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Robust Predictions for DSGE Models with Incomplete Information

Author

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  • Ryan Chahrour

    (Boston College)

  • Robert Ulbricht

    (Toulouse School of Economics)

Abstract

We provide predictions for DSGE models with incomplete information that are robust across information structures. Our approach maps an incomplete-information model into a full-information economy with time-varying expectation wedges and provides conditions that ensure the wedges are rationalizable by some information structure. Using our approach, we quantify the potential importance of information as a source of business cycle fluctuations in an otherwise frictionless model. Our approach uncovers a central role for firm-specific demand shocks in supporting aggregate confidence fluctuations. Only if firms face unobserved local demand shocks can confidence fluctuations account for a significant portion of the US business cycle.

Suggested Citation

  • Ryan Chahrour & Robert Ulbricht, 2017. "Robust Predictions for DSGE Models with Incomplete Information," Boston College Working Papers in Economics 925, Boston College Department of Economics, revised 10 Jun 2021.
  • Handle: RePEc:boc:bocoec:925
    Note: previously circulated as "Information-driven Business Cycles: A Primal Approach"
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    References listed on IDEAS

    as
    1. Bergemann, Dirk & Morris, Stephen, 2016. "Bayes correlated equilibrium and the comparison of information structures in games," Theoretical Economics, Econometric Society, vol. 11(2), May.
    2. Chahrour, Ryan & Gaballo, Gaetano, 2017. "Learning from prices: amplication and business fluctuations," Working Paper Series 2053, European Central Bank.
    3. Bartosz Maćkowiak & Mirko Wiederholt, 2015. "Business Cycle Dynamics under Rational Inattention," Review of Economic Studies, Oxford University Press, vol. 82(4), pages 1502-1532.
    4. Zhen Huo & Jess Benhabib & Sushant Acharya, 2017. "The Anatomy of Sentiment-driven Fluctuations," 2017 Meeting Papers 513, Society for Economic Dynamics.
    5. Ryan Chahrour & Robert Ulbricht, 2017. "Information-driven Business Cycles: A Primal Approach," Boston College Working Papers in Economics 925, Boston College Department of Economics.
    6. Hansen, Lars Peter & Sargent, Thomas J., 1981. "A note on Wiener-Kolmogorov prediction formulas for rational expectations models," Economics Letters, Elsevier, vol. 8(3), pages 255-260.
    7. Todd Walker & Giacomo Rondina, 2017. "Confounding Dynamics," 2017 Meeting Papers 525, Society for Economic Dynamics.
    8. Christian Hellwig & Venky Venkateswaran, 2015. "Dispersed Information, Sticky Prices and Monetary Business Cycles: A Hayekian Perspective," Working Papers 15-12, New York University, Leonard N. Stern School of Business, Department of Economics.
    9. Chahrour, Ryan & Ulbricht, Robert, 2018. "Robust Predictions for DSGE Models with Incomplete Information," TSE Working Papers 18-971, Toulouse School of Economics (TSE), revised Mar 2019.
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    Blog mentions

    As found by EconAcademics.org, the blog aggregator for Economics research:
    1. Information-driven Business Cycles: A Primal Approach
      by Christian Zimmermann in NEP-DGE blog on 2017-04-12 08:14:56

    Citations

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    Cited by:

    1. Ryan Chahrour & Robert Ulbricht, 2017. "Information-driven Business Cycles: A Primal Approach," Boston College Working Papers in Economics 925, Boston College Department of Economics.
    2. Tatsushi Okuday & Tomohiro Tsurugaz & Francesco Zanetti, 2019. "Imperfect Information, Shock Heterogeneity, and Inflation Dynamics," BCAM Working Papers 1906, Birkbeck Centre for Applied Macroeconomics.
    3. Tatsushi Okuda & Tomohiro Tsuruga & Francesco Zanetti, 2021. "Imperfect information, heterogeneous demand shocks, and inflation dynamics," CAMA Working Papers 2021-29, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    4. Ambrocio, Gene, 2019. "Measuring household uncertainty in EU countries," Research Discussion Papers 17/2019, Bank of Finland.
    5. Chahrour, Ryan & Gaballo, Gaetano, 2017. "Learning from prices: amplication and business fluctuations," Working Paper Series 2053, European Central Bank.
    6. Benhima, Kenza & Poilly, Céline, 2021. "Does demand noise matter? Identification and implications," Journal of Monetary Economics, Elsevier, vol. 117(C), pages 278-295.
    7. Chahrour, Ryan & Ulbricht, Robert, 2018. "Robust Predictions for DSGE Models with Incomplete Information," TSE Working Papers 18-971, Toulouse School of Economics (TSE), revised Mar 2019.

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    More about this item

    Keywords

    Business cycles; DSGE models; incomplete-information; information-robust predictions;
    All these keywords.

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations

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