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Analysing the effectiveness of public service producers with endogenous resourcing

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  • David Mayston
Abstract
Public services, such as education and health care, are important forms of economic activity whose performance is of wide public interest and whose assessment raises interesting issues. The paper extends the existing focus of stochastic frontier analysis (SFA) on production and cost functions by considering additional inter-relationships which may exist between a public service provider’s funding level, input prices, clientele characteristics and the level and quality of the output they achieve in different relevant directions. The potentially large multiplier effects which these additional relationships generate from efficiency and effectiveness improvements are incorporated into the analysis and the estimation process by extending the standard notion of a production possibility frontier to the more general concept of an achievement possibility frontier. The paper also generalises SFA’s use of a univariate half-normal density function by deploying a multivariate skew-normal density function in the stochastic structure of these multiple inter-relationships, thereby permitting correlations to exist between the efficiency and effectiveness deviations for individual producers across these different inter-relationships, while including a half-normal marginal distribution for production efficiency deviations as a special limiting case. This approach also generates point estimates for the cumulative effectiveness coefficient of each individual public service producer that generalise the earlier results based on a half-normal distribution. In doing so, the paper extends the analysis of SFA of feasible increases in an individual producer’s output to important contexts in which the endogeneity of key variables needs to be taken into account. Copyright Springer Science+Business Media New York 2015

Suggested Citation

  • David Mayston, 2015. "Analysing the effectiveness of public service producers with endogenous resourcing," Journal of Productivity Analysis, Springer, vol. 44(1), pages 115-126, August.
  • Handle: RePEc:kap:jproda:v:44:y:2015:i:1:p:115-126
    DOI: 10.1007/s11123-014-0428-5
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    References listed on IDEAS

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    1. David Mayston, 2007. "Competition And Resource Effectiveness In Education," Manchester School, University of Manchester, vol. 75(1), pages 47-64, January.
    2. Lounasheimo, Antton, 1999. "The Impact of Human Capital on Economic Growth," Discussion Papers 673, The Research Institute of the Finnish Economy.
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    11. Ryan Mutter & William Greene & William Spector & Michael Rosko & Dana Mukamel, 2013. "Investigating the impact of endogeneity on inefficiency estimates in the application of stochastic frontier analysis to nursing homes," Journal of Productivity Analysis, Springer, vol. 39(2), pages 101-110, April.
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    14. Chambers,Robert G., 1988. "Applied Production Analysis," Cambridge Books, Cambridge University Press, number 9780521314275.
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    16. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
    17. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
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    Cited by:

    1. Jesús A. Tapia & Bonifacio Salvador, 2022. "Data envelopment analysis efficiency in the public sector using provider and customer opinion: An application to the Spanish health system," Health Care Management Science, Springer, vol. 25(2), pages 333-346, June.
    2. David J. Mayston, 2017. "Data envelopment analysis, endogeneity and the quality frontier for public services," Annals of Operations Research, Springer, vol. 250(1), pages 185-203, March.
    3. Kristof De Witte & Laura López-Torres, 2017. "Efficiency in education: a review of literature and a way forward," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(4), pages 339-363, April.
    4. Førsund, Finn R., 2017. "Measuring effectiveness of production in the public sector," Omega, Elsevier, vol. 73(C), pages 93-103.
    5. David J. Mayston, 2015. "Data envelopment analysis, endogeneity and the quality frontier for public services," Discussion Papers 15/05, Department of Economics, University of York.
    6. David J Mayston, 2017. "Convexity, quality and efficiency in education," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(4), pages 446-455, April.
    7. Hania Arif & Mamoona Midhat Kazmi & Aamer Amin, 2021. "Improving Rice Yield Through Insufficient Water," International Journal of Agriculture & Sustainable Development, 50sea, vol. 3(2), pages 33-38, May.
    8. Sokvibol Kea & Hua Li & Linvolak Pich, 2016. "Technical Efficiency and Its Determinants of Rice Production in Cambodia," Economies, MDPI, vol. 4(4), pages 1-17, October.

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    More about this item

    Keywords

    Public services; Effectiveness; Endogeneity; Stochastic frontier analysis; Multivariate skew-normal; C13; C18; C30; D20; I23;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
    • D20 - Microeconomics - - Production and Organizations - - - General
    • I23 - Health, Education, and Welfare - - Education - - - Higher Education; Research Institutions

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