I use the stochastic cost frontier approach to investigate efficiency of banks operating in the Third Federal Reserve District, accounting for the quality and riskiness of bank output. In addition to the mean and mode of the conditional distribution of the one-sided error term, I calculate confidence intervals for the inefficiency measures based on the conditional distribution. The results indicate that Third District banks are operating at cost-efficient output levels and product mixes, but are not efficiently using their inputs. The second part of the article relates the inefficiency measures to several correlates.

Over the past several years, substantial research effort has gone into measuring the efficiency of financial institutions. Many studies have found that inefficiencies are quite large, on the order of 20% or more of total banking industry costs and about half of the industry's potential profits. There is no consensus on the sources of the differences in measured efficiency. this paper examines several possible sources, including differences in efficiency concept, measurement method, and a number of bank, market, and regulatory characteristics. We review the existing literature and provide new evidence using data on US banks over the period 1990–1995.

This paper explores how to incorporate banks' capital structure and risk-taking into models of production. In doing so, the paper bridges the gulf between (1) the banking literature that studies moral hazard effects of bank regulation without considering the underlying microeconomics of production and (2) the literature that uses dual profit and cost functions to study the microeconomics of bank production without explicitly considering how banks' production decisions influence their riskiness. Various production models that differ in how they account for capital structure and in the objectives they impute to bank managers – cost minimization versus value maximization – are estimated using U.S. data on highest-level bank holding companies. Modeling the bank's objective as value maximization conveniently incorporates both market-priced risk and expected cash flow into managers' ranking and choice of production plans. Estimated scale economies are found to depend critically on how banks' capital structure and risk-taking are modeled. In particular, when equity capital, in addition to debt, is included in the production model and cost is computed from the value-maximizing expansion path rather than the cost-minimizing path, banks are found to have large scale economies that increase with size. Moreover, better diversification is associated with larger scale economies while increased risk-taking and inefficient risk-taking are associated with smaller scale economies.

For nearly two decades banks in the US have consolidated in record numbers – in terms of both frequency and the size of the merging institutions. Rhoades (1996) (S.A. Rhoades, 1996. Bank Mergers and Industrywide Structure, 1980–1994. Board of Governors of the Federal Reserve System, Staff Study 169) hypothesizes that the main motivations were increased potential for geographic expansion created by changes in state laws regulating branching and a more favorable antitrust climate. To look for evidence of economic incentives to exploit these improved opportunities for consolidation, we examine how consolidation affects expected profit, the riskiness of profit, profit efficiency, market value, market-value efficiencies, and the risk of insolvency. Our estimates of expected profit, profit risk, and profit efficiency are based on a structural model of leveraged portfolio production that was estimated for a sample of highest-level US bank holding companies by Hughes et al. (1996) (Hughes et al., 1996. Efficient banking under interstate branching, Journal of Money, Credit, and Banking 28, 1045–1071.) Here, we also estimate two additional measures that gauge efficiency in terms of the market values of assets and of equity. Our findings suggest that the economic benefits of consolidation are strongest for those banks engaged in interstate expansion and, in particular, interstate expansion that diversifies banks’ macroeconomic risk. Not only do these banks experience clear gains in their financial performance, but society also benefits from the enhanced bank safety that follows from this type of consolidation.

We consider how size matters for banks in three size groups: small community banks with assets less than 1 billion, large community banks with assets between 1 billion and 10 billion, and midsize banks with assets between 10 billion and 50 billion. To illustrate the differences between these banks and larger banks whose business models are distinctly different, we examine large banks with assets between 50 billion and 250 billion and the largest banks with assets exceeding 250 billion. Community banks have potential advantages in relationship lending compared with large banks. However, increases in regulatory compliance and technological burdens may have disproportionately increased community banks’ costs, raising concerns about small businesses’ access to credit. Our evidence suggests several patterns: (1) while small community banks exhibit relatively more valuable investment opportunities, larger community banks, midsize banks, and larger banks exploit theirs more efficiently and achieve better financial performance; (2) average operating costs that include costs related to regulatory compliance and technology decrease with size; (3) unlike small community banks, large community banks have financial incentives to increase lending to small businesses; and (4) for business lending and commercial real estate lending, compared with small community banks, large community banks, midsize banks, and larger banks assume higher inherent credit risk and exhibit more efficient lending. Thus, concern that small business lending would be adversely affected if small community banks find it beneficial to increase their scale is not supported by our results.