Voluntary Participation as a Determinant of Social Capital in France Allowing for Parameter Heterogeneity
This paper studies the effects of active memberships in voluntary organizations on "social capital" by using individual French data and allowing for parameter heterogeneity. The model proposed in this paper is a modified version of the Neuro-Coefficient Smooth Transition Auto-Regressive (NCSTAR) model developed by Medeiros and Veiga (2000). It gives a vector of estimates for every observation of the dataset as a nonlinear function of its geographical position and its individual attributes. Our results suggest empirical evidences of significant positive direct and indirect effects of active membership in voluntary organizations on trust and individual's involvement in his or her community's life. However, the studied relationships are not stable across French departments and some regional patterns are detected.
Marie LEBRETON, Katia MELNIK
Social Capital, Parameter Heterogeneity, Neural network Models