Article

Journal of Productivity Analysis

, Volume 39, Issue 2, pp 101-110

Investigating the impact of endogeneity on inefficiency estimates in the application of stochastic frontier analysis to nursing homes

  • Ryan L. MutterAffiliated withCenter for Delivery, Organization and Markets, Agency for Healthcare Research and Quality Email author 
  • , William H. GreeneAffiliated withStern School of Business, New York University
  • , William SpectorAffiliated withCenter for Delivery, Organization and Markets, Agency for Healthcare Research and Quality
  • , Michael D. RoskoAffiliated withSchool of Business Administration, Widener University
  • , Dana B. MukamelAffiliated withDepartment of Medicine, Health Policy Research Institute, University of California, Irvine

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Abstract

This paper examines the impact of an endogenous cost function variable on the inefficiency estimates generated by stochastic frontier analysis (SFA). The specific variable of interest in this application is endogenous quality in nursing homes. We simulate a dataset based on the characteristics of for-profit nursing homes in California, which we use to assess the impact on SFA-generated inefficiency estimates of an endogenous regressor under a variety of scenarios, including variations in the strength and direction of the endogeneity and whether the correlation is with the random noise or the inefficiency residual component of the error term. We compare each of these cases when quality is included and excluded from the cost equation. We provide evidence of the impact of endogeneity on inefficiency estimates yielded by SFA under these various scenarios and when the endogenous regressor is included and excluded from the model.

Keywords

Stochastic frontier analysis Endogeneity Efficiency Quality Nursing homes

JEL Classification

C13 C15 I12