Improving the quality of economic data: Lessons from the HRS and AHEAD

被引:73
作者
Juster, FT [1 ]
Smith, JP
机构
[1] Univ Michigan, Survey Res Ctr, Ann Arbor, MI 48104 USA
[2] Rand Corp, Santa Monica, CA 90407 USA
关键词
imputation; missing data; nonignorable nonresponse;
D O I
10.2307/2965397
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
Missing data are an increasingly important problem in economic surveys, especially when trying to measure household wealth. However, some relatively simple new survey methods such as follow-up brackets appear to appreciably improve the quality of household economic data. Brackets represent partial responses to asset questions and apparently significantly reduce item nonresponse. Brackets also provide a remedy to deal with non-ignorable nonresponse bias, a critical problem with economic survey data.
引用
收藏
页码:1268 / 1278
页数:11
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