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Observed Expectations, News Shocks, and the Business Cycle

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  • Fabio Milani

    (Department of Economics, University of California-Irvine)

  • Ashish Rajrhandari

    (Department of Economics, University of California-Irvine)

Abstract

This paper exploits information from the term structure of survey expectations to identify news shocks in a a DSGE model with rational expectations. We estimate a structural business-cycle model with price and wage stickiness. We allow for both unanticipated and anticipated components ("news") in each structural disturbance: neutral and investment-specific technology shocks, government spending shocks, risk premium, price and wage markup shocks, and monetary policy shocks. We show that the estimation of a standard DSGE model with realized data obfuscates the identification of news shocks and yields weakly or non-identified parameters pertaining to such shocks. The identification of news shocks greatly improves when we re-estimate the model using data on observed expectations regarding future output, consumption, investment, government spending, inflation, and interest rates - at horizons ranging from one-period to five-periods ahead. The news series thus obtained largely differ from their counterparts that are estimated using only data on realized variables. Moreover, the results suggest that the identified news shocks explain a sizable portion of aggregate fluctuations. News about investment-specific technology and risk premium shocks play the largest role, followed by news about labor supply (wage markup) and monetary policy.

Suggested Citation

  • Fabio Milani & Ashish Rajrhandari, 2012. "Observed Expectations, News Shocks, and the Business Cycle," Working Papers 121305, University of California-Irvine, Department of Economics.
    • Handle: RePEc:irv:wpaper:121305
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    Cited by:

    1. Paul Beaudry & Franck Portier, 2014. "News-Driven Business Cycles: Insights and Challenges," Journal of Economic Literature, American Economic Association, vol. 52(4), pages 993-1074, December.
    2. 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.
    3. Jean-Paul L’Huillier & Sanjay R Singh & Donghoon Yoo, 2024. "Incorporating Diagnostic Expectations into the New Keynesian Framework," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 91(5), pages 3013-3046.
    4. Sandra Gomes, 2011. "Housing Market Dynamics: Any News?," Working Papers w201121, Banco de Portugal, Economics and Research Department.
    5. Iskrev, Nikolay, 2018. "Are asset price data informative about news shocks? A DSGE perspective," Working Paper Series 2161, European Central Bank.
    6. Iskrev, Nikolay, 2019. "On the sources of information about latent variables in DSGE models," European Economic Review, Elsevier, vol. 119(C), pages 318-332.
    7. Greta Meggiorini & Fabio Milani, 2021. "Behavioral New Keynesian Models: Learning vs. Cognitive Discounting," Working Papers 202103, University of California-Irvine, Department of Economics.
    8. Miyamoto, Wataru & Nguyen, Thuy Lan, 2020. "The expectational effects of news in business cycles: Evidence from forecast data," Journal of Monetary Economics, Elsevier, vol. 116(C), pages 184-200.
    9. Kenza Benhima & Céline Poilly, 2017. "Do Misperceptions about Demand Matter? Theory and Evidence," Cahiers de Recherches Economiques du Département d'économie 17.08, Université de Lausanne, Faculté des HEC, Département d’économie.
    10. Milani, Fabio, 2017. "Sentiment and the U.S. business cycle," Journal of Economic Dynamics and Control, Elsevier, vol. 82(C), pages 289-311.
    11. Fabio Milani, 2012. "The Modeling of Expectations in Empirical DSGE Models: A Survey," Advances in Econometrics, in: DSGE Models in Macroeconomics: Estimation, Evaluation, and New Developments, pages 3-38, Emerald Group Publishing Limited.
    12. D’Amico, Stefania & King, Thomas B., 2023. "What does anticipated monetary policy do?," Journal of Monetary Economics, Elsevier, vol. 138(C), pages 123-139.
    13. Yasuo Hirose & Takushi Kurozumi, 2017. "Changes in the Federal Reserve Communication Strategy: A Structural Investigation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(1), pages 171-185, February.
    14. Hirose, Yasuo & Kurozumi, Takushi, 2021. "Identifying News Shocks With Forecast Data," Macroeconomic Dynamics, Cambridge University Press, vol. 25(6), pages 1442-1471, September.
    15. Dongho Song & Jenny Tang, 2023. "News-Driven Uncertainty Fluctuations," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(3), pages 968-982, July.
    16. Kortelainen, Mika & Paloviita, Maritta & Viren, Matti, 2016. "How useful are measured expectations in estimation and simulation of a conventional small New Keynesian macro model?," Economic Modelling, Elsevier, vol. 52(PB), pages 540-550.
    17. Cole, Stephen J., 2020. "The influence of learning and price-level targeting on central bank forward guidance," Journal of Macroeconomics, Elsevier, vol. 65(C).
    18. Thuy Lan Nguyen & Wataru Miyamoto, 2014. "News shocks and Business cycles: Evidence from forecast data," 2014 Meeting Papers 259, Society for Economic Dynamics.

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    More about this item

    Keywords

    News Shocks; Estimation of DSGE Model with Survey Expectations; News in Business Cycles; Identification in DSGE Models; Rational Expectations;
    All these keywords.

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E50 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - General

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