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Dealing with unobservable common trends in small samples: a panel cointegration approach

Author

Listed:
  • Francesca Di Iorio

    (Universita' di Napoli Federico II)

  • Stefano Fachin

    (Universita' di Roma "La Sapienza")

Abstract

Non stationary panel models allowing for unobservable common trends have recently become very popular. However, standard methods, which are based on factor extraction or models augmented with cross-section averages, require large sample sizes, not always available in practice. In these cases we propose the simple and robust alternative of augmenting the panel regres- sion with common time dummies. The underlying assumption of additive e¤ects can be tested by means of a panel cointegration test, with no need of estimating a general interactive e¤ects model. An application to modelling labour productivity growth in the four major European economies (France, Germany, Italy and UK) illustrates the method.

Suggested Citation

  • Francesca Di Iorio & Stefano Fachin, 2014. "Dealing with unobservable common trends in small samples: a panel cointegration approach," DSS Empirical Economics and Econometrics Working Papers Series 2014/5, Centre for Empirical Economics and Econometrics, Department of Statistics, "Sapienza" University of Rome.
  • Handle: RePEc:sas:wpaper:20145
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    File URL: http://www.dss.uniroma1.it/RePec/sas/wpaper/20145_dif.pdf
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    References listed on IDEAS

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    1. Stefano Fachin & Andrea Gavosto, 2010. "Trends of labour productivity in Italy: a study with panel co-integration methods," International Journal of Manpower, Emerald Group Publishing, vol. 31(7), pages 755-769, October.
    2. Bai, Jushan & Kao, Chihwa & Ng, Serena, 2009. "Panel cointegration with global stochastic trends," Journal of Econometrics, Elsevier, vol. 149(1), pages 82-99, April.
    3. Markus Eberhardt & Francis Teal, 2011. "Econometrics For Grumblers: A New Look At The Literature On Cross‐Country Growth Empirics," Journal of Economic Surveys, Wiley Blackwell, vol. 25(1), pages 109-155, February.
    4. Kapetanios, G. & Pesaran, M. Hashem & Yamagata, T., 2011. "Panels with non-stationary multifactor error structures," Journal of Econometrics, Elsevier, vol. 160(2), pages 326-348, February.
    5. Timmer,Marcel P. & Inklaar,Robert & O'Mahony,Mary & Ark,Bart van, 2013. "Economic Growth in Europe," Cambridge Books, Cambridge University Press, number 9781107412446, October.
    6. Chang, Yoosoon & Nguyen, Chi Mai, 2012. "Residual based tests for cointegration in dependent panels," Journal of Econometrics, Elsevier, vol. 167(2), pages 504-520.
    7. Moses Abramovitz, 1956. "Resource and Output Trends in the United States since 1870," NBER Books, National Bureau of Economic Research, Inc, number abra56-1, June.
    8. Di Iorio, Francesca & Fachin, Stefano, 2012. "A note on the estimation of long-run relationships in panel equations with cross-section linkages," Economics - The Open-Access, Open-Assessment E-Journal, Kiel Institute for the World Economy (IfW), vol. 6, pages 1-18.
    9. N. Gregory Mankiw & David Romer & David N. Weil, 1992. "A Contribution to the Empirics of Economic Growth," The Quarterly Journal of Economics, Oxford University Press, vol. 107(2), pages 407-437.
    10. Moses Abramovitz, 1956. "Resource and Output Trends in the United States since 1870," NBER Chapters, in: Resource and Output Trends in the United States since 1870, pages 1-23, National Bureau of Economic Research, Inc.
    11. Peter Pedroni, 1999. "Critical Values for Cointegration Tests in Heterogeneous Panels with Multiple Regressors," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 61(S1), pages 653-670, November.
    12. Peter Pedroni, 2007. "Social capital, barriers to production and capital shares: implications for the importance of parameter heterogeneity from a nonstationary panel approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(2), pages 429-451.
    13. Jushan Bai, 2009. "Panel Data Models With Interactive Fixed Effects," Econometrica, Econometric Society, vol. 77(4), pages 1229-1279, July.
    14. Baltagi, Badi H & Griffin, James M, 1988. "A General Index of Technical Change," Journal of Political Economy, University of Chicago Press, vol. 96(1), pages 20-41, February.
    15. Pedroni, Peter, 1999. "Critical Values for Cointegration Tests in Heterogeneous Panels with Multiple Regressors," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 61(0), pages 653-670, Special I.
    16. Westerlund, J. & Urbain, J.R.Y.J., 2011. "Cross sectional averages or principal components?," Research Memorandum 053, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
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    More about this item

    Keywords

    Common trends; Panel cointegration; TFP.;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • E2 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment

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