A simple and effective misspecification test for the double-hurdle model
The commonly-used version of the double-hurdle model rests on a rather restrictive set of statistical assumptions, which are very seldom tested by practitioners, mainly because of the lack of a standard procedure for doing so, although violation of such assumptions can lead to serious modelling aws. We propose here a bootstrap-corrected conditional moment portmanteau test which is simple to implement and has good size and power properties.
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