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Voluntary Participation as a Determinant of Social Capital in France : Allowing for Parameter Heterogeneity

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  • Marie Lebreton

    () (GREQAM - Groupement de Recherche en Économie Quantitative d'Aix-Marseille - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - CNRS - Centre National de la Recherche Scientifique - ECM - Ecole Centrale de Marseille)

  • Katia Melnik

    () (GREQAM - Groupement de Recherche en Économie Quantitative d'Aix-Marseille - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - CNRS - Centre National de la Recherche Scientifique - ECM - Ecole Centrale de Marseille)

Abstract

This paper studies the effects of income, education and active memberships in voluntary organizations and clubs on "social capital" by using individual French data and allowing for parameter heterogeneity (Durlauf and Fafchamps, 2003). Survey responses to the questions concerning trust, social norms and individual involvement in the local life are used as proxies of social capital. The model developed in this paper is an Artificial Neural Network model or more precisely the Neuro-Coefficient Smooth Transition Auto-Regressive (NCSTAR) model. It gives a vector of estimates for every observation of the dataset as a nonlinear function of its geographical position and its individual attributes. We show that accounting for parameter heterogeneity considerably improves the fit of the estimated model in comparison with the broadly used multinomial logit model. Our results suggest empirical evidences of significant positive direct and indirect effects of active membership in voluntary organizations on trust (or rather trustworthiness, Glaeser et al, 2000) and individual's involvement in his or her community's life. This finding supports the considering of membership in voluntary organizations in France as promoting the values of cooperation and positive tendency towards public issues. However, the studied relationships are not stable across French departments and some regional patterns are detected.

Suggested Citation

  • Marie Lebreton & Katia Melnik, 2009. "Voluntary Participation as a Determinant of Social Capital in France : Allowing for Parameter Heterogeneity," Working Papers halshs-00410530, HAL.
  • Handle: RePEc:hal:wpaper:halshs-00410530 Note: View the original document on HAL open archive server: https://halshs.archives-ouvertes.fr/halshs-00410530
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    References listed on IDEAS

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    1. Rech, Gianluigi & Teräsvirta, Timo & Tschernig, Rolf, 1999. "A simple variable selection technique for nonlinear models," SSE/EFI Working Paper Series in Economics and Finance 296, Stockholm School of Economics, revised 06 Apr 2000.
    2. Stephen Knack & Philip Keefer, 1997. "Does Social Capital Have an Economic Payoff? A Cross-Country Investigation," The Quarterly Journal of Economics, Oxford University Press, vol. 112(4), pages 1251-1288.
    3. Steven N. Durlauf, 2002. "On the Empirics of Social Capital," Economic Journal, Royal Economic Society, vol. 112(483), pages 459-479, November.
    4. Alesina, Alberto & La Ferrara, Eliana, 2002. "Who trusts others?," Journal of Public Economics, Elsevier, pages 207-234.
    5. Charles F. Manski, 2000. "Economic Analysis of Social Interactions," Journal of Economic Perspectives, American Economic Association, vol. 14(3), pages 115-136, Summer.
    6. Marcelo C. Medeiros & Alvaro Veiga, 2003. "Diagnostic Checking in a Flexible Nonlinear Time Series Model," Journal of Time Series Analysis, Wiley Blackwell, vol. 24(4), pages 461-482, July.
    7. Medeiros, Marcelo & Veiga, Alvaro, 2000. "A Flexible Coefficient Smooth Transition Time Series Model," SSE/EFI Working Paper Series in Economics and Finance 360, Stockholm School of Economics, revised 29 Apr 2004.
    8. McMillen, Daniel P., 1996. "One Hundred Fifty Years of Land Values in Chicago: A Nonparametric Approach," Journal of Urban Economics, Elsevier, vol. 40(1), pages 100-124, July.
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    Keywords

    Neural network models; Social capital; Parameter heterogeneity; Neural network models.;

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