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Mixing properties of the dynamic Tobit model with mixing errors

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  • Michel, Jon
  • de Jong, Robert M.

Abstract

Mixing properties for the dynamic Tobit model are shown for the case of mixing innovations. We show α or β-mixing given mixing assumptions on the errors. Additionally, we show that the results here hold for a more general class of nonlinear time series for which the dynamic Tobit model is a special case.

Suggested Citation

  • Michel, Jon & de Jong, Robert M., 2018. "Mixing properties of the dynamic Tobit model with mixing errors," Economics Letters, Elsevier, vol. 162(C), pages 112-115.
    • Handle: RePEc:eee:ecolet:v:162:y:2018:i:c:p:112-115
    DOI: 10.1016/j.econlet.2017.11.008
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    References listed on IDEAS

    as
    1. de Jong, Robert M. & Woutersen, Tiemen, 2011. "Dynamic Time Series Binary Choice," Econometric Theory, Cambridge University Press, vol. 27(4), pages 673-702, August.
    2. Robert Jong & Ana María Herrera, 2011. "Dynamic Censored Regression and the Open Market Desk Reaction Function," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(2), pages 228-237, April.
    3. Hahn, Jinyong & Kuersteiner, Guido, 2010. "Stationarity and mixing properties of the dynamic Tobit model," Economics Letters, Elsevier, vol. 107(2), pages 105-111, May.
    4. Hahn, Jinyong & Kuersteiner, Guido, 2011. "Bias Reduction For Dynamic Nonlinear Panel Models With Fixed Effects," Econometric Theory, Cambridge University Press, vol. 27(6), pages 1152-1191, December.
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    Cited by:

    1. Michel, Jon & de Jong, Robert M., 2019. "A model for level induced conditional heteroskedasticity," Statistics & Probability Letters, Elsevier, vol. 145(C), pages 293-300.
    2. Anna Bykhovskaya & James A. Duffy, 2022. "The Local to Unity Dynamic Tobit Model," Papers 2210.02599, arXiv.org, revised Feb 2023.

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    More about this item

    Keywords

    Dynamic Tobit model; Mixing;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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