Reducing the Risk of Pesticide Resistance: Economic and Behavioral Factors Affecting U.S. Farmers’ Pesticide Use and Resistance Management

Abstract

In a 2017 off-target blast of dicamba, an herbicide used to control broadleaf weeds in grain crops in the U.S., news concerning possible herbicide toxicity and herbicide commercialization processes headlined the popular media and intensified academic discussions. What brought on this issue in the first place? The answer is weed resistance to multiple groups of herbicides. This dissertation deals with different challenges related to farmers’ decision making in resistance management. More precisely, questions including how farmers respond to economic and behavioral factors associated with adoption of weed management practices (Chapter 2), and how farmers value GE traits in crop seed varieties when the traits are bundled in different ways (Chapter 3) are addressed in two separate chapters. Each of them is explained in greater detail below. The theory predictions in Chapter 2 indicate that farmers’ resistance management decisions are closely related to the strategic relations between farmers’ and neighboring farmers’ management efforts. So are other factors, such as subjective beliefs of the likelihood of solutions to the resistance problem. The empirical analysis in Chapter 2 takes a broad behavioral and economic perspective to examine farmers’ weed management decision. The results, together with the conceptual analysis are of particular use in guiding crop consultants and advisors to provide farmers with efficient and effective assistance. Adopting weed resistance practices after resistance happens is not enough for long-run agricultural development, which provides a starting point for Chapter 3. It is motivated by a highly practical problem: when is the best time to introduce different types of seed products. In this case, the evaluations of farmers’ willingness to pay for different trait bundles enables researchers to proceed with analysis linking seed demand to resistance evolution.