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Measuring Wages Worldwide: Exploring the Potentials and Constraints of Volunteer Web Surveys

Measuring Wages Worldwide: Exploring the Potentials and Constraints of Volunteer Web Surveys

Stephanie Steinmetz, Damian Raess, Kea Tijdens, Pablo de Pedraza
Copyright: © 2013 |Pages: 20
ISBN13: 9781466639188|ISBN10: 1466639180|EISBN13: 9781466639195
DOI: 10.4018/978-1-4666-3918-8.ch006
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MLA

Steinmetz, Stephanie, et al. "Measuring Wages Worldwide: Exploring the Potentials and Constraints of Volunteer Web Surveys." Advancing Research Methods with New Technologies, edited by Natalie Sappleton, IGI Global, 2013, pp. 100-119. https://doi.org/10.4018/978-1-4666-3918-8.ch006

APA

Steinmetz, S., Raess, D., Tijdens, K., & de Pedraza, P. (2013). Measuring Wages Worldwide: Exploring the Potentials and Constraints of Volunteer Web Surveys. In N. Sappleton (Ed.), Advancing Research Methods with New Technologies (pp. 100-119). IGI Global. https://doi.org/10.4018/978-1-4666-3918-8.ch006

Chicago

Steinmetz, Stephanie, et al. "Measuring Wages Worldwide: Exploring the Potentials and Constraints of Volunteer Web Surveys." In Advancing Research Methods with New Technologies, edited by Natalie Sappleton, 100-119. Hershey, PA: IGI Global, 2013. https://doi.org/10.4018/978-1-4666-3918-8.ch006

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Abstract

This chapter discusses the potentials and constraints of using a volunteer Web survey as a worldwide data collection tool for wages. It provides a detailed description of the bias related to individual-level wages and core socio-demographic and employment-related variables across selected developed and developing countries and evaluates the efficiency of post-stratification weights in adjusting these biases. The results confirm that Web samples are particularly attractive to younger persons, part-timers, and persons working in non-manual occupations. This can be observed across countries, although the strength of the bias differs between them. With respect to the efficiency of post-stratification weights, the results are inconclusive. Whereas it is advisable to implement weights for descriptive purposes of socio-demographic variables, the contrary holds in case of wages. Additionally, weights can have the opposite effect by (moderately) increasing the difference in the estimated parameters between the reference and the Web sample.

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