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Estimating unobservable inflation expectations in the New Keynesian Phillips Curve

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  • Francesca Rondina

    (Department of Economics, University of Ottawa, Ottawa, ON)

Abstract

This paper uses an econometric model and Bayesian estimation to reverse engineer the path of inflation expectations implied by the New Keynesian Phillips Curve and the data. The estimated expectations roughly track the patterns of a number of common measures of expected inflation available from surveys or computed from financial data. In particular, they exhibit the strongest correlation with the inflation forecasts of the respondents in the University of Michigan Survey of Consumers. The estimated model also shows evidence of the anchoring of long run inflation expectations to a value that is in the range of the target inflation rate.

Suggested Citation

  • Francesca Rondina, 2018. "Estimating unobservable inflation expectations in the New Keynesian Phillips Curve," Working Papers 1804E, University of Ottawa, Department of Economics.
    • Handle: RePEc:ott:wpaper:1804e
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    References listed on IDEAS

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    Cited by:

    1. Rosa Ferrentino & Luca Vota, 2020. "A Mathematical Model for the Study of the Effects of the Economic Cycle on the Real GDP Growth Rate through the Expectations-Adjusted Phillips Curve," International Journal of Economics and Financial Issues, Econjournals, vol. 10(2), pages 222-234.

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    More about this item

    Keywords

    Phillips curve; expectations; survey data; Bayesian estimation.;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles
    • E5 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit

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