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Regime-Switching Density Forecasts Using Economists' Scenarios

Graziano Moramarco

arXiv 26 Oct 2021 · Econometrics · publishedJournal of Forecasting (2024)

arXiv:2110.13761 · PDF · DOI · OpenAlex · Extracted main text

Abstract

We propose an approach for generating macroeconomic density forecasts that incorporate information on multiple scenarios defined by experts. We adopt a regime-switching framework in which sets of scenarios ("views") are used as Bayesian priors on economic regimes. Predictive densities coming from different views are then combined by optimizing objective functions of density forecasting. We illustrate the approach with an empirical application to quarterly real-time forecasts of U.S. GDP growth, in which we exploit the Fed's macroeconomic scenarios used for bank stress tests. We show that the approach achieves good accuracy in terms of average predictive scores and good calibration of forecast distributions. Moreover, it can be used to evaluate the contribution of economists' scenarios to density forecast performance.

Citation extraction

44
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Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Gneiting, T. and Ranjan, R (2010) Combining Probability Forecasts0.87452100%
2Gneiting, T. and Ranjan, R (2013) Combining predictive distributions0.87452100%
3Frühwirth-Schnatter, S (2006) Finite Mixture and Markov Switching Models0.7547343%
4Rossi, B. and Sekhposyan, T (2014) Evaluating predictive densities of US output growth and inflation in a large macroeconomic data set0.73732100%
5Bauwens, L., Carpantier, J., and Dufays, A (2017) Autoregressive Moving Average Infinite Hidden Markov-Switching Models0.73732100%
6Ganics, G (2017) Optimal Density Forecast Combinations, Working papers n0.73732100%
7Garratt, A., Henckel, T., and Vahey, S.P (2023) Empirically-transformed linear opinion pools0.73732100%
8Hamilton, J (2016) Macroeconomic Regimes and Regime Shifts, in J.B0.73732100%
9Acemoglu, D., Ozdaglar, A., and Tahbaz-Salehi, A (2017) Microeconomic Origins of Macroeconomic Tail Risks0.64422100%
10Alessandri, P. and Mumtaz, H (2017) Financial conditions and density forecasts for US output and inflation0.64422100%

Showing the top 10 of 44 scored citations.