We study the behaviour of the information matrix (IM) test when maximum likelihood estimators are replaced with robust estimators. The latter may unmask outliers and hence improve the power of the test. We investigate in detail the local asymptotic power of the IM test in the normal model, for...

We propose to use multilevel discrete-time hazard models to assess the impact of societal and individual level covariates on the timing and occurrence of third births. We focus mainly on the impact of educational attainment on third births across 15 European countries. From the analysis in this...

The presence of outlying observations in panel data can affect the classical estimates in a dramatic way. Nevertheless, the common practice seems to disregard the problem. The aim of this work is to study robust regression techniques in the fixed effects linear panel data framework. Robustness...

Factor construction methods are widely used to summarize a large panel of variables by means of a relatively small number of representative factors. We propose a novel factor construction procedure that enjoys the properties of robustness to outliers and of sparsity; that is, having relatively...

Quadratic covariation is a popular descriptive measure for the volatility of a multivariate price process. It is consistently estimated by the sum of outer products of high-frequency returns. The proposed realized outlyingness weighted covariation (ROWCov) is a weighted sum of outer products of...