Combined Density Nowcasting in an Uncertain Economic Environment

Tinbergen Institute Discussion Paper 14-152/III

38 Pages Posted: 12 Dec 2014

See all articles by Knut Aastveit

Knut Aastveit

Norges Bank

Francesco Ravazzolo

Free University of Bozen-Bolzano - Faculty of Economics and Management; BI Norwegian Business School

H. K. van Dijk

Tinbergen Institute; Econometric Institute

Multiple version iconThere are 2 versions of this paper

Date Written: December 3, 2014


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 variables that depend on past nowcasting performance and other learning mechanisms. The combined density scheme is incorporated in a Bayesian Sequential Monte Carlo method which re-balances the set of nowcasted densities in each period using updated information on the time-varying weights. Experiments with simulated data show that CDN works particularly well in a situation of early data releases with relatively large data uncertainty and model incompleteness. Empirical results, based on US real-time data of 120 leading indicators, indicate that CDN gives more accurate density nowc asts of US GDP growth than a model selection strategy and other combination strategies throughout the quarter with relatively large gains for the two first months of the quarter. CDN also provides informative signals on model incompleteness during recent recessions. Focusing on the tails, CDN delivers probabilities of negative growth, that provide good signals for calling recessions and ending economic slumps in real time.

Keywords: Density forecast combination; Survey forecast; Bayesian Filtering; Sequential Monte Carlo Nowcasting, Real-time Data

JEL Classification: C11, C13, C32, C53, E37

Suggested Citation

Aastveit, Knut and Ravazzolo, Francesco and van Dijk, Herman K., Combined Density Nowcasting in an Uncertain Economic Environment (December 3, 2014). Tinbergen Institute Discussion Paper 14-152/III. Available at SSRN: or

Knut Aastveit (Contact Author)

Norges Bank ( email )

P.O. Box 1179
Oslo, N-0107

Francesco Ravazzolo

Free University of Bozen-Bolzano - Faculty of Economics and Management ( email )

Via Sernesi 1
39100 Bozen-Bolzano (BZ), Bozen 39100

BI Norwegian Business School ( email )

Nydalsveien 37
Oslo, 0442


Herman K. Van Dijk

Tinbergen Institute ( email )

Gustav Mahlerplein 117
Burg. Oudlaan 50
Amsterdam/Rotterdam, 1082 MS
+31104088955 (Phone)
+31104089031 (Fax)


Econometric Institute ( email )

P.O. Box 1738
3000 DR Rotterdam
+31 10 4088955 (Phone)
+31 10 4527746 (Fax)

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