New Model of CPI Predictions Using Time Series of GDP with Solving GDP-CPI Delay Hypothesis

Kód výsledku v IS VaVaI

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Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

New Model of CPI Predictions Using Time Series of GDP with Solving GDP-CPI Delay Hypothesis

Popis výsledku v původním jazyce

The existence of correlation between economical situation of a state and its effects on construction production is generally known. Thanks to economical and legal specifications of construction field, it is possible to qualitatively forecast future development based on macroeconomic indicators. Macroeconomic indicator of GDP (gross domestic product) is used towards mentioned goal. This paper strives to quantify general relations between these values: GDP and CPI (construction production index). For thispurpose, calculation will be used of correlation coefficient of time series based on statistical data of every state in the European Union after solving delay hypothesis. These action create an analytical map of EU with levels of GDP ? CPI dependencieswhich are used in prediction algorithm. Prediction algorithm is created in relation to levels of GDP - CPI dependences and data from their times series. Algorithm is tested on creating CPI predictions for year 2012 for EU states. Output v

Název v anglickém jazyce

New Model of CPI Predictions Using Time Series of GDP with Solving GDP-CPI Delay Hypothesis

Popis výsledku anglicky

The existence of correlation between economical situation of a state and its effects on construction production is generally known. Thanks to economical and legal specifications of construction field, it is possible to qualitatively forecast future development based on macroeconomic indicators. Macroeconomic indicator of GDP (gross domestic product) is used towards mentioned goal. This paper strives to quantify general relations between these values: GDP and CPI (construction production index). For thispurpose, calculation will be used of correlation coefficient of time series based on statistical data of every state in the European Union after solving delay hypothesis. These action create an analytical map of EU with levels of GDP ? CPI dependencieswhich are used in prediction algorithm. Prediction algorithm is created in relation to levels of GDP - CPI dependences and data from their times series. Algorithm is tested on creating CPI predictions for year 2012 for EU states. Output v

Druh

D - Stať ve sborníku

CEP obor

JN - Stavebnictví

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 statě ve sborníku

PEOPLE, BUILDINGS AND ENVIRONMENT 2014

ISBN

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ISSN

1805-6784

e-ISSN

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Počet stran výsledku

12

Strana od-do

152-163

Název nakladatele

Brno University of Technology

Místo vydání

Brno

Místo konání akce

Kroměříž

Datum konání akce

15. 10. 2014

Typ akce podle státní příslušnosti

CST - Celostátní akce

Kód UT WoS článku

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