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Social and Behavioral Sciences Commons

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Economics

University of Texas Rio Grande Valley

Stochastic frontier

Publication Year

Articles 1 - 5 of 5

Full-Text Articles in Social and Behavioral Sciences

A Time-Varying True Individual Effects Model With Endogenous Regressors, Levent Kutlu, Kien C. Tran, Mike G. Tsionas Aug 2019

A Time-Varying True Individual Effects Model With Endogenous Regressors, Levent Kutlu, Kien C. Tran, Mike G. Tsionas

Economics and Finance Faculty Publications and Presentations

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.


Estimating Efficiency In A Spatial Autoregressive Stochastic Frontier Model, Levent Kutlu Feb 2018

Estimating Efficiency In A Spatial Autoregressive Stochastic Frontier Model, Levent Kutlu

Economics and Finance Faculty Publications and Presentations

The spatial autoregressive stochastic frontier model of Glass et al.(2016) is based on distributional assumptions on two-sided and one-sided error terms. After estimating the model parameters, the efficiency estimates need to be corrected due to the presence of spatial autoregressive term in their model. Glass et al.(2016) estimate the corrected efficiencies by employing ideas from a distribution-free method on the efficiency estimation, which may be sensitive to outliers. We propose an alternative way to correct efficiency estimates that is in line with the distribution-based methods.


A Distribution-Free Stochastic Frontier Model With Endogenous Regressors, Levent Kutlu Feb 2018

A Distribution-Free Stochastic Frontier Model With Endogenous Regressors, Levent Kutlu

Economics and Finance Faculty Publications and Presentations

We provide a guideline for estimating a distribution-free panel data stochastic frontier model in the presence of endogenous variables. In particular, we consider variations of the within estimator of Cornwell et al. (1990) to allow endogenous regressors.


Endogeneity In Panel Stochastic Frontier Models: An Application To The Japanese Cotton Spinning Industry, Mustafa U. Karakaplan, Levent Kutlu Aug 2017

Endogeneity In Panel Stochastic Frontier Models: An Application To The Japanese Cotton Spinning Industry, Mustafa U. Karakaplan, Levent Kutlu

Economics and Finance Faculty Publications and Presentations

We present a panel stochastic frontier model that handles the endogeneity problem. This model can treat the endogeneity of both frontier and inefficiency variables. We apply our method to examine the technical efficiency of Japanese cotton spinning industry. Our results indicate that market concentration is endogenous, and when its endogeneity is properly handled, it has a larger negative impact on the technical efficiency of cotton spinning plants. We find that the exogenous model substantially overestimates efficiency in concentrated markets.


Us Airport Ownership, Efficiency, And Heterogeneity, Levent Kutlu, Patrick Mccarthy May 2016

Us Airport Ownership, Efficiency, And Heterogeneity, Levent Kutlu, Patrick Mccarthy

Economics and Finance Faculty Publications and Presentations

All US commercial airports are in the public sector yet not all have the same ownership type. For medium and large hub US airports we use stochastic frontier analysis to analyze the efficiency differences for alternative airport ownership types. We find that while form of ownership may matter for cost efficiency, in general its effect is relatively small. Yet type of public sector ownership does have cost efficiency implications in certain environments. Further, when heterogeneity is not controlled, the results change substantially so that type of ownership matters much more which demonstrates the importance of controlling for cross section heterogeneity.