Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/97390
Authors: 
Schennach, Susanne
Wilhelm, Daniel
Year of Publication: 
2014
Series/Report no.: 
cemmap working paper, Centre for Microdata Methods and Practice CWP10/14
Abstract: 
We propose a simple model selection test for choosing among two parametric likelihoods which can be applied in the most general setting without any assumptions on the relation between the candidate models and the true distribution. That is, both, one or neither is allowed to be correctly specified or misspecified, they may be nested, non-nested, strictly non-nested or overlapping. Unlike in previous testing approaches, no pre-testing is needed, since in each case, the same test statistic together with a standard normal critical value can be used. The new procedure controls asymptotic size uniformly over a large class of data generating processes. We demonstrate its finite sample properties in a Monte Carlo experiment and its practical relevance in an empirical application comparing Keynesian versus new classical macroeconomic models.
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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