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Government size and openness revisited: the case of financial globalization

2009· article· en· W2047218476 on OpenAlexaff
Alena Kimakova

Bibliographic record

VenueKyklos · 2009
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFiscal Policies and Political Economy
Canadian institutionsYork University
Fundersnot available
KeywordsFinancial integrationEconomicsOpenness to experienceGlobalizationGovernment spendingVolatility (finance)Government (linguistics)International economicsMonetary economicsFinancial marketEmerging marketsMacroeconomicsFinanceMarket economy

Abstract

fetched live from OpenAlex

SUMMARY The volatility of international capital flows to emerging markets has been well documented. Financial globalization may not in general fulfill its theoretical role as a risk sharing mechanism in financially underdeveloped economies, and hence may provide an impetus for compensating government spending. Comparative studies of the public sector have provided evidence of a robust positive association between government size and openness of the economy to trade flows. This paper extends the existing literature by investigating the relationship between government size and financial openness for 87 developing and developed countries between 1976 and 2003. The analysis reveals a positive relationship between exposure to international capital flows and government size. Furthermore, interacting capital flows with income levels shows that richer open economies tend to have smaller government size. These findings are consistent with the hypothesis that benefits of financial integration, in terms of improved risk‐sharing and consumption smoothing, accrue only beyond a certain minimum level of financial development.

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)0.002
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0010.004
Scholarly communication0.0020.003
Open science0.0000.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.000

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 head0.013
GPT teacher head0.217
Teacher spread0.205 · 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 designObservational
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

Citations62
Published2009
Admission routes1
Has abstractyes

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