Alternative Title

Supplementing surveys with auxiliary data with application in studying wage regression

Publication Type

Journal Article

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, regression analysis

Discipline

Econometrics

Research Areas

Econometrics

Publication

Scandinavian Journal of Statistics

Volume

42

Issue

1

First Page

155

Last Page

179

ISSN

0303-6898

Identifier

10.1111/sjos.12100

Publisher

Wiley: 12 months

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Additional URL

http://doi.org/10.1111/sjos.12100

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Econometrics Commons

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