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Aggregate Shocks or Aggregate Information? Costly Information and Business Cycle Comovement

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  • Veldkamp, Laura
  • Wolfers, Justin

Abstract

When similar patterns of expansion and contraction are observed across sectors, we call this a business cycle. Yet explaining the similarity and synchronization of these cycles across industries remains a puzzle. Whereas output growth across industries is highly correlated, identifiable shocks, like shocks to productivity, are far less correlated. While previous work has examined complementarities in production, we propose that sectors make similar input decisions because of complementarities in information acquisition. Because information about driving forces has a high fixed cost of production and a low marginal cost of replication, it can be more efficient for firms to share the cost of discovering common shocks than to invest in uncovering detailed sectoral information. Firms basing their decisions on this common information make highly correlated production choices. This mechanism amplifies the effects of common shocks, relative to sectoral shocks.

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Paper provided by C.E.P.R. Discussion Papers in its series CEPR Discussion Papers with number 5898.

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Date of creation: Oct 2006
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Handle: RePEc:cpr:ceprdp:5898

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Keywords: business cycles; comovement puzzle; costly information; information markets;

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Citations

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Cited by:
  1. Chollete, Loran & Ning, Cathy, 2012. "Asymmetric Dependence in the US Economy: Application to Money and the Phillips Curve," UiS Working Papers in Economics and Finance 2012/1, University of Stavanger.
  2. Chun, Hyunbae & Kim, Jung-Wook & Morck, Randall & Yeung, Bernard, 2008. "Creative destruction and firm-specific performance heterogeneity," Journal of Financial Economics, Elsevier, vol. 89(1), pages 109-135, July.
  3. Cathy Q. Ning & Loran Chollete, 2009. "The Dependence Structure of Macroeconomic Variables in the US," Working Papers 005, Ryerson University, Department of Economics.
  4. Saldías, Martín, 2013. "A market-based approach to sector risk determinants and transmission in the euro area," Working Paper Series 1574, European Central Bank.
  5. Sunoong Hwang & Yongsung Chang, 2011. "Asymmetric Phase Shifts in U.S. Industrial Production Cycles," 2011 Meeting Papers 31, Society for Economic Dynamics.
  6. Chollete, Loran & Jaffee, Dwight, 2009. "Economic Implications of Extreme and Rare Events," UiS Working Papers in Economics and Finance 2009/32, University of Stavanger.
  7. Lynch, Andrew & Nikolic, Biljana & Yan, Xuemin (Sterling) & Yu, Han, 2014. "Aggregate short selling, commonality, and stock market returns," Journal of Financial Markets, Elsevier, vol. 17(C), pages 199-229.
  8. Michael J. Lamla & Sarah M. Lein & Jan-Egbert Sturm, 2007. "News and Sectoral Comovement," KOF Working papers 07-183, KOF Swiss Economic Institute, ETH Zurich.
  9. Brockman, Paul & Liebenberg, Ivonne & Schutte, Maria, 2010. "Comovement, information production, and the business cycle," Journal of Financial Economics, Elsevier, vol. 97(1), pages 107-129, July.
  10. Liyan Yang & Itay Goldstein, 2014. "Good Disclosure, Bad Disclosure," 2014 Meeting Papers 42, Society for Economic Dynamics.
  11. Andrew Williams, 2014. "The effect of transparency on output volatility," Economics of Governance, Springer, vol. 15(2), pages 101-129, May.
  12. Yongsung Chang & Sunoong Hwang, 2011. "Asymmetric Phase Shifts in the U.S. Industrial Production Cycles," RCER Working Papers 564, University of Rochester - Center for Economic Research (RCER).

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