Top Income Adjustments and Inequality: An Investigation of the EU‐SILC^†

Abstract

In this paper we bridge the gap between two different approaches to measure inequality: one based on household surveys and summary measures such as the Gini, and the other focused on taxable income and top income shares. We explore how these approaches adjust the Gini for equivalised household income in 26 European countries over . On average, the Gini increases by around 2.4 points as a result of the WID adjustment, for both gross and disposable income, with notable differences across countries, affecting rankings, despite limited impact on trends. We find that differences in inequality depend less on the adjustment method and more on whether it relies on external data sources such as tax data. In fact, SILC countries that rely on administrative register data experience relatively small changes in inequality after the WID adjustment. For recent years, we find that the Gini for 'non-register' countries increases by 2.8 points on average while in 'register' countries it does so by 0.9 points. We conclude by proposing ways in which household surveys can improve their representativeness of income and living conditions. 2003-2017 using the EU-SILC, focusing on the World Inequality Database (WID) adjustment as proposed in

Automation and Income Inequality in Europe

“…Ravallion, 2022) and are therefore difficult to include reliably in our empirical analysis. Reassuringly, however, Carranza et al (2023) show that trends in income inequality over time are not overly influenced by whether or not top income households are accurately represented.…”

Wealth Inequality in Latin America

“…As they stand, administrative records and household wealth surveys serve different but complementary purposes. However, more research should look into combining the two to get adjusted survey estimates, much in the way the income literature has done so (see, e.g., Blanchet et al (2022); Carranza et al (2022)).…”

Determinants of individual income in EU countries: implications for social policy targeting

“…Similarly, Krell et al (2017) state that extremely important for international social science research and policy advice on inequality. Carranza et al (2022) use the Gini coefficient calculated from EU-SILC data to measure income inequality. However, they indicate that the Gini coefficient needs adjustments and they suggest that a more comprehensive inclusion of administrative income data should be a priority for European income statistics.…”