The Impacts of Renminbi Appreciation on Trades Flows and Reserve Accumulation in a Monetary Trade Model
Bibliographic record
Abstract
Given the rapidly growing reserves in Asia (China, Japan, Korea, Taiwan) and the pressures from trading partners to revalue, there is a need to examine commercial policy in more than a pure barter model.Here we evaluate the joint impacts of exchange rate appreciation on trade flows and country surpluses using a general equilibrium trade model with a simple monetary structure in which the trade surplus is endogenously determined in the exchange rate setting country and the exchange rate is exogenous.We illustrate its application to the Chinese case using calibration to 2005 data.Our results, while elasticity dependent, suggest that the impacts of Renminbi (RMB) revaluation on the surplus are proportionally larger than on trade flows, and that changes in trade flows can be substantial.Different treatments of China's processing trade have small impact on changes in China's trade flow under RMB appreciation, but significant impacts on the change in the surplus.Results are elasticity dependent; larger substitution elasticities in preferences yield larger effects on trade flows and the surplus.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".