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A nonlinear long memory model for US unemployment Author info | Abstract | Publisher info | Download info | Related research | Statistics D.J.C. Van Dijk ()
P.H. Franses ()
R. Paap () (FEW-Econometrie en besliskunde)
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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.
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Paper provided by Erasmus University Rotterdam, Econometric Institute in its series Econometric Institute Report with number
204.
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Date of creation: 2000Date of revision:
Handle: RePEc:dgr:eureir:2000204Contact details of provider: Web page: http://www.few.eur.nl/few
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Keywords: fractional integration smooth transition autoregression time series model specification ; Other versions of this item:
Find related papers by JEL classification: C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation and Testing E24 - Macroeconomics and Monetary Economics - - Macroeconomics: Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
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