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News Media, Common Information, and Sectoral Comovement

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  • Buchen, Teresa
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    This paper investigates whether information complementarities can explain the strong patterns of sectoral comovement observed empirically. It tests the theoretical model by Veldkamp and Wolfers (2007), which suggests that fi rms' output decisions are based on aggregate information rather than sector-specifi c information, because the former is less costly. Employing the connectedness index by Diebold and Yilmaz (2009, 2012) as a new measure of sectoral comovement and using data on media coverage of economic news in Germany, we find that a higher volume of economy-wide news indeed signifi cantly increases the comovement of sectoral business expectations. This common shock to expectations is reflected in a delayed increase of sectoral output comovement. Although fi rms tend to be more susceptible to bad news, the tone of media coverage only plays a minor role.

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    File URL: https://www.econstor.eu/bitstream/10419/100391/1/VfS_2014_pid_274.pdf
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    Paper provided by Verein für Socialpolitik / German Economic Association in its series Annual Conference 2014 (Hamburg): Evidence-based Economic Policy with number 100391.

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    Date of creation: 2014
    Handle: RePEc:zbw:vfsc14:100391
    Contact details of provider: Web page: http://www.socialpolitik.org/
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    1. Andrew T. Foerster & Pierre-Daniel G. Sarte & Mark W. Watson, 2011. "Sectoral versus Aggregate Shocks: A Structural Factor Analysis of Industrial Production," Journal of Political Economy, University of Chicago Press, vol. 119(1), pages 1-38.
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    7. Diebold, Francis X. & Yılmaz, Kamil, 2014. "On the network topology of variance decompositions: Measuring the connectedness of financial firms," Journal of Econometrics, Elsevier, vol. 182(1), pages 119-134.
    8. N. Gregory Mankiw & Ricardo Reis, 2002. "Sticky Information versus Sticky Prices: A Proposal to Replace the New Keynesian Phillips Curve," The Quarterly Journal of Economics, Oxford University Press, vol. 117(4), pages 1295-1328.
    9. Kamil Yilmaz, 2009. "International Business Cycle Spillovers," Koç University-TUSIAD Economic Research Forum Working Papers 0903, Koc University-TUSIAD Economic Research Forum, revised Nov 2009.
    10. Daron Acemoglu & Vasco M. Carvalho & Asuman Ozdaglar & Alireza Tahbaz‐Salehi, 2012. "The Network Origins of Aggregate Fluctuations," Econometrica, Econometric Society, vol. 80(5), pages 1977-2016, 09.
    11. Michael J. Lamla & Thomas Maag, 2012. "The Role of Media for Inflation Forecast Disagreement of Households and Professional Forecasters," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44(7), pages 1325-1350, October.
    12. Arthur F. Burns & Wesley C. Mitchell, 1946. "Measuring Business Cycles," NBER Books, National Bureau of Economic Research, Inc, number burn46-1, Enero-Jun.
    13. Lutz Kilian, 2009. "Not All Oil Price Shocks Are Alike: Disentangling Demand and Supply Shocks in the Crude Oil Market," American Economic Review, American Economic Association, vol. 99(3), pages 1053-1069, June.
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