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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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  • Wheelock, David C.
  • Wilson, Paul W.

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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  • Wheelock, David C. & Wilson, Paul W., 2008. "Non-parametric, unconditional quantile estimation for efficiency analysis with an application to Federal Reserve check processing operations," Journal of Econometrics, Elsevier, vol. 145(1-2), pages 209-225, July.
  • Handle: RePEc:eee:econom:v:145:y:2008:i:1-2:p:209-225
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    2. Christopher Bruffaerts & Bram De Rock & Catherine Dehon, 2014. "Outlier Detection in Nonparametric Frontier Models," Working Papers ECARES ECARES 2014-12, ULB -- Universite Libre de Bruxelles.
    3. 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.
    4. Abdelaati Daouia & Léopold Simar & Paul W. Wilson, 2017. "Measuring firm performance using nonparametric quantile-type distances," Econometric Reviews, Taylor & Francis Journals, vol. 36(1-3), pages 156-181, March.
    5. Carol Alexander & Jose Maria Sarabia, 2010. "Endogenizing Model Risk to Quantile Estimates," ICMA Centre Discussion Papers in Finance icma-dp2010-07, Henley Business School, Reading University.
    6. Xie, Shangyu & Wan, Alan T.K. & Zhou, Yong, 2015. "Quantile regression methods with varying-coefficient models for censored data," Computational Statistics & Data Analysis, Elsevier, vol. 88(C), pages 154-172.
    7. Song, Junmo & Oh, Dong-hyun & Kang, Jiwon, 2017. "Robust estimation in stochastic frontier models," Computational Statistics & Data Analysis, Elsevier, vol. 105(C), pages 243-267.
    8. 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.
    9. 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.
    10. Daouia, Abdelaati & Florens, Jean-Pierre & Simar, Léopold, 2018. "Robustified expected maximum production frontiers," TSE Working Papers 17-890, Toulouse School of Economics (TSE).
    11. Léopold Simar & Paul W. Wilson, 2015. "Statistical Approaches for Non-parametric Frontier Models: A Guided Tour," International Statistical Review, International Statistical Institute, vol. 83(1), pages 77-110, April.
    12. Simar, Léopold & Vanhems, Anne, 2012. "Probabilistic characterization of directional distances and their robust versions," Journal of Econometrics, Elsevier, vol. 166(2), pages 342-354.
    13. Ghulam, Yaseen & Jaffry, Shabbar, 2015. "Efficiency and productivity of the cement industry: Pakistani experience of deregulation and privatisation," Omega, Elsevier, vol. 54(C), pages 101-115.
    14. Gregory McKee & Albert Kagan, 2016. "Determinants of recent structural change for small asset U.S. credit unions," Review of Quantitative Finance and Accounting, Springer, vol. 47(3), pages 775-795, October.
    15. Mamatzakis, E & Koutsomanoli-Filippaki, Anastasia & Pasiouras, Fotios, 2012. "A quantile regression approach to bank efficiency measurement," MPRA Paper 51879, University Library of Munich, Germany.
    16. Mei-Ying Huang & Jia-Ching Juo & Tsu-tan Fu, 2015. "Metafrontier cost Malmquist productivity index: an application to Taiwanese and Chinese commercial banks," Journal of Productivity Analysis, Springer, vol. 44(3), pages 321-335, December.
    17. Madalina STOICA & Anamaria ALDEA, 2016. "Efficiency Of Teaching And Research Activities In Romanian Universities: An Order – Alpha Partial Frontiers Approach," ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, Faculty of Economic Cybernetics, Statistics and Informatics, vol. 50(4), pages 169-186.
    18. Bernardino Benito & José Solana & María-Rocío Moreno, 2014. "Explaining efficiency in municipal services providers," Journal of Productivity Analysis, Springer, vol. 42(3), pages 225-239, December.
    19. 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.
    20. David C. Wheelock & Paul W. 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.
    21. Christopher Bruffaerts & Bram De Rock & Catherine Dehon, 2013. "The Research Efficiency of US Universities: a Nonparametric Frontier Modelling Approach," Working Papers ECARES ECARES 2013-31, ULB -- Universite Libre de Bruxelles.

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