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Forward Guidance with Bayesian Learning and Estimation

Author

Listed:
  • Edward Herbst

    (Federal Reserve Board)

  • David Lopez-Salido

    (Federal Reserve Board)

  • Christopher Gust

    (Federal Reserve Board)

Abstract

We estimate a New Keynesian model in which the private sector has incomplete information about a central bank’s reaction function and must infer it based on economic outcomes. A central bank’s reaction function can change across regimes and we document a systematic change in U.S. policymakers’ reaction function during the 2009-2016 period in which the federal funds rate was at the effective lower bound. This regime is characterized by being more responsive to economic slack and implies that policymakers sought to keep the policy rate at the ZLB longer than would the case by the pre-existing reaction function; hence, we call this the forward guidance regime. We use the model to assess the impact of forward guidance on the macroeconomy and to evaluate the role of imperfect information and learning in limiting its effectiveness.

Suggested Citation

  • Edward Herbst & David Lopez-Salido & Christopher Gust, 2017. "Forward Guidance with Bayesian Learning and Estimation," 2017 Meeting Papers 1189, Society for Economic Dynamics.
    • Handle: RePEc:red:sed017:1189
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    Cited by:

    1. is not listed on IDEAS
    2. Spencer D. Krane & Leonardo Melosi & Matthias Rottner, 2023. "Learning Monetary Policy Strategies at the Effective Lower Bound with Sudden Surprises," Working Paper Series WP 2023-22, Federal Reserve Bank of Chicago.
    3. Tolga Özden, 2021. "Heterogeneous Expectations and the Business Cycle at the Effective Lower Bound," Working Papers 714, DNB.
    4. Martin Bodenstein & James Hebden & Fabian Winkler, 2019. "Learning and Misperception: Implications for Price-Level Targeting," Finance and Economics Discussion Series 2019-078, Board of Governors of the Federal Reserve System (U.S.).

    More about this item

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • 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
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General

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