573 - Modeling the business and financial cycle in a multivariate structural time series model

DNB Working Papers
Date 19 October 2017
We consider a multivariate unobserved component time series model to disentangle the short-term and medium-term cycle for the G7 countries and the Netherlands using four key macroeconomic and financial time series. The novel aspect of our approach is that we simultaneously decompose the short-term and medium-term dynamics of these variables by means of a combination of their estimated cycles. Our results show that the cyclical movements of credit volumes and house prices are mostly driven by the medium-term cycle, while the macroeconomic variables are equally driven by the short-term and medium-term cycle. For most countries, the co-movement between the cycles of the financial and macroeconomic variables is mainly present in the medium-term. First, we find strong co-cyclicality between the medium-term cycles of house prices and GDP in all countries we analyzed. Second, the relation between the medium-term cycles of GDP and credit is more complex. We find strong concordance between both cycles in only three countries. However, in three other countries we find ‘indirect’ concordance, i.e. the medium-term cycles of credit and house prices share co-cyclicality, while in turn the medium-term cycles of house prices and GDP share commonality. This outcome might indicate that the house price cycle is –at least partly– driven by the credit cycle. Lastly, the cross-country concordance of both the short-term cycles and the medium-term cycles of GDP, house prices and credit is low. Hence, the bulk of the cyclical movements seem to be driven by domestic rather than global factors.
 
Keywords: unobserved component time series model, Kalman filter, maximum likelihood estimation, short-term and medium-term cycles. 
JEL classifications: C32, E32, G01.