Consistent
Specification
Testing
James Davidson (University of Exeter)
11/03/11
We generalize Bierens’(1982, 1990) approach to a wider class of models
and estimators. Bierens constructs consistent moment tests in the
context of linear and nonlinear least squares but there are a number of
mis-specifications, such as heteroskedastic errors, against which they
will not typically have power. Our framework is independent of the form
of the model, and covers all variants of maximum likelihood and
quasi-maximum likelihood estimation and also the generalized method of
moments. It has particular applications in new cases such as discrete
data models, but the chief appeal of our approach is that it provides a
"one size fits all" test, that can be computed routinely, does not need
to be tailored to the particular model, and is expected to have power
against a wide class of alternatives. Although primarily envisaged as a
test of functional form, this type of moment test can also be extended
to testing for omitted variables.
Joint work with A.G. Halunga
Paper is available from here
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