Quantile regression for robust bank efficiency score estimation
We discuss quantile regression techniques as a robust and easy to implement alternative for estimating Farell technical efficiency scores. The quantile regression approach estimates the production process for benchmark banks located at top conditional quantiles. Monte Carlo simulations reveal that even when generating data according to the assumptions of the stochastic frontier model (SFA), efficiency estimates obtained from quantile regressions resemble SFA-efficiency estimates. We apply the SFA and the quantile regression approach to German bank data for three banking groups, commercial banks, savings banks and cooperative banks to estimate efficiency scores based on a simple value added function and a multiple-input-multiple-output cost function. The results reveal that the efficient (benchmark) banks have production and cost elasticities which differ considerably from elasticities obtained from conditional mean functions and stochastic frontier functions.
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- Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
- Aragon, Y. & Daouia, A. & Thomas-Agnan, C., 2005. "Nonparametric Frontier Estimation: A Conditional Quantile-Based Approach," Econometric Theory, Cambridge University Press, vol. 21(02), pages 358-389, April.
- Berger, Allen N. & Humphrey, David B., 1991.
"The dominance of inefficiencies over scale and product mix economies in banking,"
Journal of Monetary Economics,
Elsevier, vol. 28(1), pages 117-148, August.
- Allen N. Berger & David B. Humphrey, 1990. "The dominance of inefficiencies over scale and product mix economies in banking," Finance and Economics Discussion Series 107, Board of Governors of the Federal Reserve System (U.S.).
- Koetter, Michael & Karmann, Alexander & Fiorentino, Elisabetta, 2006. "The cost efficiency of German banks: a comparison of SFA and DEA," Discussion Paper Series 2: Banking and Financial Studies 2006,10, Deutsche Bundesbank, Research Centre.
- Caudill, Steven B. & Ford, Jon M., 1993. "Biases in frontier estimation due to heteroscedasticity," Economics Letters, Elsevier, vol. 41(1), pages 17-20.
- Willam Greene, 2005. "Fixed and Random Effects in Stochastic Frontier Models," Journal of Productivity Analysis, Springer, vol. 23(1), pages 7-32, January.
- William Greene, 2002. "Fixed and Random Effects in Stochastic Frontier Models," Working Papers 02-16, New York University, Leonard N. Stern School of Business, Department of Economics.
- Moshe Buchinsky, 1998. "Recent Advances in Quantile Regression Models: A Practical Guideline for Empirical Research," Journal of Human Resources, University of Wisconsin Press, vol. 33(1), pages 88-126.
- O. B. Olesen & N. C. Petersen, 1995. "Chance Constrained Efficiency Evaluation," Management Science, INFORMS, vol. 41(3), pages 442-457, March.
- Koenker,Roger, 2005. "Quantile Regression," Cambridge Books, Cambridge University Press, number 9780521845731, December.
- Roger Koenker & Kevin F. Hallock, 2001. "Quantile Regression," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 143-156, Fall.
- Koenker,Roger, 2005. "Quantile Regression," Cambridge Books, Cambridge University Press, number 9780521608275, December.
- Gary Ferrier & Joseph Hirschberg, 1997. "Bootstrapping Confidence Intervals for Linear Programming Efficiency Scores: With an Illustration Using Italian Banking Data," Journal of Productivity Analysis, Springer, vol. 8(1), pages 19-33, March.
- Elena Beccalli & Barbara Casu & Claudia Girardone, 2006. "Efficiency and Stock Performance in European Banking," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 33(1-2), pages 245-262.
- Laurent Weill, 2004. "Measuring Cost Efficiency in European Banking: A Comparison of Frontier Techniques," Journal of Productivity Analysis, Springer, vol. 21(2), pages 133-152, March.
- Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
- Daouia, Abdelaati & Simar, Leopold, 2007. "Nonparametric efficiency analysis: A multivariate conditional quantile approach," Journal of Econometrics, Elsevier, vol. 140(2), pages 375-400, October.
- Cristina Bernini & Marzia Freo & Attilio Gardini, 2004. "Quantile estimation of frontier production function," Empirical Economics, Springer, vol. 29(2), pages 373-381, May.
- Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
- Sealey, Calvin W, Jr & Lindley, James T, 1977. "Inputs, Outputs, and a Theory of Production and Cost at Depository Financial Institutions," Journal of Finance, American Finance Association, vol. 32(4), pages 1251-1266, September.
- Allen N. Berger & David B. Humphrey, 1992. "Megamergers in banking and the use of cost efficiency as an antitrust defense," Finance and Economics Discussion Series 203, Board of Governors of the Federal Reserve System (U.S.). Full references (including those not matched with items on IDEAS)