Working Paper: CEPR ID: DP9360
Authors: Alessandro Beber; Michael Brandt; Maurizio Luisi
Abstract: We propose a simple cross-sectional technique to extract daily latent factors from economic news releases available at different dates and frequencies. Our approach can effectively handle the large number of heterogeneous announcements that are relevant for tracking current economic conditions. We apply the technique to extract real-time measures of inflation, output, employment, and macroeconomic sentiment, as well as corresponding measures of disagreement among economists about these dimensions of the data. We find that our procedure provides more timely and accurate forecasts of the future evolution of the economy than other real-time forecasting approaches in the literature.
Keywords: disagreement; macroeconomic news; nowcasting
JEL Codes: G12
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| methodology (B41) | improved forecasting accuracy (C53) |
| inflation factor (E31) | actual CPI releases (C43) |
| economic uncertainty based on economist disagreement (D89) | end of recession periods (E32) |
| latent growth factor (J20) | CFNAI (E01) |
| latent growth factor (J20) | ADS index (C43) |