Extremum estimation is typically an ad hoc semi-parametric estimation procedure which is only justified on the basis of the asymptotic properties of the estimators. For a fixed finite data set, consider a large number of investigations using different extremum estimators to estimate the same...

In this paper we examine educational data whch has a cross-classified structure. A cross-classified value-added multilevel model is proposed for these data and the problem of estimation are discussed in relation to the probllem of an endogenous regressor.

It is well known that the usual techniques for estimating random and fixed effects panel data models are inconsistent in the dynamic setting. As a consequence, numerous consistent estimators have been proposed in the literature. However, all such estimators rely on certain well defined...

In this poper we present a consistent spacification test of a parametric regression function against a general nonparametric alternative. The proposed test is based on wavelet estimation ant it is shown to have similar rates of convergence to the more commonly used kernel based tests.