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Inflation Expectations with Finite Horizon Planning

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Abstract

Under finite horizon planning, households and firms evaluate a full set of state-contingent paths along which the economy might evolve out to a finite horizon but have limited ability to process events beyond that horizon. We show--analytically and empirically--that such a model accounts for an initial underreaction and subsequent overreaction of inflation forecasts. A planning horizon of four quarters can account for the evidence on the predictability of inflation forecast errors and macroeconomic data. Our identification and estimation strategies combine full-information methods based on aggregate data with regression-based estimates that directly use inflation expectations data.

Suggested Citation

  • Christopher J. Gust & Edward P. Herbst & J. David López-Salido, 2024. "Inflation Expectations with Finite Horizon Planning," Finance and Economics Discussion Series 2024-063, Board of Governors of the Federal Reserve System (U.S.).
    • Handle: RePEc:fip:fedgfe:2024-63
    DOI: 10.17016/FEDS.2024.063
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    References listed on IDEAS

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    1. Michael Woodford, 2019. "Monetary Policy Analysis When Planning Horizons Are Finite," NBER Macroeconomics Annual, University of Chicago Press, vol. 33(1), pages 1-50.
    2. Carlos Carvalho & Stefano Eusepi & Emanuel Moench & Bruce Preston, 2023. "Anchored Inflation Expectations," American Economic Journal: Macroeconomics, American Economic Association, vol. 15(1), pages 1-47, January.
    3. Arturo Ormeño & Krisztina Molnár, 2015. "Using Survey Data of Inflation Expectations in the Estimation of Learning and Rational Expectations Models," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 47(4), pages 673-699, June.
    4. Woodford, Michael & Xie, Yinxi, 2022. "Fiscal and monetary stabilization policy at the zero lower bound: Consequences of limited foresight," Journal of Monetary Economics, Elsevier, vol. 125(C), pages 18-35.
    5. N. Gregory Mankiw & Ricardo Reis, 2002. "Sticky Information versus Sticky Prices: A Proposal to Replace the New Keynesian Phillips Curve," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 117(4), pages 1295-1328.
    6. Sergey Slobodyan & Raf Wouters, 2012. "Learning in a Medium-Scale DSGE Model with Expectations Based on Small Forecasting Models," American Economic Journal: Macroeconomics, American Economic Association, vol. 4(2), pages 65-101, April.
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    Cited by:

    1. Gust, Christopher & Herbst, Edward & López-Salido, David, 2025. "Optimal monetary policy with uncertain private sector foresight," Journal of Monetary Economics, Elsevier, vol. 155(C).
    2. Haochun Ma & Jordan Roulleau-Pasdeloup, 2025. "Clearing Up the Effective Lower Bound Morass," Papers 2511.04782, arXiv.org.

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    Keywords

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    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • E70 - Macroeconomics and Monetary Economics - - Macro-Based Behavioral Economics - - - General

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