Sammenlign metoder
Gjennomgå de valgte metodene side om side; rader som avviker, er uthevet.
| Poverty Probability Index× | Microfinance Impact Assessment× | |
|---|---|---|
| Fagfelt | Development Studies | Development Studies |
| Familie | Process / pipeline | Process / pipeline |
| Opprinnelsesår≠ | 2005 | 2010 |
| Opphavsperson≠ | Mark Schreiner; Grameen Foundation (now Innovations for Poverty Action) | Dean Karlan, Jonathan Zinman; Banerjee, Duflo, Glennerster & Kinnan; J-PAL |
| Type≠ | Poverty-likelihood scoring instrument | Programme impact evaluation |
| Opprinnelig kilde≠ | Schreiner, 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 ↗ | Banerjee, A., Duflo, E., Glennerster, R., & Kinnan, C. (2015). The Miracle of Microfinance? Evidence from a Randomized Evaluation. American Economic Journal: Applied Economics, 7(1), 22–53. DOI ↗ |
| Alias | PPI, Progress out of Poverty Index, Poverty Scorecard, Poverty Likelihood Scorecard | Microcredit Impact Evaluation, Microfinance Impact Evaluation, Microcredit Impact Assessment, Microsavings Impact Assessment |
| Relaterte | 4 | 4 |
| Sammendrag≠ | The 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. | Microfinance impact assessment is the set of methods used to measure the causal effects of small loans, savings, and related financial services — long promoted as a tool against poverty — on borrowers' income, business activity, consumption, and empowerment. After two decades in which observational studies reported large gains, a wave of randomized evaluations from around 2010 onwards, exemplified by Banerjee, Duflo, Glennerster, and Kinnan's Hyderabad study with Spandana and Karlan and Zinman's randomised credit-scoring work, delivered a more sober and credible verdict. |
| ScholarGateDatasett ↗ |
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