Improving or disappearing: Firm-level adjustments to minimum wages in China
Bibliographic record
Abstract
We here consider how Chinese firms react to higher minimum wages, exploiting the 2004 minimum-wage Reform in China. After this reform, we find that the wage costs for surviving firms that were more exposed to minimum wage hikes rose, but their employment and profitability were not affected. This came about due to significant productivity gains among surviving exposed firms. Our results are robust to pre-trend analysis and an IV strategy. However, the survival probability of firms most exposed to minimum-wage hikes fell after the Reform. Firm-level productivity gains partly came from better inventory management and greater investment in capital, at the cost of a reduction in firm-level cash flow. We show that competing explanations are unlikely. In particular, there is no evidence of lower fringe benefits compensating for higher wages, the substitution of less-paid/less-protected migrants for incumbent workers, or firm-level adjustment through higher prices instead of higher productivity. This firm-level productivity adjustment to the minimum wage might be particularly relevant for developing countries where inefficiencies are still pervasive.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".