The adaptive lasso is a model selection method shown to be both consistent in variable selection and asymptotically normal in coefficient estimation. The actual variable selection performance of the adaptive lasso depends on the weight used. It turns out that the weight assignment using the OLS...

In the problem of locating multiple public facilities studied by Barbera and Bevia (2002), we offer simple necessary and sufficient conditions for effciency, decentralizability of efficient decisions in a game of community division and local public goods provision, and a constructive algorithm...

We describe some recent developments in PcGets, and consider their impact on its performance across different (unknown) states of nature. We discuss the consistency of its selection procedures, and examine the extent to which model selection is non-distortionary at relevant sample sizes. The...