Spatial stochastic frontier model with stochastic weighting matrix

Authors

• Ming-Yu Deng, Anhui University
• Levent Kutlu, The University of Texas Rio Grande ValleyFollow

Document Type

Article

Publication Date

9-7-2025

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.

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Recommended Citation

Deng, M.Y. and Kutlu, L., 2025. Spatial stochastic frontier model with stochastic weighting matrix: M.-Y. Deng, L. Kutlu. Empirical Economics, pp.1-33. https://doi.org/10.1007/s00181-025-02815-z

Publication Title

Empirical Economics

DOI

10.1007/s00181-025-02815-z