The Impact of Decarbonization Tax on Economic Growth - Evidence for Western Balkan Countries
Bibliographic record
Abstract
Decarbonization and carbon tax have become increasingly relevant in recent years, due to the economic implications in industry, and especially in the energy sector.Naturally, the implementation of decarbonization policies in Western Balkans countries is a necessity for mitigating the environmental crisis in the region.This study examines the impact of carbon tax on economic growth in Western Balkan countries including Croatia.Our research is a quantitative empirical study based on regression model.Panel data on empirical study is based on 91 years of observation of Western Balkan countries, each of these countries has a 13-year observation.Data includes two sets of variables and examines the panel data obtained from World Bank Open Data over the period 2010-2022.The results indicate a significant impact of CO2 emission tax on economic growth in Western Balkan countries.The result shows that CO2 emission tax and economic growth are negatively correlated with each other.The results indicate a significant impact of CO2 emission tax on economic growth in Western Balkan countries.A percentage CO2 emission tax, causes a 2.52 decrease in economic growth under ceteris paribus average.CO2 emission tax, FDI, GDP growth and unemployment rate indicate an inelastic relationship.The highest negative impact is shown in the state of Kosova, followed by Serbia and Bosnia and Herzegovina.The high negative impact on these countries is due to their high reliance on coal in energy production.
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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 | 0.003 |
| 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) | 0.002 | 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".