Browsing by Subject "Granger-causality"

House prices have a very important role in the economy. House prices have strong influence to the economy especially in Finland, where around one-half of the value of households' total assets is coming from households' own dwellings. The real estate investment market is large in proportion in Finland when compared internationally to the size of the economy. Surprisingly, there are not many papers discussing the relationship between house prices and output in Finland. This paper intends to enrich the recent literature about this topic. Primary research question in this paper was do house prices affect output in Finland. Secondary interests were transmission mechanisms. The methods used in this thesis are typical in vector autoregression (VAR) analysis in recent literature. First, the time series are analysed visually and with unit root tests. Then, the optimal VAR model was chosen by using different information criterion tests and correlation tests. After selecting the optimal VAR model, Granger causality was tested with Toda-Yamamoto causality test. Other methods utilized in this paper were cointegration tests, forecasting, impulse responses and forecast error variance decomposition. These empirical methods were computed in intention to answer the research question. The most important empirical results of the paper were following. The results of Toda-Yamamoto causality test suggested that there are unidirectional Granger causality going from real house prices to real GDP per capita. This indicates that house prices could have significant explanatory power for GDP. Cointegration tests implied that the series are not cointegrated. This suggests that the series do not share a common stochastic trend for the long-run. The results of forecasting supported the results of Toda-Yamamoto causality test and it seemed that house prices might be a useful predictor when forecasting output. This result implied that the house prices have an effect on output. The analysis of impulse responses suggested that a house price shock have a positive and persistent effect on output. Forecast error variance decomposition intimated that after 15 quarters 63 percent of the output variation can be explained by the house price shock which was suspiciously strong result. The conclusion were made based on the results of the empirical analysis. Answer to the primary research question were house prices seem to have effect on output in Finland. The results of this paper supported the theory behind the wealth effect. If policy makers have a desire to stabilize output in Finland, they might need to consider stabilizing the house prices to further the stabilization of the output. It is necessary to understand the effects of housing prices to the business cycle for an efficient housing policy strategy.