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Expectations, stagnation and fiscal policy : a nonlinear analysis

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Evans_2022_Expectations_stagnation_fiscal_policy_IntEconomicRev_CC.pdf (1.157Mb)
Date
08/2022
Author
Evans, George W
Honkapohja, Seppo
Mitra, Kaushik
Keywords
HB Economic Theory
T-NDAS
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Abstract
Stagnation and fiscal policy are examined in a nonlinear stochastic New-Keynesian model with adaptive learning. There are three steady states. The steady state targeted by policy is locally but not globally stable under learning. A severe pessimistic expectations shock can trap the economy in a stagnation regime, underpinned by a low-level steady state, with falling inflation and output. A large fiscal stimulus may be needed to avoid or emerge from stagnation, and the impacts of forward guidance, credit frictions, central bank credibility, and policy delay are studied. Our model encompasses a wide range of outcomes arising from pessimistic expectations shocks.
Citation
Evans , G W , Honkapohja , S & Mitra , K 2022 , ' Expectations, stagnation and fiscal policy : a nonlinear analysis ' , International Economic Review , vol. 63 , no. 3 , pp. 1397-1425 . https://doi.org/10.1111/iere.12573
Publication
International Economic Review
Status
Peer reviewed
DOI
https://doi.org/10.1111/iere.12573
ISSN
0020-6598
Type
Journal article
Rights
Copyright © 2022 The Authors. International Economic Review published by Wiley Periodicals LLC on behalf of the Economics Department of the University of Pennsylvania and the Osaka University Institute of Social and Economic Research Association. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
Description
Funding: National Science Foundation (Grant Number(s): SES-1559209; Grant recipient(s): GEORGE W. EVAN). Yrjö Jahnssonin Säätiö.
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  • University of St Andrews Research
URI
http://hdl.handle.net/10023/25148

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