TY  - JOUR
AU  - Scott, Steven L
AU  - Varian, Hal R
TI  - Bayesian Variable Selection for Nowcasting Economic Time Series
JF  - National Bureau of Economic Research Working Paper Series
VL  - No. 19567
PY  - 2013
Y2  - October 2013
DO  - 10.3386/w19567
UR  - http://www.nber.org/papers/w19567
L1  - http://www.nber.org/papers/w19567.pdf
N1  - Author contact info:
Steven L. Scott
Google
1600 Amphitheatre Parkway
Mountain View, CA 94043
E-Mail: stevescott@google.com

Hal R. Varian
576 Del Amigo Rd
Danville, CA 94526
US
Tel: 925 262 3641
E-Mail: hal@google.com
M1  - published as Steven L. Scott, Hal R. Varian. "Bayesian Variable Selection for Nowcasting Economic Time Series," in Avi Goldfarb, Shane M. Greenstein, and Catherine E. Tucker, editors, "Economic Analysis of the Digital Economy" University of Chicago Press (2015)

M3  - presented at "The Economics of Digitization: An Agenda", June 6-7, 2013
AB  - 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.
ER  -