In this article we examine how model selection in neural networks can be guided by statistical procedures such as hypotheses tests, information criteria and cross validation. The application of these methods in neural network models is discussed, paying attention especially to the identification...

A general model specification test of a parametric model against a nonparametric or semiparametric alternative is studied. The test statistic employs a fixed kernel, not varying by a bandwidth. This test is proved to be consistent, the asymptotic distribution is derived and shown to be...

We propose a methodology for constructing valid confidence regions in incomplete models with latent variables satisfying moment equality restrictions. These include moment equality and inequality models with latent variables. The confidence regions are obtained by inverting tests based on the...