Bayesian Variable Selection for Nowcasting Economic Time Series

We consider the problem of short-term time series forecasting (nowcasting) when there are more possible predictors than observations. Our approach combines three Bayesian techniques: Kalman filtering, spike-and-slab regression, and model averaging. We illustrate this approach using search engine query data as predictors for consumer sentiment and gun sales

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Year of publication:	2014
Authors:	Scott, Steven L.
Other Persons:	Varian, Hal R. (contributor)
Publisher:	[2014]: [S.l.] : SSRN
Subject:	Theorie \| Theory \| Zeitreihenanalyse \| Time series analysis \| Prognoseverfahren \| Forecasting model \| Bayes-Statistik \| Bayesian inference \| Schätzung \| Estimation \| Waffe \| Weapon \| Absatz \| Sales \| Verbrauchervertrauensindex \| Consumer confidence index

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Extent:	1 Online-Ressource (23 p)
Series:	NBER Working Paper ; No. w19567
Type of publication:	Book / Working Paper
Language:	English
Notes:	Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments October 2013 erstellt
Source:	ECONIS - Online Catalogue of the ZBW

Persistent link: https://www.econbiz.de/10013062413