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An Econometric Approach To Estimating Support Prices And Measures Of Productivity Change In Public Hospitals

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Abstract

In industry sectors where market prices are unavailable it is common to represent multiple-input multiple-output production technologies using distance functions. Econometric estimation of such functions is complicated by the fact that more than one variable in the function may be endogenous. In such cases, maximum likelihood estimation can lead to biased and inconsistent estimates of the model parameters and associated measures of firm performance. We solve the problem by using 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 and support (or shadow) prices for a sample of Australian public hospitals. We decompose the productivity index into several measures of environmental change and efficiency change. We find that the productivity effects of improvements in input-oriented technical efficiency have been largely offset by the effects of deteriorations in the production environment over time.

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  • C.J. O’Donnell & K. Nguyen, 2011. "An Econometric Approach To Estimating Support Prices And Measures Of Productivity Change In Public Hospitals," CEPA Working Papers Series WP032011, School of Economics, University of Queensland, Australia.
  • Handle: RePEc:qld:uqcepa:63
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    Cited by:

    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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).
    6. 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.
    7. 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.
    8. 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).
    9. 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.
    10. 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.
    11. 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).
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. 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.
    18. 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.
    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

    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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