Hysteresis vs. natural rate of unemployment in Brazil and Chile
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
Abstract This article examines the hysteresis hypothesis in the unemployment rates of Brazil and Chile using an LM unit root test with two endogenous breaks. The phenomenon is confirmed for both countries. However, the hysteresis hypothesis is able to account for only a small part of the unemployment evolution. Notes 1 A third theory of unemployment is described by Phelps (Citation1994). It suggests that most shocks to unemployment are temporary with occasional (but permanent) changes in the natural rate. As a result, the unemployment rate can be defined as a stationary process around a small number of (permanent) structural breaks. 2 Another argument for the presence of hysteresis in unemployment has to do with human capital depreciation when an individual is unemployed for a long period of time. 3 Recently, Mikhail et al. (Citation2005) found evidence that both the aggregate and sectoral Canadian unemployment exhibit persistence. 4 As usual, we define a k-max to choose k and use the (approximate) 10% value of the asymptotic normal distribution, 1.645, to assess the significance of the last lag. 5 We decided not to extend the period due to changes in IBGE's methodology. 6 For Chile, we decided to use the series for the metropolitan area because it is longer than the national rate and the figures are quite close. 7 An ADF test was performed previously, as a benchmark. Hysteresis was found in both series at a 10% level. 8 We also use k-max = 8, but the results don’t change. 9 These results don’t change if we use a test with just one break in level and trend.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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) | 0.000 | 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