We develop a novel Markov switching vector autoregressive model to investigate the possibility that leading indicators have different lead times at business cycle peaks and at troughs. In this model, coincident and leading indicators share a common Markov state process, but their cycles are nonsynchronous, with the nonsynchronicity varying across regimes. An application shows that on average the Conference Board’s Composite Leading Index leads the Composite Coincident Index by nearly 1 year at peaks but by only 1 quarter at troughs. Allowing for asymmetric lead times yields improved real-time dating and forecasting of business cycle turning points.

Bayesian inference, Markov switching, business cycle, leading indicators, real-time data
Bayesian Analysis (jel C11), Time-Series Models; Dynamic Quantile Regressions (jel C32), Model Construction and Estimation (jel C51), Business Fluctuations; Cycles (jel E32)
dx.doi.org/10.1198/jbes.2009.07061, hdl.handle.net/1765/18651
ERIM Top-Core Articles , Econometric Institute Reprint Series
Journal of Business and Economic Statistics
Erasmus Research Institute of Management

Paap, R. (2009). Do leading indicators lead peaks more than troughs?. Journal of Business and Economic Statistics, 27(4), 528–543. doi:10.1198/jbes.2009.07061