Essays on climate change adaptation and biotechnologies in U.S. agriculture
Wallace E. Huffman
This dissertation examines climate change adaptation and biotechnologies in United States (US) agriculture. The first essay seeks a better understanding of the long-term and short-term implications of climate change for corn yields. Bayesian dynamic regressions are estimated for non-irrigated counties during 1960-2011 and used to forecast over 2012-2031. Yields are forecasted to generally increase 10-40\% over current averages by 2031, with the Corn Belt and Great Lakes experiencing the greatest growth. The long-run relationship between climate damages and Hicks-neutral technical change is then estimated. Standard damage functions are generalized to include extreme temperatures and precipitation, while controlling for soil productivity. Results indicate significant connections between climate damages and technical change and suggest adaptation possibilities beyond 2031.
The second essay examines consumer demand for genetically modified potatoes. The US potato industry is working to lower acrylamide content, a probable human carcinogen forming naturally in potatoes and processed potato products cooked at high temperatures. Using random nth price auctions, we test combined effects of food labels and information on willingness-to-pay (WTP) for conventional potatoes and potato products using biotechnology to reduce acrylamide levels. Each subject receives a randomly-assigned information treatment that consists of one or two perspectives, e.g., an industry, scientific, and/or “environmental group” perspective. Results show for the first time that US consumers are willing to pay a premium for food safety obtained using biotechnology for two popular foods in the American diet.
The third essay expands on previous agriculture-climate links by investigating the role of environmental inputs and climate on cropland use and allocation. A discrete-continuous model of crop-tillage combinations and acreage allocation is estimated using field-level data. In the first step, a multinomial logit model is used to estimate farmers’ choices of crops and tillage. In the second step, linear regressions quantify the impacts of climate, economic factors, management, and soil characteristics on crop acreage. There are significant climate impacts on optimal input use. No-till practices may be an effective adaptation strategy to intense heat and precipitation in the short run. In the long run, farmers may adjust crops and acreage, depending on relative output prices and soil characteristics.