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Summary Compared to the extensive literature on measurement of poverty, the question of how the poor are distributed regionally has received less attention. This paper fills the gap in the literature by providing a conceptual framework to measure inequality in the distribution of the poor. A poverty segregation curve is used to compare a region’s share of the poor population with its share in the overall population. A unique contribution of the paper is formulating a generalized version of the poverty segregation curve. Unlike the segregation curve, the generalized segregation curve also takes average poverty rates into account while ranking distributions. Thus the generalized segregation curve may rank a distribution with substantially lower poverty rates above a distribution with higher poverty rates, when differences between their segregation curves are relatively small. The segregation curves are used to analyze changes in the distribution of the poor in India since the economic reforms in the early 1990s. Poverty rates and shares among all states, territories, and districts in India are estimated using data from the National Sample Survey Organization in 1994, 2004, and 2010. In the decades following the reforms India witnessed high growth rates and declining poverty rates. Despite the reduction in poverty, our analysis is the first to reveal that there was a significant rise in segregation of the poor over time. Some states had disproportionately high share of the poor compared to their share in the total population. Within states, the extent of segregation was lower among some of the poorest states and higher in less poor states. The generalized segregation curves show that the substantial decline in poverty rates since the reforms was not adequate to compensate the rise in segregation of the poor. Increase in segregation was also evident when the poor are identified as those who lacked education, health, and access to basic services. Reducing the segregation of the poor is important if India is to attain regionally balanced economic growth. [ABSTRACT FROM AUTHOR]

Summary In the context of climate change and its effect on poverty, previous studies have shown that productivity shocks in agriculture, such as rainfall variability, affect wages adversely. None of the studies, however, consider the heterogeneity in the impact of these shocks on agricultural wages by gender, a feature which has been studied for demand shocks in urban labor markets for developed countries. Using National Sample Survey data for India from 1993 to 2007, a district-level panel dataset is created to examine how a rainfall shock affects the gender wage gap. The study shows that both female and male wages are positively related to rainfall shocks. Hence, future studies must study the impact of labor market shocks in rural areas on both female and male wages separately. It also finds that the female-to-male wage ratio is significantly positively associated with a rainfall shock in regions where rainfed rice is cultivated, i.e., low (high) rainfall reduces (increases) the female-to-male ratio. The study demonstrates that this result is due to a positive association of demand for female labor with rainfall in these rainfed rice-growing regions. This finding is consistent with the greater marginal value of female labor in rice cultivation, which is also a crop highly sensitive to rainfall variability under rainfed conditions. The paper concludes that the effect of a rainfall shock on the gender wage gap depends upon the gender roles underlying the technology of production, which varies across cropping systems. [ABSTRACT FROM AUTHOR]

India has witnessed high economic growth since the 1980s, and a confirmed reduction in monetary poverty, particularly in poorer states. Poverty, however, has multiple dimensions. This paper thoroughly analyzes the change in multidimensional poverty in India between 1999 and 2006. We find a strong reduction in national poverty and each of its dimensions, but this has not been uniform across regions, castes, or religions. Probing further, we analyze changes in the distribution among the poor people nationally as well as within population subgroups. We find strong reductions among the poorer population nationally, but slower progress for most of the poorest groups. [ABSTRACT FROM AUTHOR]