Balanced sampling is a very efficient sampling design when the variable of interest is correlated to the auxiliary variables on which the sample is balanced. A procedure to select balanced samples in a stratified population has previously been proposed. Unfortunately, this procedure becomes very...

We consider how to incorporate auxiliary information to improve quantile regression via empirical likelihood. We propose a novel framework and show that our approach yields more efficient estimates compared to those from the conventional quantile regression. The efficiency gain is quantified...

Many datasets used by economists and other social scientists are collected by stratified sampling. The sampling scheme used to collect the data induces a probability distribution on the observed sample that differs from the target or underlying distribution for which inference is to be made. If...

A growing body of literature is emerging on empirical likelihood methods for complex surveys. These works largely focus on the population mean. We propose a weighted empirical likelihood approach as a method of inference for quantiles under stratified random sampling, which is one of the most...

The labour force surveys (LFSs) on all Eurostat countries underwent a substantial redesign in January 2021. To ensure coherent labour market time series for the main indicators in the Norwegian LFS, we model the impact of the redesign. We use a state-space model that takes explicit account of...

The labour force surveys (LFSs) on all Eurostat countries underwent a substantial redesign in January 2021. To ensure coherent labour market time series for the main indicators in the Norwegian LFS, we model the impact of the redesign. We use a state-space model that takes explicit account of...