Three essays in industrial organization and applied econometrics

• Online Access: http://hdl.handle.net/2047/d20002690

This section provides abstracts of the three chapters of my doctoral dissertation titled "Three Essays in Industrial Organization and Applied Econometrics." The first chapter is titled "Promotion of Prescription Drugs to Consumers and Physicians: Analysis of Strategic Firm Behavior" and is co-authored with John Kwoka. The paper focuses on the promotion of prescription drugs to consumers and physicians and analyzes it through the prism of strategic firm behavior. While the common method of exploring the impacts of prescription drug advertising has focused on consumer and physician choice of prescriptions, we choose a different approach. Our analysis casts the issue as one of optimal advertising strategies by companies. We examine the category of cholesterol-reducing drugs known as statins over a ten-year period that includes the introduction of new brands as well as a regime change due to new regulations. The findings suggest that both physician-directed and consumer-directed advertising are effective in growing sales revenue in the statins market. The evidence also points to the fact that rivals' direct-to-consumer advertising expenditures have no statistically significant current effect on own sales revenue, while rivals' physician-directed advertising expenditures have a negative impact on a brand's own sales revenue. Finally, we also find that results are sensitive to the variable form and estimation techniques used. The second chapter is titled "Analysis of Day-Ahead Premium Dynamics and Market Efficiency in the ISO New England Wholesale Energy Markets." The paper examines the dynamics and formation of day-ahead premiums in New England's wholesale energy markets from the inception of the New England "standard market design" in March, 2003 through the end of 2011. The study extends the notion of market efficiency tests in wholesale electricity markets by utilizing a Generalized Autoregressive Conditional Heteroskedasticity (GARCH) modeling framework which incorporates measures of short-term fuel cost risk, weather, and load variation. The paper also directly models the impact of structural changes in virtual bidding administrative and financial rules on the day-ahead premium over the entire period of study. The study finds that information about recent movements in fuel costs, temperature, load, and past day-ahead premiums are statistically significant determinants of the day-ahead premium. There is some evidence that the day-ahead premium has been reduced over time, which might be due to improved market design or to learning. Volatility exhibits high persistence across all markets. Finally, the study examines congestion cost dynamics in the day-ahead and real-time markets and finds volatility persistence and presence of multi-day congestion patterns. The third chapter is titled "Improving Demand Estimation in Capacity-Constrained Markets: A Semiparametric Approach." The study focuses on semiparametric techniques for estimating censored models in light of some specific limitations of the frequently used OLS and Tobit estimators. The study implements a Monte Carlo experiment to illustrate the relative performance of several conventional estimators against the semiparametric Censored Least Absolute Deviations (CLAD) estimator in the presence of heteroskedasticity and non-normality of the error term. The results confirm previous findings in the literature that the CLAD estimator outperforms the OLS and Tobit estimators and can be used as a bias-correcting tool in empirical applications. To illustrate one such empirical application, the study compiles a multi-year data set to model capacity-constrained demand for game-level attendance for Major League Baseball. Results show interesting patterns of fan behavior across teams as well as significant impacts of team performance, weather conditions, and weekly schedules on demand.