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Applied Cointegration Analysis in the Mirror of Macroeconomic Theory

Author

Listed:
  • Söderlind, Paul
  • Vredin, Anders

    (Dept. of Economics, Stockholm School of Economics)

Abstract

Applied cointegration analysis has much to gain from strong links with economic theory. For example, the current generation of equilibrium macroeconomic models have simple predi tions for cointegrating vectors. These models also suggest that important information about the economic structure can be found in the short run dynamics, which most cointegration studies disregard. Simulations of a stochastic business cycle model show that tests of cointegrating vectors, forecasts, and variance decompositions based on long run assumptions can be sharpened by imposing even very simple economic restrictions.

Suggested Citation

  • Söderlind, Paul & Vredin, Anders, 1994. "Applied Cointegration Analysis in the Mirror of Macroeconomic Theory," SSE/EFI Working Paper Series in Economics and Finance 30, Stockholm School of Economics.
  • Handle: RePEc:hhs:hastef:0030
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    Citations

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    Cited by:

    1. Barakchian , Seyed Mahdi, 2012. "Implications of Cointegration for Forecasting: A Review and an Empirical Analysis," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 7(1), pages 87-118, October.
    2. Robinson, P.M. & Iacone, F., 2005. "Cointegration in fractional systems with deterministic trends," Journal of Econometrics, Elsevier, vol. 129(1-2), pages 263-298.
    3. Alain W. HECQ, 2005. "Common Trends and Common Cycles in Latin America: A 2-step vs an Iterative Approach," Computing in Economics and Finance 2005 258, Society for Computational Economics.
    4. Tor Jacobson & Per Jansson & Anders Vredin & Anders Warne, 2001. "Monetary policy analysis and inflation targeting in a small open economy: a VAR approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(4), pages 487-520.
    5. Philip Rothman & Dick van Dijk & Philip Hans Franses, 1999. "A Multivariate STAR Analysis of the Relationship Between Money and Output," Working Papers 9913, East Carolina University, Department of Economics.
    6. Centoni, Marco & Cubadda, Gianluca & Hecq, Alain, 2007. "Common shocks, common dynamics, and the international business cycle," Economic Modelling, Elsevier, vol. 24(1), pages 149-166, January.
    7. Hurlin, Christophe & Minea, Alexandru, 2013. "Is public capital really productive? A methodological reappraisal," European Journal of Operational Research, Elsevier, vol. 228(1), pages 122-130.
    8. Ruxanda, Gheorghe & Botezatu, Andreea, 2008. "Spurious Regression And Cointegration. Numerical Example: Romania’S M2 Money Demand," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 5(3), pages 51-62, September.
    9. Milas, Costas & Rothman, Philip, 2008. "Out-of-sample forecasting of unemployment rates with pooled STVECM forecasts," International Journal of Forecasting, Elsevier, vol. 24(1), pages 101-121.
    10. Ida Wolden Bache, 2008. "Assessing estimates of the exchange rate pass-through," Working Paper 2007/12, Norges Bank.
    11. Judith A. Giles & Sadaf Mirza, 1999. "Some Pretesting Issues on Testing for Granger Noncausality," Econometrics Working Papers 9914, Department of Economics, University of Victoria.
    12. Bingham, Matthew F. & Prestemon, Jeffrey P. & MacNair, Douglas J. & Abt, Robert C. & Bingham, Matthew F., 2003. "Market structure in U. S. southern pine roundwood," Journal of Forest Economics, Elsevier, vol. 9(2), pages 97-117.
    13. Attfield, Cliff & Temple, Jonathan R.W., 2010. "Balanced growth and the great ratios: New evidence for the US and UK," Journal of Macroeconomics, Elsevier, vol. 32(4), pages 937-956, December.
    14. Gunnar Bårdsen & Luca Fanelli, 2015. "Frequentist Evaluation of Small DSGE Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(3), pages 307-322, July.
    15. Pierre St-Amant & David Tessier, 1998. "A Discussion of the Reliability of Results Obtained with Long-Run Identifying Restrictions," Staff Working Papers 98-4, Bank of Canada.
    16. Engsted, Tom, 2002. "Measures of Fit for Rational Expectations Models," Journal of Economic Surveys, Wiley Blackwell, vol. 16(3), pages 301-355, July.
    17. Kilian, Lutz & Ivanov, Ventzislav, 2001. "A Practitioner's Guide to Lag-Order Selection for Vector Autoregressions," CEPR Discussion Papers 2685, C.E.P.R. Discussion Papers.
    18. Ivanov Ventzislav & Kilian Lutz, 2005. "A Practitioner's Guide to Lag Order Selection For VAR Impulse Response Analysis," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 9(1), pages 1-36, March.
    19. Jacobson, Tor & Jansson, Per & Vredin, Anders & Warne, Anders, 1999. "A VAR Model for Monetary Policy Analysis in a Small Open Economy," Working Paper Series 77, Sveriges Riksbank (Central Bank of Sweden).
    20. Cliff L.F. Attfield & Jonathan R.W. Temple, 2003. "Measuring trend output: how useful are the Great Ratios?," Bristol Economics Discussion Papers 03/555, School of Economics, University of Bristol, UK.
    21. David Laidler, 1999. "The Quantity of Money and Monetary Policy," Staff Working Papers 99-5, Bank of Canada.
    22. Shahidur Rahman, 2005. "An Alternative Estimation to Spurious Regression Model," Economic Growth Centre Working Paper Series 0507, Nanyang Technological University, School of Social Sciences, Economic Growth Centre.
    23. Costas Milas & Phil Rothman, 2005. "Multivariate STAR Unemployment Rate Forecasts," Econometrics 0502010, University Library of Munich, Germany.
    24. Melisso Boschi, 2012. "Long- and short-run determinants of capital flows to Latin America: a long-run structural GVAR model," Empirical Economics, Springer, vol. 43(3), pages 1041-1071, December.
    25. Jonathan Temple & Cliff Attfield, 2004. "Measuring trend growth: how useful are the great ratios?," Money Macro and Finance (MMF) Research Group Conference 2003 101, Money Macro and Finance Research Group.

    More about this item

    Keywords

    Cointegration; money demand; stochastic growth model;
    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
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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