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Interest-rate volatility and volatility spillovers in emerging Europe

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  • Scott W. Hegerty

Abstract

While many transition economies -- particularly those that hope to join the Euro -- have seen their economies converge to Europe’s, this process is by no means complete. Considerable macroeconomic volatility persists. This study examines the variability of the short-term nominal interest rates of ten transition economies, finding that eight of them exhibit time-varying volatility that can be modeled as a GARCH or Exponential GARCH process. Incorporating various measures of external volatility into the models, we find that those economies with fixed or managed exchange rates tend to experience more volatility spillovers, particularly from the Eurozone, regardless of the degree of transition. Only Estonia has a fixed exchange rate and remains free of international contagion.

Suggested Citation

  • Scott W. Hegerty, 2011. "Interest-rate volatility and volatility spillovers in emerging Europe," International Review of Applied Economics, Taylor & Francis Journals, vol. 25(5), pages 599-614, October.
    • Handle: RePEc:taf:irapec:v:25:y:2011:i:5:p:599-614
    DOI: 10.1080/02692171.2011.557049
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    1. Nikiforos Laopodis, 2000. "Monetary policy implications of volatility linkages among long-term interest rates," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 24(2), pages 160-177, June.
    2. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    3. repec:bla:reviec:v:9:y:2001:i:1:p:133-52 is not listed on IDEAS
    4. Fung, Hung-Gay & Jang, Hoyoon & Lee, Wai, 1997. "International interest rate transmission and volatility spillover," International Review of Economics & Finance, Elsevier, vol. 6(1), pages 67-75.
    5. Jürgen von Hagen & Iulia Siedschlag, 2010. "Managing Capital Flows: Experiences from Central and Eastern Europe," Chapters, in: Masahiro Kawai & Mario B. Lamberte (ed.), Managing Capital Flows, chapter 7, Edward Elgar Publishing.
    6. Christine Sauer & Alok K. Bohara, 2001. "Exchange Rate Volatility and Exports: Regional Differences between Developing and Industrialized Countries," Review of International Economics, Wiley Blackwell, vol. 9(1), pages 133-152, February.
    7. Laopodis, Nikiforos T, 2002. "Volatility Linkages among Interest Rates: Implications for Global Monetary Policy," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 7(3), pages 215-233, July.
    8. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    9. Stephanos Papadamou & Georgios Oikonomou, 2007. "The Monetary Transmission Mechanism: Evidence from Eight Economies in Transition," International Economic Journal, Taylor & Francis Journals, vol. 21(4), pages 559-576.
    10. Zivot, Eric & Andrews, Donald W K, 2002. "Further Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 25-44, January.
    11. Stephanos Papadamou, 2009. "Yield spreads and real economic activity in East European transition economies," Applied Economics Letters, Taylor & Francis Journals, vol. 16(5), pages 531-537.
    12. Whitney Newey & Kenneth West, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    13. repec:bla:etrans:v:9:y:2001:i:1:p:53-86 is not listed on IDEAS
    14. Sebastian Edwards & Raul Susmel, 2003. "Interest-Rate Volatility in Emerging Markets," The Review of Economics and Statistics, MIT Press, vol. 85(2), pages 328-348, May.
    15. Taufiq Choudhry & Myles Wallace, 2008. "Interest rate convergence in the Baltic countries of Latvia, Lithuania and Estonia," Applied Economics Letters, Taylor & Francis Journals, vol. 15(14), pages 1079-1083.
    16. Hegerty, Scott W., 2009. "Capital inflows, exchange market pressure, and credit growth in four transition economies with fixed exchange rates," Economic Systems, Elsevier, vol. 33(2), pages 155-167, June.
    17. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
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    1. Scott W. Hegerty, 2014. "Interest-rate volatility and volatility transmission in nine Latin American countries," Applied Financial Economics, Taylor & Francis Journals, vol. 24(13), pages 927-937, July.
    2. Scott W. Hegerty, 2015. "Interest-Rate Volatility in the Baltics: Issues of Measurement and International Contagion," Eastern European Business and Economics Journal, Eastern European Business and Economics Studies Centre, vol. 1(1), pages 12-27.
    3. Kazeem Bello Ajide & Oluwanbepelumi Esther Osode, 2017. "Does FDI Dampen or Magnify Output Growth Volatility in the ECOWAS Region?," African Development Review, African Development Bank, vol. 29(2), pages 211-222, June.

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