Corpus ID: 209444414

Efficient and Convergent Sequential Pseudo-Likelihood Estimation of Dynamic Discrete Games

@article{Dearing2019EfficientAC,
  title={Efficient and Convergent Sequential Pseudo-Likelihood Estimation of Dynamic Discrete Games},
  author={Adam Dearing and Jason R. Blevins},
  journal={arXiv: Econometrics},
  year={2019}
}
We propose a new sequential Efficient Pseudo-Likelihood (EPL) estimator for structural economic models with an equality constraint, particularly dynamic discrete choice games of incomplete information. Each iteration in the EPL sequence is consistent and asymptotically efficient, and iterating to convergence improves finite sample performance. For dynamic single-agent models, we show that Aguirregabiria and Mira's (2002, 2007) Nested Pseudo-Likelihood (NPL) estimator arises as a special case of… Expand
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