Understanding the Sources of Inequality Throughout the Earnings Distribution

了解整个收益分配不平等的根源

• 批准号: 2886008
• 金额: --
• 依托单位: University of Liverpool
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2886008
• 关键词: Understanding; Sources; Inequality; Throughout; Earnings

The proposed project comprises three interconnected subprojects. Project 1 conducts an international comparison of educational and income inequality. It analyzes education inequality across 40 countries using the Survey of Adult Skills data, focusing on factors that impact educational and income disparities. Standard measures like the Gini coefficient and percentile ratios from OECD data are used for income inequality. For education inequality, it defines two measures: (i) "stuck at the bottom," indicating the fraction of children who stay low-educated like their parents, and (ii) "rise to the top," representing those who rise from a low-educated family to become highly-educated. Regressions at the country level explore key factors of educational systems that explain these inequalities.Project 2 uses individual-level longitudinal data from Norway and the UK to understand the influence of geography on inequality. While these countries have differing inequality levels, the trend in inequality is similar, making them comparable. The analysis explores how birthplace and geographic mobility impact overall and geographic inequality, categorizing inequality into explainable and unexplainable factors. It examines factors like area-level, school-level, student-level, and family-level influences on inequality across regions with varying levels of deprivation. Longitudinal data allows for an examination of how these factors change over time.Project 3 focuses on causal mechanisms behind inequality. It employs a "natural experiment" to estimate the relationship between education and inequality. By comparing students exposed to different economic conditions, it assesses the impact of education on inequality. For instance, students' willingness to invest in education is influenced by the state of the economy. Using birth cohorts in the same geographic area, the project compares "lucky" and "unlucky" students to determine how education affects inequality upon entering the labor market. Data on student achievement is used to control for differences in ability levels. This project can be conducted in Norway, the UK, or both, depending on the findings from the earlier projects.

拟议项目由三个相互关联的子项目组成。项目 1 对教育和收入不平等进行了国际比较。它利用成人技能调查数据分析了 40 个国家的教育不平等，重点关注影响教育和收入差距的因素。经合组织数据中的基尼系数和百分位数等标准衡量标准用于衡量收入不平等。对于教育不平等，它定义了两种衡量标准：（i）“陷入底层”，表示像父母一样受教育程度较低的儿童的比例；（ii）“上升到顶层”，表示那些从高学历上升的儿童。低学历家庭变成高学历家庭。国家层面的回归探讨了解释这些不平等的教育系统的关键因素。项目 2 使用来自挪威和英国的个人层面纵向数据来了解地理对不平等的影响。尽管这些国家的不平等程度不同，但不平等的趋势相似，因此具有可比性。该分析探讨了出生地和地理流动性如何影响整体和地理不平等，将不平等分为可解释和不可解释的因素。它研究了地区层面、学校层面、学生层面和家庭层面等因素对不同贫困程度地区不平等的影响。纵向数据可以检查这些因素如何随时间变化。项目 3 侧重于不平等背后的因果机制。它采用“自然实验”来估计教育与不平等之间的关系。通过比较处于不同经济条件下的学生，评估教育对不平等的影响。例如，学生投资教育的意愿受到经济状况的影响。该项目利用同一地理区域的出生群体，对“幸运”和“不幸”的学生进行比较，以确定教育如何影响进入劳动力市场后的不平等。学生成绩数据用于控制能力水平的差异。该项目可以在挪威、英国或两者同时进行，具体取决于早期项目的研究结果。