I focus on one of the most-commonly-cited 'facts'; about UK income inequality - that it has changed little over the last 30 years - and reflect on how robust that description is. I look at a number of fundamental issues in inequality measurement related to inequality concepts (e.g., inequality...

The generalized entropy class of inequality indices is derived for Generalized Beta of the Second Kind (GB2) income distributions, thereby providing a full range of top-sensitive and bottom-sensitive measures. An examination of British income inequality in 1994/95 and 2004/05 illustrates the...

Ibragimov, Kattuman, and Skrobotov (Econometric Reviews, 2025) propose a "t-statistic" approach to inference for inequality indices building on results provided by Ibragimov and Müller (Journal of Business & Economic Statistics, 2010), and they and Midões and de Crombrugghe (Journal of...

Because finite sample inference for inequality indices based on asymptotic methods or the standard bootstrap does not perform well, Davidson and Flachaire (Journal of Econometrics, 2007) and Cowell and Flachaire (Journal of Econometrics, 2007) proposed inference based on semiparametric methods...

The techniques of simple random sampling are seldom appropriate in the empirical analysis of income distributions. Various types of weighting schemes are usually required either from the point of view of welfare-economic considerations (the mapping of household/family distributions into...

The generalized entropy class of inequality indices is derived for Generalized Beta of the Second Kind (GB2) income distributions, thereby providing a full range of top-sensitive and bottom-sensitive measures. An examination of British income inequality in 1994/95 and 2004/05 illustrates the...

To measure income inequality with right censored (topcoded) data, we propose multiple imputation for censored observations using draws from Generalized Beta of the Second Kind distributions to provide partially synthetic datasets analyzed using complete data methods. Estimation and inference...