The Distributional Financial Accounts of the United States
This paper describes the construction of the Distributional Financial Accounts (DFA), a dataset containing quarterly estimates of the distribution of U.S. household wealth since 1989. The DFA builds on two existing Federal Reserve Board statistical products --- quarterly aggregate measures of household wealth from the Financial Accounts of the United States, and triennial wealth distribution measures from the Survey of Consumer Finances --- to incorporate distributional information into a national accounting framework. The DFA complements other sources by generating distributional statistics that are consistent with macro aggregates by providing quarterly data on a timely basis, and by constructing wealth distributions across demographic characteristics. We encourage policymakers, researchers, and other interested parties to use the DFA to better understand issues related to the distribution of U.S. household wealth.
The analysis and conclusions set forth here are those of the authors and do not indicate concurrence by other members of the research staff, the Board of Governors, or the Federal Reserve System. This project reflects the combined efforts of the Flow of Funds and Microeconomic Survey sections at the Federal Reserve Board. Sarah Reber provided outstanding research assistance. We are grateful to Marco Cagetti, Karen Pence, and Paul Smith for providing outstanding guidance and supervision of this project, as well as numerous edits to this paper's text. We also thank Kevin Moore, Jeff Thompson, Molly Shatto, Elizabeth Holmquist, Susan McIntosh, and Tom Sweeney for work on the DFA project from which this paper derives. In addition, we also thank seminar participants at the Federal Reserve Board and the NBER Conference on Research in Income and Wealth, in particular Bill Gale, for their useful feedback and suggestions. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.