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How good are out of sample forecasting tests on DSGE models?

Minford, Anthony Patrick Leslie, Xu, Yongdeng and Zhou, Peng 2015. How good are out of sample forecasting tests on DSGE models? Italian Economic Journal 1 (3) , pp. 333-351. 10.1007/s40797-015-0020-9

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Abstract

Out-of-sample forecasting tests of DSGE models against time-series benchmarks such as an unrestricted VAR are increasingly used to check (a) the specification and (b) the forecasting capacity of these models. We carry out a Monte Carlo experiment on a widely-used DSGE model to investigate the power of these tests. We find that in specification testing they have weak power relative to an in-sample indirect inference test; this implies that a DSGE model may be badly mis-specified and still improve forecasts from an unrestricted VAR. In testing forecasting capacity they also have quite weak power, particularly on the lefthand tail. By contrast a model that passes an indirect inference test of specification will almost definitely also improve on VAR forecasts.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Business (Including Economics)
Subjects: H Social Sciences > H Social Sciences (General)
Publisher: Springer
ISSN: 2199-322X
Date of First Compliant Deposit: 30 March 2016
Date of Acceptance: 9 July 2015
Last Modified: 21 Mar 2019 00:08
URI: http://orca.cf.ac.uk/id/eprint/75348

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