A Smooth Coefficient Quantile Regression Approach to the Social Capital-Economic Growth Nexus

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Title:	A Smooth Coefficient Quantile Regression Approach to the Social Capital-Economic Growth Nexus
Authors:	Deng, Wen-shuenn;Lin, Yi-chen;Gong, Jin-guo
Contributors:	淡江大學統計學系;淡江大學經濟學系
Keywords:	Semiparametric methods;Kernel smoothing;Smooth coefficient;Quantile regression;Social capital;Economic growth
Date:	2012-03
Issue Date:	2012-02-22 09:36:29 (UTC+8)
Publisher:	Amsterdam: Elsevier BV * North-Holland
Abstract:	This analysis assesses the role of social capital in generating heterogeneity in growth processes across U.S. counties by estimating growth regressions, using the novel semiparametric smooth coefficient quantile regression method in which parameters are unspecified functions of a measure of social capital. The results indicate substantial differences across the quantiles of economic growth in the profile shapes of the coefficient estimates over the level of social capital. Moreover, the coefficient function estimates are highly nonlinear over the level of social capital, providing evidence that the growth process that links initial income, education attainment, ethnic diversity, inequality, population density, and government activity to growth varies with social capital in a nonlinear way.
Relation:	Economic Modelling 29(2), pp.185-197
DOI:	10.1016/j.econmod.2011.09.008
Appears in Collections:	[Graduate Institute & Department of Economics] Journal Article [Graduate Institute & Department of Statistics] Journal Article

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