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Testing for threshold effect in ARFIMA models: Application to US unemployment rate data

  • Lahiani, A.
  • Scaillet, O.

Macroeconomic time series often involve a threshold effect in their ARMA representation, and exhibit long memory features. In this paper we introduce a new class of threshold ARFIMA models to account for this. The threshold effect is introduced in the autoregressive and/or fractional integration parameters, and can be tested for using LM tests. Monte Carlo experiments show the desirable finite sample size and the power of the test with an exact maximum likelihood estimator of the long memory parameter. Simulations also show that a model selection strategy is available to discriminate between the competing threshold ARFIMA models. The methodology is applied to US unemployment rate data, where we find a significant threshold effect in the ARFIMA representation, and a better forecasting performance relative to TAR and symmetric ARFIMA models.

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

Volume (Year): 25 (2009)
Issue (Month): 2 ()
Pages: 418-428

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Handle: RePEc:eee:intfor:v:25:y:2009:i:2:p:418-428
Contact details of provider: Web page: http://www.elsevier.com/locate/ijforecast

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  1. Geetesh Bhardwaj & Norman Swanson, 2004. "An Empirical Investigation of the Usefulness of ARFIMA Models for Predicting Macroeconomic and Financial Time Series," Departmental Working Papers 200422, Rutgers University, Department of Economics.
  2. 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.
  3. McCracken, Michael W., 2007. "Asymptotics for out of sample tests of Granger causality," Journal of Econometrics, Elsevier, vol. 140(2), pages 719-752, October.
  4. Francis X. Diebold & Atsushi Inoue, 2000. "Long Memory and Regime Switching," NBER Technical Working Papers 0264, National Bureau of Economic Research, Inc.
  5. repec:cup:cbooks:9780521779654 is not listed on IDEAS
  6. Sowell, Fallaw, 1992. "Maximum likelihood estimation of stationary univariate fractionally integrated time series models," Journal of Econometrics, Elsevier, vol. 53(1-3), pages 165-188.
  7. Hidalgo, Javier & Robinson, Peter M., 1996. "Testing for structural change in a long-memory environment," Journal of Econometrics, Elsevier, vol. 70(1), pages 159-174, January.
  8. Andersson, Michael K. & Eklund, Bruno & Lyhagen, Johan, 1999. "A simple linear time series model with misleading nonlinear properties," Economics Letters, Elsevier, vol. 65(3), pages 281-284, December.
  9. 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.
  10. repec:cup:cbooks:9780521770415 is not listed on IDEAS
  11. Hansen, Bruce E, 1996. "Inference When a Nuisance Parameter Is Not Identified under the Null Hypothesis," Econometrica, Econometric Society, vol. 64(2), pages 413-30, March.
  12. Benoit Bellone & David Saint-Martin, 2004. "Detecting Turning Points with Many Predictors through Hidden Markov Models," Econometrics 0407001, EconWPA.
  13. Donald W.K. Andrews & Werner Ploberger, 1992. "Optimal Tests When a Nuisance Parameter Is Present Only Under the Alternative," Cowles Foundation Discussion Papers 1015, Cowles Foundation for Research in Economics, Yale University.
  14. Lo, Andrew W, 1991. "Long-Term Memory in Stock Market Prices," Econometrica, Econometric Society, vol. 59(5), pages 1279-313, September.
  15. Guay, Alain & Scaillet, Olivier, 2003. "Indirect Inference, Nuisance Parameter, and Threshold Moving Average Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(1), pages 122-32, January.
  16. Philip Rothman, . "Forecasting Asymmetric Unemployment Rates," Working Papers 9618, East Carolina University, Department of Economics.
  17. Anas, Jacques & Ferrara, Laurent, 2002. "Un indicateur d'entrée et sortie de récession: application aux Etats-Unis
    [A start-end recession index: Application for United-States]
    ," MPRA Paper 4043, University Library of Munich, Germany.
  18. Alain Guay & Olivier Scaillet, 1999. "Indirect Inference, Nuisance Parameter and Threshold Moving Average," Cahiers de recherche CREFE / CREFE Working Papers 95, CREFE, Université du Québec à Montréal.
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