LEARNING ABOUT REGIME CHANGE

Andrew Foerster and Christian Matthes

International Economic Review, 2022, vol. 63, issue 4, 1829-1859

Abstract: Total factor productivity (TFP) and investment specific technology (IST) growth both exhibit regime‐switching behavior, but the regime at any given time is difficult to infer. We build a rational expectations real business cycle model where the underlying TFP and IST regimes are unobserved. We develop a general perturbation solution algorithm for a wide class of models with unobserved regime‐switching. Using our method, we show learning about regime‐switching fits the data, affect the responses to regime shifts and intraregime shocks, increase asymmetries in the responses, generate forecast error bias even with rational agents, and raise the welfare cost of fluctuations.

Date: 2022
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https://doi.org/10.1111/iere.12585

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Working Paper: Learning about Regime Change (2020)
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