| Abstrakt: |
We present a numerically convenient procedure for computing Wald criteria for nested hypotheses. Similar to Szroeter's (1983) generalized Wald test, the suggested procedure does not require explicit derivation of the restrictions implied by the null hypothesis and hence its use might eliminate an intricate step in testing linear and nonlinear hypotheses. We show that the traditional Wald test, Szroeter's (1983) generalized Wald test and our procedure are asymptotically equivalent under H. A class of nonlinear transformations of the restrictions for which the Wald statistic is asymptotically invariant is discussed. Finally, we illustrate the use of our procedure for testing the common factor restrictions in a dynamic regression model. [ABSTRACT FROM AUTHOR] |
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