We propose to construct factor models based on disaggregate survey data to forecast national aggregate macroeconomic variables. We apply our methodology to Norges Bank's regional survey, which allows to construct regional and sectoral factor models, and to the Swedish Business Tendency survey,...

We assess the forecast ability of Norges Bank's regional survey for inflation, GDP growth and the unemployment rate in Norway. We propose several factor models based on regional and sectoral information given by the survey. The analysis identifies which information extracted from the ten sectors...

We use Bayesian factor regression models to construct a financial conditions index (FCI) for the U.S. Within this context we develop Bayesian model averaging methods that allow the data to select which variables should be included in the FCI or not. We also examine the importance of different...

We introduce a Combined Density Nowcasting (CDN) approach to Dynamic Factor Models (DFM) that in a coherent way accounts for time-varying uncertainty of several model and data features in order to provide more accurate and complete density nowcasts. The combination weights are latent random...