The Presence of Chaos in the GDP Growth Rate Time Series

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25410%2F14%3A39898345" target="_blank" >RIV/00216275:25410/14:39898345 - isvavai.cz</a>

Výsledek na webu

<a href="http://www.cmsim.eu/papers_pdf/april_2014_papers/8_CMSIM-Journal_2014_Kriz_Knezackova_2_199-206.pdf" target="_blank" >http://www.cmsim.eu/papers_pdf/april_2014_papers/8_CMSIM-Journal_2014_Kriz_Knezackova_2_199-206.pdf</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

The Presence of Chaos in the GDP Growth Rate Time Series

Popis výsledku v původním jazyce

The goal of this paper is to find chaos in the Gross domestic product (GDP) growth rate of selected European countries. We chose only those European countries where data is available since 1980, because we needed the longest time series possible. These are the following states: Belgium, Finland, France, Norway, Spain, Switzerland and United Kingdom. At first we will estimate the time delay and the embedding dimension, which is needed for the largest Lyapunov exponent estimation. The largest Lyapunov exponent is one of the important indicators of chaos and is generally wellknown. Subsequently we will calculate the 0-1 test for chaos. Finally we will compute the Hurst exponent by using the Rescaled Range analysis. The Hurst exponent is a numerical estimate of the predictability of a time series. The results indicated that chaotic behaviors obviously exist in GDP growth rate.

Název v anglickém jazyce

The Presence of Chaos in the GDP Growth Rate Time Series

Popis výsledku anglicky

The goal of this paper is to find chaos in the Gross domestic product (GDP) growth rate of selected European countries. We chose only those European countries where data is available since 1980, because we needed the longest time series possible. These are the following states: Belgium, Finland, France, Norway, Spain, Switzerland and United Kingdom. At first we will estimate the time delay and the embedding dimension, which is needed for the largest Lyapunov exponent estimation. The largest Lyapunov exponent is one of the important indicators of chaos and is generally wellknown. Subsequently we will calculate the 0-1 test for chaos. Finally we will compute the Hurst exponent by using the Rescaled Range analysis. The Hurst exponent is a numerical estimate of the predictability of a time series. The results indicated that chaotic behaviors obviously exist in GDP growth rate.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

AH - Ekonomie

OECD FORD obor

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Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2014

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Chaotic Modeling and Simulation (CMSIM)

ISSN

2241-0503

e-ISSN

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Svazek periodika

2014

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

GR - Řecká republika

Počet stran výsledku

8

Strana od-do

199-206

Kód UT WoS článku

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EID výsledku v databázi Scopus

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