“…Then, the SWIID routine estimates the relationships between Gini indices based on the LIS and all of the other Ginis available for the same country‐years, and it uses these relationships to estimate what the LIS Gini would be in country‐years not included in the LIS but available from other sources. This approach has made the SWIID a preferred source of income inequality data for researchers pursuing broadly cross‐national work across a wide range of disciplines, including not only economics (e.g., Berg et al., 2018; Darvas, 2019; Palma, 2019), political science (e.g., Dorsch and Maarek, 2019; Iversen and Soskice, 2019; Engler and Weisstanner, 2020), and sociology (e.g., Steele, 2016; Dawson, 2018; Jaime‐Castillo and Marqués‐Perales, 2019) but also fields such as public health (e.g., Ngamaba, 2016; Alvarez and El‐Sayed, 2017) and psychology (e.g., Blake et al., 2018; Schmukle, Korndörfer, and Egloff, 2019).…”