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Estimating Cointegrating Relations from a Cross Section

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Author Info
Edith Madsen (Institute of Economics, University of Copenhagen)
Abstract

This paper specifies a regression model describing cointegrating relations between variables at the individual level. The models considered allow for homogeneous cointegration and heterogeneous cointegration. In both cases correlation between the regressors and the regression error can occur through aggregate shocks that are common to all cross-section units so the condition about the regressors being independent of the regression error is not imposed. It is shown that the estimator obtained by a cross-section regression performed at any point in time is a consistent estimator of the cointegrating parameters in the homogeneous case and of the cointegrating parameter means in the heterogeneous case. In both cases the limiting distribution of the cross-section estimator is normal.

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Publisher Info
Paper provided by University of Copenhagen. Department of Economics. Centre for Applied Microeconometrics in its series CAM Working Papers with number 2004-21.

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Length: 15 pages
Date of creation: Nov 2004
Date of revision:
Handle: RePEc:kud:kuieca:2004_21

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Related research
Keywords: dynamic panel data models; non-stationary panel data; cointegrating relations; cross-section regression;

Find related papers by JEL classification:
C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions

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References listed on IDEAS
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  1. Pesaran, M. Hashem & Smith, Ron, 1995. "Estimating long-run relationships from dynamic heterogeneous panels," Journal of Econometrics, Elsevier, vol. 68(1), pages 79-113, July. [Downloadable!] (restricted)
    Other versions:
  2. Banerjee, Anindya, 1999. " Panel Data Unit Roots and Cointegration: An Overview," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 61(0), pages 607-29, Special I. [Downloadable!] (restricted)
  3. Peter C.B. Phillips & Joon Y. Park, 1986. "Statistical Inference in Regressions with Integrated Processes: Part 2," Cowles Foundation Discussion Papers 819R, Cowles Foundation, Yale University, revised Feb 1987. [Downloadable!]
    Other versions:
  4. Phillips, P.C.B., 1986. "Understanding spurious regressions in econometrics," Journal of Econometrics, Elsevier, vol. 33(3), pages 311-340, December. [Downloadable!] (restricted)
    Other versions:
  5. Peter C.B. Phillips & Hyungsik R. Moon, 1999. "Linear Regression Limit Theory for Nonstationary Panel Data," Cowles Foundation Discussion Papers 1222, Cowles Foundation, Yale University. [Downloadable!]
    Other versions:
  6. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-38, May. [Downloadable!] (restricted)
  7. Badi H. Baltagi & Chihwa Kao, 2000. "Nonstationary Panels, Cointegration in Panels and Dynamic Panels: A Survey," Center for Policy Research Working Papers 16, Center for Policy Research, Maxwell School, Syracuse University. [Downloadable!]
  8. Adda, Jérôme & Robin, Jean-Marc, 1998. "Estimation from cross-sections of integrated time-series," CEPREMAP Working Papers (Couverture Orange) 9802, CEPREMAP. [Downloadable!]
  9. Baltagi, Badi H. & Boozer, Michael A., 1997. "Econometric Analysis of Panel Data," Econometric Theory, Cambridge University Press, vol. 13(05), pages 747-754, October. [Downloadable!]
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