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Real And Nominal Convergence, The Syncronization Of Business Cycles Between The New Eurozone Members (Nem) Slovenia, Slovakia, Cyprus , Estonia And The Core Eurozone

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  • Zapodeanu Daniela

    (University of Oradea)

Abstract

After the accession of newly members in the European Union in 2004 and 2007 these countries are expected to adopt the common currency: Euro. The nominal convergence must be achieved until then as the Maastricht treaty implies but in order to be an Optimum-Currency-Area (OCA) these countries economies are expect to behave similarly to those of the Eurozone. We test the synchronization of the business cycle between the EU12 and Slovenia, Slovakia, Cyprus and Estonia using as a measure their GDP evolution . The GDP for all the states are seasonally adjusted using the X12-ARIMA methodology, we apply the Hodrick-Prescott filter in order to capture the trend and cycle of GDP, using the correlation coefficient we test their level of synchronisation. The main findings are that their level of synchronisation has rise over the 1995-2011 period, also adopting the common currency Euro doesn’t seem to have an impact on the level of busyness cycle synchronisation.

Suggested Citation

  • Zapodeanu Daniela, 2012. "Real And Nominal Convergence, The Syncronization Of Business Cycles Between The New Eurozone Members (Nem) Slovenia, Slovakia, Cyprus , Estonia And The Core Eurozone," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 1(2), pages 629-634, December.
  • Handle: RePEc:ora:journl:v:1:y:2012:i:2:p:629-634
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    References listed on IDEAS

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    More about this item

    Keywords

    Eurozone; business cycle synchronisation; Hodrick-Prescott filter; Optimum-Currency-Area;
    All these keywords.

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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