| Summary: | This study focuses on people who moved out of poverty during the decade from 1995 to 2005 in rural areas of four Indian states: Andhra Pradesh, Assam, Uttar Pradesh, and West Bengal. It also considers people who have fallen into poverty, those who have remained poor, and some who have never been poor but who live alongside poor people in the same communities. The author started by setting aside official and expert opinions, ideologies of the right and left, and, to the extent possible, the beliefs and assumptions of the rich and the middle class, including the own preconceived notions. The study is unique in four ways. First, it examines changes in poverty status of the same households over time. Most poverty studies are snapshots of the poor taken at a particular point in time, with extrapolations made by comparing them with the rich at that same point in time. In the study, the author focus on understanding the dynamics of change by asking individuals to recall their life stories, particularly what happened to them over the past decade? Second, most poverty studies are conducted at the national, state, or district level. The author focuses on local communities, mainly villages, as the unit within which individuals and households are embedded. There is much variation between villages, even within a district, and our sampling strategy enables us to examine these community-level differences. Third, the author relies primarily on nonstandardized data collection methods, including life stories and discussion groups. The author complement these with data the author gather using household and community-level questionnaires. Finally, since the author deliberately adopted an open-ended approach, the author uses inductive methods to systematically aggregate data from life stories and individual discussions over 50,000 pages of notes. The author started with broad questions rather than a particular conceptual framework, but the author did impose a framework after six months of inductive data analyses, before starting the quantitative data analyses.
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