Land Tenure Security and Youth Credit Access for Cocoa Cultivation: A Systematic Review of Regression Discontinuity Evidence from Côte d'Ivoire
Bibliographic record
Abstract
{ "background": "Secure land tenure is posited as a critical determinant of agricultural investment, particularly for capital-intensive tree crops like cocoa. In Côte d'Ivoire, the world's largest cocoa producer, youth engagement is vital for sector sustainability, yet their access to formal credit remains constrained. The causal link between formal land titling and credit access for this demographic is not well established.", "purpose and objectives": "This systematic review synthesises empirical evidence on the causal effect of formal land titling on credit access for youth cultivating cocoa in the country's cocoa belt, focusing specifically on studies employing regression discontinuity designs (RDD) to identify local average treatment effects.", "methodology": "A systematic search was conducted across multiple academic databases. Studies were screened and selected based on pre-defined eligibility criteria: they must use a sharp or fuzzy RDD to evaluate a land formalisation programme's impact on credit outcomes for youth (aged 18-35) cocoa farmers. The review protocol followed PRISMA guidelines. The core RDD model for analysis is $Yi = \\alpha + \\beta Di + f(Xi - c) + \\epsiloni$, where $D_i$ is titling status, $c$ is the cutoff, and robust standard errors are clustered at the village level.", "findings": "The review identified a limited but coherent body of evidence. A key finding is that formal titling increases the likelihood of obtaining formal credit by approximately 15-20 percentage points for eligible youth near the assignment cutoff. However, this effect is highly localised and sensitive to the bandwidth selection; estimates are not statistically significant at conventional levels when using optimal bandwidths with robust bias-corrected inference.", "conclusion": "Formal land titling can improve credit access for youth cocoa farmers, but the measured effects are localised and methodologically fragile. The RDD evidence does not support broad generalisations of titling as a standalone solution for widespread youth credit constraints in the sector.", "recommendations": "Future research
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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 | 0.019 | 0.085 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.007 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".