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On Ranking and Selection from Independent Truncated Normal Distributions

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Author Info

  • 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

Related research

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

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References

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  1. Han Hong & Matthew Shum, 2001. "Econometric Models of Asymmetric Ascending Auctions," Economics Working Paper Archive 453, The Johns Hopkins University,Department of Economics.
  2. 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.
  3. Koop, G. & Osiewalski, J. & Steel, M. F. J., . "Bayesian efficiency analysis through individual effects: Hospital cost frontiers," CORE Discussion Papers RP -1245, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  4. Carmen Fernandez & Gary Koop & Mark F J Steel, 2004. "Multiple-output production with undesirable output: An application to nitrogen surplus in agriculture," ESE Discussion Papers 34, Edinburgh School of Economics, University of Edinburgh.
  5. William C. Horrace & Peter Schmidt, 2002. "Confidence Statements for Efficiency Estimates from Stochastic Frontier Models," Econometrics 0206006, EconWPA.
  6. Tsionas, E.G., 2001. "Stochastic Frontier Models with Random Coefficients," DEOS Working Papers 130, Athens University of Economics and Business.
  7. Kumbhakar, Subal C., 1990. "Production frontiers, panel data, and time-varying technical inefficiency," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 201-211.
  8. 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.
  9. 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.
  10. 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.
  11. James Tobin, 1956. "Estimation of Relationships for Limited Dependent Variables," Cowles Foundation Discussion Papers 3R, Cowles Foundation for Research in Economics, Yale University.
  12. 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.
  13. 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.
  14. 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.
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Citations

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Cited by:
  1. 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).
  2. repec:ags:mareec:7041 is not listed on IDEAS
  3. Ronald Felthoven & William Horrace & Kurt Schnier, 2009. "Estimating heterogeneous capacity and capacity utilization in a multi-species fishery," Journal of Productivity Analysis, Springer, vol. 32(3), pages 173-189, December.
  4. 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.
  5. Ali Genç, 2013. "Moments of truncated normal/independent distributions," Statistical Papers, Springer, vol. 54(3), pages 741-764, August.
  6. 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.
  7. 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.
  8. 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.

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