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