Semi-Parametric Regression Models and Economies of Scale in the Presence of an Endogenous Variable

Posted: 11 Aug 2016

See all articles by Jeffrey Cohen

Jeffrey Cohen

University of Connecticut - School of Business

Jeffrey Osleeb

University of Connecticut

Ke Yang

University of Hartford

Date Written: 2014

Abstract

Microeconomic applications of semi-parametric models with an endogenous variable have been largely ignored. Recognizing spatial heterogeneity captured by semi-parametric cost function models can impact economies of scale estimates. We estimate several cost function models, using panel data for Connecticut's 30 hospitals over a 10 year time period. We consider a variety of fixed effects and semi-parametric models. One innovation is that we address both the space and time dimensions in the kernel weights of our panel data semi-parametric regression models. We find that a life expectancy measure for years above average lifespan is positively and significantly related to hospital costs. We also address endogeneity of life expectancy. Our instrumental variable (IV) estimation approach uses locally weighted regressions in panel data models, as Baltagi and Li (2002) suggest for endogeneity in general semi-parametric panel data models. With our semi-parametric IV approach the elasticities of scale estimates are smaller than with fixed effects estimation, but still less than 1, implying a greater degree of economies of scale. Monte Carlo simulations indicate that our semi-parametric IV estimator performs well.

Keywords: semi-parametric regressions, economies of scale

JEL Classification: R1, C4, I1

Suggested Citation

Cohen, Jeffrey and Osleeb, Jeffrey and yang, ke, Semi-Parametric Regression Models and Economies of Scale in the Presence of an Endogenous Variable (2014). Regional Science and Urban Economics, Vol. 49, 2014, Available at SSRN: https://ssrn.com/abstract=2819622

Jeffrey Cohen (Contact Author)

University of Connecticut - School of Business ( email )

368 Fairfield Road
Storrs, CT 06269-2041
United States

Jeffrey Osleeb

University of Connecticut ( email )

Storrs, CT 06269-1063
United States

Ke Yang

University of Hartford ( email )

West Hartford, CT 06117-1599
United States

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