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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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References

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  3. 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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  8. Léopold Simar, 2003. "Detecting Outliers in Frontier Models: A Simple Approach," Journal of Productivity Analysis, Springer, vol. 20(3), pages 391-424, November.
  9. Ludwig Kuntz & Stefan Scholtes, 2000. "Measuring the Robustness of Empirical Efficiency Valuations," Management Science, INFORMS, vol. 46(6), pages 807-823, June.
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  21. R. Alton Gilbert & David C. Wheelock & Paul W. Wilson, 2002. "New evidence on the Fed's productivity in providing payments services," Working Papers 2002-020, Federal Reserve Bank of St. Louis.
  22. Paul W. Bauer & Gary D. Ferrier, 1996. "Scale economies, cost efficiencies, and technological change in Federal Reserve payments processing," Proceedings, Board of Governors of the Federal Reserve System (U.S.), pages 1004-1044.
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Citations

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Cited by:
  1. 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.
  2. Christopher Bruffaerts & Bram De Rock & Catherine Dehon, 2013. "The robustness of the hyperbolic efficiency estimator," ULB Institutional Repository 2013/131706, ULB -- Universite Libre de Bruxelles.
  3. 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.
  4. Simar, Léopold & Vanhems, Anne, 2010. "Probabilistic Characterization of Directional Distances and their Robust Versions," TSE Working Papers 10-195, Toulouse School of Economics (TSE).
  5. Calogero Guccio & Giacomo Pignataro & Ilde Rizzo, 2014. "Evaluating the efficiency of public procurement contracts for cultural heritage conservation works in Italy," Journal of Cultural Economics, Springer, vol. 38(1), pages 43-70, February.
  6. 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.
  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.
  8. 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.

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