In the machine learning community, the Gini index is a very popular score for model selection, and it is also used in actuarial science for evaluating insurance pricing models. The purpose of this tutorial is to discuss the Gini index, both its version in economics and its version in machine...

In explaining wage or income by personal attributes (e.g. educational attainment, age, and ethnicity) in a regression model, many researchers choose to use the log of wage or income as the dependent variable and then to estimate the unknown coefficients by some version of the least-squares...

Most equivalence scales which are applied in research on poverty and inequality do not depend on income, although there is strong empirical evidence that equivalence scales in fact are income dependent. This paper explores the consistency of results derived from income independent and income...

Program evaluations often focus on average treatment effects. However, average treatment effects miss important aspects of policy evaluation, such as the impact on inequality and whether treatment harms some individuals. A growing literature develops methods to evaluate such issues by examining...

Recentered influence functions (RIFs) are statistical tools popularized by Firpo, Fortin, and Lemieux (2009) for analyzing unconditional partial effects on quantiles in a regression analysis framework (unconditional quantile regressions). The flexibility and simplicity of these tools has opened...

This paper discusses various methods for assessing group differences in academic achievement using only the ordinal content of achievement test scores. Researchers and policymakers frequently draw conclusions about achievement differences between various populations using methods that rely on...

Recentered influence functions (RIFs) are statistical tools popularized by Firpo, Fortin, and Lemieux (2009) for analyzing unconditional partial effects on quantiles in a regression analysis framework (unconditional quantile regressions). The flexibility and simplicity of these tools has opened...

Grouped data in the form of income shares have conventionally been used to estimate income inequality due to the lack of individual records. We provide guidance on the choice between parametric and nonparametric methods and its estimation, for which we develop the GB2group R package. We present...

We show that Bertrand et al.'s (QJE 2015) finding of a sharp drop in the relative income distribution within married couples at the point where wives start to earn more than their husbands is unstable across different estimation procedures and varies across contexts. We apply the estimators by...

We examine three families of one-parameter functional forms for estimating Lorenz curves: power (elementary and Pareto), exponential (elementary and Gupta) and fractional (Rohde). The computing difficulties to determine the headcount ratio (i.e., the percentage of poor) have been underestimated....