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Poverty Probability Index×Asset Index Construction×
क्षेत्रDevelopment StudiesDevelopment Studies
परिवारProcess / pipelineProcess / pipeline
उद्भव वर्ष20052001
प्रवर्तकMark Schreiner; Grameen Foundation (now Innovations for Poverty Action)Deon Filmer & Lant Pritchett
प्रकारPoverty-likelihood scoring instrumentComposite socioeconomic-status proxy index
मौलिक स्रोतSchreiner, M. (2016). The Poverty Probability Index (PPI): A Brief on Calculating Annual Poverty Rates and Movement Across a Poverty Line. Innovations for Poverty Action / PovertyIndex.org. link ↗Filmer, D., & Pritchett, L. H. (2001). Estimating Wealth Effects without Expenditure Data—or Tears: An Application to Educational Enrollments in States of India. Demography, 38(1), 115-132. DOI ↗
उपनामPPI, Progress out of Poverty Index, Poverty Scorecard, Poverty Likelihood ScorecardWealth Index, Asset Index, PCA Wealth Index, Socioeconomic Status Index
संबंधित44
सारांशThe Poverty Probability Index (PPI), formerly the Progress out of Poverty Index, is a simple, country-specific scorecard that estimates the likelihood that a household is living below a given poverty line. Developed by Mark Schreiner and disseminated first by the Grameen Foundation and later by Innovations for Poverty Action, it reduces poverty measurement to ten easy-to-answer, verifiable questions about household characteristics. The answers produce a score from 0 to 100, which a calibration table converts into the probability that the household falls below national or international poverty lines — a low-cost alternative to a full consumption survey for organizations that need to track the poverty profile of the people they serve.Asset index construction builds a proxy for household wealth or socioeconomic status from observable possessions — durable goods, housing quality, and access to utilities — when reliable income or consumption data are unavailable. The dominant approach, popularized by Deon Filmer and Lant Pritchett in 2001, applies principal component analysis (PCA) to a set of asset variables and uses the first principal component as a set of weights, producing a single wealth score for each household. The method underlies the wealth quintiles reported in Demographic and Health Surveys and many other household surveys across low- and middle-income countries.
ScholarGateडेटासेट
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