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

Allan Dizioli and Hou Wang

No 2023/019, IMF Working Papers from International Monetary Fund

Abstract: 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.

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 (search for similar items in EconPapers)
Pages: 30
Date: 2023-01-27
New Economics Papers: this item is included in nep-ban, nep-cba, nep-dge and nep-mon
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