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Learning, Confidence and Business Cycle

Author

Listed:
  • Hikaru Saijo

    (University of California Santa Cruz)

  • Cosmin Ilut

    (Duke University)

Abstract
We construct and estimate a heterogeneous-firm business cycle model where firms face Knightian uncertainty about their profitability and learn it through production. The cross-sectional mean of firm-level uncertainty is high in recessions because firms invest and hire less. The higher uncertainty reduces agents' confidence and further discourages economic activity. This feedback mechanism endogenously generates properties traditionally explained through additional shocks or rigidities: countercyclical labor and financial wedges, co-movement driven by demand shocks, and amplified and hump-shaped dynamics. We find that endogenous idiosyncratic confidence reduces the empirical role of standard rigidities and changes inference about sources of fluctuations and policy experiments.

Suggested Citation

  • Hikaru Saijo & Cosmin Ilut, 2016. "Learning, Confidence and Business Cycle," 2016 Meeting Papers 664, Society for Economic Dynamics.
    • Handle: RePEc:red:sed016:664
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    References listed on IDEAS

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    Cited by:

    1. Saijo, Hikaru, 2017. "The uncertainty multiplier and business cycles," Journal of Economic Dynamics and Control, Elsevier, vol. 78(C), pages 1-25.
    2. Alexander W. Richter & Nathaniel A. Throckmorton, 2017. "A New Way to Quantify the Effect of Uncertainty," Working Papers 1705, Federal Reserve Bank of Dallas.
    3. Mirela Miescu, 2019. "Uncertainty shocks in emerging economies," Working Papers 277077821, Lancaster University Management School, Economics Department.
    4. Xu, Xiangyun & Li, Xing & Meng, Jie & Hu, Xueqi & Ge, Yingfan, 2024. "The impact of the tail risk of demand on corporate investment: Evidence from Chinese manufacturing firms," Pacific-Basin Finance Journal, Elsevier, vol. 85(C).
    5. George-Marios Angeletos, 2018. "Frictional Coordination," Journal of the European Economic Association, European Economic Association, vol. 16(3), pages 563-603.
    6. Yoo, Donghoon, 2019. "Ambiguous information, permanent income, and consumption fluctuations," European Economic Review, Elsevier, vol. 119(C), pages 79-96.
    7. Claudio Michelacci & Luigi Paciello, 2020. "Aggregate Risk or Aggregate Uncertainty? Evidence from UK Households," EIEF Working Papers Series 2006, Einaudi Institute for Economics and Finance (EIEF), revised Apr 2020.
    8. Paul Levine & Joseph Pearlman & Stephen Wright & Bo Yang, 2019. "Information, VARs and DSGE Models," School of Economics Discussion Papers 1619, School of Economics, University of Surrey.
    9. Jochen Guentner & Elena Afanasyeva, 2017. "Noise-Ridden Lending Cycles," 2017 Meeting Papers 1211, Society for Economic Dynamics.
    10. Guangyu PEI, 2019. "Uncertainty, Pessimism and Economic Fluctuations," 2019 Meeting Papers 1494, Society for Economic Dynamics.

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    More about this item

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy

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