UMD Theses and Dissertations
Permanent URI for this collectionhttp://hdl.handle.net/1903/3
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Item Market Structure and Congestion Externalities: Theory and application to the ride-hailing industry(2021) Gomez Gelvez, Julian Andres; Williams III, Roberton C; Agricultural and Resource Economics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The encompassing theme of this dissertation is the analysis of markets that feature market power and negative externalities. I focus mainly on congestion externalities, as externalities that affect only market participants. The first chapter evaluates the efficiency of private pricing of congestible resources. I develop a model of congestible resource use that explicitly considers a bivariate distribution of reservation values and sensitivities to congestion across potential users. This model highlights the importance of the correlation between reservation values and sensitivities to congestion to judge the efficiency of private pricing. Numerical results based on a road pricing example show that monopolistic pricing can range from very inefficient (price too high) when the correlation is negative to almost complete efficiency when it is strong and positive. The second chapter studies ride-hailing markets mediated by digital platforms like Uber. I extend the model of the first chapter to include a supply side of drivers. A monopolistic platform chooses prices on both sides of the market to maximize profit. I calibrate the model to the morning peak period of Bogota, Colombia. The results show that the price gap imposed by a monopolistic platform corresponds to about two thirds of the net marginal external cost caused by an additional ride hailer. A congestion charge on ride hailing is then justified. However, the optimal congestioncharge, as a tax on the price charged to riders, covers only 50% of the marginal external cost. The last chapter explores the effects of modifying several assumptions of the ride-hailing model developed in the second chapter. The main modification is to move from a monopolistic market structure to a duopoly. I show that absent any differentiation between platforms, competition leads to zero profits. This result supports the idea that ride-hailing markets gravitate towards a single platform. Assuming a small amount of differentiation, the duopoly equilibrium reduces the price charged to riders and increases the size of the market. This expansion reduces overall welfare due to the external effect on traffic congestion and calls for a higher congestion charge.Item Trade Policy and Industrial Concentration(2020) Graziano, Alejandro Gustavo; Limão, Nuno; Economics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)I examine the interrelationship between industrial concentration, the CES industry price index and trade policy when a subset of firms in the market takes the effect of their decisions on industry aggregates into account. In the first chapter, I develop a hybrid model that augments the standard monopolistic competition approach in the international trade literature to include an oligopolistic margin: a set of foreign and domestic heterogeneous granular firms competing in quantities. This margin predicts novel effects of trade liberalization on trade, consumer welfare, and industrial concentration. Specifically, trade liberalization generates lower consumer gains when foreign firms are more concentrated than domestic, and higher domestic industrial concentration of granular firms. In the second chapter, I study the implications of hybrid competition for the gravity equation. I show that the trade cost elasticity is attenuated by foreign firm concentration and I test the novel oligopolistic margin using diff-in-diff variation from trade policy changes in Colombia. I find robust evidence for this margin. I also show that the aggregate impact of trade liberalization can be substantially reduced by oligopolistic behavior. Moreover, foreign concentration heterogeneity across origin countries suggests a highly heterogeneous impact of trade liberalization: imports from countries in the top decile of concentration had 13 log points lower growth on average than imports from countries in the bottom decile. In the third chapter, I explore the implications of the hybrid model when there is trade policy uncertainty. When firms are uncertain about future tariffs and exporting involves sunk investments, the value of waiting increases. In the setting I propose, potential entrants also consider the strategic reaction of oligopolistic competitors: when domestic granular firms are highly concentrated, the impact of trade policy uncertainty on foreign entry is mitigated since the eventual increase in tariffs is predicted to be partially offset by an increase in domestic markups. When foreign granular exporters are highly concentrated, the impact is amplified since the increase in tariffs is predicted to not be fully passed to the price index. I discuss an empirical application in the context of Brexit uncertainty and potential ways forward.Item Equilibrium Models with Dynamic Demand and Dynamic Supply(2019) Hui, Shen; Sweeting, Andrew T; Economics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This dissertation comprises two studies of equilibrium models with both dynamic demand and dynamic supply sides. The first is an empirical study of the US video games industry, and the second is a theoretical study. Chapters 1 and 2 develop a model for quantifying the role of social learning in consumers’ dynamic demand and finding optimal intertemporal prices for profit maximizing firms in a market populated by forward-looking social learners. Optimal prices are a result of a Markov perfect equilibrium played between the firm and the consumers. Nested in the market equilibrium is a demand equilibrium played among consumers who make the “right” purchase/wait decisions given endogenously produced product information. The empirical exercises are conducted in two steps. The first step estimates demand parameters, including those associated with social learning. Endogeneity of prices is remedied with a pseudo pricing policy function of relevant state variables. In the second step, optimal prices are found by the Mathematical Programming with Equilibrium Constraints (MPEC) approach. The model is applied to the US video games industry with sales data of PlayStation 3 games. The results reveal that (1) compared to static social learning, forward- looking social learning reduces equilibrium profits of games in the sample by $5.2M (28.4%) on average; (2) an incorrect belief of consumers’ forward-looking behavior reduces a firm’s profits by a maximum of 29.92%. These results indicate great value for researches on consumers’ forward-looking social learning behavior. In chapter 3 we study the effect of adding strategic buyers to the computational model of dynamic price competition when sellers experience learning-by-doing and organizational forgetting developed by Besanko et al. (2010) (BDKS). The addition is motivated by the presence of repeat buyers in many industries where learning- by-doing has been documented, and the role that the assumption of a monopsony strategic buyer has played in the theoretical literature. We characterize the degree of strategic buyer behavior using a single parameter, and show that even quite limited strategic behavior changes the equilibrium correspondance by almost entirely eliminating the multiplicity of equilibria emphasized by BDKS, and ensuring that no seller is likely to dominate the industry in the long-run. We examine how the welfare of both buyers and sellers varies with the degree of strategic buyer behavior.Item ESSAYS IN EMPIRICAL INDUSTRIAL ORGANIZATION(2009) Chesnes, Matthew William; Rust, John; Jin, Ginger; Economics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Chapter 1: Capacity and Utilization Choice in the US Oil Refining Industry This paper presents a new dynamic model of the operating and investment decisions of US oil refiners. The model enables me to predict how shocks to crude oil prices and refinery shutdowns (e.g., in response to hurricanes) affect the price of gasoline, refinery profits, and overall welfare. There have been no new refineries built in the last 32 years, and although existing refineries have expanded their capacity by almost 13% since 1995, the demand for refinery products has grown even faster. As a result, capacity utilization rates are now near their maximum sustainable levels, and when combined with record high crude oil prices, this creates a volatile environment for energy markets. Shocks to the price of crude oil and even minor disruptions to refining capacity can have a large effect on the downstream prices of refined products. Due to the extraordinary dependence by other industries on petroleum products, this can have a large effect on the US economy as a whole. I use the generalized method of moments to estimate a dynamic model of capacity and utilization choice by oil refiners. Plants make short-run utilization rate choices to maximize their expected discounted profits and may make costly long-term investments in capacity to meet the growing demand and reduce the potential for breaking down. I show that the model fits the data well, in both in-sample and out-of-sample predictive tests, and I use the model to conduct a number of counterfactual experiments. My model predicts that a 20% increase in the price of crude oil is only partially passed on to consumers, resulting in higher gasoline prices, lower profits for the refinery, and a 45% decrease in total welfare. A disruption to refining capacity, such as the one caused by Hurricane Katrina in 2005, raises gasoline prices by almost 16% and has a small negative effect on overall welfare: the higher profits of refineries partially offsets the large reduction in consumer surplus. As the theory predicts, these shocks have a smaller effect on downstream prices when consumer demand is more elastic, resulting in a larger share of total welfare going to the consumer. Chapter 2: Consumer Search for Online Drug Information Consumers are increasingly turning to the internet and using search engines to find information on medicinal drugs. Between 2001 and 2007, the number of adults using the internet as an alternative source of health information doubled. At the same time, online and offline advertising spending by drug companies is growing rapidly. I seek to understand how consumers use search engines to find drug information and how this activity is influenced by direct to consumer advertising. I utilize a database of user click-through data from America Online to analyze the search behavior of consumers seeking drug information online. Compared with other searches, users submitting drug-related queries are more likely to click on more than one result in a search session, and when they do, they click more rapidly through the results and tend to migrate away from dot-com sites and toward those ending in dot-org and dot-net. Offline advertising on a drug serves to increase the frequency and intensity of these searches. Chapter 3: Drug Information via Online Search Engines This paper utilizes a database of organic and sponsored search results from four large search engines to analyze the supply of drug-related information available on the internet. I show that the information varies significantly across search engines, domain extensions, and between organic and sponsored results. Regression results reveal that websites with relatively more promotional content are pushed down in the search results while informational sites (including those ending in dot-gov and dot-org) are more likely to appear on page one of the results.