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On Ranking and Selection from Independent Truncated Normal Distributions

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  • William C. Horrace

    (Syracuse University)

Abstract

This paper develops probability statements and ranking and selection rules for independent truncated normal populations. An application to a broad class of parametric stochastic frontier models is considered, where interest centers on making probability statements concerning unobserved firm-level technical ineffciency. In particular, probabilistic decision rules allow subsets of firms to be deemed relatively effcient or ineffcient at pre-specified probabilities. An empirical example is provided.

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File URL: http://128.118.178.162/eps/em/papers/0306/0306009.pdf
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Bibliographic Info

Paper provided by EconWPA in its series Econometrics with number 0306009.

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Length: 31 pages
Date of creation: 27 Jun 2003
Date of revision:
Handle: RePEc:wpa:wuwpem:0306009

Note: Type of Document - Acrobat PDF; prepared on IBM PC ; to print on HP; pages: 31 ; figures: included
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Web page: http://128.118.178.162

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Keywords: Ranking and Selection; Truncated Normal; Stochastic Frontier;

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References

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  1. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
  2. Efthymios G. Tsionas, 2002. "Stochastic frontier models with random coefficients," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(2), pages 127-147.
  3. Battese, George E. & Coelli, Tim J., 1988. "Prediction of firm-level technical efficiencies with a generalized frontier production function and panel data," Journal of Econometrics, Elsevier, vol. 38(3), pages 387-399, July.
  4. Koop, Gary & Osiewalski, Jacek & Steel, Mark F. J., 1997. "Bayesian efficiency analysis through individual effects: Hospital cost frontiers," Journal of Econometrics, Elsevier, vol. 76(1-2), pages 77-105.
  5. Hong, Han & Shum, Matthew, 2003. "Econometric models of asymmetric ascending auctions," Journal of Econometrics, Elsevier, vol. 112(2), pages 327-358, February.
  6. Amemiya, Takeshi, 1974. "Multivariate Regression and Simultaneous Equation Models when the Dependent Variables Are Truncated Normal," Econometrica, Econometric Society, vol. 42(6), pages 999-1012, November.
  7. Carmen Fernandez & Gary Koop & Mark F.J. Steel, 2002. "Multiple-Output Production With Undesirable Outputs: An Application to Nitrogen Surplus in Agriculture," Econometrics 0201001, EconWPA, revised 06 Jan 2002.
  8. Kumbhakar, Subal C., 1990. "Production frontiers, panel data, and time-varying technical inefficiency," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 201-211.
  9. Greene, William, 2005. "Reconsidering heterogeneity in panel data estimators of the stochastic frontier model," Journal of Econometrics, Elsevier, vol. 126(2), pages 269-303, June.
  10. James Tobin, 1956. "Estimation of Relationships for Limited Dependent Variables," Cowles Foundation Discussion Papers 3R, Cowles Foundation for Research in Economics, Yale University.
  11. James J. Heckman, 1976. "The Common Structure of Statistical Models of Truncation, Sample Selection and Limited Dependent Variables and a Simple Estimator for Such Models," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 5, number 4, pages 475-492 National Bureau of Economic Research, Inc.
  12. 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.
  13. William C. Horrace & Peter Schmidt, 2002. "Confidence Statements for Efficiency Estimates from Stochastic Frontier Models," Econometrics 0206006, EconWPA.
  14. William C. Horrace & Peter Schmidt, 2000. "Multiple comparisons with the best, with economic applications," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(1), pages 1-26.
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Citations

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Cited by:
  1. William C. Horrace & Christopher F. Parmeter, 2014. "A Laplace Stochastic Frontier Model," Center for Policy Research Working Papers 166, Center for Policy Research, Maxwell School, Syracuse University.
  2. Ali Genç, 2013. "Moments of truncated normal/independent distributions," Statistical Papers, Springer, vol. 54(3), pages 741-764, August.
  3. Alfonso Flores-Lagunes & William C. Horrace & Kurt E. Schnier, 2006. "Identifying Technically Efficient Fishing Vessels: A Non-Empty, Minimal Subset Approach," Center for Policy Research Working Papers 78, Center for Policy Research, Maxwell School, Syracuse University.
  4. Phill Wheat & William Greene & Andrew Smith, 2014. "Understanding prediction intervals for firm specific inefficiency scores from parametric stochastic frontier models," Journal of Productivity Analysis, Springer, vol. 42(1), pages 55-65, August.
  5. Felthoven, Ronald G. & Horrace, William C. & Schnier, Kurt E., 2006. "Estimating Heterogeneous Primal Capacity and Capacity Utilization Measures in a Multi-Species Fishery," 2006 Annual meeting, July 23-26, Long Beach, CA 21276, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
  6. Ronald G. Felthovan & William C. Horrace & Kurt E. Schnier, 2006. "Estimating Heterogeneous Capacity and Capacity Utilization in a Multi-Species Fishery," Center for Policy Research Working Papers 86, Center for Policy Research, Maxwell School, Syracuse University.
  7. Jason J. Sharples & John C. V. Pezzey, 2005. "Expectations of linear functions with respect to truncazted multinormal distributions, with applications for uncertainty analysis in environmental modelling," Economics and Environment Network Working Papers 0503, Australian National University, Economics and Environment Network.
  8. William Horrace & Seth Richards-Shubik, 2013. "Expected Efficiency Ranks From Parametric Stochastic Fronteir Models," Center for Policy Research Working Papers 153, Center for Policy Research, Maxwell School, Syracuse University.
  9. William Horrace & Seth Richards-Shubik, 2012. "A Monte Carlo study of ranked efficiency estimates from frontier models," Journal of Productivity Analysis, Springer, vol. 38(2), pages 155-165, October.
  10. William C. Horrace & Seth O. Richards, 2007. "A Monte Carlo Study of Efficiency Estimates from Frontier Models," Center for Policy Research Working Papers 97, Center for Policy Research, Maxwell School, Syracuse University.

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