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Information-driven Business Cycles: A Primal Approach

Author

Listed:
  • Ryan Chahrour

    (Boston College)

  • Robert Ulbricht

    (Toulouse School of Economics)

Abstract

We develop a methodology to characterize equilibrium in DSGE models, free of parametric restrictions on information. First, we define a “primal” economy in which deviations from full information are captured by wedges in agents' expectations. Then, we provide conditions ensuring some information-structure can implement these wedges. We apply the approach to estimate a business cycle model where firms and households have dispersed information. The estimated model fits the data, attributing the majority of fluctuations to a single shock to households' expectations. The responses are consistent with an implementation in which households become optimistic about local productivities and gradually learn about others' optimism.

Suggested Citation

  • Ryan Chahrour & Robert Ulbricht, 2018. "Information-driven Business Cycles: A Primal Approach," 2018 Meeting Papers 240, Society for Economic Dynamics.
  • Handle: RePEc:red:sed018:240
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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.
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    7. 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.
    8. 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.
    9. Gorodnichenko, Yuriy & Ng, Serena, 2010. "Estimation of DSGE models when the data are persistent," Journal of Monetary Economics, Elsevier, vol. 57(3), pages 325-340, April.
    10. Todd Walker, 2017. "Confounding Dynamics," 2017 Meeting Papers 141, Society for Economic Dynamics.
    11. Ryan Chahrour & Robert Ulbricht, 2017. "Information-driven Business Cycles: A Primal Approach," Boston College Working Papers in Economics 925, Boston College Department of Economics.
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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. Ryan Chahrour & Kristoffer Nimark, 2016. "Sectoral Media Focus and Aggregate Fluctuations," 2016 Meeting Papers 1034, Society for Economic Dynamics.
    3. Ambrocio, Gene, 2019. "Measuring household uncertainty in EU countries," Research Discussion Papers 17/2019, Bank of Finland.
    4. Chahrour, Ryan & Gaballo, Gaetano, 2017. "Learning from prices: amplication and business fluctuations," Working Paper Series 2053, European Central Bank.
    5. 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

    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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