation Values Of Scarce Resources And 98. Cost Of SpeCial Restriction a. Land (S/acre) (0 - no; 1 - yes) b. Preparation (0 - no; 1 - S/acre; 2 - S/hour; 3 - both) c. Harvesting (0 - no; 1 - S/acre; 2 ' S/hour; 3 - both) d. Planting (S/hour) (0 - no; 1 - yes) 0. Alternate crops (0 - no; 1 - cost of acreage restriction; 2 - cost of forcing in nonprofitable crops; 3 - both) I. Cost of special restrictions (0 - no; 1 - yes) I';|'5I'g|1511;|jrl ADJUSTED ANALYSIS |'-;-I'g| I';I'5|-;|'3I1;? 7O EXAMPLE OUTPUT * PROFITABILITY * RETURNS ABOVE VAR COST = $ 75196. VAR COST = $ 54769. —‘ O * CORN ACRES AND SALES * 2. ACRES OWNED LAND = 478. AVER BU/ACRE = 96.5 TOTAL BUSHELS = 46114. 4. BU CORN SALES AT HARVEST = 0. BU CORN SALES AT SPRING = 46114. * SOYBEAN ACRES AND SLAES * ACRES OWNED LAND = 122. AVER BU/ACRE = 31.8 TOTAL BUSHELS = 3886. 0'! e * ALTERNATIVE CROP ACRES AND NET INCOMES * TOTAL OWNED RENTED TOTAL CODE UNITS UNITS UNITS PROFIT 1 50. 50. O. S 5250. 21. APR MAY MAY 33. MAY 41. 71 * CORN PLANT AND HARVEST SCHEDULE * OWNED LAND SCHEDULE ACRES HARVESTED ACRES SEP 27 OCT 04 OCT 11 OCT 18 PLANTED OCT 03 OCT 10 OCT 17 NOV 07 25-MAY 10 O. O. O. 270. 11-MAY 18 O. O. 18. O. 19-MAY 26 O. O. 3. O. * SOYBEAN PLANT AND HARVEST SCHEDULE * OWNED LAND SCHEDULE ACRES HARVESTED ACRES SEP 27 OCT 04 OCT 11 OCT 18 PLANTED OCT 03 OCT 10 OCT 17 NOV 07 19-MAY 26 O. 60. 62. 0. LAND PREPARATION SCHEDULE APR OT-APR 24 475. MAY 19-MAY 26 125. NOV 08 NOV 28 108: NOV 8 NOV 2 O. 72 * VALUE OF SCARCE RESOURCES * OWNED LAND ($/AC) 0.0 RENTED LAND ($/AC) 0.0 PREPARED LAND FOR PLANTING ($/AC) HARVESTING CAPACITY ($/AC) SEP 27-OCT 03 118.25 0CT 04-0CT 10 109.28 OCT 11-OCT 17 97.47 0CT 18-Nov 07 99.89 NOV 08-NOV 28 69.12 55. 57. 59. 64. PREPARATION TIME ($/HR) 0CT 18-Nov 07 399.56 PLANTING TIME ($/HR) APR ZS-MAY 10 203.34 MAY TI-MAY 18 99.70 HARVEST TIME ($/HR) SEP 27-OCT 03 473.02 OCT 04-0CT 10 437.10 OCT 11-0CT 17 389.89 0CT 18-Nov 07 399.56 NOV 08-NOV 28 311.03 COST OF ALTERNATE CROPS ACREAGE RESTRICTIONS ($/AC) CODE COST 1 -448.25 BIBLIOGRAPHY BIBLIOGRAPHY Harsh, S., L. Connor and G. Schwab. 1981. Managing the Farm Firm. (In publication process). Prentice-Hall, New York. Harsh, S. 1979. A Progress Report on TELPLAN Activities. Michigan State University, East Lansing. Heady, E.O., H.R. Jensen. 1954. Farm Management Economics. Prentice- Hall, New York. Hinton, R.A. 1973. Users Guide For Corn, Soybeans Farm Planning Guide. Michigan State University, East Lansing. Jones, A.R. 1966. Factors Affecting Tractor Purchases and Expenditures. Michigan State University, East Lansing. Knoblauch, W., S. Nott, G. Schwab, S. Harsh, J. Black. 1972 through 1976. Michigan Farm Enterprise Budgets. Michigan State University, East Lansing. Lambert, L.D. 1964. The Relationship Of Intentions to Buy and Subse- quent Purchase of Farm Machinery. Michigan State University, East Lansing. Michigan Department of Labor. 1976. "Michigan Agricultural Labor in Perspective." The Michigan Farm Worker, V01. 1, no. I. National Farm and Power Equipment Dealers Association. 1971 through 1977. Official Guide Tractors and Farm Equipment. ,Lansing. United States Department of Agriculture. 1977. "U.S. Farms: Still Disappearing." Agriculture Situation, March. White, R.G. l975. Effect of Speed on Power Requirements for Selected Farming Operations. Michigan State University, East Lansing. 73 "Illllllllllllllllllllfllfl