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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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    1. David Mayston, 2007. "Competition And Resource Effectiveness In Education," Manchester School, University of Manchester, vol. 75(1), pages 47-64, January.
    2. Izadi, Hooshang & Johnes, Geraint & Oskrochi, Reza & Crouchley, Robert, 2002. "Stochastic frontier estimation of a CES cost function: the case of higher education in Britain," Economics of Education Review, Elsevier, vol. 21(1), pages 63-71, February.
    3. 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, October.
    4. Jeremy Foltz & Bradford Barham & Jean-Paul Chavas & Kwansoo Kim, 2012. "Efficiency and technological change at US research universities," Journal of Productivity Analysis, Springer, vol. 37(2), pages 171-186, April.
    5. ., 1999. "The assessment of capital adequacy," Chapters, in: Handbook of Banking Regulation and Supervision in the United Kingdom, chapter 17, Edward Elgar Publishing.
    6. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
    7. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    8. Chambers,Robert G., 1988. "Applied Production Analysis," Cambridge Books, Cambridge University Press, number 9780521314275, January.
    9. A. Azzalini & A. Capitanio, 1999. "Statistical applications of the multivariate skew normal distribution," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 61(3), pages 579-602.
    10. 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.
    11. Lounasheimo, Antton, 1999. "The Impact of Human Capital on Economic Growth," Discussion Papers 673, The Research Institute of the Finnish Economy.
    12. 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.
    13. Adelchi Azzalini, 2005. "The Skew‐normal Distribution and Related Multivariate Families," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 32(2), pages 159-188, June.
    14. George E. Battese & Greg S. Corra, 1977. "Estimation Of A Production Frontier Model: With Application To The Pastoral Zone Of Eastern Australia," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 21(3), pages 169-179, December.
    15. Mayston, David, 2009. "The determinants of cumulative endogeneity bias in multivariate analysis," Journal of Multivariate Analysis, Elsevier, vol. 100(6), pages 1120-1136, July.
    16. A. Capitanio & A. Azzalini & E. Stanghellini, 2003. "Graphical models for skew‐normal variates," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 30(1), pages 129-144, March.
    17. 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.
    18. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    19. Battese, George E. & Corra, Greg S., 1977. "Estimation Of A Production Frontier Model: With Application To The Pastoral Zone Of Eastern Australia," Australian Journal of Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 21(3), pages 1-11, December.
    20. 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.
    21. 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.
    22. William W. Cooper & Lawrence M. Seiford & Kaoru Tone, 2007. "Data Envelopment Analysis," Springer Books, Springer, edition 0, number 978-0-387-45283-8, March.
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    Cited by:

    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. Førsund, Finn R., 2017. "Measuring effectiveness of production in the public sector," Omega, Elsevier, vol. 73(C), pages 93-103.
    7. 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; Performance measurement; Endogeneity; Stochastic frontier analysis; Data envelopment analysis;
    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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