Alternative Methods for CPS Income Imputation
作者:
Martin David,
RoderickJ. A. Little,
MichaelE. Samuhel,
RobertK. Triest,
期刊:
Journal of the American Statistical Association
(Taylor Available online 1986)
卷期:
Volume 81,
issue 393
页码: 29-41
ISSN:0162-1459
年代: 1986
DOI:10.1080/01621459.1986.10478235
出版商: Taylor & Francis Group
关键词: Missing data;Incomplete data;Hot deck;Regression imputation;Nonrandom nonresponse
数据来源: Taylor
摘要:
The U.S. Bureau of the Census imputes missing income items in the income supplement of the Current Population Survey (CPS) by a technique commonly known as the CPS hot deck. This article compares CPS hot deck imputations of wages and salary amounts with alternatives based on regression models for the logarithm of wages and salary and for the wage rate. Comparisons are effected by comparing imputations with an Internal Revenue Service (IRS) wages and salary amount found by an exact match of CPS data to IRS records. Although limitations in the matching and in the comparison variable preclude a definitive conclusion, we find that (a) the CPS hot deck does not underestimate income aggregates to any serious extent; (b) model-based alternatives have slightly smaller mean absolute error than the hot deck, when comparable data bases of respondents are used to carry out imputations; and (c) multivariate models for imputing recipiency, weeks and hours worked, and earnings need to be developed to provide realistic competitors to the current hot deck method.
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