A new method of leading index construction is proposed, which explicitly takes into account the purpose of using the index for forecasting a coincident economic indicator. This so-called principal covariate index combines the need for compressing the information in a large number of individual leading indicator variables with the objective of forecasting. In an empirical application to forecast future growth rates of the Conference Board’s Composite Coincident Index and its constituents, the forecasts of the principal covariate index are more accurate than those obtained either from the Composite Leading Index of the Conference Board or from an alternative index-based on principal components.

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Keywords business cycles, index construction, principal component, principal covariate, time series forecasting, variable selection
JEL Time-Series Models; Dynamic Quantile Regressions (jel C32), Forecasting and Other Model Applications (jel C53), Forecasting and Simulation (jel E27)
Persistent URL dx.doi.org/10.1787/jbcma-2011-5kgdwlpzs79v, hdl.handle.net/1765/25629
Groenen, P.J.F, Heij, C, & van Dijk, D.J.C. (2011). Forecasting with Leading Indicators by means of the Principal Covariate Index. OECD Journal: Journal of Business Cycle Measurement and Analysis, 4(1), 73–98. doi:10.1787/jbcma-2011-5kgdwlpzs79v