Working Paper: NBER ID: w23539
Authors: Richard V. Burkhauser; Nicolas Hrault; Stephen P. Jenkins; Roger Wilkins
Abstract: 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.
Keywords: income inequality; SPI adjustment; survey undercoverage; tax data
JEL Codes: C81; D31
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| survey undercoverage of top incomes (D31) | biased estimates of overall income inequality (D31) |
| tax data (H20) | accurate representation of high-income earners (D33) |
| SPI adjustment (E63) | accuracy of income distribution (D31) |
| SPI adjustment (E63) | higher estimates of income inequality (D31) |
| higher estimates of income inequality (D31) | higher Gini coefficient in adjusted series (D31) |
| SPI adjustment (E63) | reduces volatility in inequality measures (D31) |