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Record W2121307511 · doi:10.5539/ijef.v2n2p107

The Impact of FDI and Financial Sector Development on Economic Growth: Empirical Evidence from Asia and Oceania

2010· article· en· W2121307511 on OpenAlexvenueno aff
Yen Li Chee, Mahendhiran Nair

Bibliographic record

VenueInternational Journal of Economics and Finance · 2010
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsnot available
Fundersnot available
KeywordsForeign direct investmentPanel dataFinancial sector developmentEconomicsDeveloping countryDevelopment economicsInternational economicsEconomic growthMacroeconomicsEconometrics

Abstract

fetched live from OpenAlex

This paper empirically examines if financial sector development is an important precondition for foreign direct investment (FDI) to enhance economic growth in the Asia-Oceania region. The study will also examine whether the impact is dependent on the stages of development of the countries. Panel data methods (fixed effects-estimator and random effects-estimator) were used to analyse the relationship between FDI, financial sector development and economic growth on a sample of 44 Asia and Oceania countries for the period 1996-2005. The empirical analysis showed that financial sector development enhances the contribution of FDI on economic growth in the region. It also showed that the complementary role of FDI and financial sector development on economic growth is most important for least developed economies in the region. Key strategies to enhance the role of FDI and financial development on economic growth in developing and least developed Asia and Oceania countries are also discussed in the paper.

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)0.004
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 score0.041
Threshold uncertainty score0.082

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.062
GPT teacher head0.261
Teacher spread0.200 · 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

Citations59
Published2010
Admission routes1
Has abstractyes

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