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Recoverability and Expectations-Driven Fluctuations
[Non-Fundamentalness in Structural Econometric Models: A Review]

Author

Listed:
  • Ryan Chahrour
  • Kyle Jurado

Abstract

Time series methods for identifying structural economic disturbances often require disturbances to satisfy technical conditions that can be inconsistent with economic theory. We propose replacing these conditions with a less restrictive condition called recoverability, which only requires that the disturbances can be inferred from the observable variables. As an application, we show how shifting attention to recoverability makes it possible to construct new identifying restrictions for technological and expectational disturbances. In a vector autoregressive example using post-war U.S. data, these restrictions imply that independent disturbances to expectations about future technology are a major driver of business cycles.

Suggested Citation

  • Ryan Chahrour & Kyle Jurado, 2022. "Recoverability and Expectations-Driven Fluctuations [Non-Fundamentalness in Structural Econometric Models: A Review]," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 89(1), pages 214-239.
    • Handle: RePEc:oup:restud:v:89:y:2022:i:1:p:214-239.
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    File URL: http://hdl.handle.net/10.1093/restud/rdab010
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    Citations

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    Cited by:

    1. Pagan, Adrian & Robinson, Tim, 2022. "Excess shocks can limit the economic interpretation," European Economic Review, Elsevier, vol. 145(C).
    2. Davide Brignone & Alessandro Franconi & Marco Mazzali, 2023. "Robust Impulse Responses using External Instruments: the Role of Information," Papers 2307.06145, arXiv.org.
    3. Bartosz Maćkowiak & Mirko Wiederholt, 2021. "Rational Inattention and the Business Cycle Effects of Productivity and News Shocks," Working Papers hal-03878704, HAL.
    4. 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.
    5. Yang, Yang & Tang, Yanling & Zhang, Ren & Wu, Li, 2023. "Investigating the impact of technology and noise shocks on capital flows," Finance Research Letters, Elsevier, vol. 56(C).
    6. Guay, Alain & Pelgrin, Florian, 2023. "Structural VAR models in the Frequency Domain," Journal of Econometrics, Elsevier, vol. 236(1).

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