Economic Growth and Government Debt of Six Large National Economies before and after the 2008 Financial Crisis
Bibliographic record
Abstract
This paper investigates the causal relationship between economic growth and government debt of six large national economies ten years before and ten years after the 2008 financial crisis. There have been numerous studies on whether government debt has any negative effect on economic growth. The results of most empirical studies are mixed depending on the levels of government debt, the countries included in the sample, the sample periods chosen, and the methodologies employed. This paper focuses on six large national economies, namely, the United States, Japan, Germany, the United Kingdom, France, and Canada during the periods ten years before and ten years after the most recent financial crisis of 2008. It is found that there are significant increases in the level of government debt and decreases in economic growth during the ten years after the financial crisis for all six countries. Our results show that the hypothesis that government debt does not Granger-cause economic growth is rejected for all six countries combined for the pre- financial crisis sub-period and the whole sample period, but not for the post financial crisis sub-period. The hypothesis that economic growth does not Granger-cause government debt is also rejected for both the pre- and post- financial crisis sub-periods as well as for the whole period. In short, our investigation documented a bidirectional Granger causality between government debt and economic growth during periods ten years before, ten years after, and the combined periods before and after the 2008 financial crisis. The evidence also suggests that economic growth reduced government debt for most countries during all three sample periods.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".