We analyze cyclical co-movement in credit, house prices, equity prices, and long-term interest rates across 17 advanced economies. Using a time-varying multi-level dynamic factor model and more than 130 years of data, we analyze the dynamics of co-movement at different levels of aggregation and...

The authors analyze cyclical co-movement in credit, house prices, equity prices, and long-term interest rates across 17 advanced economies. Using a time-varying multi-level dynamic factor model and more than 130 years of data, they analyze the dynamics of co-movement and compare recent...

This paper considers a non-stationary dynamic factor model for large datasets to disentangle long-run from short-run co-movements. We first propose a new Quasi Maximum Likelihood estimator of the model based on the Kalman Smoother and the Expectation Maximisation algorithm. The asymptotic...

In the current literature uncertainty about the future course of the economy is identified as a possible driver of business cycle fluctuations. In fact, uncertainty surrounds the movements of all economic variables which gives rise to a monitoring problem. We identify the different dimensions of...

Uncertainty about the future course of the economy is a possible driver of aggregate fluctuations. To identify the different dimensions of uncertainty in the macroeconomy we construct a large dataset covering all types of economic uncertainty. We then identify two fundamental factors which...

Uncertainty about the future course of the economy is a possible driver of aggregate fluctuations. To identify the different dimensions of uncertainty in the macroeconomy we construct a large dataset covering all types of economic uncertainty. We then identify two fundamental factors which...

In this paper, we propose a method for jointly estimating indexes of economic and financial conditions by exploiting the intertemporal link between their cyclical behavior. This method combines a dynamic factor model for the joint modeling of economic and financial variables with mixed...