出勤
选择(遗传算法)
集合(抽象数据类型)
选择偏差
度量(数据仓库)
考试(生物学)
心理学
学生成绩
实证研究
变化(天文学)
感知
计量经济学
数学教育
精算学
计算机科学
学业成绩
经济
统计
数学
机器学习
数据挖掘
经济增长
神经科学
天体物理学
生物
程序设计语言
古生物学
物理
作者
Joshua D. Angrist,Peter Hull,Christopher Walters
出处
期刊:Handbook of the economics of education
日期:2023-01-01
卷期号:: 1-60
被引量:1
标识
DOI:10.1016/bs.hesedu.2023.03.001
摘要
Many personal and policy decisions turn on perceptions of school effectiveness, defined here as the causal effect of attendance at a particular school or set of schools on student test scores and other outcomes. Widely disseminated school ratings frameworks compare average student achievement across schools, but uncontrolled differences in means may owe more to selection bias than to causal effects. Such selection problems have motivated a wave of econometric innovation that uses elements of random and quasi-experimental variation to measure school effectiveness. This chapter reviews these empirical strategies, highlighting solved problems and open questions. Empirical examples are used throughout.
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