GMM, GEL, Serial Correlation, and Asymptotic Bias
By Stanislav Anatolyev. 2005
113 citations recorded by the source corpus.
Subfields: Economics and Econometrics, Management Science and Operations Research, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/abf27f1c35818ed1b20f0ebcf2ae4a21f11dd9a8
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Economics and Econometrics
- Songxi Chen
- Jinyuan Chang
- Xiaohong Chen
- A. Hall
- Andrew J. Patton
- Demian Pouzo
- Timothy M. Christensen
- H. Manner
In Management Science and Operations Research
In Statistics and Probability
- Jinyuan Chang
- Songxi Chen
- Xiaohong Chen
- A. Hall
- M. D. Cattaneo
- Andrew J. Patton
- Demian Pouzo
- Andrés Santos
Citations in the corpus
- Generalized Method of Moments (2005, background): “However, Newey and Smith (2004) and Anatolyev (2005) demonstrate analytically that the continuous-updating estimator can be expected to exhibit lower finite sample bias than its two-step counterpart.”
- High dimensional generalized empirical likelihood for moment restrictions with dependent data (2013, methodology): “ation errors of the GMM estimator were much larger than those of the GEL estimators, which confirmed the existing research on GMM versus GEL for finite fixed dimensional settings (Newey and Smith, 2004; Anatolyev, 2005). Among the three GEL estimators, we observed that while they were largely similar u”
- GEL CRITERIA FOR MOMENT CONDITION MODELS (2011, unknown): “Anatolyev (2005) provides the asymptotic bias expression counterparts for GMM and GEL for weakly dependent data to those in NS. Given these encouraging findings for the GEL class of estimators, a primary aim of this paper is to synthesize and extend this class of estimators to weakly dependent data.”