#2002-025C "Business Cycle Filtering of Macroeconomic Data Via A Latent Business Cycle Index"
by Michael J. Dueker, and Charles R. Nelson
November 2002
Revised September 2005

We use Markov Chain Monte Carlo methods to augment, via a novel multi-move sampling scheme, a vector autoregressive system with a latent business cycle index that is negative during recessions and positive during expansions. We then sample counterfactual values of the macroeconomic variables in the case where the latent business cycle index is held constant. These counterfactual values represent posterior beliefs about how the economy would have evolved absent business cycle fluctuations. More...

PUBLISHED: Macroeconomic Dynamics, November 2006, 10(5), pp. 573-94

#2001-016C "The Less Volatile US Economy: A Bayesian Investigation of Timing, Breadth,and Potential Explanations"
by Chang-Jin Kim, Charles R. Nelson, and Jeremy M. Piger
October 2001
Revised March 2003

Using a Bayesian model comparison strategy, we search for a volatility reduction within the post-war sample for the growth rates of U.S. aggregate and disaggregate real GDP. We find that the growth rate of aggregate real GDP has been less volatile since the early 1980s, and that this volatility reduction is concentrated in the cyclical component of real GDP. More...

PUBLISHED: Journal of Business and Economic Statistics, January 2004, 22(1), pp. 80-93

#2001-013A "Markov Regime Switching and Unit Root Tests"
by Charles R. Nelson, Eric Zivot, and Jeremy M. Piger
October 2001

We investigate the power and size performance of unit root tests when the data undergo Markov regime switching. All tests, including those robust to a single break in trend growth rate, have low power against a process with a Markov-switching trend. More...

PUBLISHED: Journal of Business and Economic Statistics, October 2001, 19(4), pp. 404-15