Working Paper: CEPR ID: DP6564
Authors: Antonello D'Agostino; Domenico Giannone
Abstract: This paper compares the predictive ability of the factor models of Stock and Watson (2002) and Forni, Hallin, Lippi, and Reichlin (2005) using a large panel of US macroeconomic variables. We propose a nesting procedure of comparison that clarifies and partially overturns the results of similar exercises in the literature. Our main conclusion is that for the dataset at hand the two methods have a similar performance and produce highly collinear forecasts.
Keywords: factor models; forecasting; large cross-section
JEL Codes: C31; C52; C53
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| SW method (C87) | forecasting performance (C53) |
| FHLR method (Y50) | forecasting performance (C53) |
| SW method (C87) | RMSFE (C20) |
| FHLR method (Y50) | RMSFE (C20) |
| RMSFE of SW method (C20) | forecasting performance (C53) |
| RMSFE of FHLR method (C51) | forecasting performance (C53) |
| SW method correlation with FHLR method (C59) | forecasting performance (C53) |