Nonfarm entrepreneurship, crop output, and household welfare in Tanzania: An exploration of transmission channels
Bibliographic record
Abstract
Abstract This study analyzes panel data from the Tanzania Living Standards Measurement Study‐Integrated Surveys on Agriculture by the World Bank to investigate the impact of nonfarm entrepreneurship as a nonfarm activity on the value of crop output and household welfare, and to explore the potential transmission channels among rural farm households. Using a dynamic panel model to address endogeneity, our results reveal that nonfarm entrepreneurship has a positive impact on the value of crop output and household welfare. Our findings suggest that income from nonfarm entrepreneurship may enhance crop output through crop production technology and credit access, and household welfare through an increase in consumption expenditure and food expenditure as potential transmission mechanisms. Policies that enhance nonfarm entrepreneurship may also reinforce crop production and the welfare of farm households and are thus imperative. We suggest that policies that boost nonfarm sector growth such as agro‐processing and agribusiness enterprise development might achieve the twin objectives simultaneously: enhancing crop production and household welfare [EconLit Citations: C33, D24, Q12, 012].
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".