Spatial stochastic frontier model with endogenous weighting matrix

Authors

Levent Kutlu, The University of Texas Rio Grande ValleyFollow

Document Type

Article

Publication Date

10-2022

Abstract

We propose a spatial autoregressive stochastic frontier model, which allows for endogenous weighting matrix (i.e., the spatial weighting matrix is not independent of the two-sided error term). The parameters of the model are estimated via the maximum likelihood estimation method. Monte Carlo simulations illustrate that our model performs well in finite samples. As an example, we employed our methodology to the US banks and found evidence for endogenous spillovers. The empirical example suggested potential biases in the parameter estimates when endogeneity of spillovers is ignored.

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Recommended Citation

Kutlu, L., 2022. Spatial stochastic frontier model with endogenous weighting matrix. Empirical Economics, 63(4), pp.1947-1968. https://doi.org/10.1007/s00181-021-02189-y

Publication Title

Empirical Economics

DOI

10.1007/s00181-021-02189-y