#2004-014D "A Bayesian Approach to Counterfactual Analysis of Structural Change"
by Chang-Jin Kim, James Morley, and Jeremy M. Piger
July 2004
Revised June 2006

In this paper, we develop a Bayesian approach to counterfactual analysis of structural change. Contrary to previous analysis based on classical point estimates, this approach provides a straightforward measure of estimation uncertainty for the counterfactual quantity of interest. More...

#2003-015C "Estimation of Markov Regime-Switching Regression Models with Endogenous Switching"
by Chang-Jin Kim, Jeremy M. Piger, and Richard Startz
June 2003
Revised November 2005

Following Hamilton (1989), estimation of Markov regime-switching regressions typically relies on the assumption that the latent state variable controlling regime change is exogenous. We relax this assumption and develop a parsimonious model of endogenous Markov regime-switching. Inference via maximum likelihood estimation is possible with relatively minor modifications to existing recursive filters. More...

#2002-014E "Nonlinearity and the Permanent Effects of Recessions"
by Chang-Jin Kim, James Morley, and Jeremy M. Piger
October 2002
Revised December 2003

This paper presents a new nonlinear time series model that captures a post-recession "bounce-back" in the level of aggregate output. While a number of studies have examined this type of business cycle asymmetry using recession-based dummy variables and threshold models, we relate the "bounce-back" effect to an endogenously estimated unobservable Markov-switching state variable. When the model is applied to U.S. real GDP, we find that the Markov-switching regimes are closely related to NBER-dated recessions and expansions. More...

PUBLISHED: Journal of Applied Econometrics, 2005, 20(2), pp. 291-309

#2001-017D "The Dynamic Relationship Between Permanent and Transitory Components of U.S. Business Cycles"
by Chang-Jin Kim, Jeremy M. Piger, and Richard Startz
April 2001
Revised June 2005

This paper investigates the dynamic relationship between permanent and transitory components of post-war U.S. business cycles. We specify a time-series model for real GNP and consumption in which the two share a common stochastic trend and transitory component, and Markov-regime switching is used to model business cycle phases in these components. More...

FORTHCOMING: Journal of Money, Credit, and Banking

#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

#2001-014A "Common Stochastic Trends, Common Cycles, and Asymmetry in Economic Fluctuations"
by Chang-Jin Kim, and Jeremy M. Piger
October 2001

This paper investigates the nature of U.S. business cycle asymmetry using a dynamic factor model of output, investment, and consumption. We identify a common stochastic trend and common transitory component by embedding the permanent income hypothesis within a simple growth model. More...

PUBLISHED: Journal of Monetary Economics, September 2002, 49(6), pp. 1189-1211