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Testing Parameter Constancy in Unit Root Autoregressive Models Against Continuous Change

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  • He, Changli

    ()
    (Dept. of Economic Statistics, Stockholm School of Economics)

  • Sandberg, Rickard

    ()
    (Dept. of Economic Statistics, Stockholm School of Economics)

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    Abstract

    In this paper we derive tests for parameter constancy when the data generating process is non-stationary against the hypothesis that the parameters of the model change smoothly over time. To obtain the asymptotic distributions of the tests we generalize many theoretical results, as well as new are introduced, in the area of unit roots. The results are derived under the assumption that the error term is a strong mixing. Small sample properties of the tests are investigated, and in particular, the power performances are satisfactory.

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    File URL: http://swopec.hhs.se/hastef/papers/hastef0579.pdf
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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 579.

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    Length: 26 pages
    Date of creation: 21 Jan 2005
    Date of revision: 08 Feb 2005
    Handle: RePEc:hhs:hastef:0579

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    Related research

    Keywords: Parameter constancy; LSTAR; Unit root; Brownian; motion; Strong mixing;

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    References

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    1. James H. Stock & Mark W. Watson, 1994. "Evidence on Structural Instability in Macroeconomic Time Series Relations," NBER Technical Working Papers, National Bureau of Economic Research, Inc 0164, National Bureau of Economic Research, Inc.
    2. Phillips, P.C.B., 1986. "Testing for a Unit Root in Time Series Regression," Cahiers de recherche, Universite de Montreal, Departement de sciences economiques 8633, Universite de Montreal, Departement de sciences economiques.
    3. Lin, Chien-Fu Jeff & Terasvirta, Timo, 1994. "Testing the constancy of regression parameters against continuous structural change," Journal of Econometrics, Elsevier, Elsevier, vol. 62(2), pages 211-228, June.
    4. Phillips, P C B, 1987. "Time Series Regression with a Unit Root," Econometrica, Econometric Society, Econometric Society, vol. 55(2), pages 277-301, March.
    5. Andrews, Donald W K, 1993. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Econometrica, Econometric Society, Econometric Society, vol. 61(4), pages 821-56, July.
    6. John Y. Campbell & Pierre Perron, 1991. "Pitfalls and Opportunities: What Macroeconomists Should Know About Unit Roots," NBER Chapters, National Bureau of Economic Research, Inc, in: NBER Macroeconomics Annual 1991, Volume 6, pages 141-220 National Bureau of Economic Research, Inc.
    7. Wooldridge, Jeffrey M. & White, Halbert, 1988. "Some Invariance Principles and Central Limit Theorems for Dependent Heterogeneous Processes," Econometric Theory, Cambridge University Press, Cambridge University Press, vol. 4(02), pages 210-230, August.
    8. G. William Schwert, 1988. "Tests For Unit Roots: A Monte Carlo Investigation," NBER Technical Working Papers, National Bureau of Economic Research, Inc 0073, National Bureau of Economic Research, Inc.
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    Citations

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    Cited by:
    1. He, Changli & Sandberg, Rickard, 2005. "Inference for Unit Roots in a Panel Smooth Transition Autoregressive Model where the Time Dimension is Fixed," Working Paper Series in Economics and Finance, Stockholm School of Economics 581, Stockholm School of Economics, revised 18 Feb 2005.
    2. He, Changli & Sandberg, Rickard, 2005. "Dickey-Fuller Type of Tests against Nonlinear Dynamic Models," Working Paper Series in Economics and Finance, Stockholm School of Economics 580, Stockholm School of Economics.
    3. Li, Dao & He, Changli, 2012. "Testing for Linear Cointegration Against Smooth-Transition Cointegration," Working Papers, Örebro University, School of Business 2012:6, Örebro University, School of Business.
    4. He, Changli & Sandberg, Rickard, 2005. "Testing for Unit Roots in Nonlinear Dynamic Heterogeneous Panels," Working Paper Series in Economics and Finance, Stockholm School of Economics 582, Stockholm School of Economics.

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