Cattle sharing and rental contracts in an Agrarian economy: evidence from Ethiopia
Bibliographic record
Abstract
Abstract Empirical evidence on the role of cattle sharing and rental contracts in agrarian economies is limited. This article is an investigation of different types of cattle sharing and rental contracts producers in rural Ethiopia adopt. It also investigates why households in rural Ethiopia rely on these contracts that are vulnerable and therefore subject to potential moral hazard problems described in earlier literature. We apply random effect probit and control function econometric methods to household panel data collected in 2005 and 2007 from two agro‐ecological zones in Ethiopia. Controlling for the endogeneity of access to livestock credit, we find that contracts are spatially fragmented and better developed where population density is high and credit and insurance markets are poorly developed. We also find that contracts help cash poor and credit constrained households to improve their herd dynamics, to get access to nonlivestock resources (land, labor and cash) and share risks that could have been difficult without the contract. We show that contracts are rational responses of residents in rural communities characterized by imperfect credit and insurance services, since households with better access to credit are less likely to rely on contracts.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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 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".