Property rights, labour markets, and efficiency in a transition economy: the case of rural China
Bibliographic record
Abstract
We investigate the consequences of imperfect factor market development for farm efficiency in North China. We estimate the extent to which an inverse relationship in farm productivity can be attributed to the administrative (as opposed to market) allocation of land, combined with unevenly developed off–farm opportunities. Using a new household survey, we find considerable inefficiency in the use of labour. This inefficiency is alleviated by external labour markets and, to a limited degree, by administrative reallocations. The reallocations do not go far enough, however, which raises important questions about constraints on rental activity and property rights formation more generally. JEL Classification: Q15, O12 Droits de propriété, marchés du travail et efficacité dans une économie en transition : le cas de la Chine rurale . Ce mémoire analyse les conséquences du développement de marchés imparfaits des facteurs de production sur l’efficacité des fermes dans le nord de la Chine. On examine jusqu’à quel point la relation inverse entre la productivité des fermes et leur taille est attribuable à l’allocation administrative de la terre (par opposition à l’allocation par le marché), en combinaison avec le développement inégal des opportunités en dehors de la ferme. Les auteurs utilisent une nouvelle enquête sur les ménages qui révèle une grande inefficacité dans l’utilisation du travail. Cette inefficacité est atténuée par des marchés de travail externes, et, à un moindre degré, par des ré–allocations administratives. Les ré–allocations ne vont pas assez loin cependant. Voilà qui soulève des questions importantes à propos des contraintes sur les activités de location et la formation des droits de propriété en général.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".