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Quantifying Confidence

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  • George‐Marios Angeletos
  • Fabrice Collard
  • Harris Dellas

Abstract

We develop a tractable method for augmenting macroeconomic models with autonomous variation in higher‐order beliefs. We use this to accommodate a certain type of waves of optimism and pessimism that can be interpreted as the product of frictional coordination and, unlike the one featured in the news literature, regards the short‐term economic outlook rather than the medium‐ to long‐run prospects. We show that this enrichment provides a parsimonious explanation of salient features of the data; it accounts for a significant fraction of the business‐cycle volatility in estimated models that allow for various competing structural shocks; and it captures a type of fluctuations that have a Keynesian flavor but do not rely on nominal rigidities.

Suggested Citation

  • George‐Marios Angeletos & Fabrice Collard & Harris Dellas, 2018. "Quantifying Confidence," Econometrica, Econometric Society, vol. 86(5), pages 1689-1726, September.
  • Handle: RePEc:wly:emetrp:v:86:y:2018:i:5:p:1689-1726
    DOI: 10.3982/ECTA13079
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    References listed on IDEAS

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    1. Alessandro Pavan, 2014. "Attention, Coordination, and Bounded Recall," Discussion Papers 1576, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
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    7. Chari, V.V. & Kehoe, Patrick J. & McGrattan, Ellen R., 2008. "Are structural VARs with long-run restrictions useful in developing business cycle theory?," Journal of Monetary Economics, Elsevier, vol. 55(8), pages 1337-1352, November.
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    Cited by:

    1. Oscar Pavlov & Mark Weder, 2017. "Product Scope and Endogenous Fluctuations," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 24, pages 175-191, March.
    2. Bennani, Hamza, 2019. "Does People's Bank of China communication matter? Evidence from stock market reaction," Emerging Markets Review, Elsevier, vol. 40(C), pages 1-1.
    3. Enders, Zeno & Kleemann, Michael & Müller, Gernot, 2013. "Growth expectations, undue optimism, and short-run fluctuations," Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 80009, Verein für Socialpolitik / German Economic Association.
    4. Saki Bigio & Eduardo Zilberman, 2020. "Speculation-Driven Business Cycles," Working Papers Central Bank of Chile 865, Central Bank of Chile.
    5. Alexandra Born & Zeno Enders, 2019. "Global Banking, Trade, and the International Transmission of the Great Recession," Economic Journal, Royal Economic Society, vol. 129(623), pages 2691-2721.
    6. Dées, Stephane & Zimic, Srečko, 2019. "Animal spirits, fundamental factors and business cycle fluctuations," Journal of Macroeconomics, Elsevier, vol. 61(C), pages 1-1.
    7. Lance Kent, 2015. "Relaxing Rational Expectations," Working Papers 159, Department of Economics, College of William and Mary.
    8. Bijapur, Mohan, 2014. "What Drives Business Cycle Fluctuations: Aggregate or Idiosyncratic Uncertainty Shocks?," MPRA Paper 60361, University Library of Munich, Germany.
    9. Benhabib, Jess & Liu, Xuewen & Wang, Pengfei, 2016. "Sentiments, financial markets, and macroeconomic fluctuations," Journal of Financial Economics, Elsevier, vol. 120(2), pages 420-443.
    10. Christian Myohl & Yannic Stucki, 2018. "Confidence and the Financial Accelerator," Diskussionsschriften dp1823, Universitaet Bern, Departement Volkswirtschaft.
    11. Nowzohour, Laura & Stracca, Livio, 2017. "More than a feeling: confidence, uncertainty and macroeconomic fluctuations," Working Paper Series 2100, European Central Bank.
    12. Ryan Chahrour & Kristoffer Nimark, 2016. "Sectoral Media Focus and Aggregate Fluctuations," 2016 Meeting Papers 1034, Society for Economic Dynamics.
    13. Kozeniauskas, Nicholas & Orlik, Anna & Veldkamp, Laura, 2018. "What are uncertainty shocks?," Journal of Monetary Economics, Elsevier, vol. 100(C), pages 1-15.
    14. Christian Myohl, 2018. "The Effect of a Financial Block on the Identification of Confidence Shocks in a Structural VAR Model," Diskussionsschriften dp1821, Universitaet Bern, Departement Volkswirtschaft.
    15. Angeletos, G.-M. & Lian, C., 2016. "Incomplete Information in Macroeconomics," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 1065-1240, Elsevier.
    16. Hall, R.E., 2016. "Macroeconomics of Persistent Slumps," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 2131-2181, Elsevier.
    17. Andres Algaba & David Ardia & Keven Bluteau & Samuel Borms & Kris Boudt, 2020. "Econometrics Meets Sentiment: An Overview Of Methodology And Applications," Journal of Economic Surveys, Wiley Blackwell, vol. 34(3), pages 512-547, July.
    18. Hollmayr, Josef & Kühl, Michael, 2019. "Learning about banks’ net worth and the slow recovery after the financial crisis," Journal of Economic Dynamics and Control, Elsevier, vol. 109(C).
    19. Omotosho, Babatunde S., 2019. "Business Cycle Fluctuations in Nigeria: Some Insights from an Estimated DSGE Model," MPRA Paper 98351, University Library of Munich, Germany.
    20. Anmol Bhandari & Jaroslav Borovicka & Paul M. Horvitz, 2019. "Survey Data and Subjective Beliefs in Business Cycle Models," Working Paper 19-14, Federal Reserve Bank of Richmond.

    More about this item

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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