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Ambiguous Business Cycles, Recessions and Uncertainty: A Quantitative Analysis

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  • Giulia Piccillo
  • Poramapa Poonpakdee

Abstract

This paper investigates the effects of uncertainty on the macro economy by replicating its micro effects on individual subjective beliefs. In our model, the representative household has smooth ambiguity preferences and is uncertain about which scenario the economy will be in the next period: normal growth or recession. We anchor the ratio of expected utilities between the two scenarios through the empirical macroeconomic uncertainty index. The higher the macroeconomic uncertainty is, the deeper the recession that the household is expecting. Our estimations demonstrate that the smooth ambiguity model with an appropriate level of ambiguity aversion outperforms the benchmark model with no uncertainty in fitting the US output growth rate, especially during recessions. This holds true even when tested with out-of-sample forecasts. Our analyses show that the effect of uncertainty on the representative household’s beliefs aligns with the corresponding empirical literature. Moreover, the Global Financial Crisis was associated with an increase in both risk aversion and ambiguity aversion, while the Dot-com Crisis only affected risk aversion.

Suggested Citation

  • Giulia Piccillo & Poramapa Poonpakdee, 2023. "Ambiguous Business Cycles, Recessions and Uncertainty: A Quantitative Analysis," CESifo Working Paper Series 10646, CESifo.
  • Handle: RePEc:ces:ceswps:_10646
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    References listed on IDEAS

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    1. Giorgio Fagiolo & Mauro Napoletano & Andrea Roventini, 2008. "Are output growth-rate distributions fat-tailed? some evidence from OECD countries," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(5), pages 639-669.
    2. Peter Klibanoff & Massimo Marinacci & Sujoy Mukerji, 2005. "A Smooth Model of Decision Making under Ambiguity," Econometrica, Econometric Society, vol. 73(6), pages 1849-1892, November.
    3. Fabrice Collard & Sujoy Mukerji & Kevin Sheppard & Jean‐Marc Tallon, 2018. "Ambiguity and the historical equity premium," Quantitative Economics, Econometric Society, vol. 9(2), pages 945-993, July.
    4. Francesco Bianchi & Cosmin L. Ilut & Martin Schneider, 2018. "Uncertainty Shocks, Asset Supply and Pricing over the Business Cycle," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 85(2), pages 810-854.
    5. Benjamin Born & Sebastian Breuer & Steffen Elstner, 2018. "Uncertainty and the Great Recession," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 80(5), pages 951-971, October.
    6. Guerron-Quintana, Pablo & Inoue, Atsushi & Kilian, Lutz, 2017. "Impulse response matching estimators for DSGE models," Journal of Econometrics, Elsevier, vol. 196(1), pages 144-155.
    7. Duffie, Darrell & Singleton, Kenneth J, 1993. "Simulated Moments Estimation of Markov Models of Asset Prices," Econometrica, Econometric Society, vol. 61(4), pages 929-952, July.
    8. Chatterjee, Pratiti & Milani, Fabio, 2020. "Perceived uncertainty shocks, excess optimism-pessimism, and learning in the business cycle," Journal of Economic Behavior & Organization, Elsevier, vol. 179(C), pages 342-360.
    9. Benjamin Born & Johannes Pfeifer, 2021. "Uncertainty‐driven business cycles: Assessing the markup channel," Quantitative Economics, Econometric Society, vol. 12(2), pages 587-623, May.
    10. Francesco Bianchi & Sydney C. Ludvigson & Sai Ma, 2022. "Belief Distortions and Macroeconomic Fluctuations," American Economic Review, American Economic Association, vol. 112(7), pages 2269-2315, July.
    11. Cosmin L. Ilut & Martin Schneider, 2022. "Modeling Uncertainty as Ambiguity: a Review," NBER Working Papers 29915, National Bureau of Economic Research, Inc.
    12. Giulia Piccillo & Poramapa Poonpakdee, 2021. "Effects of Macro Uncertainty on Mean Expectation and Subjective Uncertainty: Evidence from Households and Professional Forecasters," CESifo Working Paper Series 9486, CESifo.
    13. Klibanoff, Peter & Marinacci, Massimo & Mukerji, Sujoy, 2009. "Recursive smooth ambiguity preferences," Journal of Economic Theory, Elsevier, vol. 144(3), pages 930-976, May.
    14. Nengjiu Ju & Jianjun Miao, 2012. "Ambiguity, Learning, and Asset Returns," Econometrica, Econometric Society, vol. 80(2), pages 559-591, March.
    15. Scott R. Baker & Nicholas Bloom & Steven J. Davis, 2016. "Measuring Economic Policy Uncertainty," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(4), pages 1593-1636.
    16. Stéphane Lhuissier & Fabien Tripier, 2021. "Regime‐dependent effects of uncertainty shocks: A structural interpretation," Quantitative Economics, Econometric Society, vol. 12(4), pages 1139-1170, November.
    17. Kim, Jinill & Ruge-Murcia, Francisco J., 2009. "How much inflation is necessary to grease the wheels?," Journal of Monetary Economics, Elsevier, vol. 56(3), pages 365-377, April.
    18. Nicholas Bloom, 2009. "The Impact of Uncertainty Shocks," Econometrica, Econometric Society, vol. 77(3), pages 623-685, May.
    19. Laura Nowzohour & Livio Stracca, 2020. "More Than A Feeling: Confidence, Uncertainty, And Macroeconomic Fluctuations," Journal of Economic Surveys, Wiley Blackwell, vol. 34(4), pages 691-726, September.
    20. Sumru Altug & Cem Cakmakli & Fabrice Collard & Sujoy Mukerji & Han Ozsoylev, 2020. "Ambiguous Business Cycles: A Quantitative Assessment," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 38, pages 220-237, October.
    21. Ilaski Barañano & Amaia Iza & Jesús Vázquez, 2002. "A comparison between the log-linear and the parameterized expectations methods," Spanish Economic Review, Springer;Spanish Economic Association, vol. 4(1), pages 41-60.
    22. Anmol Bhandari & Jaroslav Borovicka & Paul Ho, 2019. "Survey Data and Subjective Beliefs in Business Cycle Models," Working Paper 19-14, Federal Reserve Bank of Richmond.
    23. Serena Ng & Jonathan H. Wright, 2013. "Facts and Challenges from the Great Recession for Forecasting and Macroeconomic Modeling," Journal of Economic Literature, American Economic Association, vol. 51(4), pages 1120-1154, December.
    24. Glas, Alexander, 2020. "Five dimensions of the uncertainty–disagreement linkage," International Journal of Forecasting, Elsevier, vol. 36(2), pages 607-627.
    25. Maliar, Lilia & Maliar, Serguei, 2003. "Parameterized Expectations Algorithm and the Moving Bounds," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(1), pages 88-92, January.
    26. Gilboa, Itzhak & Schmeidler, David, 1989. "Maxmin expected utility with non-unique prior," Journal of Mathematical Economics, Elsevier, vol. 18(2), pages 141-153, April.
    27. Sumru Altug & Cem Cakmakli & Fabrice Collard & Sujoy Mukerji & Han Ozsoylev, 2020. "Ambiguous Business Cycles: A Quantitative Assessment," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 38, pages 220-237, October.
    28. Guidolin, Massimo & Liu, Hening, 2016. "Ambiguity Aversion and Underdiversification," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 51(4), pages 1297-1323, August.
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    More about this item

    Keywords

    behavioural macro; uncertainty; estimated DSGE models;
    All these keywords.

    JEL classification:

    • E70 - Macroeconomics and Monetary Economics - - Macro-Based Behavioral Economics - - - General
    • D80 - Microeconomics - - Information, Knowledge, and Uncertainty - - - General
    • D90 - Microeconomics - - Micro-Based Behavioral Economics - - - General
    • E10 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - General
    • E30 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - General (includes Measurement and Data)

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