Bibliographic record
Abstract
In this paper, we quantify the changes in the relationship between international forces and many key US macroeconomic variables over the 1984-2005 period, and analyze changes in the monetary policy transmission mechanism. We do so by estimating a Factor-Augmented VAR on a large set of US and international data series. We find that the role of international factors in explaining US variables has been changing over the 1984-2005 period. However, while some US series have become more correlated with global factors, there is little evidence suggesting that these factors have become systematically more important. We don't find strong evidence of a change in the transmission mechanism of monetary policy due to global forces. Taking our point estimates literally, global forces do not seem to have played an important role in the US monetary transmission mechanism between 1984 and 1999. In addition, since the year 2000, the initial response of the US economy following a monetary policy shock ---the first 6 to 8 quarters ---is essentially the same as the one that has been observed in the 1984-1999 period. However, point estimates suggest that the growing importance of global forces might have contributed to reducing some of the persistence in the responses, two or more years after the shocks. Overall, we conclude that if global forces have had an effect on the monetary transmission mechanism, this is a recent phenomenon.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".