Please use this identifier to cite or link to this item: http://dspace.lib.uom.gr/handle/2159/18989
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dc.contributor.advisorΤσουλφίδης, Λευτέρηςel
dc.contributor.authorΤσιμής, Αχιλλεύςel
dc.date.accessioned2016-03-21T08:10:50Z-
dc.date.available2016-03-21T08:10:50Z-
dc.date.issued2016el
dc.identifier.urihttp://dspace.lib.uom.gr/handle/2159/18989-
dc.descriptionΔιπλωματική εργασία--Πανεπιστήμιο Μακεδονίας, Θεσσαλονίκη, 2016.el
dc.description.abstractThe main purpose of this study is to examine the relationship between the real output and the real financial-economic variables in the U.S. economy and whether the financial sector or the real economy can better explain growth and cycles. In order to investigate this, various econometric techniques were applied on quarterly data during the period 1965Q1 to 2010Q4 for the cross correlation analysis and the VAR model. The sample period of the VECM model was 1980Q1 to 2010Q4. In detail, this research consists of four parts. The first one refers to the definition of Business Cycles and apposes its stylized facts. In the second part, we bring up some of the existing literature and then we apply the Hodrick Prescott filter to detrend the series and extract their cyclical components in order to detect the timing and direction of our variables relative to the real GDP cycle. The examined variables are retail sales, corporate profits, credit to private sector, private residential investment, term spread and S&P500. Also, we interpret the standard deviation, skewness and kurtosis of the cyclical variables to detect the amplitude, the asymmetry and the extreme points of each cyclical component. Furthermore, in the third part, we perform Granger Causality tests, within a VAR model, to study the casual relationship between our variables. We further proceed in analyzing the dynamics of our model by applying, impulse responses to trace out the effect of a (one unit) positive shock on the output cycle, and variance decomposition in order to measure how important are these shocks in explaining the variation in the cyclical GDP. Findings suggest that financial variables are more important than real economic variables in explaining the fluctuations of real GDP. Finally, in the fourth part we test for cointegration using the Johansen approach on two different models. The first one refers to real economic variables, that is profits, retail sales, private residential investment, wages and average hours, while the second model comprises of financial variables, such as term spread, S&P500, credit to private non financial sector, household debt to income ratio and domestic bank credit to deposit ratio. Both models share a common variable which is real GDP in order to study the long-run relationship between these variables and real output. After finding at most one cointegrating relationship between these variables at each model, we introduced two VECM models and studied the short and long-run dynamics as well as the short and long-run causality between the variables. The results indicated that again the financial variables have a stronger impact on the output than the real economic variables, but the casual relationship between the later and real output was clearer than the prior.en
dc.format.extent51en
dc.language.isoenen
dc.publisherΠανεπιστήμιο Μακεδονίαςel
dc.subjectBusiness cyclesen
dc.subjectGranger causalityen
dc.subjectReal outputen
dc.subjectEconomic growthen
dc.titleFinancial versus real economic variables in explaining growth and cyclesen
dc.typeElectronic Thesis or Dissertationen
dc.contributor.departmentΔιατμηματικό Πρόγραμμα Μεταπτυχιακών Σπουδών στην Οικονομική Επιστήμηel
Appears in Collections:ΔΠΜΣ Οικονομική Επιστήμη (M)

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