U.S. Specific Studies
Bhatta (2001) explores how initial level of income inequality and poverty are
related to subsequent economic growth in the Metropolitan Statistical Areas of the United
States. While the initial level of poverty is negatively related to growth, he finds that the
initial level of inequality is positively associated with growth. He also presents evidence
that Metropolitan Statistical Area’s with high growth experience low end of the period
poverty and inequality. He measures inequality by constructing the Gini index for the
MSA’s in the U.S.
Rupasingha et al. (2002) provide evidence that social and institutional factors
largely explain the differences in economic growth in U.S. counties. They find that higher
level of income inequality is associated with lower growth rates in the US counties.
Similarly, Ruapsingha and Goetz (2007), on explaining the structural determinants of
poverty in U.S. metro and non-metro areas, find that initial level of income inequality
increases the end of the period poverty rate. The two studies mentioned above use the
ratio of mean to median income to measure inequality.
Partridge and Rickman (2005) present evidence that economic policies aimed at
stimulating job growth and increasing human capital reduce poverty even in high-poverty
counties. Levernier et al. (2000) show that the population characteristics, employment
growth, educational attainment, job-skill mismatch, migration and industrial restructuring
affect poverty both in metropolitan and non-metropolitan counties, though affecting them
in varying degrees.