Estimation of Stochastic Frontier Panel Data Models with Spatial Inefficiency

Federico Belotti, Giuseppe Ilardi and Andrea Piano Mortari

No 459, CEIS Research Paper from Tor Vergata University, CEIS

Abstract: 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 (search for similar items in EconPapers)
JEL-codes: C13 C15 C23 (search for similar items in EconPapers)
Pages: 32 pages
Date: 2019-05-30, Revised 2019-05-30
New Economics Papers: this item is included in nep-ecm, nep-eff and nep-ore
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Citations: View citations in EconPapers (2)

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