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A nonlinear long memory model for US unemployment

Author

Listed:
  • van Dijk, D.J.C.
  • Franses, Ph.H.B.F.
  • Paap, R.

Abstract

Two important empirical features of monthly US unemployment are that shocks to the series seem rather persistent and that unemployment seems to rise faster in recessions than that it falls during expansions. To jointly capture these features of long memory and nonlinearity, respectively, we put forward a new time series model and evaluate its empirical performance. We find that the model describes the data rather well and that it outperforms related competitive models on various measures of fit.

Suggested Citation

  • van Dijk, D.J.C. & Franses, Ph.H.B.F. & Paap, R., 2000. "A nonlinear long memory model for US unemployment," Econometric Institute Research Papers EI 2000-30/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    • Handle: RePEc:ems:eureir:1660
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    Cited by:

    1. Guglielmo Maria Caporale & Luis A. Gil‐Alana, 2007. "Nonlinearities and Fractional Integration in the US Unemployment Rate," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 69(4), pages 521-544, August.

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