Working Paper: CEPR ID: DP2400
Authors: Mario Forni; Marc Hallin; Marco Lippi; Lucrezia Reichlin
Abstract: This paper proposes a new way to compute a coincident and a leading index of economic activity. The method provides a unified approach for the selection of the coincident and the leading variables, for averaging them into coincident and leading indexes and for the identification of turning points. The statistical framework we propose reconciles dynamic principal components analysis wit dynamic factor analysis. We use our procedure to estimate coincident and leading indexes for the EMU area as well as country-specific indexes. Unlike other methods used in the literature, the country indexes take into consideration the cross-country as well as the within-country correlation structure.
Keywords: coincident and leading indicators; dynamic factor models; dynamic principal components
JEL Codes: C13; C33; C43
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| Cleaning data from noise (Y10) | Enhancing accuracy of the coincident index (C43) |
| Cleaning data from noise (Y10) | Identification of turning points in economic activity (E32) |
| Methodology (C90) | More nuanced understanding of relationships among economic variables (E19) |
| Methodology (C90) | Identification of turning points in economic activity (E32) |