This paper presents recent developments in model selection and model averaging for parametric and nonparametric models. While there is extensive literature on model selection under parametric settings, we present recently developed results in the context of nonparametric models. In applications,...

I analyze damage from hurricane strikes on the United States since 1955. Using machine learning methods to select the most important drivers for damage, I show that large errors in a hurricane's predicted landfall location result in higher damage. This relationship holds across a wide range of...

A specification search algorithm is proposed that aims to assist the user in the process of constructing Vector Error Correction Models. The algorithm automates testing the cointegration rank of the system and performs simplifications based on possible weak exogeneity of some variables....