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Compreender a conexão entre desigualdade e justiça é importante porque a justiça é classicamente considerado como a primeira linha de defesa contra o autointeresse e a desigualdade. Na ausência de uma ligação forte e clara entre desigualdade e justiça, o senso de justiça não iria despertar para exercer a sua persuasão moral, não importa quão grande a desigualdade ou o quão rápido o seu crescimento. Neste trabalho analisamos as ligações entre desigualdade econômica e três parâmetros da distribuição de avaliação de justiça – média, mediana e variância – através de um conjunto abrangente de medidas de desigualdade e um conjunto inicial substantivo de cenários de justa recompensa. Este trabalho mostra que não há nenhuma conexão geral necessária entre desigualdade e justiça. Há, no entanto, um padrão marcante em algumas situações: com o aumento da desigualdade econômica, a média das avaliações de justiça se move mais profundamente no território de injustamente sub-recompensado, e a distribuição se estende para fora, aumentando o abismo entre sub-recompensado e super-recompensado, esvaziando as categorias intermediárias

Inequality often appears in linked pairs of variables. Examples include schooling and income, income and consumption, and wealth and happiness. Consider the famous words of Veblen: "wealth confers honor." Understanding inequality requires understanding input inequality, outcome inequality, and the relation between the two--in both inequality between persons and inequality between subgroups. This article contributes to the methodological toolkit for studying inequality by developing a framework that makes explicit both input inequality and outcome inequality and by addressing three main associated questions: (1) How do the mechanisms for generating and altering inequality differ across inputs and outcomes? (2) Which have more inequality--inputs or outcomes? (3) Under what conditions, and by what mechanisms, does input inequality affect outcome inequality? Results include the following: First, under specified conditions, distinctive mechanisms govern inequality in inputs and inequality in outcomes. Second, input inequality and outcome inequality can be the same or different; if different, whether inequality is greater among inputs or outcomes depends on the configuration of outcome function, types of inputs, distributional form of and inequality in cardinal inputs, and number of and associations among inputs. Third, the link between input inequality and outcome inequality is multiform; it can be nonexistent, linear, or nonlinear, and if nonlinear, it can be concave or convex. More deeply, this work signals the formidable empirical challenges in studying inequality, but also the fast growing toolbox. For example, even if the outcome distribution is difficult to derive, fundamental theorems on the variance make it possible to analyze the input-outcome inequality connection. Similarly, within specified distributions, the general inequality parameter makes it possible to express results in terms of both measures of overall inequality and measures of subgroup inequality.

Newly precise evidence of the trajectory of top incomes in the United States and around the world relies on shares and ratios, prompting new inquiry into their properties as inequality measures. Current evidence suggests a mathematical link between top shares and the Gini coefficient and empirical links extending as well to the Atkinson measure. The work reported in this article strengthens that evidence, making several contributions: First, it formalizes the shares and ratios, showing that as monotonic transformations of each other, they are different manifestations of a single inequality measure, here called TopBot. Second, it presents two standard forms of TopBot, which satisfy the principle of normalization. Third, it presents a new link between top shares and the Gini coefficient, showing that properties and results associated with the Lorenz curve pertain as well to top shares. Fourth, it investigates TopBot in mathematically specified probability distributions, showing that TopBot is monotonically related to classical measures such as the Gini, Atkinson, and Theil measures and the coefficient of variation. Thus, TopBot appears to be a genuine inequality measure. Moreover, TopBot is further distinguished by its ease of calculation and ease of interpretation, making it an appealing People's measure of inequality. This work also provides new insights, for example, that, given nonlinearities in the (monotonic) relations among inequality measures, Spearman correlations are more appropriate than Pearson correlations and that weakening of correlations signals differences and shifts in distributional form, themselves signals of income dynamics.

The editorial "On poverty and its eradication" discusses the urgent need to address poverty, especially exacerbated by the COVID-19 pandemic. The research topic explores various aspects of poverty, including entrepreneurship, consumption, digital growth, health, employment, and the income tax system. The studies aim to expand knowledge about poverty, its causes, consequences, and connections to crises, inequality, and fairness, while promoting fair and inclusive societies. The editorial includes contributions from authors in China, the Philippines, the United Kingdom, and the United States, and is organized in collaboration with five journals. [Extracted from the article]

This paper develops and illustrates a method for empirically designing an income tax system that people will regard as fair. The paper begins with the classical Principles of Tax Justice, viz., as pretax income increases, three quantities should also increase – posttax income, tax amount, and tax rate. GSOEP data on residents' pretax income and the posttax income they regard as fair are used to estimate a just linear income tax system. Analytic results include a signature standard form of the tax system showing the intertwined fates of poor and rich and the conditions which threaten fairness. Empirical results show that the estimated tax system lowers taxes for a majority of respondents, especially the relatively poorer, and substantially reduces inequality. [ABSTRACT FROM AUTHOR]

Recent work revives the classic idea that the sense of justice is the first line of defense against inequality and shows that the link depends, in part, on ideas of the just reward. This paper extends earlier work, making three new contributions: (1) it expands the just reward scenarios from the micro scenarios (which start with the individual's idea of the just reward) to six new macro scenarios (which start with the distribution of everyone's ideas of the just reward); (2) it expands the set of justice measures from three to four, including now the proportion underrewarded; and (3) it obtains results for all the new cases, identifying the conditions that lead to radically different connections between inequality and justice. [ABSTRACT FROM AUTHOR]