Estimation of Stochastic Frontier Panel Data Models with Spatial Inefficiency
32 Pages Posted: 31 May 2019
Date Written: May 30, 2019
This paper proposes a stochastic frontier panel data model in which unit-specific inefficiencies are spatially correlated. In particular, this model has simultaneously three important features:
i) the total inefficiency of a productive unit depends on its own inefficiency and on the inefficiency of its neighbors;
ii) the spatially correlated and time varying inefficiency is disentangled from time invariant unobserved heterogeneity in a panel data model à la Greene (2005);
iii) systematic differences in inefficiency can be explained using exogenous determinants.
We propose to estimate both the "true" fixed- and random-effects variants of the model using a feasible simulated composite maximum likelihood approach. The finite sample behavior of the proposed estimators are investigated through a set of Monte Carlo experiments. Our simulation results suggest that the estimation approach is consistent, showing good finite sample properties especially in small samples.
Keywords: Stochastic frontiers model; Spatial inefficiency; Panel data, Fixed-effects model
JEL Classification: C13, C23, C15
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