Public Investment, Government Indebtedness and Transitional Dynamics
Bibliographic record
Abstract
This paper considers an endogenous growth model with public capital and government debt. In setting the level of public investment each period, the government is assumed to follow two commonly used in the growth literature fiscal rules: public investment is either equal to a constant fraction of output or equal to a constant share of tax revenues. In our model, we allow revenues to be raised by the government through progressive income taxation and bonds issue. For both fiscal rules, we show that the potential occurrence of either indeterminacy or instability crucially depends on whether the government is a debtor or a creditor. In particular, government indebtedness causes the economy to be prone to either belief-driven aggregate fluctuations or unstable dynamics. This is a novel result in the related literature which has largely overlooked the role of public debt as a possible contributing factor to the presence of indeterminacy and instability in growth models.
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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) | 0.001 | 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 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".