Model selection and model averaging are two important techniques to obtain practical and useful models in applied research. However, it is now well-known that many complex issues arise, especially in the context of model selection, when the stochastic nature of the selection process is ignored...

Abstract This paper describes a targeted maximum likelihood estimator (TMLE) for the parameters of longitudinal static and dynamic marginal structural models. We consider a longitudinal data structure consisting of baseline covariates, time-dependent intervention nodes, intermediate...

Abstract The notion that an independent central bank reduces a country’s inflation is a controversial hypothesis. To date, it has not been possible to satisfactorily answer this question because the complex macroeconomic structure that gives rise to the data has not been adequately...

We discuss the impact of tuning parameter selection uncertainty in the context of shrinkage estimation and propose a methodology to account for problems arising from this issue: Transferring established concepts from model averaging to shrinkage estimation yields the concept of shrinkage...

This paper studies the extent of discrimination against mainland Chinese immigrants in the Hong Kong labour market and provides a quantitative assessment of the source of wage differentials between local born Hong Kong residents and Chinese immigrants. Using the 2001 Hong Kong Population Census...