The paper introduces a two-factor model of the common leading and coincident economic indicators. Both factors are unobserved and each of them captures the dynamics of a corresponding group of the observed time series. The common leading factor is assumed to Granger-cause the common coincident factor. This property is used to estimate these two factors simultaneously and hence more efficiently. Two models of the latent leading and coincident factors are studied : a model with linear dynamics and a model with Markov-switching dynamics introduced through the leading factor intercept term. Moreover, a possibility of the individual leading variables having different leads over the common coincident indicator is considered. These models - both with linear and with regime-switching dynamics - were applied to the US monthly macroeconomic time series. The business cycle dating resulting from the nonlinear model closely corresponds to the NBER chronology and leads its turning points by 3-5 months.
[1]
R. Mariano,et al.
A New Coincident Index of Business Cycles Based on Monthly and Quarterly Series
,
2002
.
[2]
Chang‐Jin Kim,et al.
Dynamic linear models with Markov-switching
,
1994
.
[3]
Diebold,et al.
Measuring Business Cycle: A Modern Perspective
,
1998
.
[4]
Marcelle Chauvet,et al.
Coincident and Leading Indicators of the Stock Market
,
1999
.
[5]
Chang‐Jin Kim,et al.
State-Space Models with Regime-Switching: Classical and Gibbs Sampling Approaches with Applications
,
1999
.
[6]
Marcelle Chauvet,et al.
An Econometric Characterization of Business Cycle Dynamics with Factor Structure and Regime Switching
,
1998
.
[7]
J. Stock,et al.
A Probability Model of the Coincident Economic Indicators
,
1988
.