Testing DSGE models by Indirect inference and other methods: some Monte Carlo experiments

A. Patrick Minford, Michael Wickens, David Meenagh and Vo Phuong Mai Le

No 9056, CEPR Discussion Papers from Centre for Economic Policy Research

Abstract: Using Monte Carlo experiments, we examine the performance of Indirect Inference tests of DSGE models, usually versions of the Smets-Wouters New Keynesian model of the US postwar period. We compare these with tests based on direct inference (using the Likelihood Ratio), and on the Del Negro-Schorfheide DSGE-VAR weight. We find that the power of all three tests is substantial so that a false model will tend to be rejected by all three; but that the power of the indirect inference tests are by far the greatest, necessitating re-estimation by indirect inference to ensure that the model is tested in its fullest sense.

Keywords: Bootstrap; Dsge; Dsge-var weight; indirect inference; Likelihood ratio; New classical; New keynesian; Wald statistic (search for similar items in EconPapers)
JEL-codes: C12 C32 C52 E1 (search for similar items in EconPapers)
Date: 2012-07
New Economics Papers: this item is included in nep-dge and nep-ecm
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (37)

Downloads: (external link)
https://cepr.org/publications/DP9056 (application/pdf)

Related works:
Working Paper: Testing DSGE models by Indirect inference and other methods: some Monte Carlo experiments (2012)
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:cpr:ceprdp:9056

Ordering information: This working paper can be ordered from
https://cepr.org/publications/DP9056

Access Statistics for this paper

More papers in CEPR Discussion Papers from Centre for Economic Policy Research 33 Great Sutton Street, London EC1V 0DX, UK.
Bibliographic data for series maintained by CEPR ().