Maximum Likelihood Estimator for Spatial Stochastic Frontier Models
This research is devoted to analysis of efficiency estimation in presence of spatial relationships and spatial heterogeneity in data. We presented a general specification of the spatial stochastic frontier model, which includes spatial lags, spatial autoregressive disturbances and spatial autoregressive inefficiencies. Maximum likelihood estimators are derived for two special cases of the spatial stochastic frontier. Small-sample properties of these estimators and comparison with a standard non-spatial estimator were implemented using a set of Monte Carlo experiments. Finally, we tested our estimators on a real-world data set of European airports and discovered significant spatial components in data.
|Date of creation:||2012|
|Date of revision:|
|Publication status:||Published in Proceedings of the 12th International Conference “Reliability and Statistics in Transportation and Communication” (2012): pp. 11-19|
|Contact details of provider:|| Postal: Ludwigstraße 33, D-80539 Munich, Germany|
Web page: https://mpra.ub.uni-muenchen.de
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Electronic Working Papers
97-002, University of Maryland, Department of Economics, revised Aug 1997.
- Kelejian, Harry H & Prucha, Ingmar R, 1998. "A Generalized Spatial Two-Stage Least Squares Procedure for Estimating a Spatial Autoregressive Model with Autoregressive Disturbances," The Journal of Real Estate Finance and Economics, Springer, vol. 17(1), pages 99-121, July.
- Viliam Druska & William C. Horrace, 2002.
"Generalized Moments Estimation for Spatial Panel Data: Indonesian Rice Farming,"
0206004, EconWPA, revised 11 May 2003.
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- Pavlyuk, Dmitry, 2012. "Airport Benchmarking and Spatial Competition: a Critical Review," MPRA Paper 43391, University Library of Munich, Germany.
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