Doctor of Philosophy / Department of Agricultural Economics / Glynn Tonsor / Few things facing the U.S. meat industry in recent years have garnered more attention of economic researchers than food safety events, policies, and mitigation efforts. This dissertation has two main essays and themes focusing on both domestic and international food safety issues. Contributing new insights to this situation, the impacts of FSIS (Food Safety Inspection Service) recalls on consumer meat demand in the United States are estimated by a series of Rotterdam models in the first study using monthly grocery-scanner data. Multiple model specifications are employed to further assess effects across meat products and geographic regions. Recall variables are constructed separately as beef E. coli recall, beef non-E. coli recall, pork recall, and poultry recall variables to facilitate finer assessment of demand impacts. Results suggest beef E. coli recalls significantly reduce the demand for ground beef contemporaneously among most, but not all, regions in the United States. The ultimate finding of food safety effects neither being fully homogeneous nor entirely heterogeneous warrants appreciation. In order to protect domestic consumers and meat industries from potential food safety hazards, some member countries of the WTO implement sanitary and phytosanitary (SPS) measures as non-tariff barriers. The second study focuses on investigating the determinants of red meat trade patterns and associated impacts of SPS regulations. This analysis uses multiple product-level gravity equation models and PPML (Poisson Pesudo Maximum-likelihood estimators to overcome sample selection bias and heteroscedasticity and examine the trade relationship among other factors. Results indicate that, trade values of frozen beef and pork are significantly reduced by the implementation of SPS measures. Also, the spillover effects across meat products on trade were detected which provides essential information to the meat industry, policy makers, and trade representatives.

The estimation of demand equations provides the earliest example of the use of statistical and econometric techniques on economic data. It is possible to identify two distinct approaches to the estimation of demand equations. The first and original approach concentrated on the demand for particular goods by paying attention to any special characteristics of the single market involved. The second approach involved simultaneous estimation of complete systems containing the demand equations for every commodity group purchased by consumers. The estimation of a complete system of demand equations in principle enables us to obtain better estimates of each equation in the system than the first approach because of interaction in the demand behavior of different commodities. This study is directed towards the estimation of demand systems for agricultural products in the OECD countries. Three representatives demand systems with their extensions, namely the Rotterdam Model, An Almost Ideal Demand System (AIDS), and CBS model are used. These models are estimated by Seemingly Unrelated Regression (SUR) method. The procedures to estimate demand systems suggest significant empirical regularities for agricultural products in the OECD countries. The main contribution of this study is its procedure for model selection. This procedure implies the superiority of AIDS and CBS models over the Rotterdam model.