Browsing by Author "Sweeting, Andrew"

My dissertation focuses on employing microeconomic techniques to study markets and questions that are important and complex, and also have potential policy implications. Two of my chapters analyze the health industry with an emphasis on hospitals, patient welfare, and regulation. The remaining chapter focuses on the housing market in Los Angeles and explores real estate flipping.

The second chapter of my dissertation studies the impact of state level regulations on hospital bed capacity decisions. The regulations are intended to decrease hospital investments without diminishing patient access. I find that the regulation decreases total hospital investment in bed capacity as expected. When running simulations to estimate how hospitals would behave differently were the regulatory policy changed, I find that total patient utility is negatively affected by the presence of the regulation as many patients get turned away from their preferred hospital due to overcrowding. This analysis has important policy implications as it suggests that the regulation has been ineffective in ensuring that patient welfare was unharmed by the restrictions.

The third chapter is based on joint research with Patrick Bayer and James W. Roberts and studies the housing market in the Los Angeles metropolitan area from 1988 to 2009. Using novel data, I identify which housing transactions involve flippers who aim not to live in the house, but rather to quickly resell it for financial gain. I find that flipper behavior varies based on how frequently I observe the individual engage in such behavior. Experienced flippers, who are observed to flip many houses in the data, target homes being sold at below market value and earn their returns from buying them at a discount. Their effect on long term prices in the neighborhood is negligable. Inexperienced flippers who are less active, seek to earn their profits by timing the market and are more active when house prices were rapidly appreciating from 1999 to 2005. Their activity increases housing prices in the neighborhood in the short term, but decreases them in the long term. Such results are consistent with the claim that real estate flipping contributed to the housing bubble.

The fourth chapter of my dissertation again focuses on the hospital industry and looks at the question of how patient composition changes as a hospital becomes busier and has to turn patients away. I develop a theoretical model which predicts that hospitals are more likely to turn away less profitable patients. As a result, when a hospital becomes more full and therefore is more likely to have to turn patients away, its composition of patients will change and become more profitable on the whole. I test this theory by empirically analyzing the effect of hospital congestion on the composition of hospital patients using hospital discharge data. The findings are consistent with my theoretical model as when hospitals become more crowded, the fraction of uninsured patients and mental health patients (who are typically not profitable to a hospital) decreases. This result suggests that hospitals are more likely to turn away unprofitable patients while continuing to admit more profitable patients.

The dissertation consists of three chapters relating to pricing strategies. Chapter 1 studies coupons for prescription drugs and their impacts on consumer welfare, firm profits, and insurance payments. Chapter 2 examines consumer brand loyalty and learning in pharmaceutical demand and discusses implications for marketing and health care policy. Chapter 3 develops a framework for estimating demand and supply in an online market with many competing sellers and frequent price changes and proposes optimal pricing strategies for a large seller.

The first chapter studies an innovative price strategy in pharmaceuticals. Branded drug manufacturers have recently started to issue copay coupons as part of their strategy to compete with generics when their branded drugs are coming off patent. To explore the welfare implications of copay coupons, I estimate a model of demand and supply using pharmaceutical data on sales, prices, advertising, and copayments for cholesterol-lowering drugs and perform a counterfactual analysis where a branded manufacturer introduces coupons. The model allows flexible substitution patterns and consumer heterogeneity in price sensitivities and preferences for branded drugs. The counterfactuals quantify the effects of copay coupons for different assumptions about the take-up of coupons and the ability of the branded manufacturer to direct them to the most price-sensitive types of consumers. The results show that the agency problem between insurers and patients gives a branded manufacturer a strong incentive to issue copay coupons. Introducing copay coupons benefits the coupon issuer and consumers but raises insurance payments. In equilibrium, insurer spending can increase by as much as 25% even when just 5% of consumers have a coupon, with social welfare falling significantly.

Medicines for chronic conditions like high cholesterol, heart disease, and diabetes are repeatedly used for a long period of time. Consumer dynamics thus plays an important role in the demand for those drugs. In the second chapter, I estimate a demand model with brand loyalty and learning using micro-level data from cholesterol lowering drug markets in the United States. The estimates suggest high switching costs and strong learning effects at the molecule level in the markets. Switching costs raise the predicted probability of choosing the same drugs in a row and learning largely increases patient stickiness to a molecule in the long run. I discuss pricing implications of the estimation results for drug manufacturers, insurance companies, and policy makers.

The last chapter, coauthored with Dr. Andrew Sweeting and Dr. James W. Roberts, looks at pricing in a different context. We estimate a model of entry, exit and pricing decisions in an online market for event tickets where there are many competing sellers and prices change frequently. We use the estimates from our model to analyze the optimality of the pricing policy used by the largest seller (broker) in the market. We show that the broker's pricing policies substantially affect the prices set by his competitors. When we compare the broker's pricing policy with the prices that our model predicts are optimal we find that the broker sets approximately correct prices close to the game, when his pricing problem resembles a static one, but that he might be able to gain from using different pricing rules and updating prices more frequently further from the game.

This dissertation extends the economics literature in industrial organization with three empirical essays on the strategic decisions of firms in imperfectly competitive markets. Using data from the U.S. airline industry, I combine reduced-form analysis with recent econometric advances in the estimation of dynamic games to examine the market-level and industry-level behavior of oligopolistic firms. The first essay presents a framework for sensitivity analysis in merger simulation. The second essay continues the market-level analysis of merger effects by examining how airline mergers influence price dispersion. The third essay shifts focus to industry-level investment behavior, examining the role played by bankruptcy policy in disciplining capital investment.

This dissertation consists of three chapters relating to dynamic demand models of storable goods and their application to taxes that are imposed on soft drinks. Broadly speaking, the first chapter builds the estimation strategy for dynamic demand models of storable goods that allows for unobservable heterogeneous preferences in household's tastes. The second chapter uses the estimation strategy developed in the first chapter to study the policy implications of taxes that are imposed on sugary soft drinks. The last chapter explores and provides an explanation for the level of pass-through for soda taxes.

To be more specific, the first chapter develops techniques for incorporating systematic brand preferences in dynamic demand models of storable goods. Dynamic demand models are important for correctly measuring price elasticities of products that can be stockpiled. However, most of the literature excludes systematic preferences over consumers' brand tastes. This chapter resolves this issue by incorporating random coefficient Logit models into a dynamic demand framework and hence allows for realistic demand substitution patterns. It builds on Hendel and Nevo's 2006 Econometrica paper, where the authors introduce a model of dynamic demand that flexibly incorporates observable heterogeneity and estimates it via a three-step procedure that separates brand and volume choices. While a powerful tool, this method is tricky to execute. Therefore, this chapter also discusses the difficulties that may face implementers.

The second chapter predicts the effects of taxes on sugar sweetened soft drinks (sugar taxes) on both total consumption and the welfare of different types of consumers. It specifies and estimates a structural dynamic demand model of storable goods with rational and forward-looking households. It flexibly incorporates persistent heterogeneous consumer preferences and develops a computationally attractive method for estimating its parameters. Sugar taxes have been proposed at both the national and state-level, and passed in three states, as a means of slowing or reversing the growth in obesity and diabetes. To accurately analyze the effects of these policies, this chapter takes two specific aspects of soft drinks into account: storability and differentiation. It compares the results from this model to two benchmark studies: a static model with consumer heterogeneity and a dynamic model without households' persistent heterogeneous tastes. It finds that failing to account for dynamics (i.e. storability) results in overestimated reduction in consumption and failing to account for persistent heterogeneous preferences (i.e. differentiation) results in overestimated reduction in consumption and underestimated welfare loss. The model and method developed here are readily applicable to many studies involving storable goods, such as firms' optimal pricing behavior and anti-trust policies analyses.

The third and last chapter focuses on the incidence of soda taxes by studying the pass-through level of these taxes. It lays out a framework for thinking about the determinants of the pass-through level. More specifically, it builds theoretical models that examine the pass-through under more complex supply structures with multiple manufactures and retailers. In addition to providing some intuition behind theoretical predictions of the models, this chapter also presents empirical results found in the data along with their implications.

My dissertation explores the interactions between the various agents in the pharmaceutical industry and how they are affected by changes in health care policy. In my work, I examine innovation and competition among new brand drugs and the value of prescription drug insurance after patent expiration.

The second chapter of my dissertation empirically assesses the trade-off between patent breadth and patent length, a topic that has attracted significant theoretical but little empirical attention. I estimate a model of pharmaceutical demand and supply that incorporates insurance and advertising for the antidepressant market. Using these estimates, I consider the potential welfare effects of giving some of the most important product innovations broader but shorter patents, which increases the market power that these innovators have in the short-run but also allows for more rapid entry by generics. My results indicate that in this setting broader patents could increase total welfare by more than 9%, mostly through savings in insurer expenditures. These results are robust to endogenizing the entry of other branded drugs.

In the third chapter, which stems from research done jointly with Peter Arcidiacono, Paul Ellickson, and David Ridley, I use data from the pharmaceutical industry to estimate demand and supply for prescription drugs across both insured and uninsured consumers, allowing for consumer preferences organized into discrete types. I account for an important characteristic of health care markets: the price paid by insured consumers (copayment) is typically much smaller than the price received by the manufacturer. This analysis highlights how generic-drug availability differentially affects insured and uninsured consumers. In particular, generic entry disproportionately benefits insured consumers, at least in the first year to two years.

The fourth chapter in my dissertation extends the analysis in Chapter 2 to allow for a more generalized framework. In Chapter 2, the first pharmaceutical product innovation that enters a therapeutic class is assumed to be high-value while those innovations that follow are assumed to provide relatively little, if any, added therapeutic value beyond the first. Using the same data and demand model estimates, I consider the potential welfare effects of allowing these later to be considered high-value products and providing them with greater patent breadth and shorter patent length. My results indicate that in this setting, the modified patent policy could still increase total welfare by more than 8%, mostly through savings in insurer expenditures. These results are also robust to endogenizing the entry of other branded products.

This dissertation consists of three chapters relating to various topics in empirical Industrial Organization. The first two chapters deal with the empirical treatment of sales in online markets. The third chapter explores the level of pass-through for taxes on soft drinks.

In the first chapter I demonstrate that when dealing with online market places it is important to take into account the fact that multiple listings coexist. Traditionally, the economic literature has treated listings as independent. In reality, however, buyers often have the choice between multiple contemporaneous listings. I demonstrate that it is important to take this fact into account since sellers who list their items simultaneously are in direct competition. More specifically, I show that the sale probability of a given item decreases when the number of simultaneous listings increases. Thus, the aforementioned assumption of independence can lead to wrong results.

In the second chapter, I specify and estimate a structural model of mechanism choice in online markets. I consider both sides of the market: On the demand side, buyers' choices among available listings are equilibrium outcomes of an entry game. On the supply side, sellers take competition into account and make equilibrium decisions when choosing sales mechanisms and prices. I estimate this model using data from sales of baseball tickets on eBay. I find that sellers' outside options, dynamic incentives, and risk preferences affect mechanism choice. Using the estimation results from my model I analyze the welfare effects of a hybrid mechanism (buy-it-now auctions) eBay offers. I find that the existence of buy-it-now auctions increases the consumer surplus and reduces the producer surplus. The reason for this is that buy-it-now auctions diminish sellers' potential for diversification via mechanism choice and thus strengthen competition.

The third and last chapter focuses on the incidence of soda taxes by studying the pass-through level of these taxes. It lays out a framework for thinking about the determinants of the pass-through level. More specifically, it builds theoretical models that examine the pass-through under more complex supply structures with multiple manufactures and retailers. In addition to providing some intuition behind theoretical predictions of the models, this chapter also presents empirical results found in the data along with their implications.