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Weak Identification in Discrete Choice Models
We study the impact of weak identification in discrete choice models, and provide insights into the determinants of identification strength in these models.
Approximate Maximum Likelihood for Complex Structural Models
This new approach is based on using a constrained approximation to the structural model, which ensures identification and can deliver estimators that are nearly efficient.
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