How Do Adaptive Learning Expectations Rationalize Stronger Monetary Policy Response in Brazil?

January 27, 2023

Preview Citation

Format: Chicago

Allan Dizioli, and Hou Wang. How Do Adaptive Learning Expectations Rationalize Stronger Monetary Policy Response in Brazil?, (USA: International Monetary Fund, 2023) accessed November 21, 2024

Disclaimer: 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.

Summary

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.

Subject: Economic sectors, Financial crises

Keywords: Bayesian estimation., DSGE, Forecasting and Simulation, Inflation dynamics, Optimal monetary policy

Publication Details

Pages:

30
Volume:

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DOI:

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Issue:

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Series:

Working Paper No. 2023/019
Stock No:

WPIEA2023019
ISBN:

9798400229954
ISSN:

1018-5941

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