high dimensional by construction and sparse by assumption, is estimated using the Lasso. We apply this method to the …

units ("donors pool") using shrinkage methods, such as the Least Absolute Shrinkage Operator (LASSO). In the second stage …

-Sampling approach (U-MIDAS) (see Foroni et al., 2015; Castle et al., 2009; Bec and Mogliani, 2013), and the LASSO-type penalised …

In this paper we show the validity of the adaptive LASSO procedure in estimating stationary ARDL(p,q) models with GARCH … innovations. We show that, given a set of initial weights, the adaptive Lasso selects the relevant variables with probability … variables beforehand. Finally, we show that the LASSO estimator can be used to construct the initial weights. The performance of …

We study the asymptotic properties of the Adaptive LASSO (adaLASSO) in sparse, high-dimensional, linear time …

) and studies the properties of the Lasso and adaptive Lasso as estimators of this model. The parameters of the model are … finite sample properties of the Lasso by deriving upper bounds on the estimation and prediction errors that are valid with … of non zero increments grows slower than √T . By simulation experiments we investigate the properties of the Lasso and …