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Record W2283680182 · doi:10.5539/ibr.v9n3p154

The Effects of Economic Growth and Foreign Direct Investment on Air Transportation: Evidence from Turkey

2016· article· en· W2283680182 on OpenAlexvenueno aff
Salih Kalaycı, Gözde Yangınlar

Bibliographic record

VenueInternational Business Research · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFiscal Policy and Economic Growth
Canadian institutionsnot available
Fundersnot available
KeywordsVariance decomposition of forecast errorsForeign direct investmentVector autoregressionTurkishEconomicsEconometricsAviationInvestment (military)Civil aviationMacroeconomicsEngineeringPolitical science

Abstract

fetched live from OpenAlex

The major goal of this research paper is to investigate the relationship among Turkish Economic growth, airway transportation and FDI. Several research results consistent with this papers finding and it has been founded that the economic growth plays a crucial role in air transportation by implementing econometrical models including Multiple Linear Regression (MLR), Johansen co-integration test and VAR model. The variables have been put into the Vector Autoregressive Model (VAR) and Johansen co-integration test. According to the test result of Johansen co-integration test there is a long-term relationship between the variables of GDP, FDI and air transportation. According to the both variance decomposition and Impulse Response analysis, the effect of GDP is found to increase air transportation more than the FDI. Finally, the contribution of Turkish economy to civil aviation seems significant which is consistent with this paper’s research results.

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)0.002
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 score0.054
Threshold uncertainty score0.107

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.060
GPT teacher head0.298
Teacher spread0.238 · 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

Citations19
Published2016
Admission routes1
Has abstractyes

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