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Non-parametric, unconditional quantile estimation for efficiency analysis with an application to Federal Reserve check processing operations

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  • David C. Wheelock
  • Paul Wilson

Abstract

This paper examines the technical efficiency of U.S. Federal Reserve check processing offices over 1980–2003. We extend results from Park et al. (2000) and Daouia and Simar (2007) to develop an unconditional, hyperbolic, a-quantile estimator of efficiency. Our new estimator is fully non-parametric and robust with respect to outliers; when used to estimate distance to quantiles lying close to the full frontier, it is strongly consistent and converges at rate root-n, thus avoiding the curse of dimensionality that plagues data envelopment analysis (DEA) estimators. Our methods could be used by policymakers to compare inefficiency levels across offices or by managers of individual offices to identify peer offices.

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Bibliographic Info

Paper provided by Federal Reserve Bank of St. Louis in its series Working Papers with number 2005-027.

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Date of creation: 2007
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Handle: RePEc:fip:fedlwp:2005-027

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Keywords: Check collection systems ; Payment systems;

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  1. Wilson, Paul W, 1993. "Detecting Outliers in Deterministic Nonparametric Frontier Models with Multiple Outputs," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(3), pages 319-23, July.
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  3. David C. Wheelock & Paul W. Wilson, 1997. "New evidence on returns to scale and product mix among U.S. commercial banks," Working Papers 1997-003, Federal Reserve Bank of St. Louis.
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  5. Léopold Simar & Paul W. Wilson, 1998. "Sensitivity Analysis of Efficiency Scores: How to Bootstrap in Nonparametric Frontier Models," Management Science, INFORMS, vol. 44(1), pages 49-61, January.
  6. Allen N. Berger & David B. Humphrey, 1997. "Efficiency of financial institutions: international survey and directions for future research," Finance and Economics Discussion Series 1997-11, Board of Governors of the Federal Reserve System (U.S.).
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  10. David C. Wheelock & Paul Wilson, 2004. "Trends in the efficiency of Federal Reserve check processing operations," Review, Federal Reserve Bank of St. Louis, issue Sep, pages 7-20.
  11. Park, B.U. & Simar, L. & Weiner, Ch., 2000. "The Fdh Estimator For Productivity Efficiency Scores," Econometric Theory, Cambridge University Press, vol. 16(06), pages 855-877, December.
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  13. Wheelock, David C & Wilson, Paul W, 1995. "Explaining Bank Failures: Deposit Insurance, Regulation, and Efficiency," The Review of Economics and Statistics, MIT Press, vol. 77(4), pages 689-700, November.
  14. Bauer, Paul W & Ferrier, Gary D, 1996. "Scale Economies, Cost Efficiencies, and Technological Change in Federal Reserve Payments Processing," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 28(4), pages 1004-39, November.
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  19. Léopold Simar & Paul Wilson, 2000. "Statistical Inference in Nonparametric Frontier Models: The State of the Art," Journal of Productivity Analysis, Springer, vol. 13(1), pages 49-78, January.
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  21. Gilbert, R. Alton & Wheelock, David C. & Wilson, Paul W., 2004. "New evidence on the Fed's productivity in providing payments services," Journal of Banking & Finance, Elsevier, vol. 28(9), pages 2175-2190, September.
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Citations

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Cited by:
  1. Léopold Simar & Paul Wilson, 2011. "Inference by the m out of n bootstrap in nonparametric frontier models," Journal of Productivity Analysis, Springer, vol. 36(1), pages 33-53, August.
  2. Wheelock, David C. & Wilson, Paul W., 2013. "The evolution of cost-productivity and efficiency among US credit unions," Journal of Banking & Finance, Elsevier, vol. 37(1), pages 75-88.
  3. Simar, Léopold & Vanhems, Anne, 2010. "Probabilistic Characterization of Directional Distances and their Robust Versions," TSE Working Papers 10-195, Toulouse School of Economics (TSE).
  4. Simar, Léopold & Vanhems, Anne & Wilson, Paul W., 2012. "Statistical inference for DEA estimators of directional distances," European Journal of Operational Research, Elsevier, vol. 220(3), pages 853-864.
  5. Bruffaerts, C. & De Rock, B. & Dehon, C., 2013. "The robustness of the hyperbolic efficiency estimator," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 349-363.
  6. David C. Wheelock & Paul Wilson, 2009. "Robust, dynamic nonparametric benchmarking: the evolution of cost-productivity and efficiency among U.S. credit unions," Working Papers 2009-008, Federal Reserve Bank of St. Louis.
  7. Mamatzakis, E & Koutsomanoli-Filippaki, Anastasia & Pasiouras, Fotios, 2012. "A quantile regression approach to bank efficiency measurement," MPRA Paper 51879, University Library of Munich, Germany.

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