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dc.contributor.author
Chatzikyriakos, Georgios
en
dc.date.accessioned
2015-06-18T13:17:46Z
dc.date.available
2015-09-27T05:57:55Z
dc.date.issued
2015-06-18
dc.identifier.uri
https://repository.ihu.edu.gr//xmlui/handle/11544/434
dc.rights
Default License
dc.title
The impact of oil returns and their volatility on economic growth
en
heal.type
masterThesis
heal.secondaryTitle
Empirical evidence for the G7 country zone
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heal.keyword
Petroleum products--Economic aspects
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heal.keyword
Petroleum industry and trade--Economic aspects
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heal.keyword
Petroleum--Prospecting--Economic aspects
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heal.keyword
Dissertations, Academic
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heal.language
en
heal.access
free
el
heal.license
http://creativecommons.org/licenses/by-nc/4.0
heal.recordProvider
School of Science and Technology, MSc in Energy Systems
heal.publicationDate
2012-11
heal.bibliographicCitation
Chatzikyriakos, Georgios, 2012, The impact of oil returns and their volatility on economic growth ,Master's Dissertation, International Hellenic University
en
heal.abstract
This dissertation examines the relationship between oil prices and economic activity for the G7 country zone. In the analysis quarterly data from 1971 Q1 to 2010 Q1 is used. Among the countries three of them are large oil producers (Canada, UK and USA), but simultaneously they are also oil-importers. Multivariate Vector Error Correction (VEC) model with 4 variables (real gross domestic product, gross fixed capital formation, real oil prices and unemployment rate) and unrestricted bivariate Vector Autoregression (VAR) model with 2 variables (real gross domestic product and real oil prices) are analyzed as well as variance decomposition and impulse response function analysis. A GARCH (1,1) model is applied so as to introduce a second oil specification and to focus on oil price volatility. VD indicates that oil prices explain GDP significantly after one year for two countries (UK and USA), while oil price volatility is a more influential factor in affecting GDP since it is more statistically significant for four countries (Germany, Italy, UK and USA). IRFs show a negative response in the same period for four countries (Canada, France, UK and USA) and five countries (Canada, France, Germany, UK and USA) regarding the two oil proxies. However, Japan responds positively to an oil price shock, while the response to an oil price volatility shock is not statistically significant.
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heal.tableOfContents
ACKNOWLEDGMENTS…………………………………………………………...2 LIST OF TABLES……………………………………………………………….…..6 LIST OF FIGURES………………………………………………………………….8 ABSTRACT………………………………………………………………………….9 CHAPTERS 1. INTRODUCTION…………………………………………………………...10 2. LITERATURE REVIEW…………………………………………………....14 2.1 Theoretical studies………………………………………………….…….14 2.2 Empirical studies………………………………………………………....15 3. DATA………………………………………………………………….……..26 4. METHODOLOGY…………………………………………………….…….27 4.1 Vector Autoregression (VAR)……………………………………….…..27 4.1.1 Bivariate/ Four-variate specification………………………….….27 4.2 Unit root tests……………………………………………………………29 4.2.1 Augmented Dickey-Fuller…………………………………….....29 4.2.2 Phillips-Perron…………………………………………………...30 4.2.3 KPSS…………………………………………………………....31 4.2.4 GLS- Dickey Fuller…………………………………………..…31 4.3 Cointegration test…………………………………………………...…..32 4.4 Garch model……………………………………………………...……..32 5. EMPIRICAL ANALYSIS……………………………………………...….34 4 5.1 Bivariate specification…………………………………..…….…….……34 5.1.1 Cointegration analysis…………………………..…….…….……34 5.1.2 Granger causality……………………………….……..…….……34 5.2 Four-variate specification……………………………….……..…………35 5.2.1 Cointegration analysis…………………………….….….……….35 5.2.2 Short-run causality…………………………….…….….………..35 5.2.3 Joint F-test………………………………………….…..………..35 5.2.4 Coefficient of Determination………………….…….….………..36 5.2.5 Serial Correlation…………………………….……….….………36 5.2.6 Stability test……………………………………….…..…………37 5.2.7 Normality test…………………………………….….…….…….37 5.3 Variance decomposition-Impulse response function….…….….………..38 5.3.1 Variance decomposition analysis………………….…..…….…...38 5.3.1.1 Bivariate specification………………………..…….….…….38 5.3.1.2 Four-variate specification…………………….….……..……39 5.3.2 Impulse response analysis………………………….…..………..40 5.3.2.1 Bivariate specification………………………….….….…….40 5.3.2.2 Four-variate specification…………………………...….…..40 5.4 Garch model………………………….…………………….…….….....42 5.4.1 Bivariate specification………………………………...………..42 5.4.1.1 Granger causality………………………………….…….….42 5.4.2 Four-variate specification………………………………………42 5 5.4.2.1 Granger causality……………………………………..………42 5.4.2.2 Coefficient of Determination………………………….……..43 5.4.2.3 Serial Correlation…………………………………….………44 5.4.2.4 Stability…………………………………………….….……..44 5.4.2.5 Normality test……………………………………….….……45 5.4.3 Variance decomposition-Impulse response function….….……..45 5.4.3.1 Variance decomposition analysis……………….…….……..45 5.4.3.1.1 Bivariate specification………………….….………..45 5.4.3.1.2 Four-variate specification…………….…….……….45 5.4.3.2 Impulse response analysis…………………………..………46 5.4.3.2.1 Bivariate specification……………………..……….46 5.4.3.2.2 Four-variate specification…………………..………47 6. CONCLUSIONS…………………………………………………..……...48 REFERENCES…………………………………………………………….……...50 APPENDIX………………………………………………………………………128 Data source……………………………………………………………………….128
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heal.advisorName
Apergis, Dr. Nicholas
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heal.committeeMemberName
Prof. Apergis
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heal.committeeMemberName
Prof. Nomikos
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heal.committeeMemberName
Dr. Dergiades
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heal.academicPublisher
School of Science &Technology, Master of Science (MSc) in Energy Systems
en
heal.academicPublisherID
ihu
heal.numberOfPages
130
heal.fullTextAvailability
true


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