Role of Institutional Credit on Agricultural Production: A Time Series Analysis of Pakistan
Why this work is in the frame
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Bibliographic record
Abstract
In our predominant and cash-strapped agrarian sector, adequate credit provision is a definite buttress to implant technological advancements, achieve technical efficiency and hire efficient inputs to uplift agriculture output/income collectively and eradicate poverty eventually. In the midst of beleaguered informal credit sector and recent spurt in banking services in last decade diverted the attention to envisage the formal sector’s optimum potential. In this backdrop, this study is going to explore the role of institutional credit in agricultural production using the time series data for the period of 1972 to 2008. Cobb-Douglas production function is estimated using OLS and all the variables are transformed to per cultivated hectare. Results show that agricultural credit, availability of water, cropping intensity and agricultural labor force are positively significantly related to agricultural production.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it