Asymmetry, Uncertainty and International Trade
Bibliographic record
Abstract
This paper studies the role of economic policy uncertainty on the US trade with Canada, China, Germany, Japan and the United Kingdom. This paper contributes to the literature by analysing the asymmetric impact of policy uncertainty on the US trade from December 1989 to December 2016. Results suggest that there is a negative relationship between the economic policy uncertainty and the US trade flows. Further, US trade responds more sensitively to rise in the uncertainty as compared to an equal negative shock, confirming the asymmetric hypothesis both in the short and long run. Comparing the respective uncertainty indices, US EPU has a significantly greater impact on the trade relative to the EPU of its trading partners. These findings have both demand and supply side implications i.e. increase in the economic policy uncertainty can reduce the aggregate consumption significant as well as due to uncertain profit margins, businesses can choose to delay long term investment projects and inventory levels resulting in a wide spread recessionary effect on the US business cycle.
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How this classification was reachedexpand
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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".