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Activity Number: 19
Type: Topic Contributed
Date/Time: Sunday, July 29, 2012 : 2:00 PM to 3:50 PM
Sponsor: Business and Economic Statistics Section
Abstract - #306185
Title: Nowcasting Business Cycle Turning Points in an Uncertain Environment
Author(s): Francesco Ravazzolo*+ and Knut Are Aastveit and Herman van Dijk
Companies: Norges Bank and Norges Bank and Tinbergen Institute/Erasmus University Rotterdam
Address: , , ,
Keywords: Nowcasting ; Factor model ; Bayesian analysis ; Turning points ; Density combination

In this paper, we construct a combined Bayesian factor model to estimate and nowcast US business cycle turning points in real-time. Factor models are often used to construct business cycle indicators. Two approaches have mainly been used. The first approach is to identify turning points individually in a large number of series and then average (date then average). The second approach is to look for turning points in a few, or just one, aggregate (average then date). We study both approaches within a factor model framework. In the former approach we apply a nonlinear transformation to all the data series and then estimate factors. In the latter approach we estimate a single series, such as GDP, using factor models. We then apply a given rule, such as the Bry-Broschan (1971) algorithm, to the estimated series. In both approaches we propose to use a combined Bayesian factor model. An advantage of using model averaging is that we account for several sources of uncertainty such as parameter uncertainty and data input and factor structure uncertainty.

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