Spatial stochastic frontier model with stochastic weighting matrix

Ming-Yu Deng and Levent Kutlu ()
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Ming-Yu Deng: Anhui University of Finance & Economics, School of Statistics and Applied Mathematics
Levent Kutlu: University of Texas Rio Grande Valley, Department of Economics

Empirical Economics, 2025, vol. 69, issue 5, No 10, 2783-2815

Abstract: Abstract This paper develops a spatial autoregressive stochastic frontier model that allows the spatial weighting matrix to be stochastic. This approach captures spatial heterogeneity in the interactions among production units and quantifies random spatial dependencies arising from this variability. The model parameters are estimated using a simulated maximum likelihood approach. We propose a method to simulate spillover-corrected direct, indirect, and total efficiency estimates. Additionally, we conduct Monte Carlo simulations to evaluate the finite-sample performance of the proposed model. Finally, an empirical application to the efficiency of Spanish dairy farms is presented to demonstrate the practical implementation of our methodology.

Keywords: Spatial stochastic frontier; Stochastic weighting matrix; Spillover-corrected efficiency; Heterogeneity; Simulated MLE (search for similar items in EconPapers)
JEL-codes: C13 C23 C51 D24 R32 (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s00181-025-02815-z

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