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| Randomized Evaluation in Development× | Microfinance Impact Assessment× | |
|---|---|---|
| Bidang | Development Studies | Development Studies |
| Keluarga | Process / pipeline | Process / pipeline |
| Tahun asal≠ | 2003 | 2010 |
| Pengasas≠ | Esther Duflo, Abhijit Banerjee, Michael Kremer; J-PAL / IPA | Dean Karlan, Jonathan Zinman; Banerjee, Duflo, Glennerster & Kinnan; J-PAL |
| Jenis≠ | Experimental impact evaluation design | Programme impact evaluation |
| Sumber perintis≠ | Banerjee, A. V., & Duflo, E. (2009). The Experimental Approach to Development Economics. Annual Review of Economics, 1, 151–178. DOI ↗ | 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≠ | Randomized Controlled Trials, Field Experiments in Development, RCTs in Development Economics, Randomized Field Trials | Microcredit Impact Evaluation, Microfinance Impact Evaluation, Microcredit Impact Assessment, Microsavings Impact Assessment |
| Berkaitan | 4 | 4 |
| Ringkasan≠ | 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. | 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. |
| ScholarGateSet data ↗ |
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