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Functional-coefficient models under unit root behaviour

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  • Ted Juhl
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    Abstract

    We analyze the statistical properties of non-parametrically estimated functions in a functional-coefficient model if the data have a unit root. We show that the estimated function converges at a faster rate than under the stationary case. However, the estimator has a mixed normal distribution so that point-wise confidence intervals are calculated using the usual normal distribution theory rather than a Dickey--Fuller distribution. The results are used to show how one can discriminate between a unit root process and a non-linear functional-coefficient process. We illustrate the procedure using U.S. unemployment and interest rate data. Copyright 2005 Royal Economic Society

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    File URL: http://www.blackwell-synergy.com/doi/abs/10.1111/j.1368-423X.2005.00160.x
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    Bibliographic Info

    Article provided by Royal Economic Society in its journal The Econometrics Journal.

    Volume (Year): 8 (2005)
    Issue (Month): 2 (07)
    Pages: 197-213

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    Handle: RePEc:ect:emjrnl:v:8:y:2005:i:2:p:197-213

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    Cited by:
    1. Gan, Li & Hsiao, Cheng & Xu, Shu, 2014. "Model specification test with correlated but not cointegrated variables," Journal of Econometrics, Elsevier, vol. 178(P1), pages 80-85.
    2. repec:wyi:wpaper:002008 is not listed on IDEAS
    3. repec:wyi:wpaper:001966 is not listed on IDEAS
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    5. repec:wyi:journl:002112 is not listed on IDEAS
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    7. repec:wyi:journl:002195 is not listed on IDEAS
    8. repec:wyi:wpaper:002020 is not listed on IDEAS

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