A Practical Asymptotic Variance Estimator for Two-Step Semiparametric Estimators
By Daniel A. Ackerberg, Xiaohong Chen, Jinyong Hahn. Review of Economics and Statistics, 2012
94 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/8fcf0f518243111d21fb56ac3e909015593c82dc
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Whitney K. Newey
- Hidehiko Ichimura
- Xiaohong Chen
- Yulia V. Marchenko
- C. Cattaneo
- Marc G. Genton
- Samuel Bazzi
- Barry Reilly
In Statistics and Probability
- Hidehiko Ichimura
- Whitney K. Newey
- Xiaohong Chen
- Arthur Lewbel
- Stefan Wager
- Guido W. Imbens
- Victor Chernozhukov
- Susan Athey
Citations in the corpus
- Locally Robust Semiparametric Estimation (2016, unknown): “Ackerberg et al. (2014) also gave an expression for the FSIF for functionals of conditional quantiles other than the weighted average derivative.”
- The influence function of semiparametric estimators (2015, methodology): “Ai and Chen (2007, 2012), Ichimura and Lee (2010), Ackerberg et al. (2014), Chen and Liao (2015), and Chen and Pouzo (2015) gave interesting and useful characterizations of influence functions for estimators with first steps that solve conditional moment restrictions or that are maximizers of an obj”
- Asymptotic E¢ ciency of Semiparametric Two-step GMM (2012, unknown): “…g(Zi; ; eh), we can speculate that the optimal limited information procedure would now take the form of GMM, where the weight matrix converges in probability to the inverse of the asymptotic variance of n 1=2 Pn i=1 g(Zi; o; eh), which is the basis of proposal by Ackerberg, Chen, and Hahn (2012).”