Investigating the impact of endogeneity on inefficiency estimates in the application of stochastic frontier analysis to nursing homes
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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.
KeywordsStochastic frontier analysis Endogeneity Efficiency Quality Nursing homes
JEL ClassificationC13 C15 I12
This paper does not represent the policy of either the Agency for Healthcare Research and Quality (AHRQ) or the U.S. Department of Health and Human Services (DHHS). The views expressed herein are those of the authors and no official endorsement by AHRQ or DHHS is intended or should be inferred. This research was partially funded by contracts from AHRQ: AHRQ Contract Number HHSP233200900285P (Michael Rosko, Dana Mukamel) and HHSN263200500063293 (William Greene).
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