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Indeterminacy and Imperfect Information

Author

Listed:
  • Thomas Lubik

    (Federal Reserve Bank of Richmond)

  • Christian Matthes

    (Indiana University)

  • Elmar Mertens

    (Deutsche Bundesbank)

Abstract

We study equilibrium determination in an environment where two types of agents have different information sets: Fully informed agents observe histories of all exogenous and endogenous variables. Less informed agents observe only a strict subset of the full information set and need to solve a dynamic signal extraction problem to gather information about the variables they do not directly observe. Both types of agents know the structure of the model and form expectations rationally. In this environment, we identify a new channel that generates equilibrium indeterminacy: Optimal information processing of the less informed agent introduces stable dynamics into the equation system that lead to self-fulling expectations. For parameter values that imply a unique equilibrium under full information, the limited information rational expectations equilibrium is indeterminate. We illustrate our framework with monetary policy models where an imperfectly informed central bank follows an interest rate rule. (Copyright: Elsevier)

Suggested Citation

  • Thomas Lubik & Christian Matthes & Elmar Mertens, 2023. "Indeterminacy and Imperfect Information," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 49, pages 37-57, July.
  • Handle: RePEc:red:issued:20-377
    DOI: 10.1016/j.red.2022.09.003
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    1. Sorge Marco M., 2020. "Computing sunspot solutions to rational expectations models with timing restrictions," The B.E. Journal of Macroeconomics, De Gruyter, vol. 20(2), pages 1-10, June.
    2. Angelini, Giovanni & Sorge, Marco M., 2021. "Under the same (Chole)sky: DNK models, timing restrictions and recursive identification of monetary policy shocks," Journal of Economic Dynamics and Control, Elsevier, vol. 133(C).
    3. Haque, Qazi & Groshenny, Nicolas & Weder, Mark, 2021. "Do we really know that U.S. monetary policy was destabilizing in the 1970s?," European Economic Review, Elsevier, vol. 131(C).
    4. Jia, Chengcheng, 2023. "The informational effect of monetary policy and the case for policy commitment," European Economic Review, Elsevier, vol. 156(C).
    5. Jia, Chengcheng, 2023. "The informational effect of monetary policy and the case for policy commitment," European Economic Review, Elsevier, vol. 156(C).
    6. Tom D. Holden, 2024. "Robust Real Rate Rules," Econometrica, Econometric Society, vol. 92(5), pages 1521-1551, September.
    7. Paul Levine & Joseph Pearlman & Stephen Wright & Bo Yang, 2023. "Imperfect Information and Hidden Dynamics," School of Economics Discussion Papers 1223, School of Economics, University of Surrey.

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    More about this item

    Keywords

    Limited information; Rational expectations; Kalman filter; Belief shocks;
    All these keywords.

    JEL classification:

    • 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
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy

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