International information flows, sentiments and cross-country business cycle fluctuations
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Business cycles are strongly correlated between countries. One possible explanation (beyond traditional economic linkages like trade or finance) is that consumer or business sentiments spread over borders and affect cyclical fluctuations in various countries. We first lend empirical support to this concept by showing that sentiments travel fast between countries, most probably directly via information flows. Then we embed this idea into a structural two‐economy new Keynesian framework where noisy information available internationally can generate cyclical fluctuations (comovement of GDP, consumption, investments, and inflation) in both countries. Estimation with US and Canadian data reveals a significant role of US noise shocks in generating common fluctuations. They explain 20%–40% of consumption variance in the US and Canada and raise the correlation between these variables by up to unity in periods of sentiment breakdowns. We also show that our estimated noise shock can be interpreted as a sentiment shock.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it