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  • TsionasMalikovKumbhakar-Jan2018-MarketPowerEfficiency

    Rights statement: This is the author’s version of a work that was accepted for publication in European Journal of Operational Research. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in European Journal of Operational Research, 270, 2, 2018 DOI: 10.1016/j.ejor.2018.04.012

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    Available under license: CC BY-NC-ND

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An internally consistent approach to the estimation of market power and cost efficiency with an application to U.S. banking

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<mark>Journal publication date</mark>16/10/2018
<mark>Journal</mark>European Journal of Operational Research
Issue number2
Volume270
Number of pages14
Pages (from-to)747-760
Publication StatusPublished
Early online date12/04/18
<mark>Original language</mark>English

Abstract

We develop a novel unified econometric methodology for the formal examination of the market power – cost efficiency nexus. Our approach can meaningfully accommodate a mutually dependent relationship between the firm’s cost efficiency and marker power (as measured by the Lerner index) by explicitly modeling the simultaneous determination of the two in a system of nonlinear equations consisting of the firm’s cost frontier and the revenue-to-cost ratio equation derived from its stochastic revenue function. Our framework places no a priori restrictions on the sign of the dependence between the firm’s market power and efficiency as well as allows for different hierarchical orderings between the two, enabling us to discriminate between competing quiet life and efficient structure hypotheses. Among other benefits, our approach completely obviates the need for second-stage regressions of the cost efficiency estimates on the constructed market power measures which, while widely prevalent in the literature, suffer from multiple econometric problems as well as lack internal consistency/validity. We showcase our methodology by applying it to a panel of U.S. commercial banks in 1984–2007 using Bayesian MCMC methods.

Bibliographic note

This is the author’s version of a work that was accepted for publication in European Journal of Operational Research. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in European Journal of Operational Research, 270, 2, 2018 DOI: 10.1016/j.ejor.2018.04.012