poverty and economic growth crucially depend on a given level of income inequality.
Moreover, the relationship between income inequality and economic growth is
sometimes better suited to explain the relationships between poverty and economic
growth (Bhatta 2001).
Although there are more number of cross-country studies that analyze the
relationship between economic growth, poverty and income-inequality, country-specific
analysis has certain advantages over cross-country analysis. First, the method used to
gather information on the relevant variables across countries is not as uniform or
standardized compared to data collected within a country (Ravallion 2001). Second, laws
and policies, which can significantly affect economic growth, poverty and inequality,
vary across countries more than they do within a country. Third, definitions of variables
differ widely across countries. For instance, poverty is defined from a consumption angle
in India, while it is based on income levels in the United States.
I use the 1980 and 2000 U.S. decennial Census data to measure the initial values
and end of the period values, respectively. This twenty-year period serves to capture the
consequences of long run growth in the most recent past for the U.S. counties. The advent
of information technology and the resultant globalization in the late eighties and early
nineties lead to unprecedented economic growth in the U.S. (Rupasingha et al. 2002)
making the time frame informative and appropriate for this analysis. I use the change in
per capita personal income between 1979 and 1999 to measure economic growth, the
rationale for which is explained in section 4. I measure income inequality by constructing
Gini index for all the counties in the U.S. (explained in detail in section 3), and use the
percentage of poor people in each county to measure poverty.