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Political and Institutional Factors in the Convergence of International Equity Markets: Evidence from the Club Convergence and Clustering Procedure

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  • Nicholas Apergis
  • Christina Christou
  • James Payne

Abstract

In this study the new panel convergence methodology developed by Phillips and Sul ( 2007 ) is employed to explore the convergence dynamics of international equity markets and determine whether political and institutional factors can explain convergence or divergence patterns across international equity markets. The empirical findings suggest that international equity markets do not form a homogeneous convergence club. Seven specific political and institutional factors are used to explain such divergent behavior. The empirical analysis documented specific factors, i.e. democratization, unemployment benefits, and public expenditure on pensions, which seem capable of explaining such a heterogeneous divergent pattern among the equity markets under study. Copyright International Atlantic Economic Society 2011

Suggested Citation

  • Nicholas Apergis & Christina Christou & James Payne, 2011. "Political and Institutional Factors in the Convergence of International Equity Markets: Evidence from the Club Convergence and Clustering Procedure," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 39(1), pages 7-18, March.
    • Handle: RePEc:kap:atlecj:v:39:y:2011:i:1:p:7-18
    DOI: 10.1007/s11293-010-9255-x
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    Cited by:

    1. Apergis, Nicholas & Christou, Christina & Miller, Stephen M., 2014. "Country and industry convergence of equity markets: International evidence from club convergence and clustering," The North American Journal of Economics and Finance, Elsevier, vol. 29(C), pages 36-58.
    2. George A. Matysiak & Krzysztof Olszewski, 2019. "A panel analysis of Polish regional cities: residential price convergence in the primary market," NBP Working Papers 316, Narodowy Bank Polski.
    3. Nicholas Apergis & Christina Christou & Rangan Gupta & Stephen M. Miller, 2018. "Convergence in Income Inequality: Further Evidence from the Club Clustering Methodology across States in the U.S," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 24(2), pages 147-161, May.
    4. Tran Thi Xuan Anh & Ngo Thi Hang & Nguyen Thi Lam Anh, 2020. "Assessing Financial Market Integration in Vietnam: A Price – Based Approach," Academic Journal of Interdisciplinary Studies, Richtmann Publishing Ltd, vol. 9, July.
    5. Tam, Pui Sun & Tam, Pui I., 2012. "Rethinking stock market integration: Globalization, valuation and convergence," SFB 649 Discussion Papers 2012-052, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    6. Niţoi, Mihai & Pochea, Maria Miruna, 2016. "Testing financial markets convergence in Central and Eastern Europe: A non-linear single factor model," Economic Systems, Elsevier, vol. 40(2), pages 323-334.
    7. Beylunioglu Fuat C. & Stengos Thanasis & Yazgan M. Ege, 2017. "Detecting capital market convergence clubs," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(3), pages 1-14, June.
    8. Fegheh Majidi , Ali & Mohammadi , Ahmad & Nanvay Sabegh , Behnaz, 2017. "An Investigation of Convergence Hypothesis of Price Index in Asian Stock Markets," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 12(1), pages 73-88, January.
    9. repec:hum:wpaper:sfb649dp2012-052 is not listed on IDEAS

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    More about this item

    Keywords

    Equity markets convergence; Political factors; Institutional factors; Club clustering methodology; C32; C33;
    All these keywords.

    JEL classification:

    • 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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