Averaging Impulse Responses Using Prediction Pools
Abstract: 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 class of possible models. We thus alleviate the need to choose one specific model, obtaining weights that are typically positive for more than one model. Three Monte Carlo simulations and two monetary shock empirical applications illustrate how the weights leverage the strengths of each model by (i) trading off properties of each model depending on variable, horizon, and application and (ii) accounting for the full predictive distribution rather than being restricted to specific moments.
Keywords: prediction pools; model averaging; impulse responses; misspecification;
File format is application/pdf
Description: working paper
Provider: Federal Reserve Bank of Richmond
Part of Series: Working Paper
Publication Date: 2023-02