Productive Structure and Efficiency of Public Hospitals

  • Catherine J. Morrison Paul
Chapter
Part of the Studies in Productivity and Efficiency book series (SIPE, volume 1)

Abstract

This chapter focuses on the measurement of efficiency patterns for public hospitals in New South Wales (NSW), Australia. A frontier model of productivity and efficiency based on a distance function is used to represent “best practice” production methods for this set of hospitals, allowing for differential output and input compositional patterns, types of hospital, and environmental factors affecting production of hospital services.

Keywords

Distance Function Public Hospital Efficiency Score Marginal Product Stochastic Frontier 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. Aigner, D.J., C.A.K. Lovell and P. Schmidt [1977], “Formulation and Estimation of Stochastic Frontier Production Function Models”, Journal of Econometrics, 6, pp. 21–37.CrossRefGoogle Scholar
  2. Battese, G.E., and T. J. Coelli [1988], “Prediction of Firm Level Technical Efficiencies With a Generalised Frontier Production Function and Panel Data”, Journal of Econometrics, 38, pp. 387–399.CrossRefGoogle Scholar
  3. Battese, G.E. and T.J. Coelli [1992], “Frontier Production Functions, Technical Efficiency and Panel Data: With Application to Paddy Hospitalers in India”, The Journal of Productivity Analysis, 3, pp. 153–169.CrossRefGoogle Scholar
  4. Battese, G.E., and T.J. Coelli [1995], “A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data”, Empirical Economics, 20, 325–332.CrossRefGoogle Scholar
  5. Coelli, T.J. [1995a], “Recent Developments in Frontier Modelling and Efficiency Measurement”, Australian Journal of Agricultural Economics, 39, 3, December, pp. 219–245.CrossRefGoogle Scholar
  6. Coelli, T.J. [1995b], “Estimators and Hypothesis Tests for a Stochastic Frontier Function: A Monte Carlo Analysis”, Journal of Productivity Analysis, 6, pp. 247–268.CrossRefGoogle Scholar
  7. Coelli, T.J., and Sergio Perelman [1996], “Efficiency Measurement, Multiple-Output Technologies and Distance Functions: with Application to European Railways”, CREPP Working Paper #96/05, Universite de Liege, Belgium.Google Scholar
  8. Fare, R.S., Grosskopf, M. Norris and Z. Zhang [1994], “Productivity Growth, Technical Progress and Efficiency Changes in Industrialised Countries”, American Economic Review, 84, pp. 66–83.Google Scholar
  9. Farrell, M.J. [1957], “The Measurement of Productive Efficiency”, Journal of the Royal Statistical Society, ACXX, Part 3, pp. 253–290.Google Scholar
  10. Greene W.H. [1990], “A Gamma-Distributed Stochastic Frontier Model” Journal of Econometrics, 35, pp. 141–164.CrossRefGoogle Scholar
  11. Greene, W.H. [1993], “The Econometric Approach to Efficiency Analysis”, in The Measurement of Productive Efficiency (H.O. Fried, C.A.K. Lovell and S.S. Schmidt, eds), Oxford University press, New York, pp. 68–119.Google Scholar
  12. Grosskopf, S., K. Hayes, L. Taylor and W. Weber [1996], “Budget Constrained Frontier Measures of Fiscal Equality and Efficiency in Schooling”, Review of Economics and Statistics, forthcoming.Google Scholar
  13. Hallam, D. and M. Fernando [1996], European Review of Agricultural Economics, 23, pp. 79–93.CrossRefGoogle Scholar
  14. Hetemaki, L. [1996], “Environmental Regulation and Production Efficiency: Evidence from the Pulp Industry”, mimeo, Finnish Forest Research Institute, Helsinki.Google Scholar
  15. Klein, L. [1953], A Textbook of Econometrics, Row Peterson, New York.Google Scholar
  16. Kumbhakar, S., S.C. Ghosh and J.T. McGuckin [1991], “A Generalised Production Frontier Approach for Estimating Determinants of Inefficiency in U.S. Dairy Hospitals”, Journal of Business and Economic Statistics, 9, pp. 279–286.Google Scholar
  17. Lovell, C.A.K. [1993], “Production Frontiers and Productive Efficiency”, in The Measurement of Productive Efficiency (H.O. Fried, C.A.K. Lovell and S.S. Schmidt, eds.), Oxford University Press, New York, pp. 3–67.Google Scholar
  18. Lovell, C.A.K., S. Richardson, P. Travers and L.L. Wood [1994], “Resources and Functionings: A New View of Inequality in Australia”, in Models and Measurement of Welfare and Inequality, (W. Eichhorn, ed.), Berlin, Springer-Verlag Press.Google Scholar
  19. Meeusen, W., and J. van den Broeck [1977], “Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error”, International Economic Review, 18, pp. 435–444.CrossRefGoogle Scholar
  20. Morrison, C.J., W.E. Johnston and G. Frengley [1998], “Efficiency in New Zealand Sheep and Beef Farming: Pre- and Post- Reform”, manuscript.Google Scholar
  21. Olsen, J.A., P. Schmidt and D.M. Waldman [1980], “A Monte Carlo Study of Estimators of the Stochastic Frontier Production Function”, Journal of Econometrics, 13, pp. 67–82.CrossRefGoogle Scholar
  22. Pitt, M.M., and L.F. Lee [1981], “Measurement and Sources of Technical Inefficiency in the Indonesian Weaving Industry”, Journal of Development Economics, 9, pp. 4364.CrossRefGoogle Scholar
  23. Reifschneider, D., and R. Stevenson [1991], “Systematic Departures from the Frontier: A Framework for the Analysis of Firm Inefficiency”, International Economic Review, 32, pp. 715–723.CrossRefGoogle Scholar
  24. Stevenson, R.E. [1980], “Likelihood Functions for Generalised Stochastic Frontier Estimation”, Journal of Econometrics, 13, pp. 57–66.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2002

Authors and Affiliations

  • Catherine J. Morrison Paul
    • 1
  1. 1.Department of Agricultural and Resource EconomicsUniversity of California-DavisDavisUSA

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