This paper uses measurements of learning inequality to explore whether learning interventions that are aimed at improving means also reduce inequality, and if so, under what conditions. There is abundant evidence that learning levels are generally low in low- and middle-income countries (LMIC), but there is less knowledge about how learning achievement is distributed within these contexts, and especially about how these distributions change as mean levels increase. We use child-level data on foundational literacy outcomes to quantitatively explore whether and how learning inequality using metrics borrowed from the economics and inequality literature can help us understand the impact of learning interventions. The paper deepens recent work in several ways. First, it extends the analysis to six LMIC, displaying which measures are computable and coherent across contexts and baseline levels. This extension can add valuable information to program evaluation, without being redundant with other metrics. Second, we show the large extent to which the disaggregation of inequality of foundational skills between- and within-schools and grades varies by context and language. Third, we present initial empirical evidence that, at least in the contexts of analysis of foundational interventions, improving average performance can reduce inequality as well, across all levels of socioeconomic status (SES). The data show that at baseline, the groups with the highest internal inequality tend to be the groups with lowest SES and lowest reading scores, as inequality among the poor themselves is higher than among their wealthier counterparts. Regardless of which SES groups benefit more in terms of a change in mean levels of reading, there is still a considerable reduction in inequality by baseline achievement as means increase. These results have policy implications in terms of targeting of interventions: much can be achieved in terms of simultaneously improving averages and increasing equality. This seems particularly true when the initial learning levels are as low as they currently are the developing world.

本文使用学习不平等的测量来探讨旨在改善手段的学习干预是否也减少了不平等，如果是，在什么条件下。有大量证据表明，中低收入国家 (LMIC) 的学习水平普遍较低，但对学习成绩如何分配的了解较少在这些背景下，特别是关于这些分布如何随着平均水平的增加而变化。我们使用有关基础识字结果的儿童级数据，使用从经济学和不平等文献中借来的指标来定量探索学习不平等是否以及如何帮助我们了解学习干预的影响。这篇论文从几个方面深化了最近的工作。首先，它将分析扩展到六个中低收入国家，显示哪些度量是可计算的，并且跨上下文和基线水平是一致的。此扩展可以为程序评估添加有价值的信息，而不会与其他指标冗余。其次，我们展示了校内和校内基础技能不平等的分解在很大程度上因环境和语言而异。第三，我们提供的初步经验证据表明，至少在基础干预分析的背景下，提高平均绩效也可以减少所有社会经济地位 (SES) 水平的不平等。数据显示，在基线上，内部不平等程度最高的群体往往是社会经济地位最低和阅读分数最低的群体，因为穷人之间的不平等程度高于富裕群体之间的不平等程度。无论哪个 SES 群体在阅读平均水平的变化方面受益更多，随着平均水平的增加，基线成就仍显着减少了不平等。这些结果在干预措施的目标方面具有政策意义：在同时提高平均水平和增加平等方面可以取得很大成就。