Relationship between external wealth, trade balance, and the real exchange rate : a case study on the US.
Bibliographic record
Abstract
Lane and Milesi-Ferreti (2002) show that a country’s external wealth, trade balance and the real exchange rate are interrelated. They shown that in the long-run, there is a negative relation between the trade balance and the real exchange rate. And that the magnitude of the trade balance coefficient is directly proportional to country size. Inspired by the work of Lane and Milesi-Ferreti (2002), we aim to replicate their work using data of 20 OECD countries from 1970 to 2002 and draw the link between a country’s net foreign asset and its impact on real exchange rate. Besides, we also extend the data set to 2007. Additionally, we work on a case study of the United States (US) and investigate the relationship between the US’s trade position over the years with its 5 major trading partners such as Canada, Japan, China, Mexico and Germany. Finally, we examine the relationship between price of gold and the US dollar exchange rate.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".