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

Author(s): David Meenagh, Patrick Minford, Michael R. Wickens and Yongdeng Xu

Publication Date: August 2015

Keyword(s): DSGE model, error processes, indirect inference, likelihood ratio and structural parameters

Programme Area(s): Monetary Economics and Fluctuations

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.

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Bibliographic Reference

Meenagh, D, Minford, P, Wickens, M and Xu, Y. 2015. 'Comparing Indirect Inference and Likelihood testing: asymptotic and small sample results'. London, Centre for Economic Policy Research. https://cepr.org/active/publications/discussion_papers/dp.php?dpno=10765