Department of Agricultural and Resource Economics

The biofuel industry has received billions of dollars in support from governments around the world, as political leaders respond to new environmental and energy-security imperatives. However, a growing body of research highlights nontrivial costs associated with biofuel production, including environmental destruction and diminished food security, and questions the magnitude of perceived benefits. We discuss the ability of biofuels to accomplish climate change, rural development and energy-security objectives, and consider possible impacts on food production and environmental conservation. We also review methods for judging biofuels, consider how well they contribute to policy objectives, and compare policies that support biofuels.

Biofuels have been criticized for raising food prices and reducing food production. While biofuels have rightly been blamed for contributing to reduced food security at a time of record-high food prices in 2008, they have not been credited with reducing the cost of gasoline, also at a time of record-high prices. We discuss the food-versus-biofuel trade-off associated with biofuel production and model the effects of biofuel production in markets for key crops and gasoline, showing that food consumers lose from biofuels but gasoline consumers enjoy substantial benefits. We also suggest ways to address the food-versus-biofuel debate.

In this paper different models of vertical relationships between manufacturers and retailers in the supermarket industry are compared. Demand estimates are used to compute price-cost margins for retailers and manufacturers under different supply models when wholesale prices are not observed. The purpose is to identify which set of margins iscompatible with the margins obtained from estimates of cost, and to select the model most consistent with the data among non-nested competing models. The models considered are: (1) a simple linear pricing model; (2) a vertically integrated model; and (3) a variety of alternative (strategic) supply scenarios that allow for collusion, non-linear pricing and strategic behavior with respect to private label products. Using data onyogurt sold in several stores in a large urban area of the United States the results imply that wholesale prices are close to marginal cost and that retailers have pricing power in the vertical chain. This is consistent with non-linear pricing by the manufacturers, or high bargaining power of the retailers.

In this paper, different models of vertical relationships between manufacturersand retailers in the supermarket industry are compared. Demand estimates areused to compute price-cost margins for retailers and manufacturers underdifferent supply models when wholesale prices are not observed. The purpose isto identify the set of margins compatible with the margins obtained from estimates of cost and to select the model most consistent with the data among non-nested competing models. The models considered are (1) a simple linear pricing model; (2) a vertically integrated model; and (3) a variety of alternative (strategic) supply scenarios that allow for collusion, non-linear pricing, and strategic behaviour with respect to private label products. Using data on yogurt sold in several stores in a large urban area of the U.S. the results imply that wholesale prices are close to marginal cost and that retailers have pricing power in the vertical chain. This is consistent with non-linear pricing by the manufacturers or high bargaining power of the retailers.

We link farmland values to climatic, soil, and socioeconomic variables for counties east of the 100th meridian, the historic boundary of agriculture not primarily dependent on irrigation. Degree days, a non-linear transformation of the climatic variables suggested by agronomic experiments as more relevant to crop yield gives an improved fit and increased robustness. Estimated coefficients are consistent with the experimental results. The model is employed to estimate the potential impacts on farmland values for a range of recent warming scenarios. The predictions are very robust and more than 75% of the counties in our sample show a statistically significant effect, ranging from moderate gains to large losses, with losses in the aggregate that can become quite large under scenarios involving sustained heavy use of fossil fuels.