Ricardian equivalence, expansionary fiscal contraction and the stock market: a VECM approach
Bibliographic record
Abstract
The effect of government taxation on future consumption has been explained in three ways: the Keynesian approach, the Ricardian Equivalence proposition and the German view of Expansionary Fiscal Contraction (EFC). This paper reports empirical evidence on the validity of these explanations by examining the impact of a shock in government taxation upon private consumption, once the effect of the stock market is removed. A vector error-correction model is estimated for the USA, Japan, Germany, France, the UK, Italy and Canada for 1950–1997 and the impulse response functions of a shock in taxation and in expenditure are examined. The responses to an increase in government taxation appear to lend support to the EFC, while the responses to an increase in government expenditure upon consumption suggest that the reaction of private consumption is more in line with the traditional Keynesian approach.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".