Business cycle dynamics with duration dependence and leading indicators

The topography of leading and lagging business cycle indicators

Predicting Recessions with Leading Indicators: Model Averaging and Selection Over the Business Cycle

Four model selection methods are applied to the problem of predicting business cycle turning points: equally-weighted forecasts, Bayesian model averaged forecasts, and two models produced by the machine learning algorithm boosting. The model selection algorithms condition on different economic indicators at different forecast horizons. Models produced by BMA and boosting outperform equally-weig...

Assessing Malaysia’s Business Cycle indicators

An empirical assessment shows that Malaysia’s business cycle indicators can be improved. Turning point detection is not impressive, especially for troughs. Lead times are also variable. However, the relationship between the leading and coincident indicators over the entire cycle shows quite strong correlations from the late 1980s onwards, although lead times have shortened. Empirical evidence i...

The timing and accuracy of leading and lagging business cycle indicators: A new approach

Leading and trailing indexes are characterized by their timing and their accuracy. Timing is the lead or lagging (trailing) time relative to a target time series, here industrial production (IP). Accuracy is measured here by the correspondence between the directions of changes in the indicator and the target. By plotting candidate leading and trailing time series and the target time series in p...

Leading Indicators of the Business Cycle: Dynamic Logit Models for Oecd Countries and Russia