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Current account sustainability in advanced economies

Author

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  • Matteo Lanzafame

Abstract

This paper investigates the sustainability of current accounts in advanced economies using a panel of 27 countries and annual data over the 1980-2008 period. Relying on various panel unit root tests and a sequential panel selection method, we find strong evidence in favour of nonlinear but stationary current account trajectories only for 7 countries, while the remaining 20 appear to be non-stationary and thus unsustainable. Our analysis indicates that careful empirical modelling of current account dynamics, particularly in relation to cross-section dependence and nonlinear behaviour, is crucial for appropriate economic policy-making.

Suggested Citation

  • Matteo Lanzafame, 2014. "Current account sustainability in advanced economies," The Journal of International Trade & Economic Development, Taylor & Francis Journals, vol. 23(7), pages 1000-1017, October.
    • Handle: RePEc:taf:jitecd:v:23:y:2014:i:7:p:1000-1017
    DOI: 10.1080/09638199.2013.821152
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    Cited by:

    1. Sahoo, Manoranjan & babu, M. Suresh & Dash, Umakant, 2016. "Current account sustainability in SAARC economies: Evidence from combined cointegration approach," MPRA Paper 79014, University Library of Munich, Germany, revised 2016.
    2. Manoranjan SAHOO & M Suresh BABU & Umakant DASH, 2016. "Current account sustainability in SAARC economies: Evidence from combined cointegration approach," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania / Editura Economica, vol. 0(4(609), W), pages 281-298, Winter.
    3. António Afonso & José Alves & José Carlos Coelho & Jamel Saadaoui, 2025. "Fiscal and External Sustainability: a Two-Step Time-varying Granger Causality Assessment," Working Papers REM 2025/0369, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
    4. Sahoo, Manoranjan & Babu, M. Suresh & Dash, Umakant, 2016. "Long run sustainability of current account balance of China and India: New evidence from combined cointegration test," MPRA Paper 79013, University Library of Munich, Germany, revised 2016.
    5. Manoranjan SAHOO & M Suresh BABU & Umakant DASH, 2016. "Current account sustainability in SAARC economies: Evidence from combined cointegration approach," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(4(609), W), pages 281-298, Winter.
    6. Amba Oyon Claude Marius & Taoufiki Mbratana & Kane Gilles Quentin, 2017. "Assessing the current account sustainability in ECCAS economies: A dual cointegration analysis," Economics Bulletin, AccessEcon, vol. 37(3), pages 1873-1894.
    7. Singh Tarlok, 2017. "Sustainability of Current Account Deficits in the OECD Countries: Evidence from Panel Data Estimators," Global Economy Journal, De Gruyter, vol. 17(4), pages 1-16, December.
    8. Devi Prasad DASH & Debi Prasad BAL & Manoranjan SAHOO, 2016. "Nexus between defense expenditure and economic growth in BRIC economies: An empirical investigation," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania / Editura Economica, vol. 0(1(606), S), pages 89-102, Spring.
    9. Tarlok Singh, 2017. "Are Current Account Deficits in the OECD Countries Sustainable? Robust Evidence from Time-Series Estimators," The International Trade Journal, Taylor & Francis Journals, vol. 31(1), pages 29-64, January.
    10. António Afonso & Florence Huart & João Tovar Jalles & Piotr Stanek, 2020. "Long-run relationship between exports and imports: current account sustainability tests for the EU," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 19(2), pages 155-170, May.
    11. Olufemi G. Onatunji, 2023. "Sustainability of current account deficits in Nigeria: evidence from the asymmetric NARDL approach," SN Business & Economics, Springer, vol. 3(10), pages 1-22, October.

    More about this item

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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