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Predicting the Present with Search Engine Data

Predicting the Present with Search Engine Data

This video was recorded at 19th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), Chicago 2013. Many businesses now have almost real time data available about their operations. This data can be helpful in contemporaneous prediction ("nowcasting") of various economic indicators. We illustrate how one can use Google search data to nowcast economic metrics of interest, and discuss some of the ramifications for research and policy. Our approach combines three Bayesian techniques: Kalman filtering, spike-and-slab regression, and model averaging. We use Kalman filtering to whiten the time series in question by removing the trend and seasonal behavior. Spike-and-slab regression is a Bayesian method for variable selection that works even in cases where the number of predictors is... Show More
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