Before revision:  We argue that in general a large value of n is better than a large value of T. Conditions for asymptotic normality of linear and nonlinear functionals of the estimated function of interest are derived. These results are further applied to obtain the asymptotic distribution of the Wald test when the number of constraints under the null is finite and when it diverges to infinity along with other asymptotic parameters.
After revision:  We argue that in general a large value of n is better than a large value of T. Conditions for asymptotic normality of linear and nonlinear functionals of the estimator of Tand apply them to obtain the asymptotic distribution of the Wald test when the number of constraints under the null is finite and when it diverges to infinity along with other asymptotic parameters.