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Spatial Stochastic Frontier Models

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  • Lavado, Rouselle F.
  • Barrios, Erniel B.

Abstract

The stochastic frontier model with heterogeneous technical efficiency explained by exogenous variables is augmented with a sparse spatial autoregressive component for a cross-section data, and a spatial-temporal component for a panel data. An estimation procedure that takes advantage of the additivity of the model is proposed, computational advantages over simultaneous maximum likelihood estimation of all parameters is exhibited. The technical efficiency estimates are comparable to existing models and estimation procedures based on maximum likelihood methods. A spatial or spatial-temporal component can improve estimates of technical efficiency in a production frontier that is usually biased downwards.

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Bibliographic Info

Paper provided by Philippine Institute for Development Studies in its series Discussion Papers with number DP 2010-08.

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Length: 25
Date of creation: 2010
Date of revision:
Handle: RePEc:phd:dpaper:dp_2010-08

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Keywords: technical efficiency; stochastic frontier; Philippines; spatial externalities; spatial-temporal model; backfitting;

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  1. repec:wop:humbsf:1998-9 is not listed on IDEAS
  2. GIJBELS, Irène & MAMMEN, Enno & PARK, Byeong U. & SIMAR, Léopold, . "On estimation of monotone and concave frontier functions," CORE Discussion Papers RP -1392, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  3. Reifschneider, David & Stevenson, Rodney, 1991. "Systematic Departures from the Frontier: A Framework for the Analysis of Firm Inefficiency," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 32(3), pages 715-23, August.
  4. Gary Koop & M. F. J. Steel, 2004. "Bayesian Analysis of Stochastic Frontier Models," ESE Discussion Papers 19, Edinburgh School of Economics, University of Edinburgh.
  5. Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, vol. 20(2), pages 325-32.
  6. Kumbhakar, Subal C & Ghosh, Soumendra & McGuckin, J Thomas, 1991. "A Generalized Production Frontier Approach for Estimating Determinants of Inefficiency in U.S. Dairy Farms," Journal of Business & Economic Statistics, American Statistical Association, vol. 9(3), pages 279-86, July.
  7. Greene, William H., 1990. "A Gamma-distributed stochastic frontier model," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 141-163.
  8. Landagan, Ohmar Z. & Barrios, Erniel B., 2007. "An estimation procedure for a spatial-temporal model," Statistics & Probability Letters, Elsevier, vol. 77(4), pages 401-406, February.
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Cited by:
  1. Pavlyuk, Dmitry, 2010. "Regional Tourism Competition in the Baltic States: a Spatial Stochastic Frontier Approach," MPRA Paper 25052, University Library of Munich, Germany.
  2. Pavlyuk, Dmitry, 2010. "Spatial Competition and Cooperation Effects on European Airports' Efficiency," MPRA Paper 25050, University Library of Munich, Germany.
  3. Pavlyuk, Dmitry, 2011. "Efficiency of broadband internet adoption in European Union member states," MPRA Paper 34183, University Library of Munich, Germany.

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