Robust Semiparametric Estimation in the Presence of Heterogeneity of Unknown Form
AbstractWe 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.
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Bibliographic InfoPaper provided by University of Rochester - Center for Economic Research (RCER) in its series RCER Working Papers with number 416.
Length: 37 pages
Date of creation: 1996
Date of revision:
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Postal: University of Rochester, Center for Economic Research, Department of Economics, Harkness 231 Rochester, New York 14627 U.S.A.
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- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
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- Hodgson, Douglas J., 1998.
"Adaptive estimation of cointegrating regressions with ARMA errors,"
Journal of Econometrics,
Elsevier, vol. 85(2), pages 231-267, August.
- Hodgson, D.J., 1995. "Adaptive Estimation of Cointegrating Regressions with ARMA Errors," RCER Working Papers 408, University of Rochester - Center for Economic Research (RCER).
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