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An econometric approach to estimating support prices and measures of productivity change in public hospitals

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  • C. O’Donnell
  • K. Nguyen

Abstract

In industry sectors where market prices for goods and services are unavailable, it is common to use estimated output and input distance functions to estimate rates of productivity change. It is also possible, but less common, to use estimated distance functions to estimate the normalised support (or efficient) prices of individual inputs and outputs. A problem that arises in the econometric estimation of these functions is that more than one variable in the estimating equation may be endogenous. In such cases, maximum likelihood estimation can lead to biased and inconsistent parameter estimates. To solve the problem, we use linear programming to construct a quantity index. The distance function is then written in the form of a conventional stochastic frontier model where the explanatory variables are unambiguously exogenous. We use this approach to estimate productivity indexes, measures of environmental change, levels of efficiency, and support prices for a sample of Australian public hospitals. Copyright Springer Science+Business Media, LLC 2013

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  • C. O’Donnell & K. Nguyen, 2013. "An econometric approach to estimating support prices and measures of productivity change in public hospitals," Journal of Productivity Analysis, Springer, vol. 40(3), pages 323-335, December.
    • Handle: RePEc:kap:jproda:v:40:y:2013:i:3:p:323-335
    DOI: 10.1007/s11123-012-0312-0
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    Cited by:

    1. Laurenceson, James & O'Donnell, Christopher, 2014. "New estimates and a decomposition of provincial productivity change in China," China Economic Review, Elsevier, vol. 30(C), pages 86-97.
    2. Emir Malikov & Gudbrand Lien, 2021. "Proxy Variable Estimation of Multiproduct Production Functions," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(5), pages 1878-1902, October.
    3. Mamardashvili, Phatima & Bokusheva, Raushan & Schmid, Dierk, 2014. "Heterogeneous Farm Output and Technical Efficiency Estimates," Journal of International Agricultural Trade and Development, Journal of International Agricultural Trade and Development, vol. 63(1).
    4. Maietta, Ornella Wanda & De Devitiis, Biagia & Destefanis, Sergio & Suppa, Domenico, 2019. "Human capital and rural development policy: evidence from European FADN regions," Bio-based and Applied Economics Journal, Italian Association of Agricultural and Applied Economics (AIEAA), vol. 8(3), December.
    5. Malikov, Emir, 2016. "Estimating Multi-Product Production Functions and Productivity using Control Functions," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235108, Agricultural and Applied Economics Association.
    6. Shabbir Ahmad, 2020. "Estimating input-mix efficiency in a parametric framework: application to state-level agricultural data for the United States," Applied Economics, Taylor & Francis Journals, vol. 52(36), pages 3976-3997, July.
    7. Biagia De Devitiis & Ornella Wanda Maietta, 2015. "Shadow Prices of Human Capital in Agriculture. Evidence from European FADN Regions," CSEF Working Papers 415, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy.
    8. Bao Hoang Nguyen & Zhichao Wang & Valentin Zelenyuk, 2023. "Efficiency of Queensland Public Hospitals via Spatial Panel Stochastic Frontier Models," CEPA Working Papers Series WP102023, School of Economics, University of Queensland, Australia.
    9. Monica Giancotti & Annamaria Guglielmo & Marianna Mauro, 2017. "Efficiency and optimal size of hospitals: Results of a systematic search," PLOS ONE, Public Library of Science, vol. 12(3), pages 1-40, March.
    10. O’Donnell, C.J., 2016. "Using information about technologies, markets and firm behaviour to decompose a proper productivity index," Journal of Econometrics, Elsevier, vol. 190(2), pages 328-340.
    11. Zhichao Wang & Valentin Zelenyuk, 2021. "Performance Analysis of Hospitals in Australia and its Peers: A Systematic Review," CEPA Working Papers Series WP012021, School of Economics, University of Queensland, Australia.
    12. O'Donnell, C.J., 2014. "Technologies, Markets and Behaviour: Some Implications for Estimating Efficiency and Productivity Change," 2014 Conference (58th), February 4-7, 2014, Port Macquarie, Australia 165867, Australian Agricultural and Resource Economics Society.
    13. Ahmad, Shabbir & Shankar, Sriram & Steen, John & Verreynne, Martie-Louise & Burki, Abid Aman, 2021. "Using measures of efficiency for regionally-targeted smallholder policy intervention: The case of Pakistan’s horticulture sector," Land Use Policy, Elsevier, vol. 101(C).
    14. Valentin Zelenyuk & Zhichao Wang, 2023. "Random vs. Explained Inefficiency in Stochastic Frontier Analysis: The Case of Queensland Hospitals," CEPA Working Papers Series WP052023, School of Economics, University of Queensland, Australia.
    15. C. J. O’Donnell & Saeideh Fallah-Fini & Konstantinos Triantis, 2017. "Measuring and analysing productivity change in a metafrontier framework," Journal of Productivity Analysis, Springer, vol. 47(2), pages 117-128, April.
    16. Mamardashvili, Phatima & Bokusheva, Raushan & Schmid, Dierk, 2014. "Heterogeneous Farm Output and Technical Efficiency Estimates," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 63(01), pages 1-15, March.
    17. Gavilan, José M. & Ortega, Francisco J., 2020. "Productive efficiency analysis of quantitative economics journals through Stochastic Frontier Analysis using panel data || Análisis de eficiencia productiva de revistas de economía cuantitativa a trav," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 30(1), pages 297-311, December.
    18. Danelon, André Felipe & Spolador, Humberto Francisco Silva & Bergtold, Jason Scott, 2023. "The role of productivity and efficiency gains in the sugar-ethanol industry to reduce land expansion for sugarcane fields in Brazil," Energy Policy, Elsevier, vol. 172(C).
    19. C.J. O'Donnell, 2011. "The Sources of Productivity Change in the Manufacturing Sectors of the U.S. Economy," CEPA Working Papers Series WP072011, School of Economics, University of Queensland, Australia.

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    More about this item

    Keywords

    Endogeneity; Distance functions; Shadow prices; Efficient prices; Total factor productivity; Environmental change; Technical efficiency; Scale efficiency; C43; D24; I12; I18;
    All these keywords.

    JEL classification:

    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health

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