Comparing Indirect Inference and Likelihood testing: asymptotic and small sample results

A. Patrick Minford, Michael R. Wickens, David Meenagh and Yongdeng Xu

No 10765, CEPR Discussion Papers from C.E.P.R. Discussion Papers

Abstract: Indirect Inference has been found to have much greater power than the Likelihood Ratio in small samples for testing DSGE models. We look at asymptotic and large sample properties of these tests to understand why this might be the case. We find that the power of the LR test is undermined when re-estimation of the error parameters is permitted; this offsets the effect of the falseness of structural parameters on the overall forecast error. Even when the two tests are done on a like-for-like basis Indirect Inference has more power because it uses the distribution restricted by the DSGE model being tested.

Keywords: Dsge model; Error processes; indirect inference; Likelihood ratio; Structural parameters (search for similar items in EconPapers)
JEL-codes: C12 C32 C52 E1 (search for similar items in EconPapers)
Date: 2015-08
New Economics Papers: this item is included in nep-dge, nep-ger and nep-mac
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Working Paper: Comparing Indirect Inference and Likelihood testing: asymptotic and small sample results (2015)
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