DP10765 Comparing Indirect Inference and Likelihood testing: asymptotic and small sample results

Author(s): David Meenagh, Patrick Minford, Michael R. Wickens, Yongdeng Xu
Publication Date: August 2015
Keyword(s): DSGE model, error processes, indirect inference, likelihood ratio, structural parameters
JEL(s): C12, C32, C52, E1
Programme Areas: Monetary Economics and Fluctuations
Link to this Page: cepr.org/active/publications/discussion_papers/dp.php?dpno=10765

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.