Lining Up: Survey and Administrative Data Estimates of Wealth Concentration
Arthur B. Kennickell
No 2017-017, Finance and Economics Discussion Series from Board of Governors of the Federal Reserve System (U.S.)
Abstract:
The Survey of Consumer Finances (SCF) has a dual-frame sample design that supplements a standard area-probability frame with a sample of observations drawn from statistical records derived from tax returns. The tax-based frame is stratified on the basis of a \"wealth index\" constructed largely from observed income flows, with the intent of heavily oversampling wealthy households. Although the SCF is not specifically designed to estimate wealth concentration, the design arguably provides sufficient support to enable such analysis with a reasonable level of credibility. Similar estimates may also be made by using tax-based data directly, as in [1], by using a construct very close to a key part of the SCF wealth index. Such an approach has appeal as a way of tapping a much larger set of information to improve SCF estimates. Not surprisingly, there are differences in the two approaches, largely as a result of conceptual differences or complications in the survey implementation. This paper focuses on the top 1 percent of the wealth distribution, the group most intensively covered by the SCF list sample and it explores the stability of the relationship between the patterns of concentration in the survey data and parallel patterns in tax-based estimates and considers how those patterns differ across survey participants, the full sample and the entire survey frame. In addition, the paper makes as series of recommendation for further research on the technical support of the survey.
Keywords: Nonresponse; Oversampling; Sampling; Skewed distributions; Wealth measurement (search for similar items in EconPapers)
JEL-codes: C83 D31 (search for similar items in EconPapers)
Pages: 72 pages
Date: 2017-02
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Citations: View citations in EconPapers (10)
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Persistent link: https://EconPapers.repec.org/RePEc:fip:fedgfe:2017-17
DOI: 10.17016/FEDS.2017.017
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