The Determinants of Long-term Interest Rates in Eurozone: Taylor Rule and Governance Indicators
Bibliographic record
Abstract
<p>This study aims to search for the determinants of long-term interest rates in the Eurozone. Panel data analysis is employed for 14 Eurozone countries for the period of 2002-2014 to analyze the determinants of long-term interest rates. This study is carried out to find out whether the Worldwide Governance Indicators (WGI), Taylor (1993) rule and also the Eurozone crisis, as a control variable, have an impact on long-term interest rates. As WGI, Voice and Accountability, Political Stability and Absence of Violence/Terrorism, Government Effectiveness, Regulatory Quality, Rule of Law and Control of Corruption are used. The first finding of the empirical study is that inflation gap has an impact on long-term interest rates. Another finding of the study is that Political Stability and Absence of Violence/Terrorism, Government Effectiveness and Regulatory Quality effects long-term interest rates in 14 panel cross-sections. Besides, the analysis shows that the financial crisis in Eurozone as control variable affected long-term interest rates, as would be expected.</p>
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How this classification was reachedexpand
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 | 0.001 |
| 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 | 0.000 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".