Economic Policy Uncertainty and Real Output: Evidence from the G7 Countries
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
We use a new uncertainty index, proposed by Baker et al. (2016), and a relatively new methodology by Kilian and Vigfusson (2011), to assess the impact of economic policy related uncertainty on real economic activity. We use monthly data, over the period from 1985:1 to 2015:3, and impulse response functions to investigate how the economies of the G7 countries respond to positive and negative economic policy uncertainty shocks of different magnitude. We find that economic policy uncertainty is countercyclical, that the effects of uncertainty shocks increase with size, and that the responses of real output to positive and negative economic policy uncertainty shocks are country specific. Our research is important for policymaking and in favor of policies that remove economic uncertainty and its negative effects on the economy. We argue that some control over yellow journalism, a transparent tax system, and a set of predictable fiscal and monetary policies can minimize the social costs of economic policy uncertainty.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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