Exploiting the monthly data-flow in structural forecasting
Domenico Giannone (),
Francesca Monti () and
Lucrezia Reichlin ()
LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library
This paper shows how and when it is possible to obtain a mapping from a quarterly DSGE model to a monthly specification that maintains the same economic restrictions and has real coefficients. We use this technique to derive the monthly counterpart of the Gali et al (2011) model. We then augment it with auxiliary macro indicators which, because of their timeliness, can be used to obtain a now-cast of the structural model. We show empirical results for the quarterly growth rate of GDP, the monthly unemployment rate and the welfare relevant output gap defined in Gali, Smets andWouters (2011). Results show that the augmented monthly model does best for now-casting.
Keywords: DSGE models; forecasting; temporal aggregation; mixed frequency data; large datasets (search for similar items in EconPapers)
JEL-codes: C33 C53 E30 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-dge, nep-for and nep-mac
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http://eprints.lse.ac.uk/57998/ Open access version. (application/pdf)
Journal Article: Exploiting the monthly data flow in structural forecasting (2016)
Working Paper: Exploiting the monthly data flow in structural forecasting (2015)
Working Paper: Exploiting the monthly data flow in structural forecasting (2014)
Working Paper: Exploiting the monthly data-flow in structural forecasting (2014)
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Persistent link: https://EconPapers.repec.org/RePEc:ehl:lserod:57998
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