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    Agglomeration effects and spatial spillovers in efficiency analysis: a distribution-free methodology
    (Routledge Journals, Taylor & Francis Ltd, 2019) Kutlu, Levent; Nair-Reichert, Usha
    Technical efficiency estimates using standard stochastic frontier models do not include spillover effects, although the existence of such spillovers is well documented in the productivity literature. This paper proposes a regression-based, distribution-free estimation method applicable to both time-varying efficiency spatial stochastic frontier and fixed effects spatial autoregressive models, which is relatively easy to estimate. The empirical results from the Indian chemical industry illustrate that ignoring spatial dependence may seriously distort estimates for efficiency rankings. The average overall spillover effect on a firm's efficiency is 7.20 percentage points, or an average positive spillover effect of US$4.9 million in sales revenue.
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    Heterogeneity and endogeneity in panel stochastic frontier models
    (Elsevier, 2019) Kutlu, Levent; Tran K.C.
    This chapter provides a recent development in panel stochastic frontier models that allows for heterogeneity, endogeneity or both. Specifically, consistent estimation of the models’ parameters as well as observation-specific technical inefficiency is discussed. © 2019 Elsevier Inc. All rights reserved.
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    A time-varying true individual effects model with endogenous regressors
    (Elsevier Science Sa, 2019) Kutlu, Levent; Tran, Kien C.; Tsionas, Mike G.
    We propose a fairly general individual effects stochastic frontier model, which allows both heterogeneity and inefficiency to change over time. Moreover, our model handles the endogeneity problems if either at least one of the regressors or one-sided error term is correlated with the two-sided error term. Our Monte Carlo experiments show that our estimator performs well. We employed our methodology to the US banking data and found a negative relationship between return on revenue and cost efficiency. Estimators ignoring time-varying heterogeneity or endogeneity did not perform well and gave very different estimates compared to our estimator. (C) 2019 Elsevier B.V. All rights reserved.