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Technical efficiency in texas nursing facilities: A stochastic production frontier approach

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  • Kris Knox

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  • Eric Blankmeyer
  • J. Stutzman

Abstract

A rapidly aging U. S. population is straining the resources available for long term care and increasing the urgency of efficient operations in nursing homes. The scope for productivity improvements can be examined by estimating a stochastic frontier production function. We apply the methods of maximum likelihood and quantile regression to a panel of Texas nursing facilities and infer that the average productivity shortfall due to avoidable technical inefficiency is at least 8 percent and perhaps as large as 20 percent. Non-profit facilities are notably less productive than comparable facilities operated for profit, and the industry has constant returns to scale. Copyright Springer 2007

Suggested Citation

  • Kris Knox & Eric Blankmeyer & J. Stutzman, 2007. "Technical efficiency in texas nursing facilities: A stochastic production frontier approach," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 31(1), pages 75-86, March.
  • Handle: RePEc:spr:jecfin:v:31:y:2007:i:1:p:75-86
    DOI: 10.1007/BF02751513
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    References listed on IDEAS

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    1. Koenker,Roger, 2005. "Quantile Regression," Cambridge Books, Cambridge University Press, number 9780521845731, March.
    2. Nyman, John A & Bricker, Dennis L, 1989. "Profit Incentives and Technical Efficiency in the Production of Nursing Home Care," The Review of Economics and Statistics, MIT Press, vol. 71(4), pages 586-594, November.
    3. Erlandsen,E. & Forsund,F.R., 1999. "Efficiency in the provision of municipal nursing- and home-care services : the Norwegian experience," Memorandum 32/1999, Oslo University, Department of Economics.
    4. Vitaliano, Donald F. & Toren, Mark, 1994. "Cost and efficiency in nursing homes: a stochastic frontier approach," Journal of Health Economics, Elsevier, vol. 13(3), pages 281-300, October.
    5. Newhouse, Joseph P., 1994. "Frontier estimation: How useful a tool for health economics?," Journal of Health Economics, Elsevier, vol. 13(3), pages 317-322, October.
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    1. repec:dau:papers:123456789/11700 is not listed on IDEAS
    2. Per J. Agrell & Mehdi Farsi & Massimo Filippini & Martin Koller, 2013. "Unobserved heterogeneous effects in the cost efficiency analysis of electricity distribution systems," CER-ETH Economics working paper series 13/171, CER-ETH - Center of Economic Research (CER-ETH) at ETH Zurich.
    3. Galina Besstremyannaya, 2014. "The efficiency of labor matching and remuneration reforms: a panel data quantile regression approach with endogenous treatment variables," Working Papers w0206, Center for Economic and Financial Research (CEFIR).
    4. Knox, Kris Joseph & Blankmeyer, Eric C. & Trinidad, José A. & Stutzman, J.R., 2009. "Predicting bankruptcy in the Texas nursing facility industry," The Quarterly Review of Economics and Finance, Elsevier, vol. 49(3), pages 1047-1064, August.
    5. Galina Besstremyannaya, 2015. "Heterogeneous effect of residency matching and prospective payment on labor returns and hospital scale economies," Discussion Papers 15-001, Stanford Institute for Economic Policy Research.
    6. Marie-Eve Joël & Romain Sibille, 2013. "Education and career path of French nursing home managers : impact on their human resources practices," Post-Print hal-01522519, HAL.
    7. Mamatzakis, E & Koutsomanoli-Filippaki, Anastasia & Pasiouras, Fotios, 2012. "A quantile regression approach to bank efficiency measurement," MPRA Paper 51879, University Library of Munich, Germany.
    8. Iparraguirre, José Luis & Ma, Ruosi, 2015. "Efficiency in the provision of social care for older people. A three-stage Data Envelopment Analysis using self-reported quality of life," Socio-Economic Planning Sciences, Elsevier, vol. 49(C), pages 33-46.

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