Using New Longitudinal Linked Data to Investigate the Determinants of Educational Attainment and Achievement

使用新的纵向关联数据调查教育程度和成就的决定因素

• 批准号: 1948943
• 负责人: Petra Todd
• 金额: $ 41.25万
• 依托单位: University of Pennsylvania
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-15 至 2024-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1948943&HistoricalAwards=false
• 关键词: Using; New; Longitudinal; Linked; Data

In spite of the policy relevance of what determines educational attainment and achievement, economists do not have a good understanding of the issue even though there are several studies on the subject. This research will study the determinants of educational attainment and achievement, as measured by scores on standardized tests for children/youth in grades 6-12 using newly available administrative test score and survey data. The study is based on a nationwide standardized tests to children in all public schools as well as surveys of special students, teacher, principal and parents in a random sample of schools. These rich data provide opportunities to analyze how school quality, teacher quality and family characteristics affect student enrollment and performance in a way that learning is a cumulative process across grades. The researchers will also use the data to study how a program that pays subsidies to children to attend school affects child working behaviors, schooling attainment and performance. The research will also study how school quality, differences in curricula, and distances from home affect parents’ willingness to pay for education; it will also analyze how willingness to pay for their children’s education is influenced by family background. The results of this research can inform educational policies in the US and many other countries. The research project will also help establish the global leader in educational outcomes research.Despite several studies, researchers do not have a good understanding of the determinants of educational attainment and achievement, especially at the K-12 level. This research will contribute the literature on the determinants of K-12 education. Specifically, this research aims at: (i) estimating value-added models of test score dynamics to study how school quality and family inputs affect student performance and to examine how cash transfer a program affects beneficiaries and nonbeneficiaries through peer effects; (ii) develop and estimate a dynamic model of the determinants of student enrollment, achievement and grade progression that incorporates failure, grade retention and dropout; (iii) estimate the demand for different types of schools, accounting for individual-specific choice sets (based on geographic location), and analyze how demand depends on school quality, distances to schools, family background, subsidy status and local labor market conditions that affects returns to education and the demand for child labor; (iv) develop and estimate a discrete choice dynamic programming (DCDP) model of student enrollment, study effort, drop-out, and working decisions and use the model to study the effect of varying income transfer incentive payments, modifying school quality and increasing schooling access. (v) Finally, the research develops and estimate a strategic model of student effort choices within classrooms to study how initial ability distribution influences effort choices and test score outcomes. The results of this research will provide important inputs into policies to improve education outcomes, increase human capital formation, and increase long-term economic growth. The research results could also help establish the US as the global leader in research on educational outcomes.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

尽管决定教育程度和成就的因素具有政策相关性，但经济学家对这一问题并没有很好的理解，尽管对这一问题有几项研究。 这项研究将研究受教育程度和成绩的决定因素，这些决定因素是利用新获得的行政考试分数和调查数据，通过6-12年级儿童/青年标准化考试的分数来衡量的。 这项研究是基于对所有公立学校儿童的全国标准化测试以及对随机抽样学校的特殊学生、教师、校长和家长的调查。这些丰富的数据提供了机会，分析学校质量，教师质量和家庭特征如何影响学生的入学率和表现，学习是一个跨年级的累积过程。 研究人员还将利用这些数据来研究一个为儿童上学提供补贴的项目如何影响儿童的工作行为、学业成就和表现。 研究还将研究学校质量、课程差异和离家远近如何影响父母的教育支付意愿;还将分析家庭背景如何影响子女的教育支付意愿。 这项研究的结果可以为美国和许多其他国家的教育政策提供信息。该研究项目还将有助于建立教育成果研究的全球领导者。尽管有几项研究，研究人员没有很好地了解教育程度和成就的决定因素，特别是在K-12水平。 本研究将有助于文献的K-12教育的决定因素。 具体而言，本研究的目的是：（一）估计增值模型的考试成绩动态研究学校质量和家庭投入如何影响学生的表现，并检查现金转移计划如何影响受益人和非受益人通过同侪效应;（二）开发和估计的动态模型的决定因素的学生入学，成绩和年级的进展，包括失败，年级保持和辍学;（iii）估计对不同类型学校的需求，并考虑到个别学校的选择（基于地理位置），并分析需求如何取决于学校质量、学校距离、家庭背景、补贴状况和影响教育回报和童工需求的当地劳动力市场状况;（iv）发展和估计学生入学、学习努力、辍学和工作决定的离散选择动态规划模型，并使用该模型研究不同收入转移奖励金的影响，提高学校质量，增加入学机会。(v)最后，本研究发展并评估了一个学生在课堂上努力选择的策略模型，以研究初始能力分布如何影响努力选择和考试成绩结果。 这项研究的结果将为改善教育成果、增加人力资本形成和促进长期经济增长的政策提供重要投入。 该研究成果还有助于确立美国在教育成果研究方面的全球领导地位。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。