Economic freedom and democracy: determinant factors in increasing macroeconomic stability
Bibliographic record
Abstract
The main goal of the article is to analyze the role and influence of economic freedom on macroeconomic stability. For this purpose, the authors used the integrated index of economic freedom, calculated by the Heritage Foundation and Democracy Index. It is noted that this index indicator was calculated by the experts from the World Bank using the index of voice and accountability. In the paper, the authors used the multinational panel dataset for 11 countries of the EU for the purpose of checking the correlation between economic freedom, democracy and macroeconomic stability. It should be highlighted that the abovementioned 11 countries are related by the fluctuation of economic growth during the transformation process (1996–2016) from communist party to the democracy and political pluralism. In addition, the authors proposed to add the indicators of political stability and trade openness, which allowed to take into account implementation of flexible macroeconomic instruments, including monetary policy, which towards increasing the economic growth, employment and financial development of the countries. The findings are directed received using the regression equation with fixed and random effects showed the high level of correspondence of the model used with the original observations. Despite the chosen approach to estimate the macroeconomic stability, the findings showed that there is a positive and statistically significant impact of economic freedom and democracy on macroeconomic stability.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".