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Robust Semiparametric Estimation in the Presence of Heterogeneity of Unknown Form

Author

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  • Hodgson, D.J.

Abstract

We show that semiparametric adaptive maximum likelihood estimators have desirable robustness properties when the innivations in a location parameter model are uncorrelated but not necessarily independent. We show that such estimators have asymptotic covariance matrices equal to the inverse of the Fisher information of the unconditional distribution of the data in the presence of general forms of heterogeneity, including conditional dependence in even moments.

Suggested Citation

  • Hodgson, D.J., 1996. "Robust Semiparametric Estimation in the Presence of Heterogeneity of Unknown Form," RCER Working Papers 416, University of Rochester - Center for Economic Research (RCER).
    • Handle: RePEc:roc:rocher:416
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    Cited by:

    1. Hodgson, Douglas J., 1998. "Adaptive estimation of cointegrating regressions with ARMA errors," Journal of Econometrics, Elsevier, vol. 85(2), pages 231-267, August.

    More about this item

    Keywords

    TIME SERIES ; MODELS;

    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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