Cash and Conflict: Large-Scale Experimental Evidence from Niger
Bibliographic record
Abstract
Conflict undermines development, while poverty, in turn, breeds conflict. Policy interventions such as cash transfers could lower engagement in conflict by raising poor households' welfare and productivity. However, cash transfers may also trigger appropriation or looting of cash or assets. The expansion of government programs may further attract attacks to undermine state legitimacy. To investigate the net effect across these forces, this paper studies the impact of cash transfers on conflict in Niger. The analysis relies on the large-scale randomization of a government-led cash transfer program among nearly 4,000 villages over seven years, combined with geo-referenced conflict events that draw on media and nongovernmental organization reports from a wide variety of international and domestic sources. The findings show that cash transfers did not result in greater pacification but—if anything—triggered a short-term increase in conflict events, which were to a large extent driven by terrorist attacks by foreign rebel groups (such as Boko Haram) that could have incentives to “sabotage” successful government programs.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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".