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Testing linearity against smooth transition autoregression using a parametric bootstrap

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  • Skalin, Joakim

    ()
    (Dept for Economic Affairs, Ministry of Finance)

Abstract

When testing the null hypothesis of linearity of a univariate time series against smooth transition autoregression (STAR), standard asymptotic distribution results do not apply since nuisance parameters in the model are unidentified under the null hypothesis. The prevailing test of Luukkonen, Saikkonen and Teräsvirta (1988) is based on a linearization, which may adversely affect its power. This paper discusses an alternative procedure, based on a parametric bootstrap of a likelihood ratio test statistic, and investigates its size and power properties by a small simulation study. The results, however, indicate that the power of the bootstrap test is inferior to that of the existing test.

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Bibliographic Info

Paper provided by Stockholm School of Economics in its series Working Paper Series in Economics and Finance with number 276.

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Length: 8 pages
Date of creation: 28 Oct 1998
Date of revision: 13 Dec 1998
Handle: RePEc:hhs:hastef:0276

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Keywords: Linearity testing; smooth transition autoregression model; nuisance parameter; nonstandard testing problem; bootstrap test;

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Cited by:
  1. 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.
  2. Sarno, Lucio, 2001. "The behavior of US public debt: a nonlinear perspective," Economics Letters, Elsevier, vol. 74(1), pages 119-125, December.
  3. Sofiane Amri, 2008. "Analysing the forward premium anomaly using a Logistic Smooth Transition Regression model," Economics Bulletin, AccessEcon, vol. 6(26), pages 1-18.
  4. Lucio Sarno & Giorgio Valente & Hyginus Leon, 2006. "Nonlinearity in Deviations from Uncovered Interest Parity: An Explanation of the Forward Bias Puzzle," Review of Finance, European Finance Association, vol. 10(3), pages 443-482, September.
  5. Sarno, Lucio & Thornton, Daniel L., 2003. "The dynamic relationship between the federal funds rate and the Treasury bill rate: An empirical investigation," Journal of Banking & Finance, Elsevier, vol. 27(6), pages 1079-1110, June.
  6. Strohsal, Till & Weber, Enzo, 2013. "Identifying Volatility Signals from Time-Varying Simultaneous Stock Market Interaction," Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79903, Verein für Socialpolitik / German Economic Association.
  7. Taylor, Mark P & Peel, David A & Sarno, Lucio, 2001. "Nonlinear Mean-Reversion in Real Exchange Rates: Toward a Solution to the Purchasing Power Parity Puzzles," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 42(4), pages 1015-42, November.
  8. Jonathan B. Hill, 2004. "Consistent Model Specification Tests Against Smooth Transition Alternatives," Econometrics 0402004, EconWPA, revised 01 Mar 2004.
  9. Jonathan B. Hill, 2004. "Consistent LM-Tests for Linearity Against Compound Smooth Transition Alternatives," Econometric Society 2004 North American Summer Meetings 42, Econometric Society.
  10. repec:ebl:ecbull:v:6:y:2008:i:26:p:1-18 is not listed on IDEAS
  11. Matthew T. Holt & Joseph V. Balagtas, 2009. "Estimating Structural Change with Smooth Transition Regressions: An Application to Meat Demand," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 91(5), pages 1424-1431.
  12. Jonathan B. Hill, 2004. "LM-Tests for Linearity Against Smooth Transition Alternatives: A Bootstrap Simulation Study," Working Papers 0412, Florida International University, Department of Economics.
  13. Coakley, Jerry & Fuertes, Ana-Maria, 2006. "Testing for sign and amplitude asymmetries using threshold autoregressions," Journal of Economic Dynamics and Control, Elsevier, vol. 30(4), pages 623-654, April.
  14. Weber, Enzo, 2009. "Financial Contagion, Vulnerability and Information Flow: Empirical Identification," University of Regensburg Working Papers in Business, Economics and Management Information Systems 431, University of Regensburg, Department of Economics.
  15. Till Strohsal & Enzo Weber, 2012. "The Signal of Volatility," SFB 649 Discussion Papers SFB649DP2012-043, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

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