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A time deformation model and its time-varying autocorrelation: An application to US unemployment data

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  • Vijverberg, Chu-Ping C.
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    Abstract

    A G-Lambda model is characterized by a constant mean, a finite variance and a covariance that is a function of both time and lags. The Box-Cox transformation of the time scale transforms a non-stationary G-Lambda model into a stationary model. This paper explores the time-varying behavior of the G-Lambda model. Simulation results indicate that it is possible to distinguish between the G-Lambda model and other better-known models such as the ARIMA, ARFIMA and STAR models. Applying the model to US unemployment data, the performance of the G-Lambda model varies as the start of the forecast periods changes. However, the results of the sign test and the Diebold-Mariano test indicate that the G-Lambda model has significantly better long-term forecasts than other models.

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    Bibliographic Info

    Article provided by Elsevier in its journal International Journal of Forecasting.

    Volume (Year): 25 (2009)
    Issue (Month): 1 ()
    Pages: 128-145

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    Handle: RePEc:eee:intfor:v:25:y:2009:i:1:p:128-145

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    Web page: http://www.elsevier.com/locate/ijforecast

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    1. Diebold, Francis X & Mariano, Roberto S, 1995. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 253-63, July.
    2. Blanchard, Olivier J. & Summers, Lawrence H., 1987. "Hysteresis in unemployment," European Economic Review, Elsevier, vol. 31(1-2), pages 288-295.
    3. Terasvirta, Timo & van Dijk, Dick & Medeiros, Marcelo C., 2005. "Linear models, smooth transition autoregressions, and neural networks for forecasting macroeconomic time series: A re-examination," International Journal of Forecasting, Elsevier, vol. 21(4), pages 755-774.
    4. Olivier J. Blanchard & Lawrence H. Summers, 1986. "Hysteresis and the European Unemployment Problem," Working papers 427, Massachusetts Institute of Technology (MIT), Department of Economics.
    5. repec:att:wimass:9710 is not listed on IDEAS
    6. West, Kenneth D & McCracken, Michael W, 1998. "Regression-Based Tests of Predictive Ability," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 817-40, November.
    7. Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June.
    8. van Dijk, Dick & Franses, Philip Hans & Paap, Richard, 2002. "A nonlinear long memory model, with an application to US unemployment," Journal of Econometrics, Elsevier, vol. 110(2), pages 135-165, October.
    9. Chu-Ping C. Vijverberg, 2006. "Time Deformation, Continuous Euler Processes and Forecasting," Journal of Time Series Analysis, Wiley Blackwell, vol. 27(6), pages 811-829, November.
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