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Forecasting Capability of the GDP Components: Granger Causality Approach
Název práce v češtině: Prognostická síla HDP komponentů na základě Grangerovy kauzality
Název v anglickém jazyce: Forecasting Capability of the GDP Components:
Granger Causality Approach
Klíčová slova anglicky: Granger Causality, GDP, expenditure approach, forecasting, predictions, Akaike information criterion (AIC), Bayesian information criterion (BIC)
Akademický rok vypsání: 2014/2015
Typ práce: bakalářská práce
Jazyk práce: angličtina
Ústav: Institut ekonomických studií (23-IES)
Vedoucí / školitel: doc. Ing. Tomáš Cahlík, CSc.
Řešitel: skrytý - zadáno vedoucím/školitelem
Datum přihlášení: 27.05.2015
Datum zadání: 27.05.2015
Datum a čas obhajoby: 15.06.2016 08:00
Místo konání obhajoby: IES m 314
Datum odevzdání elektronické podoby:05.05.2016
Datum proběhlé obhajoby: 15.06.2016
Oponenti: PhDr. Karolína Vozková, Ph.D.
 
 
 
Kontrola URKUND:
Seznam odborné literatury
1. Granger, Clive W.J. (1969):Investigating causal relations by econometric models
and cross-spectral methods." Econometrica: Journal of the Econometric Society
37(3): pp. 424-438.

2. Granger, Clive W.J. (1980):Testing for causality: a personal viewpoint." Journal
of Economic Dynamics and control 2(4): pp. 329-352.

3. Green, Richard K. (1997):Follow the leader: how changes in residential and non-
residential investment predict changes in GDP." Real Estate Economics 25(2): pp.
253-270.

4. Hoover, Kevin D. (2008):Causality in economics and econometrics." The new
Palgrave dictionary of economics.

5. Wooldridge, Jeffrey (2013):Introductory econometrics: A modern approach."
South-Western Cengage Learning.
Předběžná náplň práce
This work aims to provide with the procedure of bivariate causality testing based on Granger (1969). We focus on exploration of forecasting capability of GDP components on output itself. We examine, which of five components defined in accordance with the expenditure approach can
be useful in forecasting economic growth.

Generally, the aim of the thesis is to determine the causal relationship between the variables defined in accordance with the expenditure approach of GDP calculation: Y = C + I + G + X -M. Overall, we are interested which of the independent variables are useful in forecasting output. In addition, the forecasting capability of GDP on its components is examined, too.

For the purpose of an empirical analysis, we collected data of three countries of the European Union (Austria, France and Germany) which
were subjects of the Granger causality tests. The bivariate causal relationship is examined on either VAR(n) model in log-differences or VEC(n) model, where n stands for the number of time lags selected either Akaike information criterion and Bayesian information criterion.
 
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