A New Instrument to Measure Wealth Inequality: Distributional Wealth Accounts. Kennickell, A. B., Lindner, P., & Schürz, M. Monetary Policy & the Economy, January, 2022. ![A New Instrument to Measure Wealth Inequality: Distributional Wealth Accounts [pdf]](https://bibbase.org/img/filetypes/pdf.svg "pdf")
Link abstract bibtex In this study we investigate the sensitivity of different wealth measurement approaches. In this context, we analyze the alignment of Household Finance and Consumption Survey (HFCS) data with national accounts data and examine the production of distributional wealth accounts, which poses severe conceptual challenges. For a number of reasons, household surveys underestimate top wealth shares. We show that different assumptions generate a wide range of results for different wealth inequality indicators. In particular, the share of the top 1% of households in net wealth ranges from about 25% to about 50%, depending on the underlying assumption. Thus, while the true value of the wealth share held by the top 1% is unknown, all available information indicates that it is closer to 50% than to HFCS results. We call for caution in interpreting top shares as the underlying assumptions are mostly ad hoc choices made by data producers. Our study argues that we need better microdata on the top end of the net wealth distribution.
@article{Kennickelletal2022,
title = {A New Instrument to Measure Wealth Inequality: Distributional Wealth Accounts},
author = {Kennickell, Arthur B. and Lindner, Peter and Sch{\"u}rz, Martin},
year = {2022},
month = jan,
journal = {Monetary Policy \& the Economy},
volume = {Q4/21},
url = {https://www.oenb.at/dam/jcr:37664c81-2d0d-409e-8d33-a19fc2b25854/05_mop_q4_21_A-new-instrument-to-measure-wealth-inequality.pdf},
urldate = {2022-02-23},
abstract = {In this study we investigate the sensitivity of different wealth measurement approaches. In this context, we analyze the alignment of Household Finance and Consumption Survey (HFCS) data with national accounts data and examine the production of distributional wealth accounts, which poses severe conceptual challenges. For a number of reasons, household surveys underestimate top wealth shares. We show that different assumptions generate a wide range of results for different wealth inequality indicators. In particular, the share of the top 1\% of households in net wealth ranges from about 25\% to about 50\%, depending on the underlying assumption. Thus, while the true value of the wealth share held by the top 1\% is unknown, all available information indicates that it is closer to 50\% than to HFCS results. We call for caution in interpreting top shares as the underlying assumptions are mostly ad hoc choices made by data producers. Our study argues that we need better microdata on the top end of the net wealth distribution.},
keywords = {Methods of Estimation of Wealth Inequality}
}
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