Comparing the DSGE model with the factor model: an out-of-sample forecasting experiment

Mu-Chun Wang

No 2008,04, Discussion Paper Series 1: Economic Studies from Deutsche Bundesbank

Abstract: In this paper, we put DSGE forecasts in competition with factor forecasts. We focus on these two models since they represent nicely the two opposing forecasting philosophies. The DSGE model on the one hand has a strong theoretical economic background; the factor model on the other hand is mainly data-driven. We show that by incooperating large information set using factor analysis can indeed improve the short horizon predictive ability, as claimed by manyresearchers. The micro founded DSGE model can provide reasonable forecasts for inflation, especially with growing forecast horizons. To a certain extent, our results are consistent with the prevailling view that simple time series models should be used in short-horizon forecasting and structural models should be used in long-horizon forecasting. Our paper compareds both state-of-the art data-driven and theory-based modelling in a rigorous manner.

Keywords: DSGE models; factor models; forecasting; forecastevaluation (search for similar items in EconPapers)
JEL-codes: C2 C3 C53 E37 (search for similar items in EconPapers)
Date: 2008
New Economics Papers: this item is included in nep-cba, nep-dge, nep-ecm, nep-for and nep-mac
References: Add references at CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
https://www.econstor.eu/bitstream/10419/19716/1/200804dkp.pdf (application/pdf)

Related works:
Journal Article: Comparing the DSGE model with the factor model: an out-of-sample forecasting experiment (2009)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:zbw:bubdp1:7115

Access Statistics for this paper

More papers in Discussion Paper Series 1: Economic Studies from Deutsche Bundesbank Contact information at EDIRC.
Bibliographic data for series maintained by ZBW - Leibniz Information Centre for Economics ().