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Information and Volatility

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Abstract

In an economy of interacting agents with both idiosyncratic and aggregate shocks, we examine how the information structure determines aggregate volatility. We show that the maximal aggregate volatility is attained in a noise free information structure in which the agents confound idiosyncratic and common components of the payoff state, and display excess response to the common component, as in Lucas (1972). The upper bound on aggregate volatility is linearly increasing in the variance of idiosyncratic shocks, for any given variance of aggregate shocks. Our results hold in a setting of symmetric agents with linear best responses and normal uncertainty. We show our results by providing a characterization of the set of all joint distributions over actions and states that can arise in equilibrium under any information structure. This tractable characterization, extending results in Bergemann and Morris (2013b), can be used to address a wide variety of questions.

Suggested Citation

  • Dirk Bergemann & Tibor Heumann & Stephen Morris, 2013. "Information and Volatility," Cowles Foundation Discussion Papers 1928R, Cowles Foundation for Research in Economics, Yale University, revised Jun 2014.
  • Handle: RePEc:cwl:cwldpp:1928r
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    1. Dirk Bergemann & Stephen Morris, 2013. "Robust Predictions in Games With Incomplete Information," Econometrica, Econometric Society, vol. 81(4), pages 1251-1308, July.
    2. Alison J. Kirby, 1988. "Trade Associations as Information Exchange Mechanisms," RAND Journal of Economics, The RAND Corporation, vol. 19(1), pages 138-146, Spring.
    3. George-Marios Angeletos & Alessandro Pavan, 2009. "Policy with Dispersed Information," Journal of the European Economic Association, MIT Press, vol. 7(1), pages 11-60, March.
    4. Dirk Bergemann & Stephen Morris, 2013. "Robust Predictions in Games With Incomplete Information," Econometrica, Econometric Society, vol. 81(4), pages 1251-1308, July.
    5. Stephen Morris & Hyun Song Shin, 2002. "Social Value of Public Information," American Economic Review, American Economic Association, vol. 92(5), pages 1521-1534, December.
    6. George-Marios Angeletos & Jennifer La'O, 2010. "Noisy Business Cycles," NBER Chapters, in: NBER Macroeconomics Annual 2009, Volume 24, pages 319-378, National Bureau of Economic Research, Inc.
    7. Raith, Michael, 1996. "A General Model of Information Sharing in Oligopoly," Journal of Economic Theory, Elsevier, vol. 71(1), pages 260-288, October.
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    9. Dirk Bergemann & Stephen Morris, 2013. "The Comparison of Information Structures in Games: Bayes Correlated Equilibrium and Individual Sufficiency," Cowles Foundation Discussion Papers 1909R, Cowles Foundation for Research in Economics, Yale University, revised May 2014.
    10. George-Marios Angeletos & Luigi Iovino & Jennifer La'O, 2011. "Cycles, Gaps, and the Social Value of Information," Levine's Working Paper Archive 786969000000000293, David K. Levine.
    11. Lucas, Robert Jr., 1972. "Expectations and the neutrality of money," Journal of Economic Theory, Elsevier, vol. 4(2), pages 103-124, April.
    12. Xavier Vives, 2014. "On The Possibility Of Informationally Efficient Markets," Journal of the European Economic Association, European Economic Association, vol. 12(5), pages 1200-1239, October.
    13. Bartosz Mackowiak & Mirko Wiederholt, 2019. "Optimal Sticky Prices Under Rational Inattention," Credit and Capital Markets, Credit and Capital Markets, vol. 52(4), pages 573-617.
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    16. Richard N. Clarke, 1983. "Collusion and the Incentives for Information Sharing," Bell Journal of Economics, The RAND Corporation, vol. 14(2), pages 383-394, Autumn.
    17. repec:cwl:cwldpp:1821rrr is not listed on IDEAS
    18. Dirk Bergemann & Stephen Morris, 2013. "Robust Predictions in Games With Incomplete Information," Econometrica, Econometric Society, vol. 81(4), pages 1251-1308, July.
    19. Venky Venkateswaran, 2011. "Heterogeneous Information and Labor Market Fluctuations," 2011 Meeting Papers 1292, Society for Economic Dynamics.
    20. George-Marios Angeletos & Alessandro Pavan, 2007. "Efficient Use of Information and Social Value of Information," Econometrica, Econometric Society, vol. 75(4), pages 1103-1142, July.
    21. Vives, Xavier, 1984. "Duopoly information equilibrium: Cournot and bertrand," Journal of Economic Theory, Elsevier, vol. 34(1), pages 71-94, October.
    22. Guido Lorenzoni, 2010. "Optimal Monetary Policy with Uncertain Fundamentals and Dispersed Information ," Review of Economic Studies, Oxford University Press, vol. 77(1), pages 305-338.
    23. Dirk Bergemann & Stephen Morris, 2013. "Robust Predictions in Games With Incomplete Information," Econometrica, Econometric Society, vol. 81(4), pages 1251-1308, July.
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    Citations

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    Cited by:

    1. Dirk Bergemann & Stephen Morris, 2019. "Information Design: A Unified Perspective," Journal of Economic Literature, American Economic Association, vol. 57(1), pages 44-95, March.
    2. Dirk Bergemann & Stephen Morris, 2016. "Information Design, Bayesian Persuasion, and Bayes Correlated Equilibrium," American Economic Review, American Economic Association, vol. 106(5), pages 586-591, May.
    3. Bergemann, Dirk & Heumann, Tibor & Morris, Stephen, 2015. "Information and Market Power," CEPR Discussion Papers 10791, C.E.P.R. Discussion Papers.
    4. Carroll, Gabriel, 2016. "Informationally robust trade and limits to contagion," Journal of Economic Theory, Elsevier, vol. 166(C), pages 334-361.
    5. Pavan, Alessandro & Vives, Xavier, 2015. "Information, Coordination, and Market Frictions: An Introduction," Journal of Economic Theory, Elsevier, vol. 158(PB), pages 407-426.
    6. Martin Ellison & Andreas Tischbirek, 2018. "Beauty Contests and the Term Structure," Economics Series Working Papers 846, University of Oxford, Department of Economics.
    7. Gaetano Gaballo, 2018. "Price Dispersion, Private Uncertainty, and Endogenous Nominal Rigidities," Review of Economic Studies, Oxford University Press, vol. 85(2), pages 1070-1110.
    8. Heumann, Tibor, 2021. "Efficiency in trading markets with multi-dimensional signals," Journal of Economic Theory, Elsevier, vol. 191(C).
    9. Shen, Dehua & Li, Xiao & Zhang, Wei, 2018. "Baidu news information flow and return volatility: Evidence for the Sequential Information Arrival Hypothesis," Economic Modelling, Elsevier, vol. 69(C), pages 127-133.
    10. Bergemann, Dirk & Morris, Stephen, 2016. "Bayes correlated equilibrium and the comparison of information structures in games," Theoretical Economics, Econometric Society, vol. 11(2), May.
    11. Eduardo Dávila & Cecilia Parlatore, 2019. "Volatility and Informativeness," NBER Working Papers 25433, National Bureau of Economic Research, Inc.
    12. 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.
    13. Christian Myohl & Yannic Stucki, 2018. "Confidence and the Financial Accelerator," Diskussionsschriften dp1823, Universitaet Bern, Departement Volkswirtschaft.

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    More about this item

    Keywords

    Incomplete information; Bayes correlated equilibrium; Volatility; Moments restrictions; Linear best responses; Quadratic payoffs;
    All these keywords.

    JEL classification:

    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
    • D43 - Microeconomics - - Market Structure, Pricing, and Design - - - Oligopoly and Other Forms of Market Imperfection
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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