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Does a non-linear mean reverting process characterize real GDP movements?

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Abstract

This paper uses non-linear models to investigate non-stationarity of real GDP per capita for seven OECD countries over the period 1900–2000. Unit root tests based on non-linear models are more powerful than traditional ADF statistics in rejecting the null unit root hypothesis. Empirical results show that, contrary to what the linear ADF statistics suggest, stationarity characterizes five out of the seven countries. This finding stands at variance with other recent studies which conclude that movements in real GDP per capita can be characterized as a non-stationary process.

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Notes

  1. Since only the magnitude of the change in the deviation matters and not the sign, I consider the absolute value of change as the switching variable. Therefore I treat π 1 and π 2 symmetrically so that \(\pi _{2} = 1 - \pi _{1}\) \(\lambda _{1} = - \lambda _{2} = \lambda\). This makes my TAR a two-regime symmetric model.

  2. In a recent paper Blake and Kapetanios (2003) consider a unit root test based on a neural network pure significance test, thus avoiding the specification of an alternative hypothesis. An anonymous referee has suggested this to me.

  3. In fact the null hypothesis (8) tests whether μ* and r* lie in area oebf of Fig. 1.

  4. The data can be downloaded from the Maddison web site. http://www.eco.rug.nl/˜Maddison/

References

  • Blake AP, and Kapetanios G (2003) Pure significance tests of the unit root hypothesis against nonlinear alternatives. J Time Ser Anal 24:253–267

    Article  MATH  MathSciNet  Google Scholar 

  • Caner M, Hansen BE (2001) Threshold autoregression with a unit root. Econometrica 69:1565–1596

    Article  MathSciNet  Google Scholar 

  • Cheung Y-W, Chinn MD (1996) Deterministic, stochastic, and segmented trends in aggregate output: a cross-country analysis. Oxford Economic Papers 48:134–162

    Google Scholar 

  • David BD, Lumsdiane RL, Papell DH (2003) Unit roots, postwar slowdown and long run growth: evidence from two structural breaks. Empir Econ 28:303–319

    Article  Google Scholar 

  • Enders W, Granger CWJ (1998) Unit root tests and asymmetric adjustment with an example using the term structure of interest rates. Journal of Business of Economic and Statistics 16:304–312

    Article  Google Scholar 

  • Enders W, Ludlow J (2002) Non-linear decay: Tests for an attractor using Fourier approximation. The University of Alabama, Economics, Finance and Legal Studies, Working Paper Series WP01-02-02

  • He C, Sandberg R (2003) A Dickey-Fuller type of test against non-linear globally stationary dynamic models. Working Paper, Department of Economic Statistics, Stockholm School of Economics

  • Kapetanios G, Shin Y, and Snell A (2003) Testing for a unit root in the non-linear STAR framework. J Econom 112:359–379

    Article  MATH  MathSciNet  Google Scholar 

  • Ludlow J, Enders W (2000) Estimating non-linear ARMA models using Fourier coefficients. Int J Forecast 16:333–347

    Article  Google Scholar 

  • Maddison A (1995) Monitoring the world economy 1820–1992. OECD Development Centre, Paris

    Google Scholar 

  • Nelson CR, Plosser CI (1982) Trends and random walks in macro-economic time series. J Monet Econ 10:139–162

    Article  Google Scholar 

  • Rapach DE (2002) Are real GDP levels nonstationary? Evidence from panel data sets. Sout Econ J 68:73–495

    Article  Google Scholar 

  • Shin DW, and Lee O (2001) Test for asymmetry in possibly nonstationary time series data. Journal of Business and Economic Statistics 19:233–244

    Article  MathSciNet  Google Scholar 

  • Thangavelu S, and James ABJ (2004) Financial development and economic growth in Australia: An empirical analysis. Empir Econ 29:247–260

    Article  Google Scholar 

  • Wasserfallen W (1986) Non-stationarities in macro-economic-time series—further evidence and implications. Can J Econ 19:498–510

    Article  Google Scholar 

Download references

Acknowledgements

Thanks go to three anonymous referees for extremely detailed and useful comments on a previous version of this paper. Thanks are also due to M.León-Ledesma for providing helpful computational assistance with Gauss code. The usual disclaimer applies to any remaining errors or omissions.

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  1. Department of Economic and Regional Development, Panteion University, Leof. Syngrou 136, 17671, Athens, Greece

    Dimitris K. Christopoulos

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Correspondence to Dimitris K. Christopoulos.

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Christopoulos, D.K. Does a non-linear mean reverting process characterize real GDP movements?. Empirical Economics 31, 601–611 (2006). https://doi.org/10.1007/s00181-005-0034-5

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