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Analysing the effectiveness of public service producers with endogenous resourcing

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  • David J. Mayston

Abstract

One of the main motivations for productivity analysis is to assess the scope for overall improvements in the output possibilities of individual producers. At times of fiscal and government budgetary pressures, attention focuses particularly on the output potential of public service providers and its relationship to the inputs provided by government funding. Public services, such as education and healthcare, are themselves an important form of economic activity whose performance is of wide public interest, and which merit an adequate recognition of the richness of the additional considerations which may arise in making effectiveness assessments using frontier techniques such as Stochastic Frontier Analysis (SFA) and Data Envelopment Analysis (DEA). The interesting example of university Departments illustrates one such additional consideration, namely endogeneity of the available resource levels through their dependence on the Department’s achieved outputs of teaching and research. Fortunately progress can be made in the presence of such endogeneity through the application of SFA to the assessments of the overall effectiveness and performance of the public service provider, and their decomposition into both technical and allocative components, using the notion of an Achievement Possibility Set that includes the multiplier effects which such resource endogeneity generates.

Suggested Citation

  • David J. Mayston, 2012. "Analysing the effectiveness of public service producers with endogenous resourcing," Discussion Papers 12/30, Department of Economics, University of York.
  • Handle: RePEc:yor:yorken:12/30
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    File URL: https://www.york.ac.uk/media/economics/documents/discussionpapers/2012/1230.pdf
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    References listed on IDEAS

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    1. Bruce Hollingsworth, 2008. "The measurement of efficiency and productivity of health care delivery," Health Economics, John Wiley & Sons, Ltd., vol. 17(10), pages 1107-1128.
    2. Atkinson, Scott E. & Primont, Daniel, 2002. "Stochastic estimation of firm technology, inefficiency, and productivity growth using shadow cost and distance functions," Journal of Econometrics, Elsevier, vol. 108(2), pages 203-225, June.
    3. Cornwell, Christopher & Schmidt, Peter & Sickles, Robin C., 1990. "Production frontiers with cross-sectional and time-series variation in efficiency levels," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 185-200.
    4. 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. Kristof de Witte & Laura López-Torres, 2015. "Efficiency in Education. A Review of Literature and a Way Forward," Working Papers 1501, Departament Empresa, Universitat Autònoma de Barcelona, revised Apr 2015.
    2. Sokvibol Kea & Hua Li & Linvolak Pich, 2016. "Technical Efficiency and Its Determinants of Rice Production in Cambodia," Economies, MDPI, Open Access Journal, vol. 4(4), pages 1-17, October.
    3. 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.

    More about this item

    Keywords

    Public services; Effectiveness; Performance measurement; Endogeneity; Stochastic frontier analysis; Data envelopment analysis;

    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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