RMB Exchange Rate and China’s Economic Growth: The Empirical Analysis from a Structural VAR Model
Bibliographic record
Abstract
This paper analyzes the relationship between the exchange rate and the real GDP of China in the long period from 1952 to 2014 using a structural VAR model. We examine the mutual effect of the two variables in three periods: The results show that there is no obvious relationship between the exchange rate and real GDP before China’s reform and opening-up period. However, a significant positive correlation is found in the sample of 1979-1993, which means that the depreciation of the RMB is associated with the output increases. The direction between the exchange rate and real GDP becomes negative after 1994, indicating that RMB appreciates with the output increases in this period. In addition, based on Granger causality test, we found the exchange rate could Granger causes GDP after 1978, but there is no Granger causality connection between the two variables before 1978.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".