Durrant, Gabriele B. and Skinner, Chris J. (2006) Using data augmentation to correct for non-ignorable non-response when surrogate data are available: an application to the distribution of hourly pay. Journal of the Royal Statistical Society. Series A: Statistics in Society, 169 (3). pp. 605-623. ISSN 0964-1998
Full text not available from this repository.Abstract
The paper develops a data augmentation method to estimate the distribution function of a variable, which is partially observed, under a non-ignorable missing data mechanism, and where surrogate data are available. An application to the estimation of hourly pay distributions using UK Labour Force Survey data provides the main motivation. In addition to considering a standard parametric data augmentation method, we consider the use of hot deck imputation methods as part of the data augmentation procedure to improve the robustness of the method. The method proposed is compared with standard methods that are based on an ignorable missing data mechanism, both in a simulation study and in the Labour Force Survey application. The focus is on reducing bias in point estimation, but variance estimation using multiple imputation is also considered briefly.
| Item Type: | Article |
|---|---|
| Official URL: | http://www.blackwellpublishing.com/journal.asp?ref... |
| Additional Information: | © 2006 Wiley-Blackwell |
| Divisions: | Statistics |
| Subjects: | H Social Sciences > H Social Sciences (General) H Social Sciences > HA Statistics H Social Sciences > HC Economic History and Conditions |
| JEL classification: | J - Labor and Demographic Economics > J3 - Wages, Compensation, and Labor Costs > J31 - Wage Level and Structure; Wage Differentials by Skill, Training, Occupation, etc. |
| Date Deposited: | 28 Oct 2011 12:39 |
| Last Modified: | 11 Dec 2024 23:04 |
| URI: | http://eprints.lse.ac.uk/id/eprint/39101 |
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