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