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Record W2036669777 · doi:10.5539/ijef.v6n4p172

The Role of Savings in Reducing the Effect of Oil Price Volatility for Sustainable Economic Growth in Oil Based Economies: The Case of GCC Countries

2014· article· en· W2036669777 on OpenAlexvenueno aff
Ritab Al‐Khouri, Aruna Dhade

Bibliographic record

VenueInternational Journal of Economics and Finance · 2014
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMarket Dynamics and Volatility
Canadian institutionsnot available
Fundersnot available
KeywordsEconomicsEndogeneityVolatility (finance)RevenueSustainable growth rateEconomic expansionMonetary economicsNational savingsInternational economicsMacroeconomicsShort runEconometricsFinance

Abstract

fetched live from OpenAlex

We investigate the simultaneous links between oil price changes, national savings, legal and institutional development, and economic growth in the Gulf Cooperation Council (GCC) countries. Our study includes six GCC countries namely, Bahrain, Kuwait, Oman, Qatar, Saudi Arabia and the United Arab Emirates. We base our analysis on annual data that covers the period from 1980 to 2011. We implement different methodologies on time series cross sectional data: First, we test our model using fixed effect and random effect model techniques; Second, we employ Arellano-Bond/Blundell-Bond estimator to reduce the endogeneity problem that is common in this kind of studies. Results reveal a nonlinear and concave relationship between saving rates and economic growth. This result suggests that, at low level of economic growth, the increase in savings leads to high economic growth. However, as the countries’ revenues and surpluses increase significantly (at higher levels in revenues and savings), high level of savings lead to lower growth in the economy. This might due to the lack of absorption capacity of the GCC markets. In addition, controlling for different factors, oil price changes explain the variability in the economic growth of the GCC countries. Economic globalization affects growth negatively, while institutional quality plays no role in economic growth of the GCC markets.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.870
Threshold uncertainty score0.392

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.005
GPT teacher head0.206
Teacher spread0.201 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations14
Published2014
Admission routes1
Has abstractyes

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