|This centre is a member of The LSE Research Laboratory [RLAB]: CASE | CEE | CEP | FMG | SERC | STICERD||Cookies?|
Paper No' CEPDP0765: | Full paper
Save Reference as: BibTeX File | EndNote Import File
Keywords: Unified Growth Theory; Human capital, Technological Progress, Inequality and Growth
JEL Classification: D31; E27; F02; N00; O40.
Is hard copy/paper copy available? YES - Paper Copy Still In Print.
This Paper is published under the following series: CEP Discussion Papers
Share: Google Bookmarks | Facebook | Twitter
Abstract:This paper is the first empirical framework that explains the phenomenon of fast growth combined with the demographic transition occurring in the United States since 1860. I propose a structural model that unifies those events through the role of education: the key feature is that parental education determines simultaneously fertility, mortality and children's education, so that the accumulation of education from one generation to another explains both fast growth and the reduction of fertility and mortality rates. Using original data, the model is estimated and fits in a remarkable way income, the distribution of education and age pyramids. Moreover, some historical data on Blacks, assumed to constitute the bottom of the distribution of education, show that the model predicts correctly the joint distribution of fertility and education, and that of mortality and education. Comparisons with the PSID suggest that the intergenerational correlation of income is also well captured. Thus, this microfunded growth model based on human capital accumulation accounts for many traits of American economic development since 1860. In a second step, I investigate the long-run influence of income inequality on growth. Because children's human capital is a concave function of parental income, income inequality slows down the accumulation of human capital across generations and hence growth. Simulations show that this effect is large.
Copyright © CEP & LSE 2003 - 2013 | LSE, Houghton Street, London WC2A 2AE | Tel: +44(0)20 7955 7673 | Email: email@example.com | Site updated 23 May 2013