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Studying Co-Movements in Large Multivariate Data Prior to Multivariate Modelling

For non-stationary vector autoregressive models (VAR hereafter, or VAR with moving average, VARMA hereafter), we show that the presence of common cyclical features or cointegration leads to a reduction of the order of the implied univariate autoregressive-moving average (ARIMA hereafter) models. This finding can explain why we identify parsimonious univariate ARIMA models in applied research although VAR models of typical order and dimension used in macroeconometrics imply nonparsimonious univariate ARIMA representations. Next, we develop a strategy for studying interactions between variables prior to possibly modelling them in a multivariate setting. Indeed, the similarity of the autoregressive roots will be informative about the presence of co-movements in a set of multiple time series. Our results justify both the use of a panel setup with homogeneous autoregression and heterogeneous cross-correlated vector moving average errors and a factor structure, and the use of cross-sectional aggregates of ARIMA series to estimate the homogeneous autoregression.

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Paper provided by Tor Vergata University, CEIS in its series CEIS Research Paper with number 125.

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Length: 26 pages
Date of creation: 14 Jul 2008
Date of revision: 14 Jul 2008
Handle: RePEc:rtv:ceisrp:125
Contact details of provider: Postal: CEIS - Centre for Economic and International Studies - Faculty of Economics - University of Rome "Tor Vergata" - Via Columbia, 2 00133 Roma
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  1. Palm, F.C. & Zellner, A., 1978. "Large sample estimation and testing procedures for dynamic equation systems," Serie Research Memoranda 0010, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
  2. Zellner, Arnold & Palm, Franz, 1974. "Time series analysis and simultaneous equation econometric models," Journal of Econometrics, Elsevier, vol. 2(1), pages 17-54, May.
  3. Jushan Bai & Serena Ng, 2001. "A PANIC Attack on Unit Roots and Cointegration," Boston College Working Papers in Economics 519, Boston College Department of Economics.
  4. PALM, Franz, . "On univariate time series methods and simultaneous equation econometric models," CORE Discussion Papers RP 293, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  5. Vahid, Farshid & Engle, Robert F., 1997. "Codependent cycles," Journal of Econometrics, Elsevier, vol. 80(2), pages 199-221, October.
  6. Gianluca Cubadda, 2007. "A Unifying Framework for Analysing Common Cyclical Features in Cointegrated Time Series," CEIS Research Paper 102, Tor Vergata University, CEIS.
  7. Wallis, Kenneth F, 1977. "Multiple Time Series Analysis and the Final Form of Econometric Models," Econometrica, Econometric Society, vol. 45(6), pages 1481-97, September.
  8. Vahid, F & Engle, Robert F, 1993. "Common Trends and Common Cycles," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(4), pages 341-60, Oct.-Dec..
  9. Stock, James H & Watson, Mark W, 2002. "Macroeconomic Forecasting Using Diffusion Indexes," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 147-62, April.
  10. Christoph Schleicher, 2007. "Codependence in cointegrated autoregressive models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(1), pages 137-159.
  11. Cubadda, Gianluca & Hecq, Alain & Palm, Franz C., 2007. "Macro-panels and Reality," Research Memorandum 009, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
  12. Centoni, Marco & Cubadda, Gianluca & Hecq, Alain, 2003. "Common Shocks, Common Dynamics, and the International Business Cycle," Economics & Statistics Discussion Papers esdp03007, University of Molise, Dept. EGSeI.
  13. Maravall, Agustin & Mathis, Alexandre, 1994. "Encompassing univariate models in multivariate time series : A case study," Journal of Econometrics, Elsevier, vol. 61(2), pages 197-233, April.
  14. Hans-Martin Krolzig & Ralf Brüggemann, 2003. "Comparison of Model Reduction Methods for VAR Processes," Economics Series Working Papers 2003-W13, University of Oxford, Department of Economics.
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  17. Robert F. Engle & Sharon Kozicki, 1990. "Testing For Common Features," NBER Technical Working Papers 0091, National Bureau of Economic Research, Inc.
  18. Bénédicte Vidaillet & V. D'Estaintot & P. Abécassis, 2005. "Introduction," Post-Print hal-00287137, HAL.
  19. Mario Forni & Marc Hallin & Lucrezia Reichlin & Marco Lippi, 2000. "The generalised dynamic factor model: identification and estimation," ULB Institutional Repository 2013/10143, ULB -- Universite Libre de Bruxelles.
  20. Cubadda, Gianluca & Hecq, Alain, 2001. "On non-contemporaneous short-run co-movements," Economics Letters, Elsevier, vol. 73(3), pages 389-397, December.
  21. Alain Hecq & Franz Palm & Jean-Pierre Urbain, 2002. "Separation, Weak Exogeneity, And P-T Decomposition In Cointegrated Var Systems With Common Features," Econometric Reviews, Taylor & Francis Journals, vol. 21(3), pages 273-307.
  22. Zellner,Arnold & Palm,Franz C. (ed.), 2004. "The Structural Econometric Time Series Analysis Approach," Cambridge Books, Cambridge University Press, number 9780521814072.
  23. Hecq, Alain & Palm, Franz C. & Urbain, Jean-Pierre, 2006. "Common cyclical features analysis in VAR models with cointegration," Journal of Econometrics, Elsevier, vol. 132(1), pages 117-141, May.
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