scholarly journals Distinguishing Between Spatial Heterogeneity and Inefficiency: Spatial Stochastic Frontier Analysis of European Airports

2013 ◽  
Vol 14 (1) ◽  
pp. 29-38 ◽  
Author(s):  
Pavlyuk Dmitry
Keyword(s):  
Spatial Heterogeneity ◽  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Model Specification ◽  
Frontier Analysis ◽  
Classical Models ◽  
Spatial Autoregressive ◽  
Biased Estimates ◽  
General Specification ◽  
Performance Estimates

Abstract A problem of distinguishing between frontier heterogeneity and inefficiency is widely acknowledged in benchmarking. A special type of heterogeneity, based on the spatial structure, can significantly affect performance estimates in the airport industry. In this research we presented a general specification of the spatial stochastic frontier model, which includes spatial lags, spatial autoregressive disturbances and spatial autoregressive inefficiencies. Maximum likelihood estimator has been derived for this model. Applying the suggested model specification to the European airports dataset, we discovered presence of significant spatial heterogeneity, which leads to biased estimates of efficiency, received using classical models.

scholarly journals Modeling Spatial Interaction in Stochastic Frontier Analysis

2021 ◽  
Vol 5 ◽  
Author(s):  
Francisco J. Areal ◽  
Valerien O. Pede
Keyword(s):  
Spatial Heterogeneity ◽  
Stochastic Frontier Analysis ◽  
Unobserved Heterogeneity ◽  
Spatial Interaction ◽  
Stochastic Frontier ◽  
The Philippines ◽  
Rice Farming ◽  
Analysis Framework ◽  
Frontier Analysis ◽  
Unobserved Effects

We compare farm level efficiency rankings derived from non-spatial and a variety of spatial model specifications that account for unobserved heterogeneity in both the production and the efficiency sides of the stochastic frontier model in an empirical application on rice farming in the Philippines. We show how not accounting for unobserved spatial heterogeneity affects efficiency estimates and farm efficiency rankings. When not accounting for unobserved spatial heterogeneity efficiency, models show farms to be relatively more inefficient than they actually are (i.e., once unobserved spatial heterogeneity is incorporated in the models). More importantly from a policy perspective, the rankings of the farms in terms of efficiency are altered once unobserved spatial heterogeneity is incorporated in efficiency models. We recommend the use of unobserved effects in both production and efficiency within the stochastic frontier analysis framework to avoid making any misleading recommendations to farmers and policymakers.

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