Tony Beatton, Michael P. Kidd, Anthony Niu, Francis Vella
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引用次数: 0
摘要
本文估计了某一年级年龄最大(接受治疗)和年龄最小(对照)学生的学习成绩差异。我们采用了昆士兰教育部学校管理小组2008-2016年公立学校学生的数据。学业成绩采用标准化考试成绩(国家算术和识字评估计划)和教师评估的3、5和7年级学生的成绩和努力衡量标准来衡量。实证分析采用了基于出生日期的回归不连续性设计,与入学年龄的行政规则相对应。班级分配机制通过已知的截止日期运行,导致年级中年龄最大的孩子比最小的孩子大近一岁。然而,缺乏入学依从性意味着回归不连续性设计是模糊的,而不是尖锐的,确定了局部平均治疗效果而不是平均治疗效果。特别是,鉴于不合规的片面性,我们采用了Battistin和Rettore的部分模糊估计量(Journal of Econometrics,142715-302008)。利用2008年入学截止日期改革,将入学年龄推迟了6岁 几个月来,我们发现入学依从性大幅提高。这种入组年龄的外生变化使人们能够衡量入组不依从性在估计队列中年龄较大与年龄较小的治疗效果方面的重要性。我们发现,改造前的治疗效果很小,通常在统计学上不显著,改造后的治疗效果相当大,在统计学上显著。
Age of Starting School, Academic Performance, and the Impact of Non-Compliance: An Experiment within an Experiment, Evidence from Australia*
This paper estimates the difference in academic performance of the oldest (treated) and youngest (control) students in a given grade. We employ Queensland Department of Education school administration panel data for the population of 2008–2016 state school students. Academic performance is measured using standardised test scores (National Assessments Program in Numeracy and Literacy) and teacher-assessed measures of performance and effort for individuals in grades 3, 5 and 7. The empirical analysis employs a regression discontinuity design based on birth date relative to administrative rules on age of school enrolment. The class-assigning mechanism operates via a known cut-off date and results in the oldest child in the grade being almost a year older than the youngest. However, lack of enrolment compliance implies the regression discontinuity design is fuzzy rather than sharp, identifying the local average treatment effect rather than the average treatment effect. In particular, given the one-sided nature of non-compliance, we employ the partially fuzzy estimator of Battistin and Rettore (Journal of Econometrics, 142, 715–30, 2008). Exploiting a 2008 enrolment cut-off date reform, which delayed school starting age by 6 months, we find a large increase in enrolment compliance. This exogenous change in the enrolment age enables one to gauge the importance of enrolment non-compliance in estimating the treatment effect of being older versus younger in cohort. We find that pre-reform the treatment effect is small and generally statistically insignificant and post-reform it is sizeable and statistically significant.