Emory University
Department of Economics
Working Papers


Title:
Number: 04-02
Author:
Issue Date: February 2004
Abstract: We utilize county-level data to explore the different roles of different types of human capital accumulation in U.S. growth determination.  The data includes over 3,000 cross-sectional observations and 39 demographic control variables.  The large number of observations provides enough degrees of freedom to obtain estimates for the U.S. as a whole and for 32 states in and of themselves.  This data contains measures of educational attainment for four distinct categories: (a) 9 to11 years, (b) high school diploma, (c) some college and (d) bachelor degree or more.  These variables represent human capital stocks for each and every county.  This is a departure from much of the economic growth literature which has (at least in part) relied on extrapolation of stocks from flows, e.g. school enrollment data.  We use a consistent two stage least squares estimation procedure.  We find that (i) the percentage of a county’s population with less than a high-school education is negatively correlated with economic growth, (ii) the percentage obtaining a high school diploma is positively correlated with growth, and (iii) the percentage obtaining some college education has no clear relationship with economic growth but (iv) the percentage that obtains a bachelor degree or more is positively correlated with growth.  Further, we find that (v) there is significant qualitative heterogeneity in estimated coefficients across states for the 9 to 11 years and high school diploma categories but (vi) no qualitative heterogeneity for the college level categories.  The most consistent conclusion across samples is that the percent of a county’s population obtaining a bachelor degree or higher level of college education has a positive relationship with economic growth.  Oddly enough, despite findings (ii), (iv) and (vi) above, we find that the percentage of a county’s population employed in educational services is negatively correlated with economic growth.

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