Bayesian Variable Selection for Nowcasting Economic Time Series
23 Pages Posted: 25 Oct 2013 Last revised: 7 Oct 2014
Date Written: October 2013
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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