Essays in Agricultural and Food Policy: Impact of Crop Insurance on Fertilizer Use, Willingness to Pay a Premium on Beef, and Estimating the Demand for Carbonated Sweetened Beverage

Abstract

In recent years, empirical economic research has witnessed significant advancements. Simple linear regressions have evolved into different applied econometrics toolkits, which cover methods such as difference-in-difference and event study type strategies, the double hurdle model, and the finite mixture model. This dissertation comprises three essays that concentrate on applying these causal inference approaches and econometric techniques to address issues in agricultural and food policy. The first essay utilizes the difference-in-difference and event study methodologies to examine the impact of the 1994 Federal Crop Insurance Reform Act (hereinafter referred to as “the Act”) on Fertilizer use rate. We employ a novel dataset on nitrogen fertilizer use rate on corn and soybeans, as well as an identification strategy focused on the Act. We address the challenge of identifying the effects of the Act by exploiting the pre-1994 county-level variations in crop insurance participation rates. We define county-level crop insurance participation rates as the ratio of insured acres of a crop type to the maximum insured acreage of the crop type in the county. Our estimation strategy compares counties with low pre-1994 crop insurance participation rates to counties with high pre-1994 insurance rates. The Act should have more “bite” in counties with low pre-1994 crop insurance participation rates. Consistent with our hypothesis, we show that counties with low pre-1994 crop insurance participation rates prior to the Act experience a higher increase in insured acres (and therefore, are referred to as “more treated” counties) compared to counties with high pre-1994 crop insurance participation rates (which are referred to as “less treated” counties). We exploit this differential increase caused by the Act across counties to quantify its effect on fertilizer use rate using the event study and difference-in-differences methodologies. Our results reveal that crop insurance significantly increased fertilizer use rate for corn. The event study results show that the differential increase in fertilizer use rate began precisely two years following the Act. Moreover, fertilizer use rate was uncorrelated with the insured rates prior to the Act: both the levels and trends in fertilizer use were nearly identical between “less treated” and “more treated” counties before 1994. The difference-in-differences results suggest that compared to “less treated” counties, “more treated” counties experienced relatively short-and-medium-run increase in fertilizer use rate on corn after the implementation of the Federal Crop Insurance Reform Act of 1994. Our estimates indicate that a percentage point increase in insured acres for the “more treated” counties relative to the “less treated” counties leads to a 1.466% and 1.377% rise in fertilizer use rate for corn in the short term and medium term, respectively. The second essay employs a hypothetical experimental approach known as the Multiple Price Lists method in a survey of beef consumers in Alabama. This survey data was then analyzed using the double hurdle (DH) model as well as the tobit model to assess consumers' willingness to pay (WTP) for local beef. Specifically, the DH model was used to analyze supermarket and direct-to-consumer (DTC) market choice problems while the tobit model was used to analyze options in the DTC market. For the comparisons between supermarkets and DTC markets, we find that consumers' age and race influence the first and second stages of the DH model. Furthermore, we find that the first-stage decision to consider a DTC option depends on household characteristics such as income, household size, age, gender, race, ownership of freezer, and an understanding of the correct definition of beef. On the other hand, we find that the second-stage decision to pay a premium depends on the "no information" and "information and hormone-free" treatments, as well as gender and race. In comparing options in the DTC markets, results from the tobit model indicate that the WTP a premium is influenced by the same treatments as the second stage of the DH model, as well as household characteristics such as age, race, ownership of freezer beef, and an understanding of the correct definition of freezer beef. On consumers’ valuation for the different labels of beef and steak, our results reveal that two niche labels—namely the “no information” and “information and hormone-free” labels—have the highest premiums across all choice problems. This study highlights the evolving beef market in the wake of the COVID-19 pandemic. The findings emphasize the importance of tailoring offerings to meet consumer preferences, improving consumer education, and targeting young consumers in DTC marketing. The third essay employs scanner data, a popular big data source, to estimate the demand for carbonated sweetened beverages (CSBs). We estimate the impact of a one percent price increase on the demand for CSBs in a one-class model compared to a three-class model, taking heterogeneity into account. In terms of methodological approach, we control for price response endogeneity using the Fisher’s price index approach as well as the Hausmann-type instrument through the two-stage residual exclusion. We further account for heterogeneity by employing a finite mixture model, which allows for the existence of different classes of models within the dataset. Within each class, the model endogenously identify the optimal number of sub-groups. Our results suggest the existence of a two-class model, which therefore has two latent sub-groups of consumers. One of the sub-group exhibits a relatively low sensitivity to price changes, whereas the other sub-group displays a relatively high sensitivity to price changes. For the sub-groups of consumers with relatively low sensitivity to price changes, we find that a percentage increase in the own price of CSBs results in a 0.03% decrease in the demand of CSBs. For the sub-groups of consumers with relatively high sensitivity to price changes, a percentage increase in the own price of CSBs leads to a 0.54% decrease in the demand for CSBs. In both the sub-groups, we find an “inelastic” demand for own price of CSBs, which implies that changes in the price have a limited impact on the quantity of the CSBs that consumers are willing to purchase. These essays collectively contribute to the body of knowledge in applied economics and underscore the need for policymakers and businesses to consider the nuances and complexities of consumer behavior and policy implementation in the areas of agriculture, food, and beverage consumption. The methodologies employed in these essays demonstrate the versatility and effectiveness of applied econometrics in addressing real-world economic challenges.