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Nonparametric estimation of concave production technologies by entropic methods

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Author Info

  • Gad Allon

    (Northwestern University)

  • Michael Beenstock

    (Hebrew University)

  • Steven Hackman

    (Georgia Tech)

  • Ury Passy

    (Technion)

  • Alex Shapiro

    (Georgia Tech)

Abstract

An econometric methodology is developed for nonparametric estimation of concave production technologies. The methodology, bases on the priciple of maximum likelihood, uses entropic distance and concvex programming techniques to estimate production functions.

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File URL: http://128.118.178.162/eps/em/papers/0512/0512003.pdf
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Bibliographic Info

Paper provided by EconWPA in its series Econometrics with number 0512003.

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Length: 30 pages
Date of creation: 06 Dec 2005
Date of revision:
Handle: RePEc:wpa:wuwpem:0512003

Note: Type of Document - pdf; pages: 30. Nonparametric estimation subject to shape constraints
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Web page: http://128.118.178.162

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Keywords: convex programming; production functions; entropy;

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References

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  1. Afriat, Sidney N, 1972. "Efficiency Estimation of Production Function," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 13(3), pages 568-98, October.
  2. Matzkin, Rosa L., 1993. "Nonparametric identification and estimation of polychotomous choice models," Journal of Econometrics, Elsevier, vol. 58(1-2), pages 137-168, July.
  3. Varian, Hal R, 1982. "The Nonparametric Approach to Demand Analysis," Econometrica, Econometric Society, vol. 50(4), pages 945-73, July.
  4. Newey, Whitney K. & McFadden, Daniel, 1986. "Large sample estimation and hypothesis testing," Handbook of Econometrics, in: R. F. Engle & D. McFadden (ed.), Handbook of Econometrics, edition 1, volume 4, chapter 36, pages 2111-2245 Elsevier.
  5. Afriat, S N, 1971. "The Output Limit Function in General and Convex Programming and the Theory of Production," Econometrica, Econometric Society, vol. 39(2), pages 309-39, March.
  6. Donald W. K. Andrews & Moshe Buchinsky, 2000. "A Three-Step Method for Choosing the Number of Bootstrap Repetitions," Econometrica, Econometric Society, vol. 68(1), pages 23-52, January.
  7. Adonis Yatchew & Len Bos, 1997. "Nonparametric Least Squares Regression and Testing in Economic Models," Working Papers yatchew-99-01, University of Toronto, Department of Economics.
  8. Matzkin, Rosa L., 1986. "Restrictions of economic theory in nonparametric methods," Handbook of Econometrics, in: R. F. Engle & D. McFadden (ed.), Handbook of Econometrics, edition 1, volume 4, chapter 42, pages 2523-2558 Elsevier.
  9. Matzkin, Rosa L, 1991. "Semiparametric Estimation of Monotone and Concave Utility Functions for Polychotomous Choice Models," Econometrica, Econometric Society, vol. 59(5), pages 1315-27, September.
  10. repec:att:wimass:9217 is not listed on IDEAS
  11. Varian, Hal R, 1984. "The Nonparametric Approach to Production Analysis," Econometrica, Econometric Society, vol. 52(3), pages 579-97, May.
  12. Christensen, Laurits R & Jorgenson, Dale W & Lau, Lawrence J, 1973. "Transcendental Logarithmic Production Frontiers," The Review of Economics and Statistics, MIT Press, vol. 55(1), pages 28-45, February.
  13. Hanoch, Giora & Rothschild, Michael, 1972. "Testing the Assumptions of Production Theory: A Nonparametric Approach," Journal of Political Economy, University of Chicago Press, vol. 80(2), pages 256-75, March-Apr.
  14. Arnold Zellner & Hang Ryu, 1998. "Alternative functional forms for production, cost and returns to scale functions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 13(2), pages 101-127.
  15. Varian, Hal R., 1985. "Non-parametric analysis of optimizing behavior with measurement error," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 445-458.
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Cited by:
  1. Daniel J. Henderson, 2009. "A Non-parametric Examination of Capital-Skill Complementarity," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(4), pages 519-538, 08.

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