Abstract
AbstractSurvey 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.
Highlights
Survey under-coverage of top incomes leads to bias in survey-based estimates of overall income inequality
We consider a pioneering variant of this approach long employed in the UK official income distribution statistics, assess its strengths and weaknesses for measuring income inequality, and discuss the extent to which the approach might be applied in other countries
Atkinson et al highlight various problems with surveys, stating that ‘such problems affect the top income ranges’ (2011: 29). They illustrate their argument by showing how estimates of the share of total income held by the top 1% derived from the US Current Population Survey (CPS) fall below the estimates derived from Internal Revenue Service Survey of Income (IRS-SOI) personal tax return data, even after the CPS estimates have been adjusted upwards by Burkhauser et al (2012) to account for their top-coding: ‘CPS data that do not measure top incomes fail to capture about half of [the] increase in overall inequality’ between 1976 and 2006 (Atkinson et al 2011: 32)
Summary
Survey under-coverage of top incomes leads to bias in survey-based estimates of overall income inequality. The under-coverage problem has been highlighted by OECD economists interested in cross-national inequality comparisons as well as national trends: On the one hand, inequality figures drawn from household surveys measure income dispersion on a comprehensive and representative portion of the population, but are not able to capture top incomes. It is in this portion of the distribution that most of the changes in inequality seem to have occurred over the last fifteen years.
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