literature, this estimator is consistent, asymptotically normal and very stable across partitions of the sample. Further, we show … in an extensive simulation study that this estimator outperforms in finite samples the logs, blocks and runs estimation … methods. Finally, we apply this new estimator to test for clustering of extremes in monthly time series of unemployment growth …

Allowing for misspecification in the linear conditional quantile function, this paper provides a new interpretation and …–Bassett estimator minimizes a weighted distribution approximation error, defined as F Y (X ′ β(τ)|X)−τ , i.e., the deviation of the … conditional distribution function, evaluated at the linear quantile approximation, from the quantile level. The second result …

The asymptotic distribution of the linear instrumental variables (IV) estimator with empirically selected ridge … characteristics of the sampling distributions and when this ridge estimator performs better than two-stage least squares. An empirical …

. The maximum likelihood estimator in the irregular case usually has a rate of convergence slower than the √n-rate in a … to select the involved tuning parameter. We show that the penalized maximum likelihood estimator has the oracle … properties. The method can implement model selection and estimation simultaneously and the estimator always has the usual √n …