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Improving the Quality of Economic Data: Lessons from the HRS and AHEAD

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TLDR
Follow-up brackets as discussed by the authors represent partial responses to asset questions and apparently significantly reduce item nonresponse, which is a critical problem with economic survey data, and also provide a remedy to deal with nonignorable nonresponse bias.
Abstract
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 nonignorable nonresponse bias, a critical problem with economic survey data.

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Journal ArticleDOI

Statistical Analysis with Missing Data

Martin G. Gibson
- 01 Mar 1989 - 
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References
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Imputation of Missing Values When the Probability of Response Depends on the Variable Being Imputed

TL;DR: In this paper, a method for imputing missing values when the probability of response depends upon the variable being imputed is developed, where the missing data problem is viewed as one of parameter estimation in a regression model with stochastic censoring of the dependent variable.
Journal ArticleDOI

Does Marital History Matter? Marital Status and Wealth Outcomes Among Preretirement Adults

TL;DR: For example, the authors found that individuals who are not continuously married have significantly lower wealth than those who remain married throughout the life course, and there are significant gender differences in these effects.
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