Trade, migration and productivity: A quantitative analysis of China
Bibliographic record
Abstract
This Version: May 2015 (Please contact us for the latest version if you plan to cite the paper) In this paper we study costs of goods and labour flows as a soure of labour mis-allocation both across regions and across firms and sectors within a region. We de-velop a general equilibrium model of internal and external trade with worker selection across locations and costs to both trade and migration. We estimate these costs using unique data on China’s trade and migration and quantify the aggregate productivity and welfare losses generated by these frictions. The costs were high in the early 2000s, but declined afterwards. We quantify the consequences of these declines and find the reduction in trade and migration costs accounts for 36 % of China’s aggregate GDP growth between 2002 and 2007. We also find that reduction in internal trade costs and migration costs dominate external trade liberalization as a source of aggre-gate productivity growth and welfare gains between 2002 and 2007. Finally, despite some decline, migration cost in China are still very high and China would see very
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".