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Old Wine in a New Bottle: Growth Convergence Dynamics in the EU

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  • Nicholas Apergis

    ()

  • Ekaterini Panopoulou

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  • Chris Tsoumas

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Abstract

In this paper, we explore convergence of real per capita output across the European Union (EU) countries, as well as the transitional behavior of possible underlying factors that are responsible for any convergence or divergence pattern. The new panel convergence methodology developed by Phillips and Sul ( 2007 ) is employed in a production function growth accounting approach and data from the Total Economy Database and the Total Economy Growth Accounting Database. The empirical findings suggest that the EU countries form two distinct convergent clubs, exhibiting considerable heterogeneity in the underlying growth factors. These findings should help policy makers in designing appropriate growth-oriented programs as well as in setting priorities in their implementation. Copyright International Atlantic Economic Society 2010

Suggested Citation

  • Nicholas Apergis & Ekaterini Panopoulou & Chris Tsoumas, 2010. "Old Wine in a New Bottle: Growth Convergence Dynamics in the EU," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 38(2), pages 169-181, June.
    • Handle: RePEc:kap:atlecj:v:38:y:2010:i:2:p:169-181
    DOI: 10.1007/s11293-010-9219-1
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    References listed on IDEAS

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    1. Romer, Paul M, 1986. "Increasing Returns and Long-run Growth," Journal of Political Economy, University of Chicago Press, vol. 94(5), pages 1002-1037, October.
    2. Salinas-Jimenez, M Mar & Alvarez-Ayuso, Inmaculada & Delgado-Rodriguez, M Jesus, 2006. "Capital accumulation and TFP growth in the EU: A production frontier approach," Journal of Policy Modeling, Elsevier, vol. 28(2), pages 195-205, February.
    3. Carmela Martín & Ismael Sanz, 2003. "Real Convergence and European Integration: The Experience of the Less Developed EU Members," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 30(3), pages 205-236, September.
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    5. Jesus Crespo Cuaresma & Doris Ritzberger-Grunwald & Maria Antoinette Silgoner, 2008. "Growth, convergence and EU membership," Applied Economics, Taylor & Francis Journals, vol. 40(5), pages 643-656.
    6. Andrews, Donald W K, 1991. "Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation," Econometrica, Econometric Society, vol. 59(3), pages 817-858, May.
    7. 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.
    8. Peter C. B. Phillips & Donggyu Sul, 2009. "Economic transition and growth," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(7), pages 1153-1185.
    9. Robert E. Hall & Charles I. Jones, 1999. "Why do Some Countries Produce So Much More Output Per Worker than Others?," The Quarterly Journal of Economics, Oxford University Press, vol. 114(1), pages 83-116.
    10. Lucas, Robert Jr., 1988. "On the mechanics of economic development," Journal of Monetary Economics, Elsevier, vol. 22(1), pages 3-42, July.
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    Citations

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    Cited by:

    1. Juan Gabriel Brida & Silvia London & Lionello Punzo & Wiston Adrian Risso, 2011. "An Alternative View of the Convergence Issue of Growth Empirics," Growth and Change, Wiley Blackwell, vol. 42(3), pages 320-350, September.
    2. Krasnopjorovs, Olegs, 2013. "Latvijas ekonomikas izaugsmi noteicošie faktori
      [Factors of Economic Growth in Latvia]      ," MPRA Paper 47550, University Library of Munich, Germany.
    3. Konrad Lyncker & Rasmus Thoennessen, 2017. "Regional club convergence in the EU: evidence from a panel data analysis," Empirical Economics, Springer, vol. 52(2), pages 525-553, March.
    4. Juan Brida & Nicolás Garrido & Francesco Mureddu, 2014. "Italian economic dualism and convergence clubs at regional level," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(1), pages 439-456, January.
    5. Crespo Cuaresma, Jesus & Havettová, Miroslava & Lábaj, Martin, 2013. "Income convergence prospects in Europe: Assessing the role of human capital dynamics," Economic Systems, Elsevier, vol. 37(4), pages 493-507.
    6. Kaitila, Ville, 2013. "Convergence, income distribution, and the economic crisis in Europe," ETLA Working Papers 14, The Research Institute of the Finnish Economy.
    7. BRIDA, Juan Gabriel & GARRIDo, Nicolas & MUREDDU, Francesco, 2014. "Club Performance Dynamics At Italian Regional Level," Regional and Sectoral Economic Studies, Euro-American Association of Economic Development, vol. 14(1), pages 47-68.
    8. Xuan-Binh Vu & Son Nghiem, 2016. "Analysis of GDP trends and inequalities in Vietnam`s provinces and groups of provinces," Asian Journal of Empirical Research, Asian Economic and Social Society, vol. 6(7), pages 167-186, July.
    9. Mahamat Hamit-Haggar, 2013. "A note on convergence across Canadian provinces: new insights from the club clustering algorithm," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 50(2), pages 591-601, April.
    10. Krasnopjorovs, Olegs, 2012. "Measuring the sources of economic growth in the EU with parametric and non-parametric methods," MPRA Paper 47583, University Library of Munich, Germany.

    More about this item

    Keywords

    Growth convergence; Growth factors; Transition paths; EU countries; Logt test; O40; O47; C32; C33;

    JEL classification:

    • O40 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - General
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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