Arbeitspapier
Survey Under-Coverage of Top Incomes and Estimation of Inequality: What Is the Role of the UK's SPI Adjustment?
Survey under-coverage of top incomes leads to bias in survey-based estimates of overall income inequality. Using income tax record data in combination with survey data is a potential approach to address the problem; we consider here the UK's pioneering 'SPI adjustment' method that implements this idea. Since 1992, the principal income distribution series (reported annually in Households Below Average Income) has been based on household survey data in which the incomes of a small number of 'very rich' individuals are adjusted using information from 'very rich' individuals in personal income tax return data. We explain what the procedure involves, reveal the extent to which it addresses survey under-coverage of top incomes, and show how it affects estimates of overall income inequality. More generally, we assess whether the SPI adjustment is fit for purpose and consider whether variants of it could be employed by other countries.
- Language
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Englisch
- Bibliographic citation
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Series: IZA Discussion Papers ; No. 10868
- Classification
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Wirtschaft
Personal Income, Wealth, and Their Distributions
Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
- Subject
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inequality
income inequality
survey under-coverage
SPI adjustment
top incomes
tax return data
survey data
- Event
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Geistige Schöpfung
- (who)
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Burkhauser, Richard V.
Hérault, Nicolas
Jenkins, Stephen P.
Wilkins, Roger
- Event
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Veröffentlichung
- (who)
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Institute of Labor Economics (IZA)
- (where)
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Bonn
- (when)
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2017
- Handle
- Last update
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10.03.2025, 11:45 AM CET
Data provider
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Arbeitspapier
Associated
- Burkhauser, Richard V.
- Hérault, Nicolas
- Jenkins, Stephen P.
- Wilkins, Roger
- Institute of Labor Economics (IZA)
Time of origin
- 2017