Robust Correlates of County-Level Growth in the U.S.
Matthew John Higgins
Georgia Institute of Technology & NBER; National Bureau of Economic Research (NBER)
Andrew T. Young
Texas Tech University - Rawls College of Business
Bar-Ilan University - Department of Economics; Emory University - Department of Economics; Rimini Center for Economic Analysis
Emory Law and Economics Research Paper No. 07-16
Higgins et al. (2006) report several statistically significant partial correlates with U.S. per capita income growth. However, Levine and Renelt (1992) demonstrate that such correlations are hardly ever robust to changing the combination of conditioning variables included. We ask whether the same is true for the variables identified as important by Higgins et al. Using the extreme bounds analysis of Levine and Renelt, we find that the majority of the partial correlations can be accepted as robust. The variables associated with those partial correlations stand solidly as variables of interest for future studies of U.S. growth.
Number of Pages in PDF File: 10
Keywords: Economic Growth, Conditional Convergence, Extreme Bounds Analysis, County-Level Data
JEL Classification: O40, O11, O18, O51, R11, H50, H70
Date posted: May 4, 2007