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Journal articles
Accurate and Robust Tests for Indirect Inference
Abstract : In this paper we propose accurate parameter and over-identification tests for indirect inference. Under the null hypothesis the new tests are asymptotically χ2-distributed with a relative error of order n−1. They exhibit better finite sample accuracy than classical tests for indirect inference, which have the same asymptotic distribution but an absolute error of order n−1/2. Robust versions of the tests are also provided. We illustrate their accuracy in nonlinear regression, Poisson regression with overdispersion and diffusion models.
https://hal-hec.archives-ouvertes.fr/hal-00585938
Contributor : Antoine Haldemann Connect in order to contact the contributor
Submitted on : Thursday, April 14, 2011 - 11:33:08 AM
Last modification on : Thursday, January 11, 2018 - 6:19:32 AM
Contributor : Antoine Haldemann Connect in order to contact the contributor
Submitted on : Thursday, April 14, 2011 - 11:33:08 AM
Last modification on : Thursday, January 11, 2018 - 6:19:32 AM
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