Impact of RMB Appreciation on Trade and Labor Markets of China and the USA: A Multi‐country Comparative General Equilibrium Model
Bibliographic record
Abstract
Abstract Since the recent economic crisis, the undervaluation of China's exchange rate has been a focus in the debate on the global policy mix. Using a non‐competitive input–output table, we establish a comparative‐static general equilibrium model to simulate the impact of real exchange rate changes on Sino–US trade and labor markets. The simulation shows that the impacts of a 10‐percent RMB revaluation on the trade surplus of China and the labor market of the USA are more modest than is generally perceived, and the negative impact on the output of the non‐processing industry in China is more significant than that on the processing industry. The Sino–US trade imbalance will continue to deteriorate, China's non‐processing trade surplus will decline and the processing trade will increase, with the combined effect being small. For the USA, labor‐intensive goods imported from China will shift to different Asian countries instead of transferring back to the US market. The simulation results indicate that the impacts of an RMB revaluation on both Chinese and US labor markets would be limited.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 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".