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Information-driven Business Cycles: A Primal Approach

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  • Chahrour, Ryan
  • Ulbricht, Robert

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

  • Chahrour, Ryan & Ulbricht, Robert, 2017. "Information-driven Business Cycles: A Primal Approach," TSE Working Papers 17-784, Toulouse School of Economics (TSE), revised Dec 2017.
    • Handle: RePEc:tse:wpaper:31575
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    References listed on IDEAS

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    6. Chahrour, Ryan & Ulbricht, Robert, 2017. "Information-driven Business Cycles: A Primal Approach," TSE Working Papers 17-784, Toulouse School of Economics (TSE), revised Dec 2017.
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    15. Ryan Chahrour & Robert Ulbricht, 2023. "Robust Predictions for DSGE Models with Incomplete Information," American Economic Journal: Macroeconomics, American Economic Association, vol. 15(1), pages 173-208, January.
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    1. Chahrour, Ryan & Ulbricht, Robert, 2017. "Information-driven Business Cycles: A Primal Approach," TSE Working Papers 17-784, Toulouse School of Economics (TSE), revised Dec 2017.
    2. Acharya, Sushant & Benhabib, Jess & Huo, Zhen, 2021. "The anatomy of sentiment-driven fluctuations," Journal of Economic Theory, Elsevier, vol. 195(C).
    3. Ryan Chahrour & Kristoffer Nimark & Stefan Pitschner, 2021. "Sectoral Media Focus and Aggregate Fluctuations," American Economic Review, American Economic Association, vol. 111(12), pages 3872-3922, December.
    4. Ambrocio, Gene, 2019. "Measuring household uncertainty in EU countries," Research Discussion Papers 17/2019, Bank of Finland.
    5. Ambrocio, Gene, 2019. "Measuring household uncertainty in EU countries," Bank of Finland Research Discussion Papers 17/2019, Bank of Finland.
    6. Chahrour, Ryan & Gaballo, Gaetano, 2017. "Learning from prices: amplication and business fluctuations," Working Paper Series 2053, European Central Bank.
    7. Han, Zhao & Tan, Fei & Wu, Jieran, 2022. "Analytic policy function iteration," Journal of Economic Theory, Elsevier, vol. 200(C).
    8. Ryan Chahrour & Robert Ulbricht, 2023. "Robust Predictions for DSGE Models with Incomplete Information," American Economic Journal: Macroeconomics, American Economic Association, vol. 15(1), pages 173-208, January.

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    Keywords

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    JEL classification:

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

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