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Abstract

This research is devoted to analysis of efficiency estimation in presence of spatial relationships and spatial heterogeneity indata. We presented a general specification of the spatial stochastic frontier model, which includes spatial lags, spatial autoregressivedisturbances and spatial autoregressive inefficiencies. Maximum likelihood estimators are derived for two special cases ofthe spatial stochastic frontier. Small-sample properties of these estimators and comparison with a standard non-spatial estimatorwere implemented using a set of Monte Carlo experiments. Finally, we tested our estimators on a real-world data set of Europeanairports and discovered significant spatial components in data.



Item Type: MPRA Paper -

Original Title: Maximum Likelihood Estimator for Spatial Stochastic Frontier Models-

Language: English-

Keywords: spatial stochastic frontier, maximum likelihood, efficiency, heterogeneity-

Subjects: C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C51 - Model Construction and EstimationL - Industrial Organization > L9 - Industry Studies: Transportation and Utilities > L93 - Air TransportationC - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C15 - Statistical Simulation Methods: GeneralC - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables > C31 - Cross-Sectional Models ; Spatial Models ; Treatment Effect Models ; Quantile Regressions ; Social Interaction Models-





Author: Pavlyuk, Dmitry

Source: https://mpra.ub.uni-muenchen.de/43390/







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