Sigma-Convergence Versus Beta-Convergence: Evidence from U.S. County-Level Data

In this paper we outline (i) why ó-convergence may not accompany â- convergence, (ii)cite evidence of â-convergence in the U.S., (iii) and use USA county-level data containing over 3,000 cross-sectional observations to demonstrate that ó-convergence does not hold across the U.S., or within the vast majority of the individual U.S. states.Economic Growth, Convergence, ó-convergence, sigma convergence, â-convergence, beta convergence, US County Level Data

Many Types of Human Capital and Many Roles in U.S. Growth: Evidence from County-Level Educational Attainment Data

We utilize county-level data to explore the 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.Human Capital Stock, Educational Attainment, Economic Growth, County Level Data

Growth and Convergence across the US: Evidence from County-Level Data

We use county data with 3,058 observations to study growth and convergence in the US. We assess the effect of 40 conditioning variables on the counties’ balanced growth paths. Using OLS and 3SLS-IV, the later yielding consistent estimates, we report estimates for the full sample and for metro, non-metro, and five regional samples. We find that (1) OLS yields convergence rates around 2 percent, but 3SLS yields 6–8 percent; (2) convergence rates vary across the U.S. E.g., Southern counties converge 2½ times faster than Northeastern counties; (3) government size at all levels (federal, state and local) is negatively correlated with growth; (4) the relation between educational attainment and growth is nonlinear; and (5) large finance, insurance and real estate industry, and entertainment industry is positively correlated with growth but the population share employed in education is negatively correlated with growth.Economic Growth, Convergence, Conditional Convergence, County- Level Data, 3SLS Instrumental Variables Estimate, Balanced Growth Path, Public Sector, Industry Composition, Educational Attainment

Federal, State, and Local Governments: Evaluating their Separate Roles in US Growth

We use new US county level data (3,058 observations) from 1970 to 1998 to explore the relationship between economic growth and the size of government at three levels: federal, state and local. Using 3SLS-IV estimation we find that the size of federal, state and local government all either negatively correlate with or are uncorrelated with economic growth. We find no evidence that government is more efficient at more or less decentralized levels. Furthermore, while we cannot separate out the productive and redistributive services of government, we document that the county-level income distribution became slightly wider from 1970 to 1998. Our findings suggest that a release of government-employed labor inputs to the private sector would be growth-enhancing.Economic Growth; Federal Government; State Government; Local Government; and County-Level Data