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Gibrat’s law and legacy for non-profit organisations: a non-parametric analysis


  • Peter G. Backus

    () (University of Southampton & University of Barcelona & IEB)


Gibrat’s Law of proportional effect (i.e. growth is independent of initial size) has been tested for firms for several decades. In this paper I test Gibrat’s Law for charities in England and Wales through time. Using a data set based on the population of registered charities from 1998 to 2009, I am able to test the ‘ex ante’ hypothesis that Gibrat’s Law holds over the long run for a sample of charities as well as testing Gibrat’s Legacy (that Gibrat’s Law holds for large and mature organisations), the ‘ex post’ hypothesis. I use nonparametric local polynomial smoothing techniques which are more robust to the issues of autocorrelation, sample selection and truncation that make the conventional parametric approaches to testing Gibrat’s Law difficult in practice. Results suggest that the dynamic processes driving growth in the charitable sectors may differ from those driving the growth of firms. Unlike for-profit firms Gibrat’s Law is found to generally hold when controlling for selection both ‘ex ante’ and ‘ex post’. Results may be driven by the absence of a minimum efficient scale which charities must achieve to survive and the different funding profiles of charities.

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  • Peter G. Backus, 2012. "Gibrat’s law and legacy for non-profit organisations: a non-parametric analysis," Working Papers 2012/8, Institut d'Economia de Barcelona (IEB).
  • Handle: RePEc:ieb:wpaper:2012/4/doc2012-8

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    References listed on IDEAS

    1. Stephen P. Jenkins & Philippe Van Kerm, 2006. "Trends in income inequality, pro-poor income growth, and income mobility," Oxford Economic Papers, Oxford University Press, vol. 58(3), pages 531-548, July.
    2. Francesca Lotti & Enrico Santarelli & Marco Vivarelli, 2009. "Defending Gibrat’s Law as a long-run regularity," Small Business Economics, Springer, vol. 32(1), pages 31-44, January.
    3. Chesher, Andrew, 1979. "Testing the Law of Proportionate Effect," Journal of Industrial Economics, Wiley Blackwell, vol. 27(4), pages 403-411, June.
    4. D.B. Audretsch & L. Klomp & E. Santarelli & A.R. Thurik, 2004. "Gibrat's Law: Are the Services Different?," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 24(3), pages 301-324, May.
    5. Richard Steinberg, 1986. "The Revealed Objective Functions of Nonprofit Firms," RAND Journal of Economics, The RAND Corporation, vol. 17(4), pages 508-526, Winter.
    6. Puhani, Patrick A, 2000. " The Heckman Correction for Sample Selection and Its Critique," Journal of Economic Surveys, Wiley Blackwell, vol. 14(1), pages 53-68, February.
    7. Timothy Dunne & Mark J. Roberts & Larry Samuelson, 1989. "The Growth and Failure of U. S. Manufacturing Plants," The Quarterly Journal of Economics, Oxford University Press, vol. 104(4), pages 671-698.
    8. Harrison Teresa D. & Laincz Christopher A, 2008. "Entry and Exit in the Nonprofit Sector," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 8(1), pages 1-42, July.
    9. Rafael González-Val, 2012. "A nonparametric estimation of the local Zipf exponent for all US cities," Environment and Planning B: Planning and Design, Pion Ltd, London, vol. 39(6), pages 1119-1130, November.
    10. José Fariñas & Lourdes Moreno, 2000. "Firms' Growth, Size and Age: A Nonparametric Approach," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 17(3), pages 249-265, November.
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    More about this item


    Gibrat’s Law; charities; nonparametric estimation;

    JEL classification:

    • L31 - Industrial Organization - - Nonprofit Organizations and Public Enterprise - - - Nonprofit Institutions; NGOs; Social Entrepreneurship
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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