Publication Type
Journal Article
Version
publishedVersion
Publication Date
3-2015
Abstract
We consider the problem of supplementing survey data with additional information from a population. The framework we use is very general; examples are missing data problems, measurement error models and combining data from multiple surveys. We do not require the survey data to be a simple random sample of the population of interest. The key assumption we make is that there exists a set of common variables between the survey and the supplementary data. Thus, the supplementary data serve the dual role of providing adjustments to the survey data for model consistencies and also enriching the survey data for improved efficiency. We propose a semi-parametric approach using empirical likelihood to combine data from the two sources. The method possesses favourable large and moderate sample properties. We use the method to investigate wage regression using data from the National Longitudinal Survey of Youth Study.
Keywords
empirical likelihood, inverse probability weighting, selection bias, supplementary data, surveys
Discipline
Econometrics | Economics
Research Areas
Econometrics
Publication
Scandinavian Journal of Statistics
Volume
42
Issue
1
First Page
155
Last Page
176
ISSN
1467-9469
Identifier
10.1111/sjos.12100
Publisher
Wiley
Citation
LEUNG, Denis H. Y.; YAMADA, Ken; and ZHANG, Biao.
Enriching Surveys with Supplementary Data and Its Application to Studying Wage Regression. (2015). Scandinavian Journal of Statistics. 42, (1), 155-176.
Available at: https://ink.library.smu.edu.sg/soe_research/1562
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1111/sjos.12100