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Finite Underidentification

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I adapt the Generalised Method of Moments to deal with nonlinear models in which a finite number of isolated parameter values satisfy the moment conditions. To do so, I initially study the closely related limiting class of first-order underidentified models, whose expected Jacobian is rank deficient but not necessarily 0. In both cases, the proposed procedures yield efficiency gains and underidentification tests within a standard asymptotic framework. I study models with and without separation of data and parameters. Finally, I illustrate the proposed inference procedures with a dynamic panel data model and a non-linear regression model for discrete data.

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  • Enrique Sentana, 2015. "Finite Underidentification," Working Papers wp2015_1508, CEMFI.
    • Handle: RePEc:cmf:wpaper:wp2015_1508
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    1. Dovonon, Prosper & Hall, Alastair R., 2018. "The asymptotic properties of GMM and indirect inference under second-order identification," Journal of Econometrics, Elsevier, vol. 205(1), pages 76-111.
    2. Ackerberg, Daniel A. & Frazer, Garth & Kim, Kyoo il & Luo, Yao & Su, Yingjun, 2023. "Under-identification of structural models based on timing and information set assumptions," Journal of Econometrics, Elsevier, vol. 237(1).

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    Keywords

    Finite set; Generalised Method of Moments; Identification test.;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General

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