In this thesis, we address the macro-economic problem that aggregated micro data from the Household Finance and Consumption Survey (HFCS) of the ECB does not match the macro data from national accounts (NtlA) statistics. Earlier studies have already identified that extremely wealthy households are generally underrepresented in household surveys. In Chapter 2, we present a method proposed by Vermeulen ([22]) to overcome this underrepresentation of very rich households. He suggests to combine the HFCS data with rich lists, enabling an estimation of the upper part of the wealth distribution via a Pareto distribution. After estimating this distribution, it is possible to sample further households of the upper part of the wealth distribution. To justify this method we additionally provide an overview of some wealth accumulation processes that lead to a Pareto distribution for wealth in the long term. Though some parts of the discrepancies between HFCS and NtlA statistics are explained by the missing wealthy, Chakraborty and Waltl ([5]) find that large parts are still unexplained. Therefore, we provide a solution to close the persisting gaps via an optimization problem that aims at preserving the level of inequality. Finally, we compare the findings with an approach that uses a multivariate calibration via a small case study covering household wealth of Germany.      «

In this thesis, we address the macro-economic problem that aggregated micro data from the Household Finance and Consumption Survey (HFCS) of the ECB does not match the macro data from national accounts (NtlA) statistics. Earlier studies have already identified that extremely wealthy households are generally underrepresented in household surveys. In Chapter 2, we present a method proposed by Vermeulen ([22]) to overcome this underrepresentation of very rich households. He suggests to combin...     »