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Robust estimators for simultaneous equations models

Authors
Journal
Journal of Econometrics
0304-4076
Publisher
Elsevier
Publication Date
Volume
78
Issue
2
Identifiers
DOI: 10.1016/s0304-4076(96)00014-0
Keywords
  • Robustness
  • Influence Function
  • M-Estimators
  • Reduced Form
  • Structural Form
  • Nonlinear Simultaneous Equations
  • Full Information Maximum Likelihood
Disciplines
  • Mathematics

Abstract

Abstract This paper presents a class of robust estimators for linear and non-linear simultaneous equations models, which are a direct generalization of the maximum likelihood estimator. The new estimators are obtained as solutions of a generalized likelihood equation. They are resistant to deviations from the model distribution, to outlying observations, and to some model misspecifications. An optimality principle leads to the construction of an optimal robust estimator which is the best trade-off between efficiency at the model and robustness.

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