Kock, Anders Bredahl; Callot, Laurent A.F. - School of Economics and Management, University of Aarhus - 2012
We show that the adaptive Lasso (aLasso) and the adaptive group Lasso (agLasso) are oracle efficient in stationary vector autoregressions where the number of parameters per equation is smaller than the number of observations. In particular, this means that the parameters are estimated...