Charles R. Smith

Economics and Finance PhD student at University of Wisconsin-Madison.

  • đź”— LinkedIn
Home About Research Teaching CV

Working Papers

A Quantitative Model of Bank Mergers with Dean Corbae and Pablo D'Erasmo  |  Slides

Abstract: We develop a simple model of the bank merger process to study the rise in bank concentration following the deregulation of bank branching in the Riegle-Neal Act of 1994. Motivated by the data where currently 4 (dominant) banks have over 40 percent of the U.S. deposit market share while the remaining over 4000 (fringe) banks cover the rest, we apply a dominant-fringe framework with a merger stage to model the rise in concentration following the change in regulation making interstate branching possible. We study the effect of the merger wave on competition, efficiency, and stability of the banking industry. We focus on the heterogeneous response of big and small banks’ lending to idiosyncratic deposit shocks (i.e. their marginal propensity to lend) and how this translates to granularity we document in the banking industry. Further, we examine how the effectiveness of monetary policy varies with rising loan market power.

Adverse Selection and Learning in Consumer Credit Markets with Minnie Cui

Abstract: This paper highlights a trade-off in credit markets between regulatory safeguards for informed consent and the informational frictions they can amplify. In our empirical setting, we find that requiring lenders to garner explicit consent prior to raising clients’ credit limits induces adverse selection. We find disproportionately higher take-up among riskier borrowers, as measured by increased utilization, delinquency, and chargeoffs, which worsens the risk profile of accounts that receive a credit limit increase. In response to the policy, we find that lenders decreased the size of credit limit increases, yet simultaneously gave more frequent limit increases. We develop a model of lender credit limit provision to study the role of adverse selection and learning. We show that learning from acceptance decisions can rationalize lenders’ increased frequency of credit limit increases, while adverse selection can rationalize the decline in the size of credit limit increases.