Proposal Number: SES - 1227613 Katheryn N. Russ University of California, Davis and National Bureau of Economic Research

The recent financial crisis prompted intense policy debate over the appropriate role for regulation in the growth and reach of large lending institutions in the U.S. and worldwide. The policy debate has far outpaced economic theory, which still provides no models featuring an array of banks that vary in size and strategically (Bertrand) compete in the macroeconomy. The need to model a large number of heterogeneous banks, each setting its own competitive markup over lending costs, has presented a serious technical challenge. This project uses recent advances in the theory of heterogeneous firms to fill the conceptual gap and present a new framework for policy analysis.

The project provides a new theoretical framework for evaluating the effects of increasing the market share of the largest banks on the pricing of loans and on macroeconomic stability. Existing models of the banking sector (1) require banks to be identical or exogenously limit their number to two or three and (2) predict that increasing concentration coincides with increasing market power when pricing loans. Empirical studies find a weak link or no link at all between concentration and the markups that banks charge borrowers over the cost of funds, a common measure of market power. This project exploits cross-country data on individual bank balance sheets to generate relevant stylized facts and uses them to construct a new modeling framework that encompasses the very different circumstances of large versus small and financially developed versus less developed countries. The goal is to derive and quantify the macroeconomic implications of a top-heavy distribution of banks, in particular the relationship between bank size and volatility in the aggregate credit supply and the gross domestic product.

The broader impact of the project is its guide for regulatory policy. The central theme of the project is that one size does not fit all when it comes to evaluating the role of large banks. Increasing capital requirements may have no impact on the cost of loans and little impact on market concentration or macroeconomic volatility in large or highly financially developed countries, yet can increase both borrowing costs and macroeconomic volatility in small or less financially developed countries. Innovation in the financial sector can increase both access to credit and macroeconomic volatility, presenting a tradeoff for policymakers. The new modeling and empirics in this study will quantify these crucial nuances for more accurate cost-benefit analysis.

Project Report

Normal 0 false false false EN-US X-NONE X-NONE Intellectual Merit This project established that the presence of big banks – by itself – is associated with greater variability in the aggregate supply of credit and the gross domestic product (GDP), even without any extra complexities that might arise from interbank connections or securitization. Thus, policies which lead to increased concentration can lead to increased macroeconomic fluctuations, even in normal times. We do this in three steps. First, we design a theory of many banks, with differing costs of lending, competing strategically for borrowers. This allows us to examine issues of concentration, which could not be done in previous models where there were only a few banks, or many banks which did not compete strategically and thus large banks had no more market power than small ones. Market concentration is an important measure used by policy makers and regulators to determine how large big players in the market are, so formalizing a measure of market concentration for banks in a theory of the macroeconomy as we have done is crucial to assess the implications of large banks for aggregate credit and GDP. This theory draws from a handful of other studies in finance and trade, which use the theory of large deviations in the natural sciences to describe systems where the behavior of individual agents even within a large population can impact the observed behavior of the entire population, if a few of those agents are large enough, which in finance and physics is referred to as "granularity." Second, we show that large banks are mathematically large enough, or granular, to affect measured changes in aggregate credit and GDP. This requires that the distribution of bank size within a country be power law distributed. For many countries, this distribution ends suddenly at the upper tail, in a truncation. We show that bank size in many countries fits a truncated power law distribution and describe the conditions under which this still implies that the banking sector can be highly concentrated enough for small changes in the behavior of large banks to have an impact on aggregate credit and GDP. Finally, we test whether our measure of granularity in the banking sector is associated with greater variability in aggregate credit and GDP. We find that for most countries, it is. The existence of very large banks can, by itself, result in larger fluctuations in macroeconomic outcomes. Broader Impact Currently, regulators around the world often respond to banking crises by encouraging consolidation or mergers of large banks. They are also charged with evaluating the effects of mergers during normal times. Our results indicate that ignoring the implications of bank size—independently of any other more subtle considerations of connectedness or trading activity—may lead to policies which encourage the disproportionate growth of big banks with the unintended consequence of increasing variability in aggregate credit and GDP even after a crisis has subsided, in normal times. Our model and quantitative results provide a simple toolkit to estimate the magnitude of these granular effects for any economy with a relatively small dataset readily available to most regulators. The project also supplemented the training of two graduate students engaged in research on the macroeconomic impacts of bank behavior, and built a network between researchers active in policy analysis in the U.S. and Germany.

National Science Foundation (NSF)
Division of Social and Economic Sciences (SES)
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Georgia Kosmopoulou
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National Bureau of Economic Research Inc
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