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Poverty, Income Inequality and Economic Growth in U.S. Counties: - page 7 / 33





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damage physical and human capital. Second, people waste their time and effort in such

disruptive activities, which they can otherwise use for productive purposes. As Bhatta

(2001) notes, social unrest can also have some positive effects on growth of certain

industries such as security, surveillance or legal services.

Alesina and Rodrik (1994) develop an endogenous growth model with distributive

conflicts between labor and capital, and provide evidence that inequality reduces growth

in democracies, while the effect disappears in non-democracies. Persson and Tabellini

(1994) use a politico-economic model and show that initial level of inequality negatively

affects subsequent economic growth only in democracies. They use income accruing to

the middle quintile of the distribution as a measure of income equality.

Deininger and Squire (1998) use a similar model and show that asset inequality is

negatively related to long-term growth. They use the data set from Deininger and Squire

(1996) that most development economists consider as the most reliable, comprehensive

and standardized data set on inequality. They also present evidence that inequality

reduces income growth for the poor but not for the rich. Li and Zhou (1998), employ a

panel analysis covering 46 countries with the data averaged over a five-year period. They

use a more expanded set of explanatory variables that also include urbanization ratio,

population growth rate, and an indicator variable denoting whether a country is a

democracy. They show that income inequality increases economic growth, and developed

countries have a more equal income distribution compared to developing countries.

Barro (1999) divides his sample into developed and less-developed countries

based on real GDP. He employs a panel regression that includes a broad range of

countries to show that there is little overall relationship between income inequality and


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