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Citations for "Impulse Response Analysis in Infinite Order Cointegrated Vector Autoregressive Processes"

by H. Lütkepohl & P. Saikkonen

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  1. Helmut Lütkepohl, 2013. "Vector autoregressive models," Chapters, in: Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 6, pages 139-164 Edward Elgar Publishing.
  2. Qu, Zhongjun & Perron, Pierre, 2007. "A Modified Information Criterion For Cointegration Tests Based On A Var Approximation," Econometric Theory, Cambridge University Press, vol. 23(04), pages 638-685, August.
  3. Dufour, Jean-Marie & Pelletier, Denis & Renault, Eric, 2006. "Short run and long run causality in time series: inference," Journal of Econometrics, Elsevier, vol. 132(2), pages 337-362, June.
  4. Bauer, Dietmar & Maynard, Alex, 2012. "Persistence-robust surplus-lag Granger causality testing," Journal of Econometrics, Elsevier, vol. 169(2), pages 293-300.
  5. Gourieroux, Christian & Jasiak, Joanna, 1999. "Nonlinear innovations and impulse responses," CEPREMAP Working Papers (Couverture Orange) 9906, CEPREMAP.
  6. Fathali Firoozi & Donald Lien, 2011. "A Procedure for Testing Granger Causality of Infinite Order," International Journal of Business and Economics, College of Business, and College of Finance, Feng Chia University, Taichung, Taiwan, vol. 10(2), pages 165-170, August.
  7. Lütkepohl, Helmut & Saikkonen, Pentti, 1997. "Order selection in testing for the cointegrating rank of a VAR process," SFB 373 Discussion Papers 1997,93, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
  8. Peter Reinhard Hansen, . "The Johansen-Granger Representation Theorem: A Closed Form Expression for I(1)Processes Creation-Date: 2000," Working Papers 2000-19, Brown University, Department of Economics.
  9. Marcelo Savino Portugal & Igor Alexandre Clemente de Morais, 2004. "Business Cycle In The Industrial Production Of Brazilian States," Econometric Society 2004 Latin American Meetings 23, Econometric Society.
  10. S Ouliaris & A R Pagan, 2015. "A New Method for Working With Sign Restrictions in SVARs," NCER Working Paper Series 105, National Centre for Econometric Research.
  11. BATTISTI,Michele, 2006. "Assessing persistence in the Italian rate of unemployment in presence of structural breaks and regional asymmetries, 1977 to 2004," Applied Econometrics and International Development, Euro-American Association of Economic Development, vol. 6(3).
  12. Keating, John W., 2000. "Macroeconomic Modeling with Asymmetric Vector Autoregressions," Journal of Macroeconomics, Elsevier, vol. 22(1), pages 1-28, January.
  13. Bierens, Herman J., 1997. "Nonparametric cointegration analysis," Journal of Econometrics, Elsevier, vol. 77(2), pages 379-404, April.
  14. Zernov, Serguei & Zinde-Walsh, Victoria & Galbraith, John W., 2009. "Asymptotics for estimation of quantile regressions with truncated infinite-dimensional processes," Journal of Multivariate Analysis, Elsevier, vol. 100(3), pages 497-508, March.
  15. Hansen, Peter Reinhard, 2000. "The Johansen-Granger Representation Theorem: An Explicit Expression for I(1) Processes," University of California at San Diego, Economics Working Paper Series qt832256dg, Department of Economics, UC San Diego.
  16. Serguei Zernov & Victoria Zindle-Walsh & John Galbraith, 2006. "Asymptotics For Estimation Of Truncated Infinite-Dimensional Quantile Regressions," Departmental Working Papers 2006-16, McGill University, Department of Economics.
  17. Dietmar Bauer & Martin Wagner, 2000. "Estimating Cointegrated Systems Using Subspace Algorithms," Econometric Society World Congress 2000 Contributed Papers 0293, Econometric Society.
  18. Helmut Luetkepohl, 2011. "Vector Autoregressive Models," Economics Working Papers ECO2011/30, European University Institute.
  19. Dietmar Bauer & Alex Maynard, 2010. "Persistence-robust Granger causality testing," Working Papers 1011, University of Guelph, Department of Economics and Finance.
This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.