scispace - formally typeset
Open AccessPosted Content

Imputing Income in the CPS: Comments on "Measures of Aggregate Labor Cost in the United States"

Donald B. Rubin
- pp 333-344
Reads0
Chats0
About
The article was published on 1983-01-01 and is currently open access. It has received 9 citations till now.

read more

Citations
More filters
Book ChapterDOI

Empirical Strategies in Labor Economics

TL;DR: In this article, the authors provide an overview of the methodological and practical issues that arise when estimating causal relationships that are of interest to labor economists, including identification, data collection, and measurement problems.
Posted Content

Match Bias in Wage Gap Estimates Due to Earnings Imputation

TL;DR: In this article, the authors derived an expression for "match bias" in which attenuation equals the sum of match error rates, in practice, attenuation can be approximated by the proportion with imputed earnings.
Journal Article

An analysis of nonignorable nonresponse to income in a survey with a rotating panel design

TL;DR: A sensitivity analysis is described to assess the impact of departures from MAR for refusals, based on SRMI for a pattern-mixture model, which avoids the well-known problems of underidentification of parameters of missing not at random models.
References
More filters
Journal ArticleDOI

An Analysis of Transformations

TL;DR: In this article, Lindley et al. make the less restrictive assumption that such a normal, homoscedastic, linear model is appropriate after some suitable transformation has been applied to the y's.
Journal ArticleDOI

Inference and missing data

Donald B. Rubin
- 01 Dec 1976 - 
TL;DR: In this article, it was shown that ignoring the process that causes missing data when making sampling distribution inferences about the parameter of the data, θ, is generally appropriate if and only if the missing data are missing at random and the observed data are observed at random, and then such inferences are generally conditional on the observed pattern of missing data.
Book ChapterDOI

Controlling Bias in Observational Studies: A Review.

TL;DR: This article reviewed the effectiveness of matched sampling and statistical adjustment, alone and in combination, in reducing bias due to confounding x-variables when comparing two populations, and the adjustment methods were linear regression adjustment for x continuous and direct standardization for x categorical.
Journal ArticleDOI

Bias Reduction Using Mahalanobis-Metric Matching

Donald B. Rubin
- 01 Jun 1980 - 
TL;DR: Monte Carlo methods are used to study the ability of nearest available Mahalanobis metric matching to make the means of matching variables more similar in matched samples than in random samples.
Related Papers (5)