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Did monetary or technology shocks move euro area stock prices?

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  • Tim Berg

Abstract

Using a Bayesian vector autoregressive (VAR) model, I investigate the impact of monetary and technology shocks on the euro area stock market. I find an important role for technology surprise shocks, but not monetary shocks, in explaining variations in real stock prices. Specifically, the pronounced boom–bust cycle of 1995–2003 is largely due to technology surprise shocks. The identification method allows me to study the effects of technology news shocks. The responses are consistent with the idea that news on technology improvements has an immediate impact on stock prices. These findings are robust to several modelling choices, including the productivity measure, the specification of the VAR model, and the identifying restrictions. Copyright Springer-Verlag 2012

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  • Tim Berg, 2012. "Did monetary or technology shocks move euro area stock prices?," Empirical Economics, Springer, vol. 43(2), pages 693-722, October.
    • Handle: RePEc:spr:empeco:v:43:y:2012:i:2:p:693-722
    DOI: 10.1007/s00181-011-0497-5
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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. Baumeister, Christiane & Hamilton, James D., 2020. "Drawing conclusions from structural vector autoregressions identified on the basis of sign restrictions," Journal of International Money and Finance, Elsevier, vol. 109(C).
    3. Ronayne, David, 2011. "Which Impulse Response Function?," The Warwick Economics Research Paper Series (TWERPS) 971, University of Warwick, Department of Economics.
    4. Cavallo, Antonella & Ribba, Antonio, 2015. "Common macroeconomic shocks and business cycle fluctuations in Euro area countries," International Review of Economics & Finance, Elsevier, vol. 38(C), pages 377-392.
    5. Gangopadhyay, Kausik & Nishimura, Atsushi & Pal, Rupayan, 2016. "Can the information technology revolution explain the incidence of co-movement of skill premium and stock prices?," Economic Modelling, Elsevier, vol. 53(C), pages 107-120.
    6. Shi, Yangyan & Feng, Yu & Zhang, Qi & Shuai, Jing & Niu, Jiangxin, 2023. "Does China's new energy vehicles supply chain stock market have risk spillovers? Evidence from raw material price effect on lithium batteries," Energy, Elsevier, vol. 262(PA).
    7. Baumeister, Christiane & Hamilton, James D., 2021. "Reprint: Drawing conclusions from structural vector autoregressions identified on the basis of sign restrictions," Journal of International Money and Finance, Elsevier, vol. 114(C).
    8. Dohyun CHUN & Hoon CHO & Doojin RYU, 2018. "Macroeconomic Structural Changes in a Leading Emerging Market: The Effects of the Asian Financial Crisis," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 22-42, December.
    9. Prabu A, Edwin & Bhattacharyya, Indranil & Ray, Partha, 2016. "Is the stock market impervious to monetary policy announcements: Evidence from emerging India," International Review of Economics & Finance, Elsevier, vol. 46(C), pages 166-179.

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    More about this item

    Keywords

    Monetary policy; Technology shocks; News; Stock prices; Boom–bust cycle; Euro area; Bayesian VAR; Sign restrictions; E44; E52; G1; O33;
    All these keywords.

    JEL classification:

    • G1 - Financial Economics - - General Financial Markets
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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