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Volatility Regimes in Macroeconomic Time Series: The Case of the Visegrad Group

The authors analyze several monthly and quarterly macroeconomic time series for the Czech Republic, Poland, Hungary, and Slovakia. These countries embarked on an economic transition in the early 1990s which ultimately led to their membership in the European Union, with Slovakia joining the euro area in 2009. It is natural to assume that changes of such a magnitude should also influence the major macroeconomic indicators. The authors explore the characteristics of these series by endogenously identifying their volatility regimes. In the course of their analysis, they show the difficulties in the handling of unit roots as a necessary step preceding volatility modeling. The final set of breaks identified shows very few changes near the beginning of the series, which corresponds to the transition period.

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Article provided by Charles University Prague, Faculty of Social Sciences in its journal Finance a uver - Czech Journal of Economics and Finance.

Volume (Year): 61 (2011)
Issue (Month): 6 (December)
Pages: 530-544

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Handle: RePEc:fau:fauart:v:61:y:2011:i:6:p:530-544
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  1. Wang, Jiahui & Zivot, Eric, 2000. "A Bayesian Time Series Model of Multiple Structural Changes in Level, Trend, and Variance," Journal of Business & Economic Statistics, American Statistical Association, vol. 18(3), pages 374-86, July.
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  3. E. Baumohl & S. Lyocsa & T. Vyrost, 2011. "Shift contagion with endogenously detected volatility breaks: the case of CEE stock markets," Applied Economics Letters, Taylor & Francis Journals, vol. 18(12), pages 1103-1109.
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  5. Giorgio Canarella & WenShwo Fang & Stephen M. Miller & Stephen K. Pollard, 2008. "Is the Great Moderation Ending? UK and US Evidence," Working papers 2008-24, University of Connecticut, Department of Economics.
  6. Saul Estrin & Jan Hanousek & Evzen Kocenda & Jan Svejnar, 2009. "The Effects of Privatization and Ownership in Transition Economies," Journal of Economic Literature, American Economic Association, vol. 47(3), pages 699-728, September.
  7. Lyócsa, Štefan & Výrost, Tomáš & Baumöhl, Eduard, 2011. "Unit-root and stationarity testing with empirical application on industrial production of CEE-4 countries," MPRA Paper 29648, University Library of Munich, Germany.
  8. Schwert, G William, 2002. "Tests for Unit Roots: A Monte Carlo Investigation," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 5-17, January.
  9. WenShwo Fang & Stephen M. Miller & ChunShen Lee, 2008. "Cross-Country Evidence On Output Growth Volatility: Nonstationary Variance And Garch Models," Scottish Journal of Political Economy, Scottish Economic Society, vol. 55(4), pages 509-541, 09.
  10. James H. Stock & Mark W. Watson, 2002. "Has the Business Cycle Changed and Why?," NBER Working Papers 9127, National Bureau of Economic Research, Inc.
  11. Kocenda, Evzen, 2000. "Detecting Structural Breaks in Exchange Rates in Transition Economies," CEPR Discussion Papers 2546, C.E.P.R. Discussion Papers.
  12. Kenneth D. West & Whitney K. Newey, 1995. "Automatic Lag Selection in Covariance Matrix Estimation," NBER Technical Working Papers 0144, National Bureau of Economic Research, Inc.
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