Testing Unemployment Hysteresis with Multi-Factor Panel Unit Root: Evidence from OECD Countries
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Bibliographic record
Abstract
Hysteresis is a dominant feature of unemployment in numerous countries. According to the hysteresis hypothesis, it is a well-known fact that high unemployment may persist and remain an economic threat in the long run if policy measures are not taken. In this study, it is tested whether the unemployment rates for 10 selected countries of the Organisation for Economic Co-operation and Development (OECD) (Belgium, Canada, Czech Republic, Estonia, France, Japan, Netherlands, Spain, Britain and the USA) contain unit root or not, in other words, whether the hysteresis effect is valid for these countries. For this purpose, this study utilises the concept of the multi-factor panel unit root test proposed by Pesaran, Smith and Yamagata. This method measures cross-section dependence through factors. The test analyses whether the unit root is valid or not, using information about a sufficient number of additional explanatory variables. The characteristic of these additional variables is that they must share a common factor with the variable whose stationarity is tested. It is accepted that this common factor causes cross-sectional dependence. We have taken tax wedge, trade union density and minimum wage as factors that cause cross-sectional dependency and affect unemployment hysteresis. In this test developed by the authors, in the case of a multi-factor error structure, the test procedure is completed by using the information contained in 3 additional variables. The study explores not only the validity of unemployment hysteresis but also the factors that affect the rigidity of the unemployment rate. However, the research was unable to encompass the entire OECD countries and all times because of the lack of data. The results showed that the hysteresis is valid for 10 selected OECD countries.
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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 | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it