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Nonparametric quantile frontier estimation under shape restriction

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  • Wang, Yongqiao
  • Wang, Shouyang
  • Dang, Chuangyin
  • Ge, Wenxiu
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    Abstract

    This paper proposes a shape-restricted nonparametric quantile regression to estimate the τ-frontier, which acts as a benchmark for whether a decision making unit achieves top τ efficiency. This method adopts a two-step strategy: first, identifying fitted values that minimize an asymmetric absolute loss under the nondecreasing and concave shape restriction; second, constructing a nondecreasing and concave estimator that links these fitted values. This method makes no assumption on the error distribution and the functional form. Experimental results on some artificial data sets clearly demonstrate its superiority over the classical linear quantile regression. We also discuss how to enforce constraints to avoid quantile crossings between multiple estimated frontiers with different values of τ. Finally this paper shows that this method can be applied to estimate the production function when one has some prior knowledge about the error term.

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    Bibliographic Info

    Article provided by Elsevier in its journal European Journal of Operational Research.

    Volume (Year): 232 (2014)
    Issue (Month): 3 ()
    Pages: 671-678

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    Handle: RePEc:eee:ejores:v:232:y:2014:i:3:p:671-678

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    Web page: http://www.elsevier.com/locate/eor

    Related research

    Keywords: Productivity and competitiveness; Production frontier; Quantile regression; Shape restriction; Concavity; Non-crossing;

    References

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    1. Somers, Mark & Whittaker, Joe, 2007. "Quantile regression for modelling distributions of profit and loss," European Journal of Operational Research, Elsevier, vol. 183(3), pages 1477-1487, December.
    2. Martins-Filho, Carlos & Yao, Feng, 2008. "A smooth nonparametric conditional quantile frontier estimator," Journal of Econometrics, Elsevier, vol. 143(2), pages 317-333, April.
    3. Lee, Chia-Yen & Johnson, Andrew L. & Moreno-Centeno, Erick & Kuosmanen, Timo, 2013. "A more efficient algorithm for Convex Nonparametric Least Squares," European Journal of Operational Research, Elsevier, vol. 227(2), pages 391-400.
    4. Taylor, James W., 2007. "Forecasting daily supermarket sales using exponentially weighted quantile regression," European Journal of Operational Research, Elsevier, vol. 178(1), pages 154-167, April.
    5. 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.
    6. Timo Kuosmanen & Mika Kortelainen, 2012. "Stochastic non-smooth envelopment of data: semi-parametric frontier estimation subject to shape constraints," Journal of Productivity Analysis, Springer, vol. 38(1), pages 11-28, August.
    7. Timo Kuosmanen, 2008. "Representation theorem for convex nonparametric least squares," Econometrics Journal, Royal Economic Society, vol. 11(2), pages 308-325, 07.
    8. 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.
    9. Daouia, Abdelaati & Simar, Leopold, 2007. "Nonparametric efficiency analysis: A multivariate conditional quantile approach," Journal of Econometrics, Elsevier, vol. 140(2), pages 375-400, October.
    10. Howard D. Bondell & Brian J. Reich & Huixia Wang, 2010. "Noncrossing quantile regression curve estimation," Biometrika, Biometrika Trust, vol. 97(4), pages 825-838.
    11. Behr, Andreas, 2010. "Quantile regression for robust bank efficiency score estimation," European Journal of Operational Research, Elsevier, vol. 200(2), pages 568-581, January.
    12. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    13. 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.
    14. Cristina Bernini & Marzia Freo & Attilio Gardini, 2004. "Quantile estimation of frontier production function," Empirical Economics, Springer, vol. 29(2), pages 373-381, 05.
    15. Toriello, Alejandro & Vielma, Juan Pablo, 2012. "Fitting piecewise linear continuous functions," European Journal of Operational Research, Elsevier, vol. 219(1), pages 86-95.
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