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Cited by 1,407

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Pseudo Maximum Likelihood Methods: Theory

Open access
Gourieroux, C., Monfort, A., Trognon, A.·1984·Econometrica
DOI 10.2307/1913471
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Abstract

Estimators obtained by maximizing a likelihood function are studied in the case where the true p.d.f. does not necessarily belong to the family chosen for the likelihood function. When such a procedure is applied to the estimation of the parameters of the first order moments, it is possible to prove a necessary and sufficient condition for its consistency. Asymptotic normality is shown as well as the existence of a lower bound for the asymptotic covariance matrix. It is also seen that this bound can be reached if consistent estimates are available for the parameters of the second order moments. Finally, a necessary and sufficient condition for the consistency if the pseudo maximum likelihood estimation of the first and second moments is given.

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Metadata

Authors
Gourieroux, C., Monfort, A., & Trognon, A.
Venue
Econometrica
Publisher
JSTOR
Published
1984-05
Volume
52
Issue
3
Pages
681
ISSN
0012-9682 (ISSN-L)
DOI
10.2307/1913471
OpenAlex
W2070047061
Cited by
1,407
References
0
FWCI
12.86
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Pseudo Maximum Likelihood Methods: Theory. https://app.cochat.ai/papers/10.2307/1913471
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Gourieroux, C., Monfort, A., & Trognon, A. (1984). Pseudo Maximum Likelihood Methods: Theory. Econometrica. https://doi.org/10.2307/1913471

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.