Income Distribution Dependence of Poverty Measure: A Theoretical Analysis

Abstract

With a new deprivation (or poverty) function, in this paper, we theoretically study the changes in poverty with respect to the `global' mean and variance of the income distribution using Indian survey data. We show that when the income obeys a log-normal distribution, a rising mean income generally indicates a reduction in poverty while an increase in the variance of the income distribution increases poverty. This altruistic view for a developing economy, however, is not tenable anymore once the poverty index is found to follow a pareto distribution. Here although a rising mean income indicates a reduction in poverty, due to the presence of an inflexion point in the poverty function, there is a critical value of the variance below which poverty decreases with increasing variance while beyond this value, poverty undergoes a steep increase followed by a decrease with respect to higher variance. Following these results, we make quantitative predictions to correlate a developing with a developed economy.

13 pages in single spaced latex, 4 figures, submitted to 'Econometrica'

References in corpus (5)

• Evidence for Power-law tail of the Wealth Distribution in India
• The Power-law Tail Exponent of Income Distributions
• Correlation between Risk Aversion and Wealth distribution
• Inequalities of wealth distribution in a conservative economy
• The distribution of wealth in the presence of altruism for simple economic models

Cited by in corpus (4)

• Proportionate vs disproportionate distribution of wealth of two individuals in a tempered Paretian ensemble
• Poverty Index With Time Varying Consumption and Income Distributions
• Stochastic Effects in a Discretized Kinetic Model of Economic Exchange
• Taxes in a simple wealth distribution model by inelastically scattering particles