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An Information Theoretic Approach to Flexible Stochastic Frontier Models

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    Abstract

    Parametric stochastic frontier models have a long history in applied production eco- nomics, but the class of tractible parametric models is relatively small. Consequently, researchers have recently considered nonparametric alternatives such as kernel den- sity estimators, functional approximations, and data envelopment analysis (DEA). The purpose of this paper is to present an information theoretic approach to constructing more flexible classes of parametric stochastic frontier models. Further, the proposed class of models nests all of the commonly used parametric methods as special cases, and the proposed modeling framework provides a comprehensive means to conduct model specification tests. The modeling framework is also extended to develop information theoretic measures of mean technical efficiency and to construct a profile likelihood estimator of the stochastic frontier model.

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    Bibliographic Info

    Paper provided by Department of Economics, University of Missouri in its series Working Papers with number 0717.

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    Length: 26 pgs.
    Date of creation: 16 Jul 2007
    Date of revision:
    Handle: RePEc:umc:wpaper:0717

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    Keywords: KullbackLeibler information criterion; output distance function; profile likelihood; stochastic frontier; technical efficiency;

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    1. Stevenson, Rodney E., 1980. "Likelihood functions for generalized stochastic frontier estimation," Journal of Econometrics, Elsevier, vol. 13(1), pages 57-66, May.
    2. Imbens, Guido W, 1997. "One-Step Estimators for Over-Identified Generalized Method of Moments Models," Review of Economic Studies, Wiley Blackwell, vol. 64(3), pages 359-83, July.
    3. Zellner, A & Revankar, N S, 1969. "Generalized Production Functions," Review of Economic Studies, Wiley Blackwell, vol. 36(106), pages 241-50, April.
    4. Lee, Lung-Fei & Tyler, William G., 1978. "The stochastic frontier production function and average efficiency : An empirical analysis," Journal of Econometrics, Elsevier, vol. 7(3), pages 385-389, April.
    5. Robin Sickles & David Good & Lullit Getachew, 2002. "Specification of Distance Functions Using Semi- and Nonparametric Methods with an Application to the Dynamic Performance of Eastern and Western European Air Carriers," Journal of Productivity Analysis, Springer, vol. 17(1), pages 133-155, January.
    6. Douglas J. Miller, 2002. "Entropy-Based Methods of Modeling Stochastic Production Efficiency," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 84(5), pages 1264-1270.
    7. D. Ormoneit & H. White, 1999. "An efficient algorithm to compute maximum entropy densities," Econometric Reviews, Taylor & Francis Journals, vol. 18(2), pages 127-140.
    8. Schmidt, Peter & Lin, Tsai-Fen, 1984. "Simple tests of alternative specifications in stochastic frontier models," Journal of Econometrics, Elsevier, vol. 24(3), pages 349-361, March.
    9. Yuichi Kitamura & Michael Stutzer, 1997. "An Information-Theoretic Alternative to Generalized Method of Moments Estimation," Econometrica, Econometric Society, vol. 65(4), pages 861-874, July.
    10. Sengupta, Jati K., 1992. "The maximum entropy approach in production frontier estimation," Mathematical Social Sciences, Elsevier, vol. 25(1), pages 41-57, December.
    11. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-44, June.
    12. Ryu, Hang K., 1993. "Maximum entropy estimation of density and regression functions," Journal of Econometrics, Elsevier, vol. 56(3), pages 397-440, April.
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    Cited by:
    1. Lakshmi Balasubramanyan & Spiro Stefanou & Jeffrey Stokes, 2012. "An entropy approach to size and variance heterogeneity in U.S. commercial banks," Journal of Economics and Finance, Springer, vol. 36(3), pages 728-749, July.

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