Abstract
We examine two issues in business cycle research. We first compare the performance of Hamilton's Markov-Switching (MS) model and the Bry and Boschan algorithm in replicating the US business cycle features. A number of studies, especially Harding and Pagan, have demonstrated that Hamilton's nonlinear MS model do not replicate business cycle features better than simpler linear models. Second, we compare the ability of the U.S. real GDP and a relatively new coincident index of four economic indicators, published by the Federal Reserve Bank of Philadelphia, in replicating features of the U.S. business cycle. We find that Hamilton's MS model is not robust when compared to the Bry and Boschan algorithm with respect to different sample periods and to different measures of real income. Second, we also find that a constructed quarterly version of the coincident index is slightly preferred over the real GDP.