In this paper we provide simulation and theoretical results concerning the finite sample theory of QML estimators in ARCH models when we include an exogenous variable in the conditional variance equation. In this setting, we find theoretical and simulation support to suggest that if we consider two exogenous variables with the same variance, the one that has the larger sample mean is more likely to produce a larger bias in the QML estimators, in such a way that can be quite misleading in practical applications. We warn about the existence of important biases and potentially low power of the t-tests in these cases. We also propose ways to deal with them. Finally, we generalize the Lumsdaine (1995) invariance properties for the biases in these situations. An empirical application shows the usefulness of our theoretical results.
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.