Empirical economic research typically uses education as a proxy for human capital. However, research aimed at validating the inclusion of education measures in growth regressions has yet to reach a consensus, often finding that the sign and significance of education depends on the sample of...

Bayesian model averaging has increasingly witnessed applications across an array of empirical contexts. However, the dearth of available statistical software which allows one to engage in a model averaging exercise is limited. It is common for consumers of these methods to develop their own...

This paper describes the relative merits and attractiveness of the newest Bayesian model averaging package, BMS, available in the statistical software R to implement a Bayesian model averaging exercise. This package provides the user with a wide range of customizable priors for conducting a BMA...

Modeling the cross-country distribution of per capita using mixture analysis provides a natural platform for the recovery or detection of clubs of countries. Unfortunately, these mixture methods, when based on a strictly univariate approach are limiting towards one's ability to learn about the...

A well established fact in the growth empirics literature is the increasing variation in output per capita across countries. This phenomena however does not adequately describe changes in the distribution of output since it does not account for changes in the covariates which undoubtedly in...

In this note we present r th order kernel density derivative estimators using canonical higher-order kernels. These canonical rescalings uncouple the choice of kernel and scale factor. This approach is useful for selection of the order of the kernel in a data-driven procedure as well as for...

This note derives the general form of the approximate mean integrated squared error for the q-variate, th-order kernel density r th derivative estimator. This formula allows for normal reference rule-of-thumb bandwidths to be derived. We give tables for some of the most common cases in the...

Uncovering gradients is of crucial importance across a broad range of economic environments. Here we consider data-driven bandwidth selection based on the gradient of an unknown regression function. The procedure developed here is automatic and does not require initial estimation of unknown...

There has recently been a dramatic increase in the number of papers that have combined quasi-experimental methods with hedonic property models. This is largely due to the concern that cross-sectional hedonic methods may be severely biased by omitted variables. While the empirical literature has...