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Scale and efficiency measurement using a semiparametric stochastic frontier model: evidence from the U.S. commercial banks

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Abstract

In this paper, we use the local maximum likelihood (LML) method proposed by Kumbhakar et al. (J Econom, 2007) to estimate stochastic cost frontier models for a sample of 3,691 U.S. commercial banks. This method relaxes several deficiencies in the econometric estimation of frontier functions. In particular, we relax the assumption that all banks share the same production technology and provide bank-specific measures of returns to scale and cost inefficiency. The LML method is applied to estimate the cost frontiers in which a truncated normal distribution is used to model technical inefficiency. This formulation allows the cost frontier, inefficiency effects and heteroskedasticity in both noise and inefficiency components to be quite flexible.

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Authors and Affiliations

  1. Department of Economics, State University of New York at Binghamton, Binghamton, NY, 13902, USA

    Subal C. Kumbhakar

  2. Department of Economics, Athens University of Economics and Business, 76 Patission Street, 104 34, Athens, Greece

    Efthymios G. Tsionas

Authors
  1. Subal C. Kumbhakar
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  2. Efthymios G. Tsionas
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Correspondence to Subal C. Kumbhakar.

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Kumbhakar, S.C., Tsionas, E.G. Scale and efficiency measurement using a semiparametric stochastic frontier model: evidence from the U.S. commercial banks. Empirical Economics 34, 585–602 (2008). https://doi.org/10.1007/s00181-007-0137-2

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  • DOI: https://doi.org/10.1007/s00181-007-0137-2

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