Are Eastern European Countries Catching Up? Time Series Evidence for Czech Republic, Hungary, and Poland
AbstractThe catching up process in Czech Republic, Hungary, and Poland is analyzed by investigating the integration properties of log-differences in per-capita GDP versus the EU15 and a Mediterranean country group. We account for structural changes by using unit root tests that allow for two endogenous breaks in the level and the trend. We find that Czech Republic and Hungary are stochastically converging towards the Mediterranean group, while only Czech Republic is stochastically converging towards EU15. Remaining per capita GDP differences are only reduced by deterministic trends. Extrapolating these trends we find that catching up will take about 20 years.
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Bibliographic InfoPaper provided by Sonderforschungsbereich 649, Humboldt University, Berlin, Germany in its series SFB 649 Discussion Papers with number SFB649DP2005-014.
Length: 9 pages
Date of creation: Mar 2005
Date of revision:
Stochastic convergence; Catching up; Unit root tests; EU accession;
Other versions of this item:
- Ralf Bruggemann & Carsten Trenkler, 2007. "Are Eastern European Countries Catching Up? Time Series Evidence for Czech Republic, Hungary and Poland," Applied Economics Letters, Taylor and Francis Journals, vol. 14(4), pages 245-249.
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
- E24 - Macroeconomics and Monetary Economics - - Macroeconomics: Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution
This paper has been announced in the following NEP Reports:
- NEP-ALL-2005-10-29 (All new papers)
- NEP-EEC-2005-10-29 (European Economics)
- NEP-MAC-2005-10-29 (Macroeconomics)
- NEP-TRA-2005-10-29 (Transition Economics)
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- Sigbert Klinke & Uwe Ziegenhagen & Yuval Guri, 2005. "Yxilon – a Modular Open-Source Statistical Programming Language," SFB 649 Discussion Papers SFB649DP2005-018, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
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