THE MOVING BLOCKS BOOTSTRAP FOR PANEL LINEAR REGRESSION MODELS WITH INDIVIDUAL FIXED EFFECTS

By Sílvia Gonçalves. Econometric Theory, 2011

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Asymptotic theory and wild bootstrap inference with clustered errors (2019, background): “6) assumes equal-sized, homogeneous (same variance) clusters, and Hansen (2007) assumes equal-sized, heterogeneous clusters.”
Heteroskedasticity, autocorrelation, and spatial correlation robust inference in linear panel models with fixed-effects (2012, background): “(6)Simulations reported by Gonçalves (2011) suggest that the moving blocks bootstrap can further reduce the over-rejection problem of tHACSC , relative to using xed-b critical values, when the serial correlation is strong.”
Should we go one step further? An accurate comparison of one-step and two-step procedures in a generalized method of moments framework (2018, background): “…Sun, Phillips and Jin (2008), Sun and Phillips (2009), Gonçlaves and Vogelsang (2011), and Zhang and Shao (2013) in the time series setting; Bester, Conley, Hansen and Vogelsang (2014) in the spatial setting; and Gonçalves (2011), Kim and Sun (2013), and Vogelsang (2012) in the panel data setting.”
Fitting Vast Dimensional Time-Varying Covariance Models (2020, background): “A similar assumption has also appeared in the recent paper by Gonçalves (2011). This is a high-level, yet intuitively reasonable assumption.”