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Testing for Granger causality between stock prices and economic growth

Author

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  • Foresti, Pasquale

Abstract

This paper has focused on the relationship between stock market prices and growth. A Granger-causality analysis has been carried out in order to assess whether there is any potential predictability power of one indicator for the other. The conclusion that can be drawn is that stock market prices can be used in order to predict growth, but the opposite it is not true.

Suggested Citation

  • Foresti, Pasquale, 2006. "Testing for Granger causality between stock prices and economic growth," MPRA Paper 2962, University Library of Munich, Germany, revised 2007.
  • Handle: RePEc:pra:mprapa:2962
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    File URL: https://mpra.ub.uni-muenchen.de/2962/1/MPRA_paper_2962.pdf
    File Function: original version
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    References listed on IDEAS

    as
    1. Barry Bosworth, 1975. "The Stock Market and the Economy," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 6(2), pages 257-300.
    2. Douglas K. Pearce, 1983. "Stock prices and the economy," Economic Review, Federal Reserve Bank of Kansas City, issue Sep, pages 7-22.
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    Citations

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    Cited by:

    1. Shen, Chung-Hua & Lee, Yen Hsien & Wu, Meng-Wen & Guo, Na, 2016. "Does housing boom lead to credit boom or is it the other way around? The case of China," International Review of Economics & Finance, Elsevier, vol. 42(C), pages 349-367.
    2. Manuel Hoffmann & Matthias Neuenkirch, 2017. "The pro-Russian conflict and its impact on stock returns in Russia and the Ukraine," International Economics and Economic Policy, Springer, vol. 14(1), pages 61-73, January.
    3. Sirucek, Martin, 2012. "The impact of money supply on stock prices and stock bubbles," MPRA Paper 40919, University Library of Munich, Germany.
    4. Georgeta VINTILA & Ioana Laura TIBULCA, 2014. "Can the Corporate Tax Burden be used to predict the Evolution of Business Confidence?," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 62(1), pages 143-150, January.
    5. Šoba, Oldřich & Širůček, Martin & Havíř, Tomáš, 2013. "Závislost cen akcií ropných společností na ceně ropy
      [The dependence of oil company's stock price on oil price]
      ," MPRA Paper 62899, University Library of Munich, Germany, revised 2013.
    6. Horobet, Alexandra & Lupu, Radu, 2009. "Are Capital Markets Integrated? A Test of Information Transmission within the European Union," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 6(2), pages 64-80, June.
    7. Kwame Mireku & Kwaku Sarkodie & Kwasi Poku, 2013. "Effect of Macroeconomic Factors on Stock Prices in Ghana: A Vector Error Correction Model Approach," International Journal of Academic Research in Accounting, Finance and Management Sciences, Human Resource Management Academic Research Society, International Journal of Academic Research in Accounting, Finance and Management Sciences, vol. 3(2), pages 32-43, April.
    8. Albu, Lucian Liviu & Lupu, Radu & Calin, Cantemir, 2014. "A Nonlinear Model to Estimate the Long Term Correlation between Market Capitalization and GDP per capita in Eastern EU Countries," Working Papers of Institute for Economic Forecasting 141115, Institute for Economic Forecasting.
    9. Horobet, Alexandra & Ilie, Livia, 2007. "On the dynamic link between stock prices and exchange rates: evidence from Romania," MPRA Paper 6429, University Library of Munich, Germany.
    10. Jaunky, Vishal Chandr, 2013. "A cointegration and causality analysis of copper consumption and economic growth in rich countries," Resources Policy, Elsevier, vol. 38(4), pages 628-639.
    11. Daniel Ventosa-Santaulària & José Eduardo Vera-Valdés, 2008. "Granger-Causality in the presence of structural breaks," Economics Bulletin, AccessEcon, vol. 3(61), pages 1-14.
    12. Širůček, Martin, 2015. "Kauzalní vztah peněžní nabídky a amerického akciového trhu
      [Money supply and US stock market causality]
      ," MPRA Paper 66357, University Library of Munich, Germany, revised 30 Aug 2015.

    More about this item

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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