Macroeconomists construct impulse responses using many competing time series models and different statistical paradigms (Bayesian or frequentist). We adapt optimal linear prediction pools to efficiently combine impulse response estimators for the effects of the same economic shock from this vast...

This paper addresses the challenge of inflation forecasting by adopting a thick modeling approach that integrates forecasts from time- and frequency-domain models. Frequency-domain models excel at capturing long-term trends while also accounting for short-term fluctuations. Combining these...

We introduce a frequency-domain forecast combination method that leverages time- and frequencydependent predictability to enhance forecast accuracy. By decomposing both the target variables (equity premium and real GDP growth) and predictor variables into distinct frequency components, this...

This paper explores the out-of-sample forecasting performance of 25 equity premium predictors over a sample period from 1973 to 2023. While conventional time-series methods reveal that only one predictor demonstrates significant out-of-sample predictive power, frequency-domain analysis uncovers...