Are Shocks to Unemployment Rate in OECD Countries Permanent or Temporary? Evidence From Unit Root Tests With Non-Normal Errors
Bibliographic record
Abstract
In this paper, we tested the validity of unemployment hysteresis for the 21 Organisation for Economic Cooperation and Development (OECD) countries in the 1990Q1-2017Q3 period using recently developed unit root tests with structural breaks and non-normal errors.There are three different economic approaches to unemployment in the literature: natural-rate hypothesis, structuralist hypothesis, and unemployment hysteresis.Overall, we found support for unemployment hysteresis in 11 of the 21 OECD countries (Australia, Canada, Spain, Finland, France, Italy, Japan, Mexico, Norway, Portugal and Sweden).According to this hypothesis, shocks on unemployment have a permanent effect, and unemployment rates have no tendency to revert to a steady state in the long run.Conversely, the hysteresis hypothesis was rejected for 10 of the 21 OECD countries (Belgium, Chile, Denmark, Ireland, Korea, Luxemburg, Netherlands, New Zealand, the United Kingdom, and the United States) in at least one unit root test.We found the structuralist hypothesis in all 10 of these countries, whereas we could not find the natural-rate hypothesis.
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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 | 0.007 | 0.049 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".