An Empirical Likelihood-based Local Estimation1
نویسنده
چکیده
This paper considers a modified empirical likelihood and uses it to estimate models with imperfect moment restrictions. Consistency, local normality and asymptotic optimality of the new estimator only require the local identifiability and the linear-quadratic representation. In imperfect situations, classical sandwich algorithms give bias estimations while the new estimator preserves its asymptotic properties. We consider two imperfect cases that are unbounded moment restrictions and weakly identified moment restrictions.
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