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a Dep. of Agric. Econ., Texas A&M Univ., College Station, TX 78843-2124
b Dep. of Soil and Crop Sci., Texas A&M Univ., College Station, TX 78843-2474
* Corresponding author (lribera{at}tamu.edu).
Received for publication September 25, 2002.
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONNOTESMATERIALS AND METHODSRESULTS AND DISCUSSIONSUMMARY AND CONCLUSIONSLIMITATIONS OF THE STUDYREFERENCES |
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Abbreviations: CDF, cumulative distribution function • CE, certainty equivalents • CT, conventional tillage • MVE, multivariate empirical • NT, no-tillage • RAC, risk aversion coefficient • S, grain sorghum • SB, soybean • SWSB, sorghum–wheat–soybean (rotation) • W, wheat • WSB, wheat–soybean (rotation)
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONNOTESMATERIALS AND METHODSRESULTS AND DISCUSSIONSUMMARY AND CONCLUSIONSLIMITATIONS OF THE STUDYREFERENCES |
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No-tillage farming involves planting seeds in a narrow slot that is opened by the planter with minimal disturbance of the surface crop residue. No additional tillage is done for seedbed preparation. Additional soil and residue disturbance is limited to fertilizer and pesticide placement and possibly cultivation for weed control, if necessary (Hanna, 1995).
No-tillage is beneficial because the soil and its overlaying residue are not disturbed (Shouse, 1990). With reduced tillage and/or NT, less organic matter is oxidized and lost (exposure to air) as comes with frequent moldboard and chisel tillage (Bremer et al., 2001). The long-range benefits of conservation tillage include increases in soil organic matter and favorable types of microbes and earthworms. The latter are soil builders that improve soil structure and increase its capacity to hold soil moisture and nutrients to enable root proliferation (Bremer et al., 2001). Such soils are not as compacted and will hold soil moisture as much as 2 wk after a conventionally tilled field has been lost due to drought. This water-holding capacity can also be important in getting a uniformly emerged stand at planting time (Bremer et al., 2001). Such fields may retain planting moisture longer where others using CT may have lost their planting-moisture–controlling weeds and be forced to delay their planting (Bremer et al., 2001). In addition, NT also helps to sequester CO2 from the air, which in turn helps to slow global warming (Shouse, 1990).
Although agronomic benefits of NT are easy to recognize, economic benefits are not. Most studies agree that using conservational and/or NT systems reduces input costs such as fuel, labor, and machinery repair and depreciation costs (Harman et al., 1996; Smart and Bradford, 1998; Bryant, 1998; Bremer et al., 2001). However, in most cases, there is an increase in herbicide costs and/or a decrease in yield when conservation tillage systems are used. As a consequence, many studies comparing net income between CT and NT systems are contradictory (Harman et al., 1996; Haack and Haskins, 1999; Bryant, 1998; Bremer et al., 2001). 1
All of the above studies compare only average net income between CT and reduced-tillage and/or NT systems, leaving out an important area that affects profit, which is the impact on business risk. In other words, the effects of alternative production systems on mean net income and variation in net income need to be considered when comparing production systems. If decisions are made without considering risk, the decision maker can easily determine which strategy is best, the one with the greatest average net income (Richardson, 2003). When decisions are made considering risk, such as in agriculture, the decision maker cannot use such a simple rule because the economic return for each alternative is a distribution of returns rather than a single value. The method used in this study for decision making under risk is to simulate two alternative strategies, CT and NT, to estimate the distribution for each alternative's net income and then base the decision on the characteristics of the simulated net income distributions using a risk ranking technique (Richardson, 2003).
The objective of this study was to compare the economics of CT and NT systems on three commercial crops produced in South Texas: grain sorghum (S), wheat (W), and soybean (SB). The yield data used to simulate the distribution of net income for NT and CT were collected over an 18-yr field experiment from 1984 to 2001 in the Brazos River floodplain. When considering the economics of both tillage systems, three areas affecting profit are addressed: changes in cost per hectare, changes in yield per hectare, and the impact on business risk.
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MATERIALS AND METHODS |
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TOPABSTRACTINTRODUCTIONNOTESMATERIALS AND METHODSRESULTS AND DISCUSSIONSUMMARY AND CONCLUSIONSLIMITATIONS OF THE STUDYREFERENCES |
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ij is stochastic yield of crop j in rotation i 
j is stochastic price for crop j Prices and yields are the stochastic variables in the model. A multivariate empirical (MVE) distribution of prices and yields was estimated and used to simulate these variables. A MVE distribution has been shown to appropriately correlate random variables based on their historical correlation (Richardson et al., 2000). Additionally, the MVE distribution is a closed form distribution, which eliminates the possibility of values exceeding reasonable values observed in history, i.e., negative yields and prices. Parameters for the MVE distribution were estimated using historical yields and prices.
Yield Data
A long-term CT and NT field experiment was conducted from 1984 to 2001 in the Brazos River floodplain in south-central Texas on Weswood silty clay loam soil. Wheat–soybean (WSB) and sorghum–wheat–soybean (SWSB) rotations and continuous S, W, and SB were managed under CT and NT. Conventional tillage operations in S and SB consisted of disking after harvest, followed by chisel plowing, a second disking, ridging before winter, and cultivating two or three times during early crop growth. Conventional tillage operations in W consisted of disking two to three times following harvest. No soil disturbance occurred under NT, except for banded fertilizer application in S and planting. Plots measured 4 by 12.2 m. Treatments were arranged as a randomized complete block with four replications. Each crop in each sequence was represented in the study each year.
Each crop rotation has 18 yr of yield data. Yields for SB and W were zero in some years because either severe drought and/or bird damage resulted in no harvestable yield. Zero yields were incorporated into the study for nonharvested years because they represent the yield risk that producers could expect. The historical yields were detrended using linear regression to remove the effects of trend. Residuals from trend were used to estimate the parameters for the MVE yield and price distribution.2 The mean values over the 18-yr experiment were used as the average yields in 2003 for the MVE distribution (Table 1).
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Cost of Production Budgets
Cost of production budgets were constructed for each tillage system (Appendix 1). Input prices were taken from the 2003 Texas Crop Enterprise Budgets prepared by the Texas Cooperative Extension Service at Texas A&M University (Texas Coop. Ext., 2003). Input items such as seed and chemicals with their respective amount applied to each cropping system either under CT or NT are identical to the ones used in the experiment. For an approximation of labor and tillage operation costs, the Texas Crop Enterprise Budgets for South Texas were used. A 30% reduction in fuel, lubricants, labor, and machinery repair and depreciation from CT budgets was used to estimate the NT budgets. This assumed reduction is based on Harman et al. (1996), the Texas Crop Enterprise Budgets for 2003 (Texas Coop. Ext., 2003) and Arkansas Crop Enterprise Budgets for 2003 (Univ. of Arkansas Coop. Ext. Serv., 2003).
Net Income and Risk Analysis
Simulated probability distributions of net income for each of the tillage systems in 2003 were used as an indicator of their risk and profitability. Ranking risky alternatives such as tillage systems is more difficult than simply comparing the average net income. In the literature, risky alternatives have been ranked using mean variance analysis and stochastic dominance (Richardson, 2003). These procedures often result in inconclusive rankings for some types of decision makers (McCarl, 1988).
A procedure proposed by Richardson (2003), certainty equivalents (CE), ranks risky decisions for different types of decision makers based on a range of risk aversion levels. The procedure calls for calculating the CE4 that a decision maker would place on a risky alternative relative to a no risk investment at different risk aversion coefficients (RACs).5 An advantage of CE over other methods is that a risk ranking can be done without calculating RAC as a range of RACs is used to represent a wide range or class of risk preference/aversion decision makers. Thus, preferences can be projected for different classes of decision makers based on their risk preference (different RACs). Additionally, the absolute differences in the CE values between risky alternatives represent the risk premium that decision makers place on the preferred alternative over another alternative. The risk premium represents the amount of money that the decision maker would have to be paid to be indifferent between two tillage systems; in this case, between NT and CT. For this study, the CE ranking procedure was applied over a wide range of risk aversion levels to project tillage system preferences for different classes of decision makers, i.e., risk preferring to risk averse.
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RESULTS AND DISCUSSION |
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TOPABSTRACTINTRODUCTIONNOTESMATERIALS AND METHODSRESULTS AND DISCUSSIONSUMMARY AND CONCLUSIONSLIMITATIONS OF THE STUDYREFERENCES |
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Nonstochastic Results
Based on a mean (risk free) net income ranking of the tillage systems, the system with the highest net income per hectare is preferred. In this case, the least negative net income tillage system, SWSB-NT, is preferred, followed by W-NT, WSB-NT, SB-CT, and S-CT (Table 3). (Net incomes are estimated in the absence of direct and counter cyclical payments as these payments depend on historical crop hectarage and yield.) The SWSB rotation gave a –$75.91 net income per hectare for CT and –$62.39 for NT (Table 3). The WSB rotation yielded a –$105.95 net income per hectare for CT and –$79.41 for NT. Continuous S gave a net income per hectare of –$91.28 and –$95.07 for CT and NT, respectively. Continuous W produced a net income per hectare of –$106.49 and –$72.82 for CT and NT, respectively. Finally, continuous SB yielded a net income per hectare of –$80.84 and –$111.35 for CT and NT, respectively (Table 3).
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The CE was used to predict rankings or preferences of CT vs. NT for decision makers possessing different levels of risk preference or aversion (Fig. 2 and Table 5). The CE results from comparing SWSB rotation under NT and CT indicate that NT is preferred by all classes of decision makers because the CE line for NT is above the CE line for CT for RAC levels of –0.15 to +0.15 (Fig. 2A).6 No-tillage has a risk premium over CT of $8.45 and $17.79 per hectare for risk-neutral (RAC = 0) and risk-averse (RAC > 0) decision makers, respectively (Table 5). Risk-preferring decision makers would have a risk premium of $51.99 per hectare for NT over CT. For the WSB rotation, all decision makers, regardless of risk preference, would prefer the NT strategy over the CT, with a degree of conviction of $18.38 and $32.57 per hectare for risk-neutral and risk-averse decision makers, respectively (Table 5 and Fig. 2B).
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Continuous SB presents an interesting situation as the ranking of NT and CT changes twice over the range of RACs (Fig. 2E). Soybean-NT is preferred over SB-CT for moderately risk-loving and moderately risk-averse decision makers, with a risk premium of $27.75 and $27.82 per hectare, respectively. However, for slightly risk-loving to slightly risk-averse individuals, CT strategy is preferred over NT, with a risk premium of $47.05 per hectare.
Finally, Figure 3 compares the CE for net income among each of the five crop rotations for each tillage system, CT and NT. Under CT, risk-neutral decision makers would prefer continuous S over SWSB rotation, the second preferred choice, followed by continuous SB, WSB, and continuous W, with risk premiums per hectare of $4.18, $14.70, $49.99, and $53.50, respectively (Fig. 3A). In other words, a farmer would have to be paid $4.18 per hectare to change from continuous S to SWSB rotation, $14.70 to change from continuous S to continuous SB, $49.99 to change from continuous S to SWB, and $53.50 to change from continuous S to continuous W. Risk-averse decision makers producing under CT would prefer continuous S over SWSB rotation, followed by W, WSB, and SB, with risk premiums of $32.59, $99.36, $121.60, and $172.18, respectively (Fig. 3A). Under NT, risk-neutral decision makers would prefer SWSB rotation over S, W, WSB, and SB, with risk premiums per hectare of $8.13, $23.89, $35.88, and $66.10, respectively (Fig. 3B). Risk-averse decision makers producing under NT would prefer continuous S over SWSB, followed by W, WSB, and SB, with risk premiums of $25.77, $72.35, $99.06, and $153.94 per hectare (Fig. 3B).
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SUMMARY AND CONCLUSIONS |
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TOPABSTRACTINTRODUCTIONNOTESMATERIALS AND METHODSRESULTS AND DISCUSSIONSUMMARY AND CONCLUSIONSLIMITATIONS OF THE STUDYREFERENCES |
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Based on a mean net income ranking of the tillage systems, the system with the best net income per hectare, in this case the least negative net income, is SWSB-NT, followed by W-NT, WSB-NT, SB-CT, and S-CT. Results of simulating the different tillage systems under risk were presented as CDFs of net income per hectare. Since the net income CDFs cross for each tillage system, one cannot say that CT is preferred to NT for all decision makers or vice versa. Therefore, CE was used to rank the tillage systems analyzed. The risk premium for risk-averse decision makers who prefer the NT over the CT strategy ranges between $12.60 and $34.25 per hectare for all five crop rotations.
Risk-neutral decision makers would prefer continuous S over all other rotations under CT. However, under NT, risk-neutral decision makers would prefer SWSB rotation over all other crop rotations. Moreover, risk-averse decision makers would prefer continuous S over all other rotations either under CT or NT.
The results suggest that under risk-neutral rankings, NT would be preferred over CT in three out of the five crop rotations tested. However, assuming a risk-averse decision maker, NT would be preferred over CT for all five crop rotations. Many producers in South Texas continue to use CT over NT, and the results of this study provide useful information to compare the risks and benefits of producing under CT and NT practices so that farmers will be able to make better management decisions. Additionally, the results suggest that as more producers adopt NT, the hectarage of S will likely expand relative to W and SB since risk-averse decision makers would prefer continuous S over all other rotations either under CT or NT. Moreover, even if the producers in South Texas do not adopt NT, the results suggest that continuous S would still be the preferred rotation for either risk-neutral or risk-averse decision makers.
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LIMITATIONS OF THE STUDY |
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TOPABSTRACTINTRODUCTIONNOTESMATERIALS AND METHODSRESULTS AND DISCUSSIONSUMMARY AND CONCLUSIONSLIMITATIONS OF THE STUDYREFERENCES |
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Appendix 1.
Estimated costs of production per hectare for sorghum, wheat, and soybean using conventional and no-tillage systems, Burleson County, Texas.
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Appendix 2.
Validation of the simulated yield and price multivariate distribution.
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S, sorghum; CT, conventional tillage; NT, no-tillage; W, wheat; SB, soybean.
P value is the probability (ranging from 0 to 1) under null hypothesis (H0) of obtaining a test statistic at least as extreme as the observed value; in these cases, the probability to fail to reject the H0, that the means are equal.
Fail to reject the H0 that the means are equal at the 0.05 significance level.
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NOTES |
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TOPABSTRACTINTRODUCTIONNOTESMATERIALS AND METHODSRESULTS AND DISCUSSIONSUMMARY AND CONCLUSIONSLIMITATIONS OF THE STUDYREFERENCES |
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2 A MVE distribution is defined using the actual historical values rather than assuming a parametric distribution. Parameters for the distribution are the means, deviations from trend expressed as a fraction for each variable, and the correlation among variables. An empirical distribution is analogous to simulating random values from a frequency distribution made up of the actual historical data.
3 All parameters used to simulate yields and prices in the MVE are available upon request from the authors.
4 The CE is the amount of money a decision maker would be willing to pay to gain a fair bet (risky alternative or investment) vs. a risk-free alternative with the same average return. The concept was introduced by Freund (1956) and can be used to rank risky investments—the investment with the greater CE is the preferred strategy. To personalize the CE, Freund proposed calculating the CE value using the decision maker's own RAC.
5 Pratt (1964) and Arrow (1965) defined RAC or r(x) as a function of wealth (x) as the negative ratio of the second and first derivatives of a utility function, u(x), or r(x) = –u''(x)/u'(x). Therefore, this coefficient is positive for risk aversion and diminishes for increasing x if there is diminishing risk aversion (Hardaker et al., 1997). The RACs represent the decision maker's degree of risk aversion (RAC > 0), neutrality (RAC = 0), or preference (RAC < 0) and are used to classify decision makers into classes. Risk-averse decision makers are willing to take a fair bet if the increased risk has an increased payoff, risk-neutral persons prefer strategies with the highest mean payoff without regard for the risk (variance of the payoff), and risk-preferring people prefer strategies with greater downside risk if the potential exists for a large payoff. The CE procedure ranks risky strategies over a feasible range of RACs and thus avoids having to estimate RACs for individual decision makers. Meyer (1977) suggested using a range of RACs so that rankings of risky scenarios could be made for policy applications.
6 Ranges of RAC values of –0.15 to 0.15 were used to demonstrate the ranking of alternative cropping systems across a range of decision makers. If the rankings do not change over the range, then the preferences can be considered to be more robust.
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REFERENCES |
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TOPABSTRACTINTRODUCTIONNOTESMATERIALS AND METHODSRESULTS AND DISCUSSIONSUMMARY AND CONCLUSIONSLIMITATIONS OF THE STUDYREFERENCES |
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