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Consistent Pseudo-Maximum Likelihood Estimators

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  • Christian Gouriéroux

    (CREST, University of Toronto)

  • Alain Monfort

    (CREST)

  • Eric Renault

    (Brown University)

Abstract

This paper provides an updated survey of the literature on consistent pseudo maximum likelihood (PML) estimators. We emphasize the role of the white noise assumptions on the set of pseudo distributions leading to consistent estimators. Stronger these assumptions, larger the set of consistent PML estimators. We also illustrate the importance of these PML approaches in big data environment. The development of the literature on PML estimators would not have been so e cient without the modern proof of consistency of extremum estimators introduced at the end of the sixties by Jennrich and Malinvaud. We also discuss this proof and replace it in an historical perspective.

Suggested Citation

  • Christian Gouriéroux & Alain Monfort & Eric Renault, 2016. "Consistent Pseudo-Maximum Likelihood Estimators," Working Papers 2016-33, Center for Research in Economics and Statistics.
    • Handle: RePEc:crs:wpaper:2016-33
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    References listed on IDEAS

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    Cited by:

    1. Gouriéroux, Christian & Monfort, Alain & Zakoian, Jean-Michel, 2017. "Pseudo-Maximum Likelihood and Lie Groups of Linear Transformations," MPRA Paper 79623, University Library of Munich, Germany.
    2. Moreno Bevilacqua & Christian Caamaño‐Carrillo & Reinaldo B. Arellano‐Valle & Víctor Morales‐Oñate, 2021. "Non‐Gaussian geostatistical modeling using (skew) t processes," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 48(1), pages 212-245, March.

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    More about this item

    Keywords

    Pseudo-Likelihood; Composite Pseudo-Likelihood; Consistency; Big Data; ARCH Model; Normalized Data; Lie Group.;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis

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