Estimation bias and bias correction in reduced rank autoregressions
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DOI: 10.1080/07474938.2017.1308065
Abstract: ABSTRACT This paper characterizes the finite-sample bias of the maximum likelihood estimator (MLE) in a reduced rank vector autoregression and suggests two simulation-based bias corrections. One is a simple bootstrap implementation that approximates the bias… read more here.
Keywords: reduced rank; bias bias; correction reduced; bias correction ... See more keywords