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Inattentive agents and inflation forecast error dynamics: A Bayesian DSGE approach

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  • Kim, Insu
  • Kim, Young Se

Abstract

This paper studies a dynamic stochastic general equilibrium model with inattentive agents to explain the dynamic patterns of inflation forecast errors. Empirical findings suggest that inflation forecasts implied by the model are quite similar to survey expectations. This model dominates a full-information rational expectations model in its ability to account for why actual inflation is systematically associated with inflation expectations and survey forecast errors, and for generating excessively persistent forecast errors. Historical decomposition analysis reveals that supply shock and measurement errors in inflation are found to be dominant forces driving variations in inflation forecast errors, while secular shifts in inflation are generated mainly by supply and inflation target shocks.

Suggested Citation

  • Kim, Insu & Kim, Young Se, 2019. "Inattentive agents and inflation forecast error dynamics: A Bayesian DSGE approach," Journal of Macroeconomics, Elsevier, vol. 62(C).
  • Handle: RePEc:eee:jmacro:v:62:y:2019:i:c:s0164070418303033
    DOI: 10.1016/j.jmacro.2019.103139
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    Cited by:

    1. Casarin, Roberto & Costantini, Mauro & Paradiso, Antonio, 2021. "On the role of dependence in sticky price and sticky information Phillips curve: Modelling and forecasting," Economic Modelling, Elsevier, vol. 105(C).

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    More about this item

    Keywords

    Sticky information; Forecast error; Survey forecasts; Rational expectations; Bayesian estimation;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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