In hypothesis testing with nuisance parameters present only under the alternative two issues typically arise: (i) critical values are data dependent and so cannot be tabulated; (ii) we need to choose a functional over the nuisance parameter space. We address the first issue by providing easily computable bounds for the case of dependent and heterogeneous observations. We tackle the second issue by suggesting a weighted average statistic with weights given by the (quasi) likelihood over the nuisance parameter space. The small sample behavior of our procedure is analyzed via Monte Carlo simulations; we consider conditional moment tests and tests for nonlinearities in the SETAR model. An empirical illustration to the modeling of US male unemployment is provided. Copyright Royal Economic Society, 2002
Download Info
To download:
If you experience problems downloading a file, check if you have the
proper application to
view it first. Information about this may be contained
in the File-Format links below. In case of further problems read
the IDEAS help
page. Note that these files are not on the IDEAS
site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Cited by: (explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)