Missing data is a very frequent obstacle in many social science studies. The absence of values on one or more variables can signi?cantly affect statistical analyses by reducing their precision and by introducing selection biases. Being unable to account for these aspects may result in severe...

This paper introduces the Luxembourg Household Finance and Consumption Survey (LU-HFCS), presents its background and aim, the field phase, the data treatment, including editing, imputation, and anonymisation, and some basic descriptive findings. The estimated average (median) total net wealth of...