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Micro versus macro cointegration in heterogeneous panels

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  • Trapani, Lorenzo
  • Urga, Giovanni

Abstract

We consider the issue of cross-sectional aggregation in nonstationary and heterogeneous panels where each unit cointegrates. We derive asymptotic properties of the aggregate estimate, and necessary and sufficient conditions for cointegration to hold in the aggregate relationship. We then analyze the case when cointegration does not carry through the aggregation process, and we investigate whether the violation of the formal conditions for perfect aggregation can still lead to an aggregate equation that is observationally equivalent to a cointegrated relationship. We derive a measure of the degree of noncointegration of the aggregate relationship and we explore its asymptotic properties. We propose a valid bootstrap approximation of the test. A Monte Carlo exercise evaluates size and power properties of the bootstrap test.

Suggested Citation

  • Trapani, Lorenzo & Urga, Giovanni, 2010. "Micro versus macro cointegration in heterogeneous panels," Journal of Econometrics, Elsevier, vol. 155(1), pages 1-18, March.
  • Handle: RePEc:eee:econom:v:155:y:2010:i:1:p:1-18
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    1. Suzanne McCoskey & Chihwa Kao, 1998. "A residual-based test of the null of cointegration in panel data," Econometric Reviews, Taylor & Francis Journals, vol. 17(1), pages 57-84.
    2. Tuomo Vuolteenaho, 2002. "What Drives Firm-Level Stock Returns?," Journal of Finance, American Finance Association, vol. 57(1), pages 233-264, February.
    3. Hashem Pesaran, M., 2003. "Aggregation of linear dynamic models: an application to life-cycle consumption models under habit formation," Economic Modelling, Elsevier, vol. 20(2), pages 383-415, March.
    4. 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.
    5. Stoker, Thomas M, 1993. "Empirical Approaches to the Problem of Aggregation Over Individuals," Journal of Economic Literature, American Economic Association, vol. 31(4), pages 1827-1874, December.
    6. Park, Joon Y. & Phillips, Peter C.B., 1999. "Asymptotics For Nonlinear Transformations Of Integrated Time Series," Econometric Theory, Cambridge University Press, vol. 15(03), pages 269-298, June.
    7. Campbell, John Y & Shiller, Robert J, 1987. "Cointegration and Tests of Present Value Models," Journal of Political Economy, University of Chicago Press, vol. 95(5), pages 1062-1088, October.
    8. Yoosoon Chang & Joon Y. Park, 2003. "A Sieve Bootstrap For The Test Of A Unit Root," Journal of Time Series Analysis, Wiley Blackwell, vol. 24(4), pages 379-400, July.
    9. Kwiatkowski, Denis & Phillips, Peter C. B. & Schmidt, Peter & Shin, Yongcheol, 1992. "Testing the null hypothesis of stationarity against the alternative of a unit root : How sure are we that economic time series have a unit root?," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 159-178.
    10. Yan Shen & Cheng Hsiao & Hiroshi Fujiki, 2005. "Aggregate vs. disaggregate data analysis-a paradox in the estimation of a money demand function of Japan under the low interest rate policy," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(5), pages 579-601.
    11. Evan Gatev & William N. Goetzmann & K. Geert Rouwenhorst, 2006. "Pairs Trading: Performance of a Relative-Value Arbitrage Rule," Review of Financial Studies, Society for Financial Studies, vol. 19(3), pages 797-827.
    12. Forni, Mario & Lippi, Marco, 1997. "Aggregation and the Microfoundations of Dynamic Macroeconomics," OUP Catalogue, Oxford University Press, number 9780198288008.
    13. 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.
    14. Park, Joon Y. & Phillips, Peter C.B., 1988. "Statistical Inference in Regressions with Integrated Processes: Part 1," Econometric Theory, Cambridge University Press, vol. 4(03), pages 468-497, December.
    15. 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.
    16. Granger, C. W. J., 1993. "Implications of seeing economic variables through an aggregation window," Ricerche Economiche, Elsevier, vol. 47(3), pages 269-279, September.
    17. Chang, Yoosoon & Park, Joon Y. & Song, Kevin, 2006. "Bootstrapping cointegrating regressions," Journal of Econometrics, Elsevier, vol. 133(2), pages 703-739, August.
    18. Bai, Jushan, 2004. "Estimating cross-section common stochastic trends in nonstationary panel data," Journal of Econometrics, Elsevier, vol. 122(1), pages 137-183, September.
    19. Forni, Mario & Lippi, Marco, 1999. "Aggregation of linear dynamic microeconomic models," Journal of Mathematical Economics, Elsevier, vol. 31(1), pages 131-158, February.
    20. Gonzalo, Jesus, 1993. "Cointegration and aggregation," Ricerche Economiche, Elsevier, vol. 47(3), pages 281-291, September.
    21. Phillips, P.C.B., 1986. "Understanding spurious regressions in econometrics," Journal of Econometrics, Elsevier, vol. 33(3), pages 311-340, December.
    22. Lippi, Marco, 1988. "On the dynamic shape of aggregated error correction models," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 561-585.
    23. Park, Joon Y., 2002. "An Invariance Principle For Sieve Bootstrap In Time Series," Econometric Theory, Cambridge University Press, vol. 18(02), pages 469-490, April.
    24. Kao, Chihwa, 1999. "Spurious regression and residual-based tests for cointegration in panel data," Journal of Econometrics, Elsevier, vol. 90(1), pages 1-44, May.
    25. Yoosoon Chang & Joon Park, 2002. "On The Asymptotics Of Adf Tests For Unit Roots," Econometric Reviews, Taylor & Francis Journals, vol. 21(4), pages 431-447.
    26. Shin, Yongcheol, 1994. "A Residual-Based Test of the Null of Cointegration Against the Alternative of No Cointegration," Econometric Theory, Cambridge University Press, vol. 10(01), pages 91-115, March.
    27. Xiao, Zhijie, 1999. "A residual based test for the null hypothesis of cointegration," Economics Letters, Elsevier, vol. 64(2), pages 133-141, August.
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    Cited by:

    1. Syed Abul Basher & Elsayed Mousa Elsamadisy, 2012. "Country heterogeneity and long-run determinants of inflation in the Gulf Arab states," OPEC Energy Review, Organization of the Petroleum Exporting Countries, vol. 36(2), pages 170-203, June.
    2. Pesaran, M. Hashem & Chudik, Alexander, 2014. "Aggregation in large dynamic panels," Journal of Econometrics, Elsevier, vol. 178(P2), pages 273-285.
    3. Stephan Smeekes & Jean-Pierre Urbain, 2014. "On the Applicability of the Sieve Bootstrap in Time Series Panels," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(1), pages 139-151, February.
    4. Dario Fauceglia & Anirudh Shingal & Martin Wermelinger, 2014. "Natural Hedging of Exchange Rate Risk: The Role of Imported Input Prices," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 150(IV), pages 261-296, December.

    More about this item

    Keywords

    Heterogeneous panels Aggregation Cointegration Spurious regression Bootstrap;

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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