Output volatility in the OECD: Are the member states becoming less vulnerable to exogenous shocks?
Bibliographic record
Abstract
This paper analyses the vulnerability of OECD member states to external shocks by estimating the degree of asymmetric effects from positive and negative shocks. We use asymmetric conditional heteroscedasticity models with endogenously determined regime changes in a context of progressive moderation in both moments. The results suggest that recessions are associated with higher volatility and significant leverage effects. The estimated impacts of negative and positive shocks amount to 0.961 and 0.028 respectively. The disaggregated analysis over different periods reveals an increasing pattern of these asymmetries, as well as huge differences among the countries. The country-specific analysis suggest an increasing vulnerability to negative exogenous shocks in Australia, Denmark, Finland, Japan, Mexico, the Netherlands, Turkey and the United Kingdom, although with different levels, and decreasing vulnerability in Canada, Greece, Italy and New Zealand. Finally, some economies seem to have developed higher levels of immunity to external shocks by reaching balanced effects from positive and negative shocks. Among these are the largest European economies, together with the northern economies, the United States and the wealthiest economies of Luxembourg and Switzerland.
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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 | 0.003 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.007 |
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; both teacher heads agree on what is shown here.
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".