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A Measure of our Uncertainty: Households’ Inflation Expectation and Information Shocks

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  • Ignacio Galará

    (Banco de España)

Abstract

This work focus on understanding deeper how the general public form their inflation expectations, addressing the importance of having well (micro)founded models to forecast consumer’s inflation expectations, not only for inflationary countries (like some developing ones) or inflationary contexts (like the one that begins after COVID-19 pandemic), but also when there exist some information breaks driven by specific global or national events. By a proposed VAR structural model based on behavioral mechanisms, and a state-space model based on Bayesian’s principles, I use data from Argentina and the US to retrieve a latent variable of attention to own beliefs and to outside information, which proves to be related to information outbreaks, and that correlates with different uncertainty measures, specially during those breaks.

Suggested Citation

  • Ignacio Galará, 2023. "A Measure of our Uncertainty: Households’ Inflation Expectation and Information Shocks," Working Papers 273, Red Nacional de Investigadores en Economía (RedNIE).
    • Handle: RePEc:aoz:wpaper:273
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    File URL: https://rednie.eco.unc.edu.ar/files/DT/273.pdf
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    References listed on IDEAS

    as
    1. Canova, Fabio, 2007. "G-7 Inflation Forecasts: Random Walk, Phillips Curve Or What Else?," Macroeconomic Dynamics, Cambridge University Press, vol. 11(1), pages 1-30, February.
    2. Michael J. Lamla & Samad Sarferaz, 2012. "Updating inflation expectations," KOF Working papers 12-301, KOF Swiss Economic Institute, ETH Zurich.
    3. Michael Weber, 2022. "Subjective inflation expectations of households," Business Economics, Palgrave Macmillan;National Association for Business Economics, vol. 57(4), pages 217-221, October.
    4. Canova, Fabio & Ferroni, Filippo, 2020. "A hitchhiker guide to empirical macro models," CEPR Discussion Papers 15446, Centre for Economic Policy Research.
    5. Andrew Atkeson & Lee E. Ohanian, 2001. "Are Phillips curves useful for forecasting inflation?," Quarterly Review, Federal Reserve Bank of Minneapolis, vol. 25(Win), pages 2-11.
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    More about this item

    JEL classification:

    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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