Rubin & Schenker (1986) proposed the approximate Bayesian bootstrap, a two-stage resampling procedure, as a method of creating multiple imputations when missing data are ignorable. Kim (2002) showed ...
This is a preview. Log in through your library . Abstract This paper considers the issue of bootstrap resampling in panel data sets. The availability of data sets with large temporal and ...
Bootstrap procedures for local projections typically rely on assuming that the data generating process (DGP) is a finite order vector autoregression (VAR), often taken to be that implied by the local ...
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