A nonlinear long memory model for US unemployment
Dick van Dijk (),
Philip Hans Franses and
No EI 2000-30/A, Econometric Institute Research Papers from Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute
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.
Keywords: fractional integration; smooth transition autoregression; time series model specification (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:ems:eureir:1660
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