A generalized goodness-of-functional form test for binary and fractional regression models
This paper proposes a new conditional mean test to assess the validity of binary and fractional parametric regression models. The new test checks the joint significance of two simple functions of the fitted index and is based on a very flexible parametric generalization of the postulated model. A Monte Carlo study reveals a promising behaviour for the new test, which compares favourably with that of the well-known RESET test as well as with tests where the alternative model is nonparametric.
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