by Matteo Luciania, b and Lorenzo Riccia
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.
JEL Codes: C32, C53, E37.
Full article (PDF, 34 pages, 558 kb)
a ECARES, SBS-EM, Universit´e libre de Bruxelles