Alternative Methods for CPS Income Imputation
比较了美国人口普查局在CPS中使用的热板插补法与基于回归模型的替代方法，发现模型方法在平均绝对误差上略优，但热板法未严重低估收入总量。
Abstract 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.