Cyclical components in economic time series are analysed in a Bayesian framework, thereby allowing prior notions about periodicity to be used. The method is based on a general class of unobserved component models that encompasses a range of dynamics in the stochastic cycle. This allows for...

We develop a formal statistical approach to investigate the possibility that leading indicator variables have different lead times at business cycle peaks and troughs. For this purpose, we propose a novel Markov switching vector autoregressive model, where economic growth and leading indicators...

Economic variables like GDP growth, employment, interest rates and consumption show signs of cyclical behavior. Many variables display multiple cycles, with lengths ranging in between 5 to even up to 100 years. We argue that multiple cycles can be associated with long-run stability of the...

We propose a new method of leading index construction that combines the need for data compression with the objective of forecasting. This so-called principal covariate index is constructed to forecast growth rates of the Composite Coincident Index. The forecast performance is compared with an...

__Abstract__ Over the years we see that mortgages with less risk of loss, due to more asset accumulation, have become more popular. We examine if this popularity resonates with macroeconomic features, business cycle movements and policy measures. Using detailed data from an important player in...