Aggregation and the Estimated Effects of School Resources
Aggregation and the Estimated Effects of School Resources
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学校资源的聚合和估计效果
DOI：
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发表时间：
1996
期刊：
影响因子：
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通讯作者：
L. Taylor
中科院分区：
文献类型：
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作者：
E. Hanushek;Steven G. Rivkin;L. Taylor
本文试图通过强调在存在遗漏变量偏差的情况下聚合的作用来调和关于学校资源和学校效能的争论中的矛盾结果。虽然数据聚合良好指定的线性模型产生无偏的参数估计，聚合改变任何遗漏的变量偏差的大小。总的来说，聚合的理论影响是模糊的。然而，在一个非常相关的特殊情况下，省略的变量涉及国家在学校政策的差异，汇总意味着明显的向上偏置估计学校资源的影响。对高中及以上数据的分析提供了强有力的证据，表明汇总会扩大学校资源的系数。此外，结果模式与变量误差解释不一致，变量误差解释是对总体估计影响较大的另一种解释。由于使用汇总数据的研究更有可能发现学校资源对成绩的积极影响，这些结果进一步支持了这样一种观点，即单独增加支出不太可能改善学生的成绩。
This paper attempts to reconcile the contradictory findings in the debate over school resources and school effectiveness by highlighting the role of aggregation in the presence of omitted variables bias. While data aggregation for well-specified linear models yields unbiased parameter estimates, aggregation alters the magnitude of any omitted variables bias. In general, the theoretical impact of aggregation is ambiguous. In a very relevant special case where omitted variables relate to state differences in school policy, however, aggregation implies clear upward bias of estimated school resource effects. Analysis of High School and Beyond data provides strong evidence that aggregation inflates the coefficients on school resources. Moreover, the pattern of results is not consistent with an errors-in-variables explanation, the alternative explanation for the larger estimated impact with aggregate estimates. Since studies using aggregate data are much more likely to find positive school resource effects on achievement, these results provide further support to the view that additional expenditures alone are unlikely to improve student outcomes.