Heterogeneous Impacts of Conditional Cash Transfers: Evidence from Nicaragua
Bibliographic record
Abstract
In the last decade, the most popular policy tool used to increase human capital in developing countries has been the conditional cash transfer program. A large literature has shown significant mean impacts on schooling, health, and child labor. This paper examines heterogeneous effects using random-assignment data from the Red de Proteccion Social in rural Nicaragua. Using interactions between the targeting criteria and the treatment indicator, estimates suggest that children located in more impoverished localities experienced a larger impact of the program on schooling in 2001, but this finding is reversed in 2002. Estimated quantile treatment effects indicate that there is considerable heterogeneity in the impacts of the program on the distribution of food expenditures, as well as total expenditures. In particular, households at the lower end of the expenditure distribution experienced a smaller increase in expenditures. This paper also presents evidence of the rank invariance assumption to help clarify the interpretation of the quantile treatment effect in the development literature context.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| 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 source (direct Gemma or distilled Codex), 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".