Bibliographic record
Abstract
The purpose of this paper is to estimate NAIRU for the Turkish economy using the structural VAR method. NAIRU is defined as the part of the measured unemployment rate unrelated with inflation in the long run. The estimates are obtained by applying the bivariate VAR model to quarterly data on unemployment rate and the consumer price index for the period from 1989:01 to 2011:01. In this study, NAIRU shocks and inflation shocks are defined as two types of structural shocks and the shocks are separated from each other by their effects on inflation. According to the findings of the study, NAIRU is observed to be gradually rising in parallel to the economic and social transformation in Turkey between 1989 and 2011. In addition, NAIRU is observed as more volatile during economic crisis experienced in the period 1989-2001 compared to that of the period 2002-2008 in which the more stable growth rates were observed. NAIRU is estimated at an average of 8.4% between the years 1989 and 2001 and at an average of 9.6% from 2002 until the second quarter of 2008. NAIRU is estimated at the average 12.50% after the third quarter of 2008. An estimated rate for the first quarter of 2011 is 10.75%.
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".