Trade Deficit And Currency Devaluation: Testing The J-Curve
Bibliographic record
Abstract
This paper is testing empirically the effect of a devaluation of a currency on the trade account of the country, the J-curve effect, by using the trade between the U.S. and seven countries (Euro-zone, Mexico, Canada, United Kingdom, Switzerland, Japan, and Australia). A devaluation (depreciation) of the U.S. dollar is increasing the spot exchange rate ($/FC) and increases the price of imports and reduces the price of exports. Then, imports are falling and exports are increasing and the trade account is improved in the long-run. In the short-run, the trade account is deteriorated because the international trade transactions are pre-arranged and the invoices are in foreign currency, so it cannot be adjusted. This J-curve hypothesis is tested by using a regression equation and a VAR model, where the volatility of the real exchange rate (TOT) is specified with a GARCH-M process. Also, different stationary tests are taking place, like, unit root and cointegration ones. The empirical results mostly are supporting the J-curve effect.
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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 | 0.006 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".