HOW DOES NATIONAL FOREIGN TRADE REACT TO THE EUROPEAN CENTRAL BANK’S POLICY?
Bibliographic record
Abstract
This paper examines how external foreign trade reacts to the European Central Bank’s (ECB) Official Discount Rate, considering exports to the US and Japan in EU27 and in four European countries. Although many previous studies have measured the cointegration and causality among exchange rate, exports, and imports, to date, no research has considered these relationships while introducing monetary variables into the analysis. The objective of this article is to fill this gap in the literature. We use the bounds testing approach to cointegration and error-correction modelling to test relations between monetary policy, exports, and terms of trade, making the distinction between short and long-run effects possible. Our datasets include quarterly data on exports, imports, income, relative price, and the official ECB discount rate. The quarterly data starts from the first quarter of 1999 and ends in the last quarter of 2008. The results show that a long-run relationship exists between real exports, real foreign income, real bilateral cross rates and interest rates for a large part of these countries. Also long run parameter estimates are consistent with economic theory in most of the cases. More importantly the statistically significant error-correction term corroborates the results of the long-run parameter.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.004 | 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".