wild cluster bootstrapSummary We provide computationally attractive methods to obtain jackknife‐based cluster‐robust variance matrix estimators (CRVEs) for linear regression models estimated by least squares.
(2022), "Fast and reliable jackknife and bootstrap methods for cluster-robust inference,"QED Working Paper No. 1485. Sasaki, Yuya and Yulong Wang (2022), "Non-Robustness of the Cluster-Robust Inference: with a Proposal of a New Robust Method,"arXiv:2210.16991v1. T with Di¤erent Degrees...
Basics of cluster-robust inference 2.2 Cluster-robust variance matrix estimate 2.2 Cluster-robust variance matrix for OLS Linear model for G clusters with Ng individuals per cluster yig = xi0g β + uig , i = 1, ..., Ng , g = 1, ..., G , N = ∑Gg =1 Ng yg = Xg0 β + ...
goes well this provides valid statistical inference, as well as estimates of the parameters of the original regression model that are more e cient than OLS. However, these desirable properties hold only under the very strong assumption that the model for within-cluster error correlation is correctly...
1 A Practitioner’s Guide to Cluster-Robust Inference A. Colin Cameron and Douglas L. Miller Abstract We consider statistical inference for regression when data are grouped into clusters, with regression model errors independent across clusters but correlated within clusters. Examples include data on ...
C. A. Cameron, J. B. Gelbach, and D. L. Miller. Robust inference with multiway clustering. NBER Working Paper, T0327, 2006. URL http://.nber/ papers/t0327. 5 M. A. Petersen. Estimating standard errors in finance panel data sets: Compar-...
McLachlan, G.J. and Basford, K.E. (1988).Mixture Models: Inference and Applications to Clustering. New York: Marcel Dekker. Google Scholar McLachlan, G.J. and Krishnan, T. (1997).The EM Algorithm and Extensions. New York: Wiley. ...
(2009). The elements of statistical learning: data mining, inference, and prediction. Springer Science & Business Media. Henderson, C., & Dancy, M. H. (2007). Barriers to the use of research-based instructional strategies: The influence of both individual and situational characteristics. ...
The approach consisted of an improved fuzzy clustering algorithm accompanied by a stage to identify the structure and an inference stage that does not involve parameter estimation. Baser and Demirhan [28] developed the Fuzzy Regression Function with SVM (FRF-SVM) approach by applying SVMs using ...
In this article I develop a wild bootstrap procedure for cluster-robust inference in linear quantile regression models. I show that the bootstrap leads to asymptotically valid inference on the entire quantile regression process in a setting with a large number of small, heterogeneous clusters and ...