Maximum Likelihood Estimator for Spatial Stochastic Frontier Models
AbstractThis 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.
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 43390.
Date of creation: 2012
Date of revision:
spatial stochastic frontier; maximum likelihood; efficiency; heterogeneity;
Find related papers by JEL classification:
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
- L93 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Air Transportation
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
- C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
This paper has been announced in the following NEP Reports:
- NEP-ALL-2013-01-07 (All new papers)
- NEP-ECM-2013-01-07 (Econometrics)
- NEP-EFF-2013-01-07 (Efficiency & Productivity)
- NEP-ORE-2013-01-07 (Operations Research)
- NEP-URE-2013-01-07 (Urban & Real Estate Economics)
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