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Methodologies for assessing government efficiency

Author

Listed:
  • O’Loughlin, Caitlin
  • Simar, Léopold

    (Université catholique de Louvain, LIDAM/ISBA, Belgium)

  • Wilson, Paul W.

Abstract

Nonparametric methods are widely used for assessing the performance of firms and other organizations in the private and public sectors. Typically, FDH or DEA estimators that estimate the attainable sets and its efficient boundary by enveloping the cloud of observed units in the appropriate input-output space are used. The statistical properties of these estimators have been established and inference is available using appropriate nonparametric techniques. In particular, hypotheses on model structure and the production process can be tested using using recent theoretical results including Central Limit Theorems on limiting distribution of means of efficiency scores. This chapter shows how these results can be used for testing the equality of means of efficiency, convexity of production sets and separability with respect to environmental factors are considered, and in addition for analyzing the dynamics of the production process over time. An empirical illustration is provided by using the various results and tests to examine the performance of municipal governments in the U.S. in providing local public goods.

Suggested Citation

  • O’Loughlin, Caitlin & Simar, Léopold & Wilson, Paul W., 2023. "Methodologies for assessing government efficiency," LIDAM Reprints ISBA 2023009, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
  • Handle: RePEc:aiz:louvar:2023009
    DOI: https://doi.org/10.4337/9781839109164.00010
    Note: In: Handbook on Public Sector Efficiency, ed. by António Afonso, João Tovar Jalles and Ana Venâncio, E. Elgar, 2023, p. 72-101 (chap. 4)
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    Cited by:

    1. Paul W. Wilson, 2025. "A Generalized Hyperbolic Distance Function for Benchmarking Performance: Estimation and Inference," Computational Economics, Springer;Society for Computational Economics, vol. 65(6), pages 3077-3110, June.

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