# natural logarithm, and differentiating with respect to time yields the following per-capita

version of equation (1):

( ) y A H N i t i t i t i t 1

----

(2)

# While various county-specific characteristics determine the productivity term A, I

include three important factors (following Bhatta 2001): initial levels of income

inequality, poverty and real per capita income. Thus, I estimate the following reduced

form equation:

y E V P V G V H N S F e i t i i i i t i t i i 0 1 2 3 4 5 - - - - ( 3 )

where y_{it }measures the growth rate of real per capita income in county i over a ,,

twenty year period between 1979 and 1999.^{2 }I follow Bhatta (2001) in using per capita

personal income to measure economic growth. Bhatta argues that most of the components

used to compute gross domestic product and national income overlap, and consequently,

there is almost a one to one correlation between gross domestic product and gross

national income (nominal). Hence, per capita income is a reasonable proxy for gross

domestic product.

E V i , t h e e c o n o m i c v a r i a b l e s , i n c l u d e p o v e r t y , i n c o m e i n e q u a l i t y a n d r e a l p e r

capita income in 1979.^{3 }I use the percentage of population falling below the poverty line,

fixed by the U.S. government to measure poverty. The U.S. Census uses people’s

(individual and family) pre-tax income to compute poverty status. The income includes

transfer payments, non-cash benefits (such as food stamps), and excludes capital gains or

losses. Each person or family is assigned one of the 48 possible poverty thresholds based

2 I use the BLS database for the CPI values to calculate the real per capita income. The BLS uses 1983 as the base year to measure the CPI changes. Variables without time subscripts indicate that they do not measure the variation over time. 3

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