We develop a dynamic factor model with Markov switching to examine secular and business cycle fluctuations in the U.S. unemployment rates. We extract the common dynamics amongst unemployment rates disaggregated for 7 age groups. The framework allows analysis of the contribution of demographic...

We develop a dynamic factor model with Markov switching to examine secular and business cycle fluctuations in the U.S. unemployment rates. We extract the common dynamics amongst unemployment rates disaggregated for 7 age groups. The framework allows analysis of the contribution of demographic...

Recent work in the macroeconometric literature considers the problem of summarising efficiently a large set of variables and using this summary for a variety of purposes including forecasting. Work in this field has been carried out in a series of recent papers. This paper provides an...

The estimation of dynamic factor models for large sets of variables has attracted considerable attention recently, due to the increased availability of large datasets. In this paper we propose a new methodology for estimating factors from large datasets based on state space models, discuss its...

Recently, considerable emphasis has been placed on the problems arising out of cross-sectional dependence in panel unit root tests. This paper adopts the factor based cross-sectional dependence paradigm of Bai and Ng (2004) but suggests alternative factor extraction methods. Some theoretical...

The aim of this paper is to consider multivariate stochastic volatility models for large dimensional datasets. We suggest use of the principal component methodology of Stock and Watson (2002) for the stochastic volatility factor model discussed by Harvey, Ruiz, and Shephard (1994). The method is...

We produce predictions of the current state of the Indonesian economy by estimating a Dynamic Factor Model on a dataset of 11 indicators (also followed closely by market operators) over the time period 2002 to 2014. Besides the standard difficulties associated with constructing timely indicators...

In this paper we investigate whether accounting for non-pervasive shocks improves the forecast of a factor model. We compare four models on a large panel of US quarterly data: factor models, factor models estimated on selected variables, Bayesian shrinkage, and factor models together with...

In this paper, we propose an econometric model of the joint dynamic relationship between the yield curve and the economy to predict business cycles. We examine the predictive value of the yield curve to forecast future economic growth as well as the beginning and end of economic recessions at...

We produce predictions of Norwegian GDP. To this end, we estimate a Bayesian Dynamic Factor model on a panel of 14 variables (all followed closely by market operators) ranging from 1990 to 2011. By means of a pseudo real-time exercise we show that the Bayesian Dynamic Factor Model performs well...