Monitoring Euro Area Real Exchange Rates

  • Philipp Aschersleben
  • Martin WagnerEmail author
  • Dominik Wied
Conference paper
Part of the Springer Proceedings in Mathematics & Statistics book series (PROMS, volume 122)


We apply the stationarity and cointegration monitoring procedure of Wagner and Wied in (Monitoring stationarity and cointegration. SFB823 Discussion Paper 23/14., 2014) to monthly real exchange rate indices, vis-\(\grave{a}\)-vis Germany, of the first round Euro area member states. For all countries except Portugal structural breaks are detected prior to the onset of the Euro area crisis triggered in turn by the global financial crisis. The results indicate that a more detailed investigation of RER behavior in the Euro area may be useful for understanding the unfolding of the deep crisis currently plaguing many countries in the Euro area.


Euro Area Real Exchange Rate Purchase Power Parity Calibration Period Nominal Exchange Rate 
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Financial support from Deutsche Forschungsgemeinschaft via the Collaborative Research Center 823: Statistical Modelling of Nonlinear Dynamic Processes (Projects A1, A3 and A4) is gratefully acknowledged. The second author additionally acknowledges financial support from the Jubiläumfonds of the Oesterreichische Nationalbank (Grant No. 15334). The authors furthermore thank two anonymous referees for valuable suggestions.


  1. 1.
    Chu C-SJ, Stinchcombe M, White H (1996) Monitoring structural change. Econometrica 64:1045–1065 CrossRefzbMATHGoogle Scholar
  2. 2.
  3. 3.
    Kwiatkowski D, Phillips PCB, Schmidt P, Shin Y (1992) Testing the null hypothesis of stationarity against the alternative of a unit root. J Econ 54:159–178 CrossRefzbMATHGoogle Scholar
  4. 4.
    OECD (10 Sep 2014) Main economic indicators. Cited 10 Sep 2014
  5. 5.
    Phillips PCB, Hansen BE (1990) Statistical inference in instrumental variables regression with I(1) processes. Rev Econ Stud 57:99–125 MathSciNetCrossRefzbMATHGoogle Scholar
  6. 6.
    Saikkonen P (1991) Asymptotically efficient estimation of cointegrating regressions. Econom Theory 7:1–21 MathSciNetCrossRefzbMATHGoogle Scholar
  7. 7.
    Vogelsang TJ, Wagner M (2014) Integrated modified OLS estimation and fixed-b inference for cointegrating regressions. J Econ 178:741–760 MathSciNetCrossRefGoogle Scholar
  8. 8.
    Wagner M (2005) The Balassa–Samuelson effect in “East & West”: differences and similarities. Rev Econ 56:230–248 Google Scholar
  9. 9.
    Wagner M (2008) On PPP, unit roots and panels. Empir Econ 35:229–249 CrossRefGoogle Scholar
  10. 10.
    Wagner M, Wied D (2014) Monitoring stationarity and cointegration. SFB823 discussion paper 23/14.

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Philipp Aschersleben
    • 1
  • Martin Wagner
    • 1
    Email author
  • Dominik Wied
    • 1
  1. 1.Faculty of StatisticsTechnical University DortmundDortmundGermany

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