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Maximum likelihood estimation of misspecified models. (English) Zbl 0478.62088
Econometrica 50, 1-25 (1982); correction ibid. 51, 513 (1983).
Author’s summary: This paper examines the consequences and detection of model misspecification when using maximum likelihood techniques for estimation and inference. The quasi-maximum likelihood estimator (QMLE) converges to a well defined limit, and may or may not be consistent for particular parameters of interest. Standard tests (Wald, Lagrange Multiplier, or Likelihood Ratio) are invalid in the presence of misspecification, but more general statistics are given which allow inferences to be drawn robustly. The properties of the QMLE and the information matrix are exploited to yield several useful tests for model misspecification.
Reviewer: Jochen Schwarze

MSC:
62P20 Applications of statistics to economics
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