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How Do Adaptive Learning Expectations Rationalize Stronger Monetary Policy Response in Brazil?
Author:
Allan Dizioli
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Hou Wang
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Series:
IMF Working Papers
Volume/Issue:
Volume 2023: Issue 019
Language:
English
Publication Date:
27 Jan 2023
DOI:
https://doi.org/10.5089/9798400229954.001
ISBN:
9798400229954
ISSN:
1018-5941
Pages:
30
Keywords:
DSGE; Inflation dynamics; optimal monetary policy; Forecasting and Simulation; Bayesian estimation.; learning expectation; inflation expectation; wages expectation; Inflation; Output gap; Real wages; Wage gap; Central bank policy rate; Global
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IMF Working Papers describe research in progress by the author(s) and are published to elicit comments and to encourage debate. The views expressed in IMF Working Papers are those of the author(s) and do not necessarily represent the views of the IMF, its Executive Board, or IMF management.
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This paper estimates a standard Dynamic Stochastic General Equilibrium (DSGE) model that includes a wage and price Phillip's curves with different expectation formation processes for Brazil and the USA. Other than the standard rational expectation process, we also use a limited rationality process, the adaptive learning model. In this context, we show that the separate inclusion of a labor market in the model helps to anchor inflation even in a situation of adaptive expectations, a positive output gap and inflation above target. The estimation results show that the adaptive learning model does a better job in fitting the data in both Brazil and the USA. In addition, the estimation shows that expectations are more backward-looking and started to drift away sooner in 2021 in Brazil than in the USA. We then conduct optimal policy exercises that prescribe early monetary policy tightening in the context of positive output gaps and inflation far above the central bank target.
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Cover IMF Working Papers
IMF Working Papers
ISSN:
1018-5941
Publisher:
International Monetary Fund
Volume 2023: Issue 019