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Cointegration Versus Spurious Regression In Heterogeneous Panels

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  • Giovanni Urga
  • Lorenzo Trapani

Abstract

We consider the issue of cross sectional aggregation in nonstationary, heterogeneous panels where each unit cointegrates. We first derive the asymptotic properties of the aggregate estimate, and a necessary and sufficient condition for cointegration to hold in the aggregate relationship. We also develop an estimation and testing framework to verify whether the condition is met. Secondly, we analyze the case when cointegration doesn't carry through the aggregation process, investigating whether a mild violation can still lead to an aggregate estimator that summarizes the micro relationships reasonably well. We derive the asymptotic measure of the degree of non cointegration of the aggregated estimate and we provide estimation and testing procedures. A Monte Carlo exercise evaluates the small sample properties of the estimator.

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Paper provided by Royal Economic Society in its series Royal Economic Society Annual Conference 2004 with number 74.

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Date of creation: 17 Sep 2004
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Handle: RePEc:ecj:ac2004:74

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  1. Snell, Andy, 1998. "Testing for r versus r-1 cointegrating vectors," Journal of Econometrics, Elsevier, vol. 88(1), pages 151-191, November.
  2. Ghose, Devajyoti, 1995. "Linear aggregation in cointegrated systems," Journal of Economic Dynamics and Control, Elsevier, vol. 19(5-7), pages 1011-1032.
  3. Hall, Stephen & Lazarova, Stepana & Urga, Giovanni, 1999. " A Principal Components Analysis of Common Stochastic Trends in Heterogeneous Panel Data: Some Monte Carlo Evidence," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 61(0), pages 749-67, Special I.
  4. Gonzalo, Jesus, 1993. "Cointegration and aggregation," Ricerche Economiche, Elsevier, vol. 47(3), pages 281-291, September.
  5. Phillips, P.C.B., 1986. "Understanding spurious regressions in econometrics," Journal of Econometrics, Elsevier, vol. 33(3), pages 311-340, December.
  6. Harris, D., 1996. "Principal Components Analysis of Cointegrated Time Series," Monash Econometrics and Business Statistics Working Papers 2/96, Monash University, Department of Econometrics and Business Statistics.
  7. Pesaran, M.H. & Smith, R., 1992. "Estimating Long-Run Relationships From Dynamic Heterogeneous Panels," Cambridge Working Papers in Economics 9215, Faculty of Economics, University of Cambridge.
  8. Peter C.B. Phillips & Joon Y. Park, 1986. "Statistical Inference in Regressions with Integrated Processes: Part 2," Cowles Foundation Discussion Papers 819R, Cowles Foundation for Research in Economics, Yale University, revised Feb 1987.
  9. Phillips, P. C. B. & Ouliaris, S., 1988. "Testing for cointegration using principal components methods," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 205-230.
  10. Peter C.B. Phillips & Joon Y. Park, 1986. "Statistical Inference in Regressions with Integrated Processes: Part 1," Cowles Foundation Discussion Papers 811R, Cowles Foundation for Research in Economics, Yale University, revised Aug 1987.
  11. Granger, C. W. J., 1993. "Implications of seeing economic variables through an aggregation window," Ricerche Economiche, Elsevier, vol. 47(3), pages 269-279, September.
  12. Lazarov , tep na & Trapani, Lorenzo & Urga, Giovanni, 2007. "Common Stochastic Trends And Aggregation In Heterogeneous Panels," Econometric Theory, Cambridge University Press, vol. 23(01), pages 89-105, February.
  13. Peter C. B. Phillips & Hyungsik R. Moon, 1999. "Linear Regression Limit Theory for Nonstationary Panel Data," Econometrica, Econometric Society, vol. 67(5), pages 1057-1112, September.
  14. Clive W. J. Granger, 1988. "Aggregation of time series variables-a survey," Discussion Paper / Institute for Empirical Macroeconomics 1, Federal Reserve Bank of Minneapolis.
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