The financial cycle captures systematic patterns in the financial system and is closely related to the concept of procyclicality of systemic risk. This paper investigates the characteristics of financial cycles using a multivariate model-based filter. We extract cycles using an unobserved components time series model and applying state space methods. We estimate financial cycles for the United States, Germany, France, Italy, Spain and the Netherlands, using data from 1970 to 2014. For these countries, we find that the individual financial variables we examine have medium-term cycles which share a few common statistical properties. We therefore refer to these cycles as ’similar’. We find that overall financial cycles are longer than business cycles and have a higher amplitude. Moreover, such behaviour varies over time and across countries. Our results suggest that estimates of the financial cycle can be a useful monitoring tool for policymakers as they may provide a broad indication about when risks to financial stability increase, remain stable, or decrease.
Keywords: unobserved component models, state space method, maximum likelihood, bandpass filter, short and medium term cycles.
JEL classifications: C22, C32, E30, E50, E51, G01.
495 - Measuring financial cycles with a model-based filter: Empirical evidence for the United States and the euro area
- DNB Working Papers
Date 26 January 2016