Simple and powerful GMM over-identification tests with accurate size

DOI10.1016/J.JECONOM.2011.09.039zbMath1441.62881OpenAlexW2112262946MaRDI QIDQ738121

Yixiao Sun, Min Seong Kim

Publication date: 15 August 2016

Published in: Journal of Econometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jeconom.2011.09.039

zbMATH Keywords

long-run varianceover-identification testrobust standard error\(F\)-distributionheteroscedasticity and autocorrelation robustseries estimator

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10)

Related Items (10)

Fixed-smoothing asymptotics in the generalized empirical likelihood estimation framework ⋮ The cross-quantilogram: measuring quantile dependence and testing directional predictability between time series ⋮ An asymptotically F-distributed Chow test in the presence of heteroscedasticity and autocorrelation ⋮ SIMPLE, ROBUST, AND ACCURATEFANDtTESTS IN COINTEGRATED SYSTEMS ⋮ Heteroskedasticity and spatiotemporal dependence robust inference for linear panel models with fixed effects ⋮ Testing over-identifying restrictions without consistent estimation of the asymptotic covariance matrix ⋮ Sieve semiparametric two-step GMM under weak dependence ⋮ Asymptotic \(F\) and \(t\) tests in an efficient GMM setting ⋮ A simple and trustworthy asymptotic \(t\) test in difference-in-differences regressions ⋮ Simple and trustworthy cluster-robust GMM inference

Uses Software

• sapa

Cites Work

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• HAC ESTIMATION BY AUTOMATED REGRESSION

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