In this paper we establish the consistency of the model selection criterion based on the quasi-marginal likelihood obtained from Laplace-type estimators (LTE). We consider cases in which parameters are strongly identified, weakly identified and partially identified. Our Monte Carlo results...

In high-dimensional factor models, both the factor loadings and the number of factors may change over time. This paper proposes a shrinkage estimator that detects and disentangles these instabilities. The new method simultaneously and consistently estimates the number of pre- and post-break...

Confidence sets based on sparse estimators are shown to be large compared to more standard confidence sets, demonstrating that sparsity of an estimator comes at a substantial price in terms of the quality of the estimator. The results are set in a general parametric or semiparametric framework.