What Are We Weighting For?
What Are We Weighting For?
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DOI：
10.3368/jhr.50.2.301
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发表时间：
2015-03-01
影响因子：
5.2
通讯作者：
Wooldridge, Jeffrey M.
中科院分区：
文献类型：
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作者：
Solon, Gary;Haider, Steven J.;Wooldridge, Jeffrey M.
在估计人群描述性统计量时，如果需要使分析样本代表目标人群，则需要加权。关于直接估计因果效应的研究，我们讨论了三种不同的加权动机：（1）通过校正异方差性来实现精确估计;（2）通过校正内生抽样来实现一致估计;（3）在存在未建模的效应异质性的情况下识别平均部分效应。在每一种情况下，我们发现动机有时并不适用于实践者经常假设它的情况。
When estimating population descriptive statistics, weighting is called for if needed to make the analysis sample representative of the target population. With regard to research directed instead at estimating causal effects, we discuss three distinct weighting motives: (1) to achieve precise estimates by correcting for heteroskedasticity; (2) to achieve consistent estimates by correcting for endogenous sampling; and (3) to identify average partial effects in the presence of unmodeled heterogeneity of effects. In each case, we find that the motive sometimes does not apply in situations where practitioners often assume it does.