Group versus Individual Liability: A Field Experiment in the Philippines
Bibliographic record
Abstract
Group liability is often portrayed as the key innovation that led to the explosion of the microcredit movement, which started with the Grameen Bank in the 1970s and continues on today with hundreds of institutions around the world. Group lending claims to improve repayment rates and lower transaction costs when lending to the poor by providing incentives for peers to screen, monitor and enforce each other's loans. However, some argue that group liability creates excessive pressure and discourages good clients from borrowing, jeopardizing both growth and sustainability. Therefore, it remains unclear whether group liability improves the lender's overall profitability and the poor's access to financial markets. We worked with a bank in the Philippines to conduct a field experiment to examine these issues. We randomly assigned half of the 169 pre-existing group liability "centers" of approximately twenty women to individual-liability centers (treatment) and kept the other half as-is with group liability (control). We find that the conversion to individual liability does not affect the repayment rate, and leads to higher growth in center size by attracting new clients.
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How this classification was reachedexpand
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".