Spatial stochastic frontier model with endogenous weighting matrix

Levent Kutlu ()
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Levent Kutlu: University of Texas Rio Grande Valley

Empirical Economics, 2022, vol. 63, issue 4, No 9, 1947-1968

Abstract: 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.

Keywords: Endogeneity; Endogenous spatial weight; Spatial autoregressive model; Stochastic frontier; US banks (search for similar items in EconPapers)
JEL-codes: C13 C21 C36 D24 (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s00181-021-02189-y

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