Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Microfinance Impact Assessment× | Randomized Evaluation in Development× | |
|---|---|---|
| Область | Development Studies | Development Studies |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 2010 | 2003 |
| Автор метода≠ | Dean Karlan, Jonathan Zinman; Banerjee, Duflo, Glennerster & Kinnan; J-PAL | Esther Duflo, Abhijit Banerjee, Michael Kremer; J-PAL / IPA |
| Тип≠ | Programme impact evaluation | Experimental impact evaluation design |
| Основополагающий источник≠ | 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 ↗ | Banerjee, A. V., & Duflo, E. (2009). The Experimental Approach to Development Economics. Annual Review of Economics, 1, 151–178. DOI ↗ |
| Другие названия≠ | Microcredit Impact Evaluation, Microfinance Impact Evaluation, Microcredit Impact Assessment, Microsavings Impact Assessment | Randomized Controlled Trials, Field Experiments in Development, RCTs in Development Economics, Randomized Field Trials |
| Связанные | 4 | 4 |
| Сводка≠ | 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. | Randomized evaluation applies the logic of the controlled experiment to development policy: an intervention — a school grant, a deworming pill, an insurance product — is assigned at random to some units and withheld from others, so that any subsequent difference in outcomes can be attributed causally to the intervention rather than to confounding. Championed from the early 2000s by the Abdul Latif Jameel Poverty Action Lab (J-PAL) and Innovations for Poverty Action (IPA), the approach earned its leading proponents — Esther Duflo, Abhijit Banerjee, and Michael Kremer — the 2019 Nobel Memorial Prize in Economics for transforming how anti-poverty programmes are tested. |
| ScholarGateНабор данных ↗ |
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