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The purpose of this paper is to study its relative asymptotic efficiency relationship with respect to quasi-limited information maximum likelihood estimator (QLIML) and two-step control function (CF) approach.
First, it is shown that MD estimator is asymptotically efficient relative to two other estimators.
Transformation of sieve elements into generalized Mundlak form is considered to make sparsity assumption more plausible in some cases.
The empirical application to birth weight analysis demonstrates a convincing case where the proposed estimator works as intended in real data.
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Second, based upon an analogous result of Crepon, Kramarz and Trognon (1997), it is proved that concentration of reduced form equation estimates does not affect asymptotic efficiency of structural parameter estimates in MD estimation.
Third, in a class of model, if and only if condition for MD and other estimators to be asymptotically equivalent under the null hypothesis of exogeneity is derived.
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