IDEAS home Printed from https://ideas.repec.org/p/tse/wpaper/33124.html
   My bibliography  Save this paper

Robust Predictions for DSGE Models with Incomplete Information

Author

Listed:
  • Chahrour, Ryan
  • Ulbricht, Robert

Abstract

We study the quantitative potential of DSGE models with incomplete information. In contrast to existing literature, we offer predictions that are robust across all possible private information structures that agents may have. Our approach maps DSGE models with information-frictions into a parallel economy where deviations from fullinformation are captured by time-varying wedges. We derive exact conditions that ensure the consistency of these wedges with some information structure. We apply our approach to an otherwise frictionless business cycle model where firms and households have incomplete information. We show how assumptions about information interact with the presence of idiosyncratic shocks to shape the potential for confidence-driven fluctuations. For a realistic calibration, we find that correlated confidence regarding idiosyncratic shocks (aka “sentiment shocks”) can account for up to 51 percent of U.S. business cycle fluctuations. By contrast, confidence about aggregate productivity can account for at most 3 percent.

Suggested Citation

  • Chahrour, Ryan & Ulbricht, Robert, 2018. "Robust Predictions for DSGE Models with Incomplete Information," TSE Working Papers 18-971, Toulouse School of Economics (TSE), revised Mar 2019.
  • Handle: RePEc:tse:wpaper:33124
    as

    Download full text from publisher

    File URL: https://www.tse-fr.eu/sites/default/files/TSE/documents/doc/wp/2018/wp_tse_971.pdf
    File Function: Full text
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Chahrour, Ryan & Gaballo, Gaetano, 2017. "Learning from prices: amplication and business fluctuations," Working Paper Series 2053, European Central Bank.
    2. Bartosz Maćkowiak & Mirko Wiederholt, 2015. "Business Cycle Dynamics under Rational Inattention," Review of Economic Studies, Oxford University Press, vol. 82(4), pages 1502-1532.
    3. Christian Hellwig & Venky Venkateswaran, 2015. "Dispersed Information, Sticky Prices and Monetary Business Cycles: A Hayekian Perspective," Working Papers 15-12, New York University, Leonard N. Stern School of Business, Department of Economics.
    4. Acharya, Sushant & Benhabib, Jess & Huo, Zhen, 2021. "The anatomy of sentiment-driven fluctuations," Journal of Economic Theory, Elsevier, vol. 195(C).
    5. Lucia Foster & John Haltiwanger & Chad Syverson, 2008. "Reallocation, Firm Turnover, and Efficiency: Selection on Productivity or Profitability?," American Economic Review, American Economic Association, vol. 98(1), pages 394-425, March.
    6. Chahrour, Ryan & Ulbricht, Robert, 2017. "Information-driven Business Cycles: A Primal Approach," TSE Working Papers 17-784, Toulouse School of Economics (TSE), revised Dec 2017.
    7. Bergemann, Dirk & Morris, Stephen, 2016. "Bayes correlated equilibrium and the comparison of information structures in games," Theoretical Economics, Econometric Society, vol. 11(2), May.
    8. Harald Uhlig, 2004. "Do Technology Shocks Lead to a Fall in Total Hours Worked?," Journal of the European Economic Association, MIT Press, vol. 2(2-3), pages 361-371, 04/05.
    9. Hansen, Lars Peter & Sargent, Thomas J., 1981. "A note on Wiener-Kolmogorov prediction formulas for rational expectations models," Economics Letters, Elsevier, vol. 8(3), pages 255-260.
    10. Lawrence J. Christiano & Martin Eichenbaum & Robert Vigfusson, 2003. "What Happens After a Technology Shock?," NBER Working Papers 9819, National Bureau of Economic Research, Inc.
    11. Todd Walker & Giacomo Rondina, 2017. "Confounding Dynamics," 2017 Meeting Papers 525, Society for Economic Dynamics.
    12. Benjamin M. Friedman & Michael Woodford (ed.), 2010. "Handbook of Monetary Economics," Handbook of Monetary Economics, Elsevier, edition 1, volume 3, number 3.
    13. Ryan Chahrour & Robert Ulbricht, 2017. "Robust Predictions for DSGE Models with Incomplete Information," Boston College Working Papers in Economics 925, Boston College Department of Economics, revised 10 Jun 2021.
    Full references (including those not matched with items on IDEAS)

    Citations

    Blog mentions

    As found by EconAcademics.org, the blog aggregator for Economics research:
    1. Information-driven Business Cycles: A Primal Approach
      by Christian Zimmermann in NEP-DGE blog on 2017-04-12 08:14:56

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Tatsushi Okuday & Tomohiro Tsurugaz & Francesco Zanetti, 2019. "Imperfect Information, Shock Heterogeneity, and Inflation Dynamics," BCAM Working Papers 1906, Birkbeck Centre for Applied Macroeconomics.
    2. Tatsushi Okuda & Tomohiro Tsuruga & Francesco Zanetti, 2021. "Imperfect information, heterogeneous demand shocks, and inflation dynamics," CAMA Working Papers 2021-29, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    3. Chahrour, Ryan & Ulbricht, Robert, 2017. "Information-driven Business Cycles: A Primal Approach," TSE Working Papers 17-784, Toulouse School of Economics (TSE), revised Dec 2017.
    4. Ryan Chahrour & Robert Ulbricht, 2017. "Robust Predictions for DSGE Models with Incomplete Information," Boston College Working Papers in Economics 925, Boston College Department of Economics, revised 10 Jun 2021.
    5. Benhima, Kenza & Poilly, Céline, 2021. "Does demand noise matter? Identification and implications," Journal of Monetary Economics, Elsevier, vol. 117(C), pages 278-295.
    6. Camille Cornand & Rodolphe Dos Santos Ferreira, 2021. "Central bank’s stabilization and communication policies when firms have motivated overconfidence in their own information accuracy or processing," Working Papers 2118, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.
    7. Ambrocio, Gene, 2019. "Measuring household uncertainty in EU countries," Research Discussion Papers 17/2019, Bank of Finland.
    8. Chahrour, Ryan & Gaballo, Gaetano, 2017. "Learning from prices: amplication and business fluctuations," Working Paper Series 2053, European Central Bank.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Chahrour, Ryan & Ulbricht, Robert, 2017. "Information-driven Business Cycles: A Primal Approach," TSE Working Papers 17-784, Toulouse School of Economics (TSE), revised Dec 2017.
    2. Straub, Ludwig & Ulbricht, Robert, 2015. "Endogenous Uncertainty and Credit Crunches," TSE Working Papers 15-604, Toulouse School of Economics (TSE), revised Dec 2017.
    3. Andrei Polbin & Sergey Drobyshevsky, 2014. "Developing a Dynamic Stochastic Model of General Equilibrium for the Russian Economy," Research Paper Series, Gaidar Institute for Economic Policy, issue 166P, pages 156-156.
    4. George-Marios Angeletos, 2018. "Frictional Coordination," Journal of the European Economic Association, European Economic Association, vol. 16(3), pages 563-603.
    5. Acharya, Sushant & Benhabib, Jess & Huo, Zhen, 2021. "The anatomy of sentiment-driven fluctuations," Journal of Economic Theory, Elsevier, vol. 195(C).
    6. Ramey, V.A., 2016. "Macroeconomic Shocks and Their Propagation," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 71-162, Elsevier.
    7. Lindé, Jesper & Smets, Frank & Wouters, Rafael, 2016. "Challenges for Central Banks´ Macro Models," Working Paper Series 323, Sveriges Riksbank (Central Bank of Sweden).
    8. Zheng Liu, 2009. "Sources of the Great Moderation: Shocks, Frictions, or Monetary Policy?," 2009 Meeting Papers 379, Society for Economic Dynamics.
    9. Waters, George A., 2013. "Quantity rationing of credit and the Phillips curve," Journal of Macroeconomics, Elsevier, vol. 37(C), pages 68-80.
    10. Giancarlo Corsetti & Luca Dedola & Sylvain Leduc, 2008. "Productivity, External Balance, and Exchange Rates: Evidence on the Transmission Mechanism among G7 Countries," NBER Chapters, in: NBER International Seminar on Macroeconomics 2006, pages 117-194, National Bureau of Economic Research, Inc.
    11. Cristiano Cantore & Miguel León-Ledesma & Peter McAdam & Alpo Willman, 2014. "Shocking Stuff: Technology, Hours, And Factor Substitution," Journal of the European Economic Association, European Economic Association, vol. 12(1), pages 108-128, February.
    12. Maćkowiak, Bartosz & Matějka, Filip & Wiederholt, Mirko, 2018. "Dynamic rational inattention: Analytical results," Journal of Economic Theory, Elsevier, vol. 176(C), pages 650-692.
    13. Anat Bracha & Jenny Tang, 2019. "Inflation Thresholds and Inattention," Working Papers 19-14, Federal Reserve Bank of Boston.
    14. Justiniano, Alejandro & Primiceri, Giorgio E. & Tambalotti, Andrea, 2010. "Investment shocks and business cycles," Journal of Monetary Economics, Elsevier, vol. 57(2), pages 132-145, March.
    15. Ferre De Graeve & Karl Walentin, 2015. "Refining Stylized Facts from Factor Models of Inflation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(7), pages 1192-1209, November.
    16. Giancarlo Corsetti & Luca Dedola & Sylvain Leduc, 2008. "International Risk Sharing and the Transmission of Productivity Shocks," Review of Economic Studies, Oxford University Press, vol. 75(2), pages 443-473.
    17. Mäkinen, Taneli & Ohl, Björn, 2015. "Information acquisition and learning from prices over the business cycle," Journal of Economic Theory, Elsevier, vol. 158(PB), pages 585-633.
    18. Bachmann, Rüdiger & Zorn, Peter, 2020. "What drives aggregate investment? Evidence from German survey data," Journal of Economic Dynamics and Control, Elsevier, vol. 115(C).
    19. Almut Balleer & Thijs van Rens, 2013. "Skill-Biased Technological Change and the Business Cycle," The Review of Economics and Statistics, MIT Press, vol. 95(4), pages 1222-1237, October.
    20. Miyamoto, Wataru & Nguyen, Thuy Lan, 2017. "Understanding the cross-country effects of U.S. technology shocks," Journal of International Economics, Elsevier, vol. 106(C), pages 143-164.

    More about this item

    Keywords

    Business cycles; DSGE models; incomplete-information; information-robust predictions;
    All these keywords.

    JEL classification:

    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:tse:wpaper:33124. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: https://edirc.repec.org/data/tsetofr.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (email available below). General contact details of provider: https://edirc.repec.org/data/tsetofr.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.