Mean Diversion: When Getting Back to the Old Economy Isn’t Possible
Why this work is in the frame
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Bibliographic record
Abstract
Policy makers love to speak about restoring the economy and the associated “good” jobs as voters imagine they were in the past. But is such economic nostalgia reasonable in a dynamic global economy? Moreover, has it actually been true that the economy, and particularly the labor market, were ever as stable as we imagine? Our work here suggests that the labor market has been constantly evolving since 1970 and that there is no tendency to return to “normal” if such a normal were to be defined as it was in the good old days. Moreover, labor market policies built on such nostalgia in an attempt to return to the past are misplaced at best and likely to hurt workers more by providing false hopes and also lead to a misallocation of economic resources than if forward looking policies were adopted to adapt workers for the future of the labor market opportunities. Our efforts suggest that since 1970 the mean and standard deviation of employment growth had actually been decreasing for each decade up until the 1990-99. For the most recent (2000-09) period, the standard deviation shows an uptick and a significant reduction in the mean. Moreover, when we evaluate the entire period as a whole, 1970-2009, we find that the trend coefficient is statistically significant and has a negative sign. That implies the employment growth rate has a decreasing pattern over time. In addition, the high volatility in the employment series is evidence by a standard deviation (1.93%) that is greater than the mean (1.63%). We apply the traditional unit root tests, efficient unit root tests, and unit root tests with structural break on the employment series. In addition, we follow Hamilton’s approach and apply an Auto Regressive Conditional Heteroscedasticity (ARCH) approach on the employment series Our results suggest that the level of the employment growth rates is mean-diverting and subject to a structural break. Second, in the presence of the ARCH effect, OLS standard errors can be misleading, with a spurious regression possibility. Finally, the ARCH effect and unit root problem have serious consequences for forecasting and the forecast band could be narrower than the actual. Key Words: Employment; Structural Change; ARCH; Mean Diversion.JEL Classification: C10; J21; J30
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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 | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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