ON THE ASYMPTOTIC EFFICIENCY OF GMM

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Efficiently Breaking the Curse of Horizon in Off-Policy Evaluation with Double Reinforcement Learning (2019, methodology): “Another approach is to use a sieve GMM estimator, using a basis expansion for fw(s) (Carrasco and Florens, 2014; Hahn, 1997).”
A regularization approach to the many instruments problem (2012, methodology): “Such an estimator is investigated by Chaussé (2009). The GMM estimator is also implementable in a time-series context as shown in Carrasco et al.”
Efficiently Breaking the Curse of Horizon: Double Reinforcement Learning in Infinite-Horizon Processes (2019, methodology): “Another approach is to use a sieve GMM estimator, using a basis expansion for fw(s) (Carrasco and Florens, 2014; Hahn, 1997).”