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.

尽管决定了教育成就和成就的政策相关性，但即使有几项关于该问题的研究，经济也对问题没有很好的了解。这项研究将研究教育成就和成就的决定者，通过使用新近可用的行政测试评分和调查数据在6至12年级的儿童/青少年的标准化测试中衡量的。该研究基于对所有公立学校的儿童进行全国标准化测试，以及在随机的学校样本中对特殊学生，老师，校长和父母的调查。这些丰富的数据提供了分析学校质量，教师质量和家庭特征如何影响学生入学和表现的机会，以学习是整个成绩的累积过程。研究人员还将使用这些数据来研究向儿童支付补贴的计划如何影响儿童的工作行为，学校尝试和表现。这项研究还将研究学校质量，课程差异以及与家庭距离的距离如何影响父母支付教育费用的意愿；它还将分析如何为孩子的教育付款的意愿受家庭背景的影响。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。尽管有一些研究，但研究人员对确定教育成就和成就的确定没有很好的了解，尤其是在K-12水平上。这项研究将贡献有关确定K-12教育的文献。具体而言，这项研究的目的是：（i）估计测试评分动态的增值模型，以研究学校质量和家庭的投入如何影响学生的绩效，并研究现金转移计划如何通过同伴效应影响受益人和非社交者； （ii）开发和估计学生入学，成就和成绩的决定性模型，该模型融合了失败，保留和辍学； （iii）估计对不同类型的学校的需求，考虑到个人特定选择集（基于地理位置），并分析需求如何取决于学校，家庭背景，补贴状态和当地劳动力市场条件，影响教育的回报以及对童工的需求； （iv）开发和估计学生入学，学习工作，辍学和工作决策的离散选择动态编程（DCDP）模型，并使用该模型来研究不同收入转移激励付款，修改学校质量和增加学校的效果。 （v）最后，研究发展并估算了课堂内学生努力选择的战略模型，以研究初始能力分配如何影响努力选择和测试成绩成果。这项研究的结果将为改善教育成果，增加人力资本形成并增加长期经济增长的政策提供重要的意见。该研究结果还可以帮助将美国建立为教育成果研究的全球领导者。该奖项反映了NSF的法定任务，并使用基金会的知识分子优点和更广泛的影响审查标准，被视为通过评估而被视为珍贵的支持。