Salīdzināt metodes

	Microfinance Impact Assessment	Poverty Probability Index
Nozare	Development Studies	Development Studies
Saime	Process / pipeline	Process / pipeline
Izcelsmes gads	2010	2005
Autors	Dean Karlan, Jonathan Zinman; Banerjee, Duflo, Glennerster & Kinnan; J-PAL	Mark Schreiner; Grameen Foundation (now Innovations for Poverty Action)
Tips	Programme impact evaluation	Poverty-likelihood scoring instrument
Pirmavots	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.	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.
Citi nosaukumi	Microcredit Impact Evaluation, Microfinance Impact Evaluation, Microcredit Impact Assessment, Microsavings Impact Assessment	PPI, Progress out of Poverty Index, Poverty Scorecard, Poverty Likelihood Scorecard
Saistītās	4	4
Kopsavilkums	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.	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.