Central banks

FEDS Paper: Bells and Whistles of Nowcasting Models: Which Matter and When?

Freddy García-Albán and Manuel González-AstudilloThis paper investigates which features of a Bayesian dynamic factor model improve U.S. GDP nowcasts and whether their contribution varies across historical episodes. Using pseudo-real-time information sets for 25 series, we estimate 16 combinations of dynamic heterogeneity, stochastic volatility, time-varying long-run growth, and a multiplicative outlier adjustment.

Forecasting wages with local linear forests

This study applies a Local Linear Forest (LLF) for wage forecasting in France. The LLF outperforms benchmarks such as Random Walk (RW), Ridge Regressions (RR) and Random Forests (RF). We also show that adding foreign predictors (i.e. measures of real activity, price and wage pressures from Germany and Italy) to French economic variables significantly improves wage predictions in France.

Forecasting wages with local linear forests

This study applies a Local Linear Forest (LLF) for wage forecasting in France. The LLF outperforms benchmarks such as Random Walk (RW), Ridge Regressions (RR) and Random Forests (RF). We also show that adding foreign predictors (i.e. measures of real activity, price and wage pressures from Germany and Italy) to French economic variables significantly improves wage predictions in France.

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