Modeling Spatial Interaction in Stochastic Frontier Analysis

Abstract

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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.

Keywords

• spatial dependency
• Bayesian approach
• technical efficiency
• rice farming
• unobserved heterogeneity