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Stock Prices and Economic Fluctuations: A Markov Switching Structural Vector Autoregressive Analysis

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  • Markku Lanne
  • Helmut Luetkepohl

Abstract

The role of expectations for economic fluctuations has received considerable attention in recent business cycle analysis. We exploit Markov regime switching models to identify shocks in cointegrated structural vector autoregressions and investigate different identification schemes for bivariate systems comprising U.S. stock prices and total factor productivity. The former variable is viewed as re°ecting expectations of economic agents about future productivity. It is found that some previously used identification schemes can be rejected in our model setup. The results crucially depend on the measure used for total factor productivity.

Suggested Citation

  • Markku Lanne & Helmut Luetkepohl, 2008. "Stock Prices and Economic Fluctuations: A Markov Switching Structural Vector Autoregressive Analysis," Economics Working Papers ECO2008/29, European University Institute.
    • Handle: RePEc:eui:euiwps:eco2008/29
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    References listed on IDEAS

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    1. Christiano, Lawrence J. & Eichenbaum, Martin & Evans, Charles L., 1999. "Monetary policy shocks: What have we learned and to what end?," Handbook of Macroeconomics, in: J. B. Taylor & M. Woodford (ed.), Handbook of Macroeconomics, edition 1, volume 1, chapter 2, pages 65-148, Elsevier.
    2. Nir Jaimovich & Sergio Rebelo, 2008. "News and Business Cycles in Open Economies," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 40(8), pages 1699-1711, December.
    3. Lanne, Markku & Lütkepohl, Helmut, 2010. "Structural Vector Autoregressions With Nonnormal Residuals," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(1), pages 159-168.
    4. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    5. Nir Jaimovich & Sergio Rebelo, 2009. "Can News about the Future Drive the Business Cycle?," American Economic Review, American Economic Association, vol. 99(4), pages 1097-1118, September.
    6. Bénédicte Vidaillet & V. d'Estaintot & P. Abécassis, 2005. "Introduction," Post-Print hal-00287137, HAL.
    7. Beaudry, Paul & Portier, Franck, 2005. "The "news view" of economic fluctuations: Evidence from aggregate Japanese data and sectoral US data," Journal of the Japanese and International Economies, Elsevier, vol. 19(4), pages 635-652, December.
    8. Guido Lorenzoni, 2009. "A Theory of Demand Shocks," American Economic Review, American Economic Association, vol. 99(5), pages 2050-2084, December.
    9. Paul Beaudry & Franck Portier, 2006. "Stock Prices, News, and Economic Fluctuations," American Economic Review, American Economic Association, vol. 96(4), pages 1293-1307, September.
    10. Lucke, Bernd & Haertel, Thomas, 2008. "Do News Shocks Drive Business Cycles? Evidence from German Data," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 2, pages 1-21.
    11. John B. Taylor, 1999. "Monetary Policy Rules," NBER Books, National Bureau of Economic Research, Inc, number tayl99-1.
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    Cited by:

    1. Adél Bosch & Franz Ruch, 2013. "An Alternative Business Cycle Dating Procedure for South Africa," South African Journal of Economics, Economic Society of South Africa, vol. 81(4), pages 491-516, December.
    2. 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.
    3. Yukai Yang, 2014. "Testing Constancy of the Error Covariance Matrix in Vector Models against Parametric Alternatives using a Spectral Decomposition," CREATES Research Papers 2014-11, Department of Economics and Business Economics, Aarhus University.

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    More about this item

    Keywords

    Cointegration; Markov regime switching model; vector error correction model; structural vector autoregression; mixed normal distribution;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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