Year of Publication
Doctor of Philosophy (PhD)
Agriculture, Food and Environment
Dr. Timothy A. Woods
Dr. Yuqing Zheng
This dissertation consists of three essays addressing different topics in health economics. In the first essay, we perform a systematic review of peer-reviewed articles examining consumer preference for the main electronic cigarette (e-cigarette) attributes namely flavor, nicotine strength, and type. The search resulted in a pool of 12,933 articles; 66 articles met the inclusion criteria for this review. Current literature suggests consumers preferred flavored e-cigarettes, and such preference varies with age groups and smoking status. Consumer preference for nicotine strength and types depend on smoking status, e-cigarette use history, and gender. Adolescents consider flavor the most important factor trying e-cigarettes and were more likely to initiate vaping through flavored e-cigarettes. Young adults prefer sweet, menthol, and cherry flavors, while non-smokers, in particular, prefer coffee and menthol flavors. Adults in general also prefer sweet flavors (though smokers like tobacco flavor the most) and dislike flavors that elicit bitterness or harshness. Non-smokers and inexperienced e-cigarettes users tend to prefer no nicotine or low nicotine e-cigarettes while smokers and experienced e-cigarettes users prefer medium and high nicotine e-cigarettes. Weak evidence exists regarding a positive interaction between menthol flavor and nicotine strength.
In the second essay, we investigate U.S. adult consumer preference for three key e-cigarette attributes––flavor, nicotine strength, and type––by applying a discrete choice model to the Nielsen scanner data (Consumer Panel data combined with retail data) for 2013 through 2017, generating novel findings as well as complementing the large literature on the topic using focus groups, surveys, and experiments. We found that (adult) vapers prefer tobacco flavor, medium nicotine strength, and disposables, and such preference can vary over cigarette smoking status, purchase frequency, gender, race, and age. In particular, smokers prefer tobacco flavor, non-smokers or female vapers prefer medium strength, and infrequent vapers prefer disposables. Vapers also display loyalty (inertia) to e-cigarette brands, flavor, and nicotine strength. One key policy implication is that a flavor ban will likely have a relatively larger impact on adolescents and young adults than adults.
The third essay employs a machine learning algorithm, particularly a random forest, to identify the importance of BMI information during kindergarten on predicting children most likely to be obese by the 4th grade. We use the Arkansas BMI screening program dataset. The potential value of BMI information during early childhood to predict the likelihood of obesity later in life is one of the main benefits of a BMI screening program. This study identifies the value of this information by comparing the results of two random forests trained with and without kindergarten BMI information to assess the ability of BMI screening to improve a predictive model beyond personal, demographic, and socioeconomic measures that are typically used to identify children at high risk of excess weight gain. The BMI z-score from kindergarten is the most important variable and increases the accuracy of the prediction by 14%. The ability of BMI screening programs to identify children at greatest risk of becoming obese is an important but neglected dimension that should be used in evaluating the overall utility.
In the last essay, we use Nielson retail scanner dataset and apply a difference-in-differences (DID) approach and synthetic control method, and we test whether consumers in Utah reduced beef purchases after the 2009 Salmonella outbreak of ground beef products. The result of DID approach indicates that the Salmonella event reduced ground beef purchases in Utah by 17% in four weeks after the recall. Price elasticity of demand is also estimated to be -2.04; therefore, the reduction in ground beef purchases as a result of recall is comparable to almost 8.3% increase in the price of this product. Using the synthetic control method that allows us to use all of the control states to produce synthetic Utah, we found the effect of this event minimal compared to the DID effect.
Digital Object Identifier (DOI)
Zarebanadkoki, Samane, "Essays on Health Economics Using Big Data" (2019). Theses and Dissertations--Agricultural Economics. 82.