Volume 10, Issue 4 December 2014

Nowcasting Norway

Abstract

We produce predictions of Norwegian GDP. To this end, we estimate a Bayesian dynamic factor model on a panel of fourteen variables (all followed closely by market operators) ranging from 1990 to 2011. By means of a pseudo real-time exercise, we show that the Bayesian dynamic factor model performs well both in terms of point forecast and in terms of density forecasts. Results indicate that our model outperforms standard univariate benchmark models, that it performs as well as the Bloomberg survey, and that it outperforms the predictions published by the Norges Bank in its Monetary Policy Report.

Authors

  • Matteo Luciani
  • Lorenzo Ricci

JEL codes

  • C32
  • C53
  • E37

Other papers in this issue

Michael Koetter and Kasper Roszbach and Giancarlo Spagnolo

Céline Gauthier and Moez Souissi and Xuezhi Liu

Evangelos Benos and Rodney J. Garratt and Peter Zimmerman

Sophocles N. Brissimis and Manthos D. Delis and Maria Iosifidi