Inference with dependent data using cluster covariance estimators

By C. Bester, Timothy G. Conley, Christian Hansen. 2011

286 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/ffe5d676e36f386b436b2ec1dd4ee3c4288b36d1

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Citations in the corpus

Cluster-Robust Bootstrap Inference in Quantile Regression Models (2014, background): “The over-rejection could, in principle, be avoided by replacing standard normal and chisquare critical values with larger critical values from the Student tn−1 and similarly scaled F distributions (Donald and Lang 2007; Bester et al. 2011).”
Asymptotic theory for clustered samples (2019, unknown): “Hence we prefer the assumptions (5)-(8).”
Inference with Few Heterogeneous Clusters (2016, methodology): “…Monte Carlo simulations that under homogeneous clusters (Γi ≈ Γj and Ψi ≈ Ψj for all i, j), this procedure works well even for fairly small q. Alternatively, Bester et al. (2011) (BCH in the following) suggest relying on tcluster with a critical value from a Studentt with q − 1 degrees of freedom.”
Large Panels with Common Factors and Spatial Correlation (2011, methodology): “Recently, non-parametric methods based on heteroskedasticity and autocorrelation consistent estimators applied to spatial models have also been proposed (Conley (1999); Kelejian and Prucha (2007); Bester, Conley, and Hansen (2009)).”
Randomization Tests Under an Approximate Symmetry Assumption (2017, methodology): “By replacing the time index t with a vector index, as in Bester et al. (2011), we can accommodate more complicated dependence structures, such as those found in spatially dependent data or in panel data.”
Regression Analysis of Country Effects Using Multilevel Data: A Cautionary Tale (2013, methodology): “Recent studies have indicated that a simple rescaling of the cluster-robust standard errors, and the use of critical values from the t-distribution, may deliver reliable test results (Bester et al 2011, Brewer et al 2013).”
“Rugged individualism” and collective (in)action during the COVID-19 pandemic (2020, methodology): “In all regressions, we cluster standard errors based on an arbitrary grid-cell approach that allows for correlated unobservables across all counties within 60 miles (Bester et al., 2011).”
Estimating peer effects in networks with peer encouragement designs (2016, background): “Proc Natl Acad Sci USA 96(8): 4730–4734.”
Let's Fix It: Fixed-b Asymptotics versus Small-b Asymptotics in Heteroskedasticity and Autocorrelation Robust Inference (2010, unknown): “where ût is a plug-in estimator of ut given by ût = R(̂T ) GT (̂T )WTGT (̂T ) 1 GT (̂T )WT f(vt; ̂T ); (4) k ( ) is a kernel function, and kb (x) = k (x=b) for x 2 [ 1; 1]: Here b is the smoothing parameter that a¤ects the asymptotic properties of ̂T and the associated test statistic.”