This study assesses the economic and environmental effects to hog finishing farms from residual taxes/standards and restrictions on manure application and stocking density. Economic effects are measured in terms of net farm income and land prices, while levels of ammonia and excess nitrogen and phosphorus proxy the environmental effects. Any environmental policy requiring the need for additional land comes at a small cost to farmers who have access to adequate neighboring land. If this is not the case, then manure application and stocking density restrictions are expensive since the producer is basically forced to either purchase land or reduce hog production levels.

The decision to adopt a potentially profitable but unfamiliar conservation technology is cast in a multi-period Bayesian framework. Specifically, dairy farmers who are both risk-averse and susceptible to peer group influence progressively learn about the true impact of adopting reduced phosphorus dairy diets on their income distributions as they repeatedly experiment with this new technology. Empirically calibrated simulations are used to examine the effects of a voluntary green payment program on the rate of technological diffusion. Results suggest that (a) green payments can accelerate learning and produce significant, permanent changes in behavior relatively quickly and for a reasonable cost; (b) shorter contracts offering larger incentives may be more cost-effective when learning plays an important role in behavioral change; and (c) unknown prior beliefs can reduce the efficacy of a green payment program, implying efforts to verify these priors or to ensure against them by increasing the payment level may be worthwhile.

There is growing interest in green payments subsidizing conservation measures on working farmland based on the premise that they have positive effects on the environment and agriculture simultaneously without causing international trade distortions. This paper uses a Ricardian land market equilibrium model to examine the impacts of green payments. The analysis shows green payments can worsen ambient pollution damage by subsidizing the expansion of more intensive crop cultivation. Some forms of green can increase cultivation intensity (and thus environmental damage) as well. These adverse effects can be avoided by careful targeting, but such targeting is likely to be quite difficult.

Genetically engineered (GE) soybeans first became available to farmers in 1996. Despite the common questions regarding any new crop technology, the new seeds were rapidly adopted. This study examines the characteristics of adopters, as well as yield and weed control cost changes, using survey results from Delaware farmers at the start of the 2000 season. Duration analysis reveals that earlier-adopting farmers had larger farms and tended to use computers for financial management, while regression analysis shows significantly lower weed control costs and, to a lesser extent, higher yields for GE soybeans.

USDA uses the concept of “publish-ability” rather than statistical reliability of an estimate for quality validation of USDA estimates, which is solely based on the sample size and the coefficient of variation (CV). We demonstrate conceptually how the reliability of the sample mean can be tested by estimating the upper and lower bounds of the confidence interval for an unknown population mean using the CV. However, the reliability test for the sample mean can be made only under the normality assumption. USDA multiple-way Agricultural Resource Management Survey (ARMS) estimates are used to illustrate the relative measure of precision for sample-based estimators.

This study investigates the environmental impacts of several forms of policies that offer farmers subsides in return for the adoption of conservation tillage. The policies differ as to whether the tillage practice or one of several environmental benefits is targeted. We develop an Environmental Lorenz Curve which fully represents the performance of the targeting policies, and show that this curve can be directly used to help select the optimal targeting strategy for special classes of social welfare functions. The model is applied to the state of Iowa.