MétaCan
Menu
Back to cohort
Record W2809870571 · doi:10.15353/rea.v10i2.1441

Public Investment, Government Indebtedness and Transitional Dynamics

2018· article· en· W2809870571 on OpenAlexaffvenue
Constantine Angyridis, Panagiotis Tsintzos

Bibliographic record

VenueReview of Economic Analysis · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFiscal Policy and Economic Growth
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsEconomicsPublic financeMonetary economicsDebtInvestment (military)Public capitalIndeterminacy (philosophy)Government revenueGovernment (linguistics)Government debtRevenueMacroeconomicsTax revenueGovernment spendingFiscal policyMarket economyFinancePublic investment

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0030.003
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.046
GPT teacher head0.240
Teacher spread0.193 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2018
Admission routes2
Has abstractyes

Explore more

Same venueReview of Economic AnalysisSame topicFiscal Policy and Economic GrowthFrench-language works237,207