Impact measurement in microfinance: Is the measurement of the social return on investment an innovation in microfinance?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
What is the impact of microfinance and how can it be measured? This paper analyzes the current status of microfinance and methods that are used to analyze its outreach and its impact. Especially on the background of the discussion about a mission drift in microfinance away from a poverty alleviation concept to a financial system approach the impact indicators of microfinance are discussed. So far, many methods measure the output of microfinance rather than the outcome. An analysis of the current mission of the 50 biggest microfinance institutions will be presented that shows that their missions are much more diverse than poverty alleviation or the financial system approach and that it is not possible to connect missions of microfinance institutions with their outreach. Based on this analysis the concept of Social Return on Investment (SROI) and social cost-benefit calculation will be discussed as methods to assess the impact of microfinance. We apply the methods in an exemplary way to demonstrate how they could be used. Based on this analysis we conclude that outcome-based approaches are better suited to measure the impact and outreach of microfinance but that they need much higher efforts because necessary data has to be assessed and useful indicators have to be developed.JEL Codes: A13, C18, C83, D61, G20
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it