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Learning, Confidence and Business Cycle

Author

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  • 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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    1. Susanto Basu & Brent Bundick, 2017. "Uncertainty Shocks in a Model of Effective Demand," Econometrica, Econometric Society, vol. 85, pages 937-958, May.
    2. Venky Venkateswaran & Laura Veldkamp & Julian Kozlowski, 2015. "The Tail that Wags the Economy: Belief-Driven Business Cycles and Persistent Stagnation," 2015 Meeting Papers 800, Society for Economic Dynamics.
    3. Joel M. David & Hugo A. Hopenhayn & Venky Venkateswaran, 2016. "Information, Misallocation, and Aggregate Productivity," The Quarterly Journal of Economics, Oxford University Press, vol. 131(2), pages 943-1005.
    4. Lawrence J. Christiano & Martin Eichenbaum & Charles L. Evans, 2005. "Nominal Rigidities and the Dynamic Effects of a Shock to Monetary Policy," Journal of Political Economy, University of Chicago Press, vol. 113(1), pages 1-45, February.
    5. Pablo D. Fajgelbaum & Edouard Schaal & Mathieu Taschereau-Dumouchel, 2017. "Uncertainty Traps," The Quarterly Journal of Economics, Oxford University Press, vol. 132(4), pages 1641-1692.
    6. Tatsuro Senga, 2014. "A New Look at Uncertainty Shocks: Imperfect Information and Misallocation," UTokyo Price Project Working Paper Series 042, University of Tokyo, Graduate School of Economics.
    7. Bidder, R.M. & Smith, M.E., 2012. "Robust animal spirits," Journal of Monetary Economics, Elsevier, vol. 59(8), pages 738-750.
    8. Matthias Kehrig, 2011. "The Cyclicality of Productivity Dispersion," 2011 Meeting Papers 484, Society for Economic Dynamics.
    9. Marinacci, Massimo, 1999. "Limit Laws for Non-additive Probabilities and Their Frequentist Interpretation," Journal of Economic Theory, Elsevier, vol. 84(2), pages 145-195, February.
    10. Straub, Ludwig & Ulbricht, Robert, 2015. "Endogenous Uncertainty and Credit Crunches," TSE Working Papers 15-604, Toulouse School of Economics (TSE), revised Dec 2017.
    11. Guido Lorenzoni, 2009. "A Theory of Demand Shocks," American Economic Review, American Economic Association, vol. 99(5), pages 2050-2084, December.
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    1. repec:eee:dyncon:v:78:y:2017:i:c:p:1-25 is not listed on IDEAS

    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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