This paper reviews and compares twenty-one different model selection algorithms (MSAs) representing a diversity of approaches, including (i) information criteria such as AIC and SIC; (ii) selection of a “portfolio” or best subset of models; (iii) general-to-specific algorithms, (iv)...

This review surveys a number of common Model Selection Algorithms (MSAs), discusses how they relate to each other, and identifies factors that explain their relative performances. At the heart of MSA performance is the trade-off between Type I and Type II errors. Some relevant variables will be...

This study investigates U.S. state economic growth from 1970-1999. I innovate on previous studies by developing a new approach for addressing "model uncertainty" issues associated with estimating growth equations. My approach borrows from the "extreme bounds analysis" (EBA) approach of Leamer...