Small sample performance of indirect inference on DSGE models

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

No 10382, 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 in small samples, using various models in widespread use. We compare these with tests based on direct inference (using the Likelihood Ratio). We find that both tests have power so that a substantially false model will tend to be rejected by both; but that the power of the indirect inference test is by far the greater, necessitating re-estimation to ensure that the model is tested in its fullest sense. We also find that the small-sample bias with indirect estimation is around half of that with maximum likelihood estimation.

Keywords: Bootstrap; Dsge; 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: 2015-02
New Economics Papers: this item is included in nep-dge and nep-mac
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
https://cepr.org/publications/DP10382 (application/pdf)

Related works:
Working Paper: Small sample performance of indirect inference on DSGE models (2015)
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:10382

Ordering information: This working paper can be ordered from
https://cepr.org/publications/DP10382

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 ().