Estimating Soil Erosion and Fuel Use Changes and Their Monetary Values with AGSIM: A Case Study for Triazine Herbicides

This technical report describes a method to use the AGSIM policy model to estimate changes in soil erosion and diesel fuel consumption for tillage that result from agricultural policy changes. This report uses triazine herbicides as a case study to explain the development of the method and illustrate its use. The method assumes farmers shift their adoption of different tillage systems as a result of the agricultural policy being examined. Based on these shifts in tillage adoption rates, changes in farmer costs, erosion rates, and consumption of diesel fuel for tillage occur. The changes in farm costs are used as input by AGSIM, along with other changes in costs and/or yields due to the agricultural policy being examined. Based on these inputs, AGSIM then projects crop acreage and prices, as well as changes in consumer surplus, that would occur as a result of the policy. Based on projected crop acreage changes, the method estimates changes in soil erosion and consumption of diesel fuel for tillage, as well as the monetary value of soil erosion changes and the carbon dioxide emission changes resulting from the fuel use changes. As an illustration of the method, this report presents an updated assessment of the benefits of triazine herbicides to the U.S. economy. For the base year of 2009, this assessment finds that triazine herbicides provide total benefits to the U.S. economy of $3.8 to$4.8 billion per year. Because the triazine herbicides increase the total supply of corn and sorghum, which decreases grain prices, most of these benefits accrue to consumers, especially the livestock and ethanol industries that are major users of corn. These consumer benefits are the sum of the benefits flowing to everyone along the supply chain--livestock farmers, processors and handlers, distributors, retailers, and final consumers. Triazine herbicides also reduce the use of tillage for crop production and the conversion of land to crop production, which reduces soil erosion from U.S. cropland by 56 to 85 million tons per year. Based on these reductions, triazine herbicides provide $210 to$350 million per year in benefits from reduced soil erosion as part of this total benefit to the U.S. economy. In addition, triazine herbicides reduce consumption of diesel fuel for tillage by 18 to 28 million gallons per year, implying a decrease in carbon dioxide emissions of 180,000 to 280,000 metric tons per year. This total benefit of $3.8 to$4.8 billion is a lower bound on the full value of triazine herbicides to the U.S. economy, because several benefits are not accounted for in this assessment. Among the most substantial benefits missing from this assessment are estimates of the resistance management benefits of triazine herbicides for other herbicides and crops, environmental benefits other than reduced soil erosion, and the benefits to crops not modeled by AGSIM (e.g., sweet corn, sugarcane, citrus, grapes, and other fruits and nuts).

YIELD BENEFIT OF CORN EVENT MON 863

Data from field experiments are used to estimate the yield benefit of corn hybrids containing event MON 863 relative to nontransgenic corn hybrids without corn rootworm control and with a soil insecticide for corn rootworm control. Over typical ranges for corn rootworm population pressure, event MON 863 provides a yield benefit of 9-28% relative to no control and of 1.5-4.5% relative to control with a soil insecticide. For a reasonable range of prices and yields, the value of the event MON 863 yield benefit is $25-$75/ac relative to no control and $4-$12/ac relative to control with a soil insecticide, depending on corn rootworm pressure. Because of the low correlation between yield loss and the root rating difference, a common empirical finding when estimating yield loss with root ratings, the 95% confidence intervals around these averages are quite wide. Though on average, event MON 863 has substantial value, the wide confidence intervals imply that farmers will see a wide variety of actual performance levels in their fields. This uncertainty in the realized yield benefit is not due to any property of event MON 863, but rather due to the inherent randomness in the numerous environmental and agronomic factors determining a corn plant's yield and yield response to corn rootworm larval feeding damage.Crop Production/Industries,

ADDITIVE VERSUS PROPORTIONAL PEST DAMAGE FUNCTIONS: WHY ECOLOGY MATTERS

Economic analyses of pests typically assume damage is either additively separable from pest free yield or proportional to it. This paper describes the ecological assumptions required for additive and proportional damage functions to demonstrate that both specifications are reasonable. Ecological research supports a proportional damage function for competitive pests such as weeds, while for insect pests the appropriate damage function depends on the level of pest free yield. Theoretical analysis identifies differences between additive and proportional damage functions in terms of the impact of pest control on output variance and the concavity of output in the pest control input.Pest Economics, Damage Function, Damage Control, Risk Reducing Input, Increasing Returns, Functional Response, Crop Production/Industries, Environmental Economics and Policy,

RURAL CREDIT RATIONING AND NATIONAL DEVELOPMENT BANKS IN DEVELOPING COUNTRIES

A common problem in agricultural credit markets in developing countries is the coexistence of a competitive market equilibrium interest rate and credit rationing. The literature typically explains the existence of credit rationing in competitive credit markets using adverse selection and moral hazard. Unfortunately these analyses are not consistent with the empirical reality that developing countries deal with in terms of subsidized credit, especially in the agricultural sector. This paper presents an alternative explanation for credit rationing in the agricultural sector in developing countries based on the fact that the requested loans are usually for small amounts, with many farmers making applications. As a result, the costs of operation increase with the number of loans given, so that inefficiencies in credit allocation occur when national development banks are present. It is shown that credit rationing can be reduced if shutting-down the national development bank is a feasible policy. Two other cases show that a national development bank is welfare-improving if an incentive compatible contract is used.Financial Economics,

UNBALANCED NESTED COMPONENT ERROR MODEL FOR ESTIMATING PEST DAMAGE FUNCTIONS

A recently developed nested error component model for unbalanced panel data is used to estimate insect damage functions. The model estimates the separate random effects for location and year on the variability of yield loss and has smaller standard errors for the regression coefficient than the comparable OLS model.Crop Production/Industries,

An Unbalanced Nested Error Component Model for Estimating Pest Damage Functions and the Value of Rootworm Bt Corn

We apply Antweiler’s (2001) double-nested unbalanced panel data model to estimate a western corn rootworm damage function using data from field trials in Illinois and Nebraska. Results imply that expected yield losses for a one unit difference in the node injury scale are 16.4%. Estimated random year and state effects are statistically significant, as is the estimated random experimental effect. The experimental effect is relatively large indicating the tremendous variability in yield losses at the small scale for plots with the same node injury scale measure of root damage. Using the estimated pest damage function to assess the value of Bt corn for farmers in Nebraska and Illinois, we find that, with a mean yield of 200 bu/ac, a yield CV of 25%, a corn price of $3.50/bu, and a Bt corn technology fee of$16/ac, the value of Bt corn for farmers is $173.35/ac and$156.14/ac under very high and high pest pressure respectively.Crop Production/Industries,

Solving the Problem of Sustainable Use of Bt Crops

Transgenic plants producing insecticidal protein derived from Bacillus thuringiensis (Bt) have been widely adopted since their commercial introduction in 1996. The widespread adoption of such plants has reduced use of conventional insecticides while attaining yield gains, thus providing economic, environmental and human health benefits. However, the benefits from Bt crops will be reduced or even eliminated if pests develop resistance to these toxins so that Bt crops are less or no longer effective. Although field resistance to Bt crops has not yet been found in the continental U.S., resistance to Bt sprays has been found in diamondback moth and greenhouse populations of cabbage looper. Hence, considerable attention has been devoted to developing management programs to prevent, delay or even reverse the spread of resistance. The existing literature on the economic management of pest resistance has generally assumed that pest susceptibility (the converse of pest resistance) is nonrenewable, which means resistance can only increase once it has happened. With the assumption of irreversible resistance, the optimal policy is not to exhaust susceptibility before the new technology, if any, becomes available. Following this logic, the U.S. Environmental Protection Agency (EPA) currently requires Bt crop growers to also plant non-Bt (conventional) crops on a minimum percentage of their total Bt crop acreage as a refuge for susceptible (Bt toxin sensitive) pests. Refuge allows susceptible pests to survive and mate with resistant adults surviving on Bt crops and so delays the development of resistance in the pest population. The cost of this resistance control method includes yield loss of conventional crops relative to Bt crops and sometimes conventional pesticide use. Instead of assuming susceptibility is nonrenewable, some have proposed an alternative source of susceptibility — mass-rearing and releasing harmless susceptible (toxin-sensitive) pests into the environment (Alphey et al. 2007). With this resistance control method in hand, pest susceptibility is now renewable and resistance could be reversed. Based on this method, it is plausible to predict that the optimal resistance management policy should take a cycling pattern, i.e., not planting refuge and allowing resistance to increase until a critical threshold is reached. Once resistance exceeds this threshold, it becomes economical to release susceptible pests to reverse the development of resistance. After resistance is reduced to a desired level, again no refuge needs to be planted and no alternative resistance management actions need to be used until the resistance reaches the threshold again. The cycling feature of the optimal path is due to the reversibility of resistance under this scenario. Also, there is no need to continuously use a resistance control method (as in the case of current refuge policy), since the desired level of resistance can be achieved, at a cost, when needed. However, the crucial consideration is that it is less costly to manage resistance when it is low rather than high. The task of dynamic programming is to find the optimal path where the marginal benefit of resistance control can just cover the marginal cost of resistance. We notice the cycling pattern of this resistance management model and introduce a real options approach originally used in financial analysis. We propose to view pest susceptibility as an investment and the possibility to release susceptible pests as a real option, which can be exercised to improve the expected value of this investment. We formulate the social planner’s decision of releasing susceptible pests as an optimal sequential stopping problem and solve it using stochastic dynamic programming. We first consider releasing pests with a constant ratio for released to natural pests, but then extend the model to allow for selection of a time-varying ratio. The cost of this resistance control technology includes only the cost of monitoring resistance and rearing and releasing susceptible pests. The cycling pattern of this resistance management method is attractive since cost tends to be lower than continuous refuge-based resistance management, as costs are targeted to areas and times when it is needed, rather than being annually implemented across all acres planted to Bt crops. We compare three resistance management programs: refuge only, releasing susceptible pests only, and using both refuge and released pests. The dynamic optimizations are solved numerically using parameters for Bt corn and western corn rootworm. Consistent with previous economic analyses, our dynamic refuge study finds that more refuge should be planted early in commercialization to prevent the rapid development of resistance and that refuge should be planted continuously so that the evolution of resistance is always under control. Once refuge is no longer planted, resistance develops rapidly. For the dynamic releasing of susceptible pests, there is a steady state (economic threshold) of the level of resistance. Whenever the threshold is crossed, resistance control is triggered. The optimal path of the pest population peaks whenever the resistance control (releasing susceptible pests) is exercised. Intuition might consider the pest population peaks as a failure of optimization, however, taking into account that those pests are harmless as long as Bt toxins stay effective, these “bumps” in pest population are fairly acceptable. Our analysis compare these three resistance management programs and find that the optimal resistance control strategy depends on many factors such as yield loss on refuge, the cost of monitoring resistance and rearing and releasing pests, as well as the natural growth rate of pests and the discount rate. We see high potential for generating discussion as the EPA and researchers have been examining changes in refuge requirements for Bt corn, including the recent approval use of mixed seed; however, mitigation once resistance has developed has received little attention. Although we discuss resistance control mostly in the scenario of agricultural pests, the same or similar methodology can also be used in a much broader context in public health economics such as antibiotic resistance or using genetically engineered mosquitoes to fight malaria.resistance, bio-tech, sustainable, Agricultural and Food Policy, Crop Production/Industries, Environmental Economics and Policy,

Economic Analysis of Supplemental Deductible Coverage as Recommended in the USDA's 2007 Farm Bill Proposal

A primary change to crop insurance contained in the USDA's Farm Bill Proposal is Supplemental Deductible Coverage (SDC). SDC would allow farmers who purchase individual crop insurance coverage to purchase GRP in the amount of the individual policy deductible. GRP indemnities would be accelerated compared with the current GRP policy. Analysis indicates that SDC provides substantial benefits in terms of certainty equivalent gains. The largest benefits are realized by low risk farmers, compared to others in the county, and farmers whose yields are highly correlated with the county yield. Optimal individual policy coverage levels generally decrease when SDC is taken.

Economic Analysis of Supplemental Deductible Coverage as Recommended in the USDA's 2007 Farm Bill Proposal

A primary change to crop insurance contained in the USDA’s Farm Bill proposal is supplemental deductible coverage (SDC). SDC would allow farmers who purchase individual crop insurance coverage to purchase area-wide coverage in the amount of the individual policy deductible. This supplemental area-wide coverage would be similar to the existing Group Risk Plan policy, but with an accelerated indemnity schedule. Analysis indicates that SDC increases farmer certainty equivalents. The largest benefits are realized by farmers with high yield potential in counties with greater systemic risk. In general, optimal individual policy coverage levels modestly decrease when SDC is taken.crop insurance, area-wide coverage, actual production history (APH), group risk plan (GRP), yield distribution, Risk and Uncertainty,

Generation of Simulated Daily Precipitation and Air and Soil Temperatures

Mitchell describes a maximum likelihood method using historical weather data to estimate a parametric model of daily precipitation and maximum and minimum air temperatures. Historical weather data from Brookings, SD, and Boone, IA, are used to create the model. Mitchell describes the process of estimation for the precipitation parametric model, and then reports the actual parametric estimates. Next, he presents an algorithm designed to generate a simulated time series of weather variables using the parametric model. Finally, he describes a model that determines soil temperatures as functions of air temperatures and precipitation