Generalized method of moments with many weak moment conditions

By Whitney K. Newey, F. Windmeijer. 2009

252 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/cd992c9572f02443eb0a74435cb96e0f698737c0

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Citations in the corpus

Can ESG Indices Improve the Enterprises’ Stock Market Performance?—An Empirical Study from China (2019, methodology): “Therefore, the validation of the analysis is ensured, and it can also help to alleviate potential biases in estimators and the corresponding standard errors [31,32].”
Robust Inference for Consumption‐Based Asset Pricing (2019, unknown): “This “limited T versus large N” problem is not accounted for in standard asymptotic approximations of t and Wald statistics (Bekker (1994), Newey and Windmeijer (2009)) and thus provides a second argument for why researchers cannot rely on standard t/Wald-tests to conduct dependable statistical…”
Robust Standard Errors in Transformed Likelihood Estimation of Dynamic Panel Data Models (2015, unknown): “Although Newey and Windmeijer (2009) prove the validity of these tests under many weak moments asymptotics, they are essentially imposing m 2 /N → 0 or a stronger restriction where m is the number of moment conditions, which is unlikely to hold when N is small and/or T is large.”
Redistribution, inequality, and growth: new evidence (2018, background): “One approach to address the potential weak instrument problem is provided by Newey and Windmeijer (2009).”
How to Deal With Reverse Causality Using Panel Data? Recommendations for Researchers Based on a Simulation Study (2019, background): “In addition, AB estimators show poor finite-sample performance (Newey and Windmeijer 2009) and require a large number of sampled units (Moral-Benito, Allison, and Williams 2018).”
Weak Instrument Robust Tests in GMM and the New Keynesian Phillips Curve (2009, background): “…the number of instruments is not too large relative to the sample size, the identification robust statistics remain size-correct in the instrumental variables regression model with many weak instruments, while Newey and Windmeijer (2009) obtained a similar result for the KLM statistic in GMM.”
Empirical Evidence on Inflation Expectations in the New Keynesian Phillips Curve (2014, background): “A recent contribution by Newey and Windmeijer (2009) demonstrates some robustness properties of the weak identification robust methods to many weak instruments.”
Choosing instrumental variables in conditional moment restriction models (2009, methodology): “This fact simplifies considerably the instrument choice criteria and was also noted in Newey and Windmeijer (2009).”
A review of instrumental variable estimators for Mendelian randomization (2015, background): “A variance estimator for a generalized empirical likelihood approach with good coverage properties has also been developed.(48) These intervals give appropriate confidence levels under the null hypothesis with weak instruments but may be underpowered with stronger instruments.”