A spatial stochastic frontier model introducing inefficiency spillovers

2023/02/24 by Federica Galli
Decision Sciences · Economics, Econometrics and Finance · #Efficiency Analysis Using DEA #Regional Economics and Spatial Analysis #Spatial and Panel Data Analysis

paper · pdf · doi:10.1093/jrsssc/qlad012

crossref issued 2023/02/24 · crossref published 2023/02/24 · crossref published-online 2023/02/24 · openalex publication_date 2023/02/24 · crossref created 2023/02/24 · crossref published-print 2023/05/12 · crossref deposited 2023/05/12 · openalex created_date 2025/10/10 · crossref indexed 2026/07/28 · openalex updated_date 2026/07/30

Abstract

Abstract This paper develops a spatial Durbin stochastic frontier model for panel data introducing spillover effects in the determinants of technical efficiency (SDF-STE). The model nests several existing spatial and non-spatial stochastic frontier specifications and is estimated using maximum-likelihood techniques. Estimates are shown to be unbiased even for small sample sizes and for alternative specifications of the spatial weight matrix implementing different Monte Carlo simulations. Finally, an application to the Italian accommodation sector is provided. Empirical findings suggest the relevance of the SDF-STE model in capturing labour productivity and knowledge spillover effects.

Citations

• Formulation and estimation of stochastic frontier production function models
• Frontier production functions, technical efficiency and panel data: With application to paddy farmers in India
• Identification of Endogenous Social Effects: The Reflection Problem
• A Generalized Moments Estimator for the Autoregressive Parameter in a Spatial Model
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• Cost Reduction, Competition, and Industry Performance
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