Labor Supply Responses to Adverse Shocks under Credit Constraints: Evidence from Bukidnon, Philippines
Bibliographic record
Abstract
The ability of households to insure consumption from adverse shocks is an important aspect of vulnerability to poverty. How is consumption insurance achieved in a low-income setting where formal credit and insurance markets have been observed to be imperfect or missing? Using 2003 data from the Philippine province of Bukidnon, we investigate how labor supply is used to buffer transitory income shocks in light of credit constraints. We find that the most vulnerable households are those with little education and with few or no able-bodied male members. Appropriate policy responses include countercyclical workfare programs directed at households with high female-to-male ratios, households with high dependency ratios, and households with little or no education, as well as the provision of universal education and health care. These programs are likely to be effective in strengthening the labor endowments of households and improving their ability to cope with adverse shocks in the future.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".