纵向调查数据测量误差的大规模验证研究

Nicolai Kristensen, N. Westergaard-Nielsen
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引用次数: 19

摘要

在本文中,我们分析了几个关键变量的测量和分类误差,包括收入和教育程度,在一个匹配的调查样本和行政纵向数据。这些数据跨越1994-2001年,涵盖了丹麦经济的所有部门,比通常在验证研究中看到的要全面得多。研究发现,收益的测量误差比以往仅限于一家公司的研究报告要大得多。从小组中剔除的个人报告其收入的准确性明显低于在整个抽样期间观察到的个人。此外,女性报告收入的准确性明显高于男性,兼职工人报告的准确性明显低于全职工人,低收入工人报告的准确性明显低于收入相对较高的工人。发现分类变量的分类误差与以前在文献中发现的大致相同。我们分析了一个变量的响应误差是否使同一受访者更有可能报告其他有错误的变量,但没有找到支持这一假设的证据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Large-Scale Validation Study of Measurement Errors in Longitudinal Survey Data
In this paper, we analyze measurement and classification errors in several key variables, including earnings and educational attainment, in a matched sample of survey and administrative longitudinal data. The data, spanning 1994-2001 and covering all sectors in the Danish economy, are much more comprehensive than usually seen in validation studies. Measurement errors in earnings are found to be much larger than reported in previous studies limited to one single firm. Individuals who attrite from the panel report their earnings significantly less accurate than individuals who are observed throughout the entire sampling period. Furthermore, females are found to report their earnings significantly more precise than males, part-time workers report significantly less accurate than full-time workers and low-income workers report significantly less accurate than workers with relatively higher income. Classification errors in categorical variables are found to be of about the same magnitude as previously found in the literature. We analyze whether response error in one variable makes it more likely that the same respondent will report other variables with error but do not find support for this hypothesis.
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