Macroeconomic aggregates on households' wealth have a long tradition and are widely used to analyse and compare economies, yet they do not provide any information about the distribution of assets and liabilities within the population. The Household Finance and Consumption Survey (HFCS) constitutes a rich source of micro data that can be used to link macro aggregates with distributional information to compile Distributional National Accounts for wealth. Computing aggregates from this survey usually yields much lower amounts than what is reported by macroeconomic statistics. An important source of this gap may be the lack of the wealthiest households in the HFCS. This article combines a semi-parametric Pareto model estimated from survey data and observations from rich lists with a stratification approach making use of HFCS portfolio structures to quantify the impact of the missing wealthy households on instrument-specific gaps between micro and macro data. We analyse data for Austria and Germany, and find that adjusting for the missing wealthy pushes up inequality even further, increases instrument-specific aggregates, has large effects on equity, but explains less than ten percentage points of the micro-macro gap for most other instruments. Additionally, we document that some countries' lack of an oversampling strategy for wealthy households limits the cross-country comparability of wealth inequality statistics.
Distributional National Accounts (DINA) National Accounts HFCS Micro-Macro Comparison Semi-parametric Pareto Model for Wealth Wealth distribution