On estimating the distribution of data envelopment analysis efficiency scores: an application to nursing homes' care planning process

B. J. Gajewski, R. Lee, M. Bott, U. Piamjariyakul and R. L. Taunton

Journal of Applied Statistics, 2009, vol. 36, issue 9, 933-944

Abstract: Data envelopment analysis (DEA) is a deterministic econometric model for calculating efficiency by using data from an observed set of decision-making units (DMUs). We propose a method for calculating the distribution of efficiency scores. Our framework relies on estimating data from an unobserved set of DMUs. The model provides posterior predictive data for the unobserved DMUs to augment the frontier in the DEA that provides a posterior predictive distribution for the efficiency scores. We explore the method on a multiple-input and multiple-output DEA model. The data for the example are from a comprehensive examination of how nursing homes complete a standardized mandatory assessment of residents.

Keywords: bounded DEA; MCMC; binomial distribution; posterior predictive distribution; sampling; imputation (search for similar items in EconPapers)
Date: 2009
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Citations: View citations in EconPapers (4)

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DOI: 10.1080/02664760802552986

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