A new approach to multi-step forecasting using dynamic stochastic general equilibrium models

Working papers set out research in progress by our staff, with the aim of encouraging comments and debate.
Published on 20 November 2015

Working Paper No. 567
By George Kapetanios, Simon Price and Konstantinos Theodoridis 

DSGE models are of interest because they offer structural interpretations, but are also increasingly used for forecasting. Estimation often proceeds by methods which involve building the likelihood by one-step ahead (h=1) prediction errors. However in principle this can be done using different horizons where h>1. Using the well-known model of Smets and Wouters (2007), for h=1 classical ML parameter estimates are similar to those originally reported. As h extends some estimated parameters change, but not to an economically significant degree. Forecast performance is often improved, in several cases significantly.

PDFDownload PDF

Was this page useful?
Add your details...