Economic Risk and the 92-Yarf

"Old R ton

Implications for a 250-Acre Farm
Circular 300 February 1990 Alabama Agricultural Experiment Station Lowell T. Frobish, Director Auburn University Auburn Univ ersit, Alabama

CONTENTS
Page DESCRIPTION OF THE STUDY .................................... DESCRIPTION OF THE DATA ..................................... RESULTS ......................................... SUMMARY AND CONCLUSIONS ............................... ..............

4 6

7

8
9

LITERATURE CITED ............................................. APPENDIX A. NET RETURNS PER PERIOD FOR ALTERNATIVE ...................... .......... OLD ROTATIONS APPENDIX B. TARGET-MOTAD MATRIX FOR THE OLD

10

ROTATION, 1978-1988 .....................
APPENDIX C. RISK-RETURNS FOR A TARGET INCOME LEVEL

11 13 13 14 ................. ................ ................. 14 15 15

OF $5,000 ........... OF 10,000 .........................
OF $15,000

......................... ................

APPENDIX D. RISK-RETURNS FOR A TARGET INCOME LEVEL

APPENDIX E. RISK-RETURNS FOR A TARGET INCOME LEVEL

...............................................

APPENDIX F. RISK-RETURNS FOR A TARGET INCOME LEVEL

OF $20,000 ........................ OF $25,000 ......................... OF $30,000 ........................

APPENDIX G. RISK-RETURNS FOR A TARGET INCOME LEVEL

APPENDIX H. RISK-RETURNS FOR A TARGET INCOME LEVEL

FIRST PRINTING 3M, FEBRUARY 1990

Information contained herein is available to all persons without regard to race, color, sex, or national origin.

ECONOMIC RISK AND THE 92-YEAR "OLD ROTATION"
Implications for a 250-Acre Farm

JAMES L. NOVAK, CHARLES C. MITCHELL, JR., AND JERRY R. CREWS'

OVER the 92-year history of the Alabama Agricultural Experiment Station's "Old Rotation," data have been collected to analyze the effect of alternative cotton-based rotation schemes on sustainable cotton yields. In particular, these analyses have investigated the effect of winter legumes following cotton on sustainable cotton yields. Winter legumes provide a source of green manure and nitrogen for crops following cotton in the rotation. Evidence from the "Old Rotation" indicates diversification in crop rotations can be used to reduce the economic risk of a farm operation. Conditions in agriculture call for farm decision makers to formulate and implement optimal farm plans in an increasingly risky environment. The implication of these conditions for farm plans that are sustainable over long periods is that crop rotations used should provide the minimum possible risk for an acceptable level of return. Motivated by these conditions, this study used Target-MOTAD to analyze the "Old Rotation" as sustainable crop rotation schemes that might be implemented by farm managers on a 250-acre farm. The primary purpose of this research was to determine the risk minimizing rotation scheme(s) that would optimize expected returns for this size farm operations. The use of legume nitrogen as a substitute for nitrogen fertilizer is expected to provide positive environmental benefit. However, because of the near impossibility of measuring the benefit of this substitution on a small acreage, it was assumed to be insignificant for this analysis. Risk efficiency in farm planning has been widely discussed in the literature. Alternative techniques, such as econometric estimation of stochastic dominance, Chance Constrained Programming,
'Associate Professor of Agricultural Economics and Rural Sociology, Associate Professor of Agronomy and Soils, and Associate Professor of Agricultural Economics and Rural Sociology, respectively.

simulation, Quadratic Programming, MOTAD, and extensions of MOTAD, have been used to suggest risk minimizing farm plans that have involved optimal fertilizer response (5) and contract grazing (9), changing crop mix in response to leverage and safety first (2), policy considerations (12), diversification (7), changing crop cultural practices (13), and analyzing optimal crop rotations (3). The "Old Rotation" was designed to appeal to a wide range of cotton producers, whose preferences for taking risks would most likely differ. It was therefore decided that the method of choice for this study was Target-MOTAD. Target-MOTAD was used to develop a wide range of feasible and economically optimal rotation schemes for alternative target income and risk levels. DESCRIPTION OF THE STUDY The "Old Rotation" experiment consists of 13 plots, 21.5 by 136.1 feet, which have been maintained in cotton-based rotations since 1896. In 1988, the site was listed on the National Register of Historical Places as the oldest continuous cotton study in the United States. The study has been revised several times since its inception, the latest in 1960 (10,4,6). Basic rotations in the study included: Continuous Cotton: (1) With winter legumes; no nitrogen fertilizer (RI) (2) No winter legumes; no nitrogen fertilizer (R2) (3) No winter legumes; 120 pounds of nitrogen per acre (R3) Two Years, Cotton-Corn: (4) With winter legumes; no nitrogen fertilizer (R4) (5) With winter legumes; 120 pounds of nitrogen per acre on each crop (R5) Three Years Cotton-Corn-Rye/Soybeans: (6) Winter legumes after cotton; 60 pounds of nitrogen per acre on rye (R6) The test is a non-replicated study. However, different scheduling of phosphorus and potassium fertilizer applications to crops in the rotation results in rotations with multiple replications. Timing of fertilizer application had an effect in the early days of the experiment, but is no longer significant because of a buildup of soil phosphorus and potassium levels (4). For this study, only crop rotation effects were considered. This study used the past 10 years of available data from the "Old Rotation" to analyze the profitability of six alternative rotation schemes. Structural changes due to changing hybrids, machinery, pest control, etc. are minimized by using data only from this time period. Enterprise budgets were developed for each of the alterna4

tive rotations and net returns over variable costs were indexed to 1988 prices and costs. Target-MOTAD is an extension of MOTAD that is used to determine the set of feasible risk-minimizing crop rotations from the possible set of profitable "Old Rotation" alternatives (11,8). TargetMOTAD was chosen over other possible methods because of its practical and theoretical appeal. As demonstrated by Tauer (11), TargetMOTAD results are Second-degree Stochastic Dominant to solutions provided by MOTAD. The Target-MOTAD model can be formulated as:
n

(1)

Maximize E (Return) =

CjX j=1

subject to
(2)

n

AijX

Bi

j=1
n

(3)

T -

C CtjX - Yt j=1
s

0

(4) (5) (6) and (7) where

t=1

PtYt = K

i = 1, 2, ...... ,m K = M to 0 Xj, Yt, = 0

E(return) is the expected return from the optimal plan; Cj is the expected return from activity j; Xj is the level of activity j; A, is the technical requirement of activity j for resource i; Bi is the level of resource i; T is the target level of return; Ctj is the return of activity j for period t; Yt is the deviation below T for time period t; Pt is the probability of the state of nature occurring at time t; K is a risk constant parameterized from M to 0; m is the number of resource constraint equations; s is the number of time periods or states of nature; and M begins as an arbitrary large number. Risk is measured, in dollars, as the expected sum of the negative deviations of the optimal solution from some target income level. The model is programmed to maximize expected returns, which are subject to achieving a satisfactory level of compliance with target
5

income (T). A set of efficient farm plans is obtained for alternative levels of risk (K), where risk is varied from the arbitrarily large number (M) to 0. The resulting farm plans maximize expected returns for a given risk level, subject to minimized negative deviations from T. Changes are made in the value of K and optimal solutions are obtained until all realistic possible changes in basis occur and the value of expected net return cannot be improved by increasing risk. DESCRIPTION OF THE DATA Objective function activities consist of net returns over variable costs from rotations 1 (R1), 3 (R3), 5 (R5), and 6 (R6). These data are shown in the table. Historic net returns used to derive the values are shown in Appendix A. Rotations 2 and 4 were not included because of negative returns. Technical resource constraints on the system consist of land, labor, and deviations from target income. One acre of land is required to produce 1 acre of crop activity up to a maximum of 250 planted acres of land. Labor requirements are restricted to a maximum of 300 hours of labor per month. Deviation constraints relate returns per period to the target income level. The last row sums negative deviations from target income, under the assumption that deviations for each period are equally as likely to occur (P,). The summed deviations are used with the parameterized value of risk to generate the optimal risk-return frontier for a given value of target income. Rotations 1, 2, and 3 will consist of 250 planted acres of cotton in each year of the farm plan. To satisfy rotation requirements, rotations 4 and 5 will consist of 125 acres of cotton and 125 acres of corn in each year. Rotation 6 will allocate one-third of the 250 planted acres to cotton, one-third to corn, and one-third to rye-soybeans double cropped in each year. It is further assumed that the farm manager participated in the farm program at the minimal set-aside required and that these acreages satisfied the respective program base requirements
AVERAGE ANNUAL NET RETURNS ASSOCIATED WITH THE OLD ROTATION

Rotations, 1978-88 1. 2. 3. 4. 5. 6. Continuous cotton with winter legumes (0-80-60)' ........... Continuous cotton without legumes (0-80-60) .................Continuous cotton without legumes (120-80-60) ............. 2 years cotton (0-80-60) - legumes - corn (0-80-60) ............ 2 years cotton (120-80-60) - legumes - corn (120-0-0) .......... 3 years cotton (0-80-60) - legumes - corn (0-0-0) - small grain (60-0-0) - soybeans....................................... 'Values in parenthesis are annual rates of N-P 2O5 -K20 per acre. 6

Net returns over variable costs/acre 55.09 153.98 21.42 -. 51 9.89 120.31

for participation in the program. Gross income used for the analysis included farm program payments. Two hundred and fifty planted acres was selected as the land base because cotton is the primary crop of the rotation. This acreage can be adequately handled by one 2-row cotton picker. Variable costs for associated machinery operations were incorporated in the net return estimates. With the introduction of corn, rye, and soybeans into the rotations, machinery investment costs can be expected to rise. For this analysis, custom rates were used for corn, rye, and soybean harvesting. It was assumed that the other necessary machinery was owned for all of the rotation schemes. Expected returns were defined as net returns over variable costs. The matrix of annual returns for each rotation was analyzed using yields from the past 10 years of available rotation data. Thirty observations on the distribution of net returns over time (C,) were developed from these data. The structure of the Target-MOTAD model and the data used in the analysis are shown in Appendix B. Rotations that resulted in 10-year average negative net returns were not included in the programming analysis. Therefore, rotations 2 and 4 were dropped. Crop rotations 1, 3, 5, and 6 were the only ones included in the Target-MOTAD analysis. RESULTS Risk-returns for alternative target income levels are presented in Appendix Tables C through H. Results of the Target-MOTAD analysis show that risk is reduced by substituting part of the 3-year cotton, winter legume-corn, rye-soybean rotation (R6) with a continuous cotton-winter legume rotation (R1). This substitution continues to take place until the negative deviations from target income become large enough to drive the system to infeasibility. The trade off of R6 for R1 results in a lowering of net returns as risk is reduced. At each target income level, the highest net return over variable costs results from using the 3-year R6 rotation. As target income is increased from $5,000 to $30,000, commensurately higher risk is incurred in achieving a given level of net return with a given combination of rotations R6 and R1. For an expected return of $30,077.50 and a $5,000 target income level, a $4,050.09 risk must be incurred. A $14,321.18 risk is incurred for the same expected return at a $30,000 target income. A production possibilities curve for the rotations and a $25,000 target income is shown in the figure. This curve shows that to achieve the $25,000 target income at minimum risk, a producer should plant approximately 172 acres (69 percent) in rotation scheme R6 and 78
7

Cotton-legumes-corn-rye-soybeans, acres 260 250 240 230 220 210 200 190 180 170 160 0 10 20 I I 50 60 70 30 40 Continuous cotton-legumes, acres I 80 I 90

Risk, $ 11,890 11,772 11,653 11,535 11,416 11,298 11,180 11,061 10,943 10,824 100 10,706

Economic risk and the 92-year "Old Rotation" at Auburn University, Alabama, from 1978 to

1988.

acres (31 percent) in rotation R1. A producer's preference for greater risk taking will result in a higher proportion of R6 being used in relation to the Ri rotation. SUMMARY AND CONCLUSIONS This study compared the risk and returns from the past 10 years of Auburn University's 92-year "Old Rotation" for a 250-acre farm. Comparisons were made of sustainable, continuous cotton rotations to cotton and corn rotations, with and without nitrogen and winter legumes, and to a 3-year rotation of cotton, legumes, corn, rye, and soybeans. Target-MOTAD specifies a set of optimal results for alternative target income and risk levels. The method does not assume a level of risk or income preference. Rather, it presents optimal results for alternative income and risk levels. The best rotation scheme for a producer will depend on attitudes towards risk versus the expected returns at the time production practices are put into action. The results indicate that the optimal farm plan will include a 3year rotation of cotton, winter legumes, corn, small grains, and soybeans (R6). The highest expected return at each target income level will result from planting the entire acreage to the R6 rotation. As
8

risks are reduced, more and more of the continuous cotton with winter legume rotation (Ri) will enter the farm plan. The trade off from reducing risk is a lowering of expected returns. The best strategy to minimize risk at each target income level will include the Ri rotation in the farm plan. The risk minimizing proportion of R1 to include in the farm plan ranges from 37.5 percent at a target income of $5,000 to 32 percent at a $25,000 target income (Appendices C-H). Diversification by use of a mix of these two different sustainable rotations is shown to result in the least risky alternative farm plan for each alternative target income level.

LITERATURE CITED (1)
(2) ALABAMA AGRICULTURAL STATISTICS. 1988. Alabama Agricultural Statistics

Service, Montgomery, Ala. Bull. 30.
ATWOOD, JOSEPH A., MYLES J. WATTS, AND GLENN A. HELMERS. 1988.

Chance- Constrained Financing as a Response to Financial Risk. Amer. Jour. of Agr. Econ. 70:79-89.

(3)

CRISOSTOMO, MARIO E,

ROBERT O.

BURTON, JR., ORLAN H.

BULLER, AND

KENNETH W. KELLEY. 1988. A Target MOTAD Analysis of Double-Cropping

and Alternative Cropping Patterns in Southeast Kansas. Kan. State Univ., Dept. of Ag. Econ. Staff Paper No.88-9. (4) DAVIS, F.L. 1949. The Old Rotation at Auburn, Alabama. Better Plants With Plant Food. Amer. Potash Inst. Inc., Washington, D.C., Reprint DD-8-49. (5) DEJANVRY, ALAIN. 1972. Optimal Levels of Fertilization Under Risk: The Potential for Corn and Wheat Fertilization Under Alternative Price Policies in Argentina. Amer. Jour. of Ag. Econ. 54:1-10. (6) EVANS, E.M. AND D.G. STURKIE. 1974. Winter Legumes Can Help Supply Nitrogen Need. Highlights of Agr. Res., Ala. Agr. Exp. Sta. Auburn Univ. Ala. 21:2.
(7) FALATOONZADEH, HAMID, J. RICHARD CONNER, AND RULON D. POPE. 1985.

Risk Management Strategies To Reduce Net Income Variability For Farmers. Sou. Jour. of Ag. Econ. 17:117-130.

(8)
(9)

HAZELL, P. B. R. 1971. A Linear Alternative to Quadratic and Semivariance

Programming for Farm Planning. Amer. Jour. of Ag. Econ. 53:53-62.
JOHNSON, FRANK, THOMAS H. SPREEN, AND TIMOTHY HEWITT. 1987. A Sto-

chastic Dominance Analysis of Contract Grazing Feeder Cattle. Sou. Jour. of Agr. Econ. 19:11-19. (10)
MITCHELL, C. C., JR. 1988. New Information From Old Rotation. Highlights

(11) (12)
(13)

of Agr. Res., Ala. Agr. Exp. Sta., Auburn Univ., Ala. 35:4. TAUER, LOREN W 1983. Target MOTAD. Amer. Jour. of Ag. Econ. 65:606610.
TAYLOR, C. ROBERT. 1988. Two Practical Procedures for Estimating Multi-

variate Nonnormal Probability Density Functions. Ala. Agr. Exp. Sta., Auburn Univ. Ala. ES88-1.
TEAGUE, PAUL

W. AND

JOHN G. LEE. 1988.

Risk Efficient Perennial Crop Se-

lection: A MOTAD Approach to Citrus Production. Sou. Jour. of Agr. Econ. 20:145-152.

APPENDIX A. NET RETURNS PER PERIOD FOR ALTERNATIVE OLD ROTATION

NET RETURNS OVER VARIABLE COSTS Continuous cotton rotations With winter legumes No winter legumes

Period ............................. ............................ .............................. .............................. ............................. ............. ................. .............................. .............................. ............................. .............................. Average ......................... 1 2 3 4 5 6 7 8 9 10

(0-80-60)' (R1)2 96.98 -11.49 65.40 165.40 203.43 6.68 230.87 -136.20 -89.21 18.83 55.09

(0-80-60) (R2) -188.18 -175.81 -124.03 -114.77 -107.16 -175.29 -188.01 -202.48 -179.25 -84.80 -153.98

(120-80-60) (R3) -. 98 8.47 85.22 95.37 152.51 8.19 147.83 -327.62 -30.49 75.74 21.42

2-year cotton-legume-corn rotations

Period

No nitrogen fertilizer (0-80-60) (0-80-60) Corn (R4) Cotton (R4) -86.48 -26.91 -87.97 -11.63 59.67 -43.46 -77.76 -117.93 -15.08 -20.27 -42.78

With nitrogen fertilizer (120-0-0) (120-80-60) Corn (R5) Cotton (R5) 52.67 -36.25 5.11 206.17 172.08 65.18 270.42 -112.89 97.17 29.87 74.95 -66.32 -51.98 -85.64 -32.18 50.62 -74.90 -110.58 -123.58 -38.58 -18.58 -55.17

23.17 1 .......................... -59.15 2 .......................... 53.18 3 ......................... 143.48 4 .......................... 176.79 5 .......................... 22.60 6 .......................... 155.11 7 .......................... -70.23 8 .......................... -1.94 9 ........................... -25.30 10 .......................... . 41.77 Average ..................... Period 1 ..................... 2 ..................... 3 ..................... 4 ..................... 5 ..................... 6 ..................... 7 ..................... 8 ..................... 9 ..................... 10 ..................... Average ................
2

3-year cotton-legume-corn-rye-soybean rotation (0-80-60) (0-0-0) (60-0-0) Rye-soy (R6) Corn (R6) Cotton (R6) 98.88 89.05 279.11 284.77 273.70 178.49 256.24 -22.17 86.53 50.41 157.50 per acre. -28.27 -5.05 -56.07 -54.49 74.31 -32.53 -8.26 -118.84 34.76 -14.33 -20.88 177.78 217.35 183.33 359.86 155.68 320.69 0 211.99 36.58 355.49 224.31

IPounds of fertilizer applied
Rotation identifier.

10

APPENDIX B. TARGET-MOTAD MATRIX FOR THE OLD ROTATION, 1978-1988 R6 OBJ FCN Land .... L Lab 3-1 ... L Lab4-1 .. L Lab 5-1. L Lab 6-1 ... L Lab7-1 .. L Lab 8-1 ... L Lab 10-1.. L Lab 11-1.. L Lab 12-1 .. L Lab3-2 . .. L Lab4-2. . L Lab5-2. . . L Lab 6-2... L L Lab 7-2.. Lab8-2 .. L Lab 10-2.. L Lab 11-2.. L Lab 12-2.. L Lab3-3. .. L Lab4-3 . .. L Lab5-3... L Lab 6-3 ... L Lab 7-3.. L Lab 8-3 ... L Lab 10-3 . .L Lab 11-3 .. L Lab 12-3 . L Targ 11 . . . G Targ21 . . G Targ 31 . . G Targ41 . . C Targ51 . . C Targ 61 . . G Targ 71 . . C Targ 81 . . G Targ 91 . . G Targ 101 . . C Targ 12 . . .G 120.31 1 .25 .13 .33 .26 .2 .06 .5 .94 .12 .62 .22 R5 9.89 1 .25 .13 .33 .26 .2 .06 .5 .94 R1 55.09 1 .25 .13 .33 .26 .2 .06 .5 .94 R3 D1 D2 D3 D4 D5 D6 D7 D8 D9 D10 D11 D12 D13 D14 D15 D16 D17 D18 D19 D20 D21 D22 D23 D24 D25 D26 D27 D28 D29 D30 RHS 250 300 300 300 300 300 300 300 300 300 300 300 300 300 300 300 300 300 300 300 300 300 300 300 300 300 300 25,000 25,000 25,000 25,000 25,000 25,000 25,000 25,000 25,000 25,000 25,000

.75

.71 .31 .2 .25

98.88 89.05 279.11 284.77 273.7 178.49 256.24 -22.17 86.53 50.41 -28.27

21.42 1 .25 .13 .33 .26 .2 .06 .5 .26 .42 .12 .25 .25 .62 .13 .13 .33 .22 .33 .26 .26 .2 .2 .06 .06 .25 .5 .5300 .43 .94 .26 .42 .25 .25 .25 .13 .13 .13 .33 .33 .33 .26 .26 .26 .2 .2 .2 .06 .06 .06 .5 .5 .5 .94 .94 .26 .42 -. 98 1 52.67 96.98 8.47 -36.25 -11.49 85.22 5.11 65.4 95.37 206.17 165.57 172.08 203.43 152.51 8.19 65.18 6.68 270.42 230.87 147.83 -327.62 -112.89 -136.2 -30.49 97.17 -89.21 29.87 18.83 75.74 -. 98 -66.32 96.98

1 1 1 1 1 1 1 1 1 1

Continued

APPENDIX B (CONTINUED). TARGlET-MOTAkD MATRIX FOR THE OL D ROTATION, R6 Targ 22 . .. Targ . . . 32 Targ 42 . .. Targ 52 . .. Targ 62 . . . Targ 72 .. Targ 82 . .. Targ 92 .. . Targ 102.. . STargil3 . .. Targ 23 Trg33.. . Targ 43 . .. Targ 53 . ..
G

1978-1988
RHS

65

Ri

R3

Di

D2 D3 D4 D5 D6 D7 D8 D9 D10 D11 D12 D13 D14 D15 D16 D17 D18 D19 D20 D21 D22 D23 D24 D25 D26 D27 D28 D29 D30

-5.05 -56.07 -5449 C 74.31

C C C C C C C C Targ 63 . . . C Targ 73 ... G Targ 83 . .. C Targ 93 .. . C Targ 103..C TMOTAD E

IUIAVYV-Z IYVIVV VYI VIIV VV Y VY

-51.89 -11.49 8.47 1 25000 -85.64 65.4 85.22 1 25,000 -32.18 165.57 95.37 1 25,000 5062 203.43 152.51 1 25,000 -74.9 6.68 8 19 1 25,000 -8.26 -110.58 230.17 147.83 1 25000 118.84 -123.58 -136.2 -327.62 1 25,000 34.76 -38.58-89.21 -30.49 1 25,000 1433 -1858 18.83 75.74 1 25,000 177.78 52.67 96.98 1 25,000 21735 -36.25 -11.49 8.47 1 25,000 183.33 5.11 65.4 85.22 1 25,000 359.86 206.17 16557 9537 1 25,000 155.68 172.08 203.43 152.51 1 320.69 65.18 6.68 819 1 25,000 0 270.42 230.87 147.83 1 25,000 211.99 -112.89 -136.2 -327.62 1 25,000 36.58 97.17 -89.21 -3049 1 25,000 355.49 29.87 18.83 75.74 1 25,000 .03 .03 .03 .03 .03 .03 .03 .03 .03 .03 .03 .03 .03 .03 .03 .03 .03 .03 .03 .03 .03 .03 .03 .03 .03 .03 .03 .03 .03 .03 11,772

-32.53

-.98

25,000

APPENDIX C. RISK-RETURNS FOR A TARGET INCOME LEVEL OF $5,000 ($20IACRE~ Acres planted to Percent of acreage in 3-year rotation Continuous cotton

Risk Dol. 4,050.09 4,050.00 3,483.50 3,332.00 3,329.00 3,303.00 3,068.00

Expected return Dol.
30,077.50

3-year rotation

Continuous cotton

30,077.31 28,663.44
28,148.33 28,130.23 27,924.80

2,900.00 2,800.00 2,794.50 2,700.00 2,600.00 2,500.00 2,400.00 2,285.00 2,240.00
2,147.00 2,121.41

24,553.55
21, 936.47 20, 378.60 20, 292.97 18, 797.59 17, 215.16 15, 632.74 14, 050.32 12, 230.12 11, 346.94

8,416.09 5,887.07

Acres 250.00 250.00 228.32 220.42 220.14 216.99 165.34 146.44 135.18 134.57 125.96 116.85 107.75 98.64 88.16 83.04 59.07 38.39

Acres .00 .00 21.68 29.58 29.86 33.01 84.61 78.39 74.69 74.48 66.13 57.30 48.46 39.63 29.47 24.63 23.77 23.03

Pct. 100.000 99.999 91.327 88.168 88.057 86.797 66.148 65.133 64.412 64.372 65.574 67. 100 68.976 71.339 74.950 77. 125 71.305 62.501

Pct. .000 .001 8.673 11.832 11.943 13.203 33.852 34.867 35.588 35.628 34.426 32.900 31.024 28.661 25.050 22.875 28.695 37.499

APPENDIX D. RISK-RETURNS FOR ATARGET INCOME LEVEL OF $10,000 ($40/ACRE) Acres planted to 3-year Continuous rotation cotton Percent of acreage in 3-year Continuous rotation cotton

Rik

Rik

Expected return

Dol.

Dol.
30, 077.50

Acres
250.00
249.99

Acres
.00
.00

5,615.04 5,615.00 4,807.00

Pct.
100.000
99.999

Pct.
.000
.001

30,07.41

4,723.00 4,652.00 4,600.00 4,570.30 4,535.00 4,)480.00 4,450.00

27,250.59 26,777.25
25,758.66 24,935.81 24, 465.83 23,778.47 22, 693.88

206.66

199.40 183.80 179.06
176.36

43.34 50.60

66.18
61.59 58.96 55.13 49.25 48.98 48.80 48.52 48.06 47.79 47.51 47.14 46.70 46.41 46.06

172.40
166.07 158.37 153.24 145.54 132.71 125.01 117.33 106.82 94.70 86.62 76.77

4,430.00 4,400.00' 4,350.00 4,320.00

21,752.41
21,124.76 20,183.28 18,614.16 17,672.69 16, 733.35 15, 448.58 13, 966.15 12, 977.86 11, 774.13

4,293.00 4,280.00
4,265.00 4,255.00 4,242.82

82.662 79.759 73.525 74.408 74.943 75.771 77. 127 76.378 75.848 74.997 73.413 72.345 71.177 69.384 66.972 65.111 62.501

17.338 20.241 26.475 25.592 25.057 24.229 22.873 23.622

24.152
25.003 26.587 27.655 28.823 30.616 33.028 34.889 37.499

13

APPENDIX E. RISK-RETURNS FOR A TARGET INCOME LEVEL OF

$15,000

($60/ACRE)

Rsk Expected return Dol. 7,486.96 7,485.00 7,450.00 7,400.00 7,350.00 7,300.00 7,200.00 7,100.00 7,000.00 6,900.00 6,818.00 6,700.00 Dol. 30, 077.50 30,070.31 29,941.34 29,757.10 29,572.86 29,388.61 29,020.13 28,651.64 28,283.15 27,914.67 27,610.99 26,991.71
26,466.89 25, 821.56

6,479.00 6,444.00 6,420.00 6,390.00 6,375.00 6,364.22

6,600.00

Acres planted to 3-year Continuous rotation cotton Acres Acres 250.000 .000 249.890 .110 247.912 2.088 245.087 4.913 242.263 7.738 239.438 10.562 233.788 16.212 228.138 21.862 222.488 27.512 216.838 33.162 212.182 37.818 202.687 47.314
194.640 184.745
178.278

Percent of acreage in 3-year Continuous rotation cotton Pct. Pct.
100.000 99.956
99.165

.000 .044
.835

98.035
96.905 95.775
93.515

1.965
3.095 4.225
6.485

91.255
88.995 86.735 84.873 81.075 77.856 73.898
71.417

8.745
11.005 13.265 15.127 18.925 22.144 26. 102
28.583

25,39.26

55.360 65.255
71.350

23,172.86 20, 208.01 18, 725.58 17, 660.21

160.234 135.988 123.865 115. 152

70.704 69.837 69.403 69.092

69.384 66.070 64.090 62.500

30.616 33.930 35.910 37.500

APPENDIX F. RISK-RETURNS FOR A TARGET INCOME LEVEL OF

$20,000 ($80/ACRE)

Risk Dol.

Expected return Dol.
30,077.50 30,063.52 29, 761.20 29,454.74

9,479.64 9,475.00 9,375.00 9,275.00
9, 250.00 9,100.00

9,000.00

29, 353.38 28, 552.17
27, 859.15

8, 900.00 8, 00.00

8,750.00 8,)700.00 8, 600.00 8,550.00 8,500.00 8,491.00 8,490.00 8,486.00
8,485.65

27,166.13 26, 473.11
26,126.60 25, 780.09

25, 087.07
24, 740.56 24, 300.64 24,064.43 23, 979.16 23, 583.85

23,549.26 I~LUILI

Acres planted to 3-year Continuous rotation cotton Acres Acres 250.000 .000 249.786 .214 245. 150 4.850 240.451 9.549 238.897 11.103 226.613 23.388 215.987 34.013 205.361 44.639 194.735 55.265 189.422 60.578 184. 109 65.891 173.483 76.517 168.170 81.830 161.425 88.575 157.803 92. 197 157.071 92.248 153.838 92. 133 153.555 92. 123

Percent of acreage in 3-year Continuous rotation cotton Pet. Pet. 100.000 .000 99.914 .086 98.060 1.940 96. 181 3.819 95.559 4.441 90.645 9.355 86.395 13.605 82. 144 17.856 77.894 22.106 75.769 24.231 73.644 26.356 69.393 30.607 67.268 32.732 64.570 35.430 63. 121 36.879 63.000 37.000 62.543 37.457 62.503 37.497

14

APPENDIX G. RISK-RETURNS FOR A TARGET INCOME LEVEL OF $25,000 ($100/ACRE)

Risk Dol. 11,771.18 11,770.00 11,600.00 11,500.00 11,400.00 11,300.00 11,200.00 11,110.00 11,050.00 11,000.00 10,950.00 10,900.00 10,850.00 10,840.00 10,830.00 10,826.37

Expected return Dol. 30,077.50 30,071.71 29,233.51 28.740.45 28,247.38 27,754.33 27,261.27 26,810.92 26,392.58 26,043.96 25,695.34 25,346.71 24,998.09 24,928.37 24,858.65 24,833.34

3-year rotation Acres 250.000 249.911 237.059 229.499 221.939 214.379 206.820 199.915 193.500 188.155 182.810 177.464 172.119 171.050 169.981 169.593

Acres planted to Continuous cotton Acres .000 .089 12.941 20.501 28.061 35.621 43.181 50.086 56.500 61.845 67.190 72.536 77.881 78.950 80.019 80.407

Percent of acreage in Continuous 3-year rotation cotton Pct. Pct. 100.000 .000 99.964 .036 94.824 5.176 91.800 8.200 88.776 11.224 14.248 85.752 17.272 82.728 79.966 20.034 77.400 22.600 75.262 24.738 26.876 73.124 70.986 29.014 68.848 31.152 68.420 31.580 67.992 32.008 67.837 32.163

APPENDIX H. RISK-RETURNS FOR A TARGET INCOME LEVEL OF $30,000 ($120/ACRE)

Risk Expected return Dol. 14,321.18 14,320.00 14,250.00 14,100.00 14,000.00 13,900.00 13,800.00 13,700.00 13,600.00 13,500.00 13,445.00 13,425.00 13,400.00 13,394.50 Dol. 30,077.50 30,071.71 29,726.57 28,986.98 28,493.92 28,000.86 27,507.79 27,014.74 26,521.68 26,028.62 25,710.98 25,242.10 24,655.99 24,526.72

Acres planted to Continuous 3-year rotation cotton Acres 250.000 249.911 244.619 233.279 225.719 218.159 210.600 203.040 195.480 187.920 183.050 175.860 166.874 164.896 Acres .000 .089 5.381 16.721 24.281 31.841 39.401 46.961 54.520 62.080 66.951 74.140 83.127 85.104

Percent of acreage in Continuous 3-year rotation cotton Pct. 100.000 99.964 97.848 93.312 90.288 87.264 84.240 81.216 78.192 75.168 73.220 70.344 66.749 65.959 Pct. .000 .036 2.152 6.688 9.712 12.736 15.760 18.784 21.808 24.832 26.780 29.656 33.251 34.041

15

Alabama's Agricultural Experiment Station System AUBURN UNIVERSITY

inral r~ejraC h ut in1 ev erv\ tttdJ( r oil airea,0
Auihtrn

I Tnverty

tt3x

-

serves the needs offield crop, livestock, forestry, and h()r ticulturatl prodlucers
in-

eac h reg.ionl

ill

,.

-

-

Alahixm. Ev ery citi-sa Zen of the State has at stake in this researc h program, since any advantage from~ nexx atnd nmore econon1(11 w\iys of producing and handling fir-m prodlucts dlirectdy henetits the consunming puhlic.

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®

j
-0

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7
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i 19

2
11

Research Unit Identification

® Main Agricultural Experiment Station, Auburn. SE. V. Smith Research Center, Shorter.
1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. Tennessee Valley Substation, Belle Mina. Sand Mountain Substation, Crossville. North Alabama Horticulture Substation, Cullman. Upper Coastal Plain Substation, Winfield. Forestry Unit. Fayette County. Chilton Area Horticulture Substation, Clanton. Forestry Unit, Coosa County. Piedmont Substation, Camp Hill. Plant Breeding Unit, Tallassee. Forestry Unit, Autauga County. Prattville Experiment Field, Prattville. Black Belt Substation, Marion Junction. The Turn ipseed-Ikenberry Place, Union Springs. Lower Coastal Plain Substation, Camden. Forestry Unit, Barbour County. Monroeville Experiment Field, Monroeville. Wiregrass Substation, Headland. Brewton Experiment Field, Brewton. Solon Dixon.Forestry Education Center, Covington and Escambia counties. Ornamental Horticulture Substation, Spring Hill. Gult Coast Substation, Fairhope.

13.
14. 15. 16. 17. 18. 19. 20. 21.