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...

The objective of this paper is to determine how finite dimensional parameters can be efficiently estimated for an important class of economic models.

We develop regression-based tests of hypotheses about out of sample prediction errors. Representative tests include ones for zero mean and zero correlation between a prediction error and a vector of predictors. The relevant environments are ones in which predictions depend on estimated...

In many time series models, an infinite number of moments can be used for estimation in a large sample. I supply a technically undemanding proof of a condition for optimal instrumental variables use of such moments in a parametric model. I also illustrate application of the condition in...

This paper combines techniques drawn from the literature on evolutionary optimization algorithms along with bootstrap based statistical tests. Bootstrapping is used as a general framework for estimating objectives out of sample by redrawing subsets from a training sample. Evolution is used to...