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Testing for Common Cyclical Features in Nonstationary Panel Data Models

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Author Info

  • Alain Hecq
  • Franz Palm
  • Jean-Pierre Urbain

Abstract

In this paper we extend the concept of serial correlation common features to panel data models. This analysis is motivated both by the need to develop a methodology to systematically stu dy and test for common structures and comovements in panel data with autocorrelation present and by an increase in efficiency coming from pooling procedures. We propose sequential testing procedures and study their properties in a small scale Monte Carlo analysis. Finally, we apply the framework to the well known permanent income hypothesis for 22 OECD countries, 1950-1992.

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File URL: http://www.cesifo-group.de/portal/page/portal/DocBase_Content/WP/WP-CESifo_Working_Papers/wp-cesifo-2000/wp-cesifo-2000-02/WP248.PDF
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Bibliographic Info

Paper provided by CESifo Group Munich in its series CESifo Working Paper Series with number 248.

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Date of creation: 2000
Date of revision:
Handle: RePEc:ces:ceswps:_248

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Related research

Keywords: Panel data; serial correlation common features; permanent income;

References

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Citations

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Cited by:
  1. Tommaso Mancini-Griffoli & Laurent L. Pauwels, 2006. "Is There a Euro Effect on Trade? An Application of End-of-Sample Structural Break Tests for Panel Data," IHEID Working Papers 04-2006, Economics Section, The Graduate Institute of International Studies, revised Apr 2006.
  2. 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.
  3. Marco Centoni & Gianluca Cubadda, 2011. "Modelling comovements of economic time series: a selective survey," Statistica, Department of Statistics, University of Bologna, vol. 71(2), pages 267-294.
  4. 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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