Causality Between the Tax Burden of Direct Taxes and Economic Growth in European Union Countries with Proportional Taxation
Bibliographic record
Abstract
The present study examines the relationship between economic growth and the tax burden that is formed as a result of income taxes. The main goal is to verify whether there is a link between these research variables in the long run and if this is confirmed, to analyze the manner in which these processes interact. The research applies a range of econometric techniques, including stationary tests, pairwise Granger causality test, Johansen cointegration test, impulse functions, and variance decompositions in order to investigate causality in the short- and long-term. The study is based on 49 observations and covers four European Union (EU) member states (Bulgaria, Hungary, Romania, and Estonia), which continue to impose a proportional (flat) tax on personal and corporate income. The analysis relies on quarterly data for the period 2013Q1–2025Q1. The results obtained are quite heterogeneous, which can be explained by the significant differences in the tax policy pursued, as well as by a number of other features determining the growth of national economies.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 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".