The paper evaluates the usefulness of a nonparametric approach to Bayesian inferece by presenting two applications. Our first application considers an educational choice problem. The second application is to quantile regression.

In this paper, we explore Bayesian inference in models with many instrumental variables that are potentially weakly correlated with the endogenous regressor. The prior distribution has a hierarchical (nested) structure.

This paper provides a unified framework for interpreting a wide range of interactions models which have appreared in the economic literature. The framework bears a close relationship to econometric models of descrete choice and therefore holds the potential for rendering interactions models...

This paper puts forth a concept of Adptivety Rational Equilibrium (A.R.E) where agents base decisions upon predictions of future values of endogenous variables whose actual values are determined by equilibrium equations.

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...