Classical exponential-family statistical theory is employed to characterize the class of exactly similar tests for a structural coefficient in a simultaneous equations model with normal errors and known reduced-form covariance matrix. We also find a necessary condition for tests to be unbiased and derive their power envelope. When the model is just-identified, we show that the Anderson-Rubin score, and conditioal likelihood ratio tests are optimal. When the model is over-identified, there exists no optimal tests. Nevertheless, Monte Carlo simulations indicate that the power curve of the conditional likelihood ratio tests is reasonably close to the power envelope.
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.
For technical questions regarding this item, or to correct its listing, contact: (Thomas Krichel).
Related research
Keywords:
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.)