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Empirical Studies of Competition in Interrelated Markets


Advances in technology have made interactions between previously isolated markets, increasingly prevalent. Even so, much of the research on firm competition in economics has focused on independent markets and how firms compete within these distinct markets. This dissertation extends the literature by studying competition in settings with interrelated markets.

Chapter 1 studies how firm expansion into multiple geographic markets has affected local market competition. As a case study I examine the banking industry, where deregulation in the early 1990s encouraged banks to expand their branch networks into multiple markets. I estimate a model of branch entry that explicitly allows for spillovers across markets, which in banking include demand advantages in attracting more consumer deposits, cost advantages from economies of scale or density, or a diversification of risks. To do this I use a revealed preference approach that also deals with unobserved firm and market heterogeneity. I find that spillover benefits explain 20% of the branches built in the observed equilibrium. The additional observed branches increase consumer surplus, and in most markets lead to a larger share of deposits being collected by banks as opposed to non-bank alternatives. The exception is in the largest markets, where multi-market banks overemphasize competing with additional branches, as opposed to offering better service or higher deposit rates. Because of the lower deposit rates, this leads rich customers, whom are more price sensitive then the average consumer, to switch to outside options such as disintermediation or credit unions. This effect costs banks $115 billion in lost deposits.

In chapter 2, I study auction markets where bidders are competitors in some downstream market. I do this by extending the auction estimation literature to an auction model with externalities. In such a model, in addition to each bidder having a private value for the object, which they receive if they win the auction, some bidders, upon losing, will receive a negative externality that depends on which of their rivals has won the object in their stead. I identify and estimate the externality values by using structural auction estimation techniques to estimate bidder valuations as functions of the negative externalities, and then using variation in the sets of competitors to infer the externality values. I introduce three different estimators for the externalities and provide Monte Carlo results for each.

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