Monetary Policy Shocks in Open Economies and the Inflation Unemployment Trade-Off: The Case of the Euro Area
Bibliographic record
Abstract
In this paper, we show that in order to obtain a sound identification of Euro Area monetary policy shocks, one needs to deal with the interaction of the European Central Bank and the US Federal Reserve. In other words, a proper identification of monetary policy shocks for an open economy like the Euro Area requires consideration of the US policy rate. Indeed, when we exclude the Federal Funds Rate from an estimated VAR model including a set of Euro Area variables, i.e., Eonia, inflation and unemployment, we detect a wrong sign in the response of inflation to contractionary monetary policy shocks. Moreover, even adding the world price of oil does not help to overcome the problem. Instead, for a sample covering the period 1999–2019, when the Federal Funds Rate and the Euro–Dollar exchange rate are added to the VAR model inflation shows statistically non-significant effects for two years and thereafter decreases. Under this specification of the model, a clear and significant unemployment inflation trade-off emerges. These conclusions are confirmed by using industrial production instead of the unemployment rate in the VAR model.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".