Can a voluntary web survey be useful beyond explorative research?

References

• Altonji, J. G., & Blank, R. M. (1999). Race and gender in the labor market. In O. Ashenfelter, R. Layard, & D. Card (Eds.), Handbook of labor economics (pp. 3143–3259). Amsterdam: Elsevier.
   Google Scholar
• Antonovics, K., & Town, R. (2004). Are all the good men married? Uncovering the sources of the marital wage premium. American Economic Review, 94, 317–321.10.1257/0002828041301876
   Web of Science ®Google Scholar
• Askitas, N., & Zimmermann, K. F. (2015). The internet as a data source for advancement in social sciences. International Journal of Manpower, 36, 2–12. doi:10.1108/IJM-02-2015-0029
   Web of Science ®Google Scholar
• Averett, S. L., & Hotchkiss, J. L. (1996). Discrimination in the payment of full-time wage premiums. ILR Review, 49, 287–301. doi:10.1177/001979399604900207
   Google Scholar
• Baltar, F., & Brunet, I. (2012). Social research 2.0: Virtual snowball sampling method using Facebook. Internet Research, 22, 57–74. doi:10.1108/10662241211199960
   Web of Science ®Google Scholar
• Bandilla, W., Bosnjak, M., & Altdorfer, P. (2003). Survey administration effects? A comparison of web-based and traditional written self-administered surveys using the issp environment module. Social Science Computer Review, 21, 235–243. doi:10.1177/0894439303021002009
   Web of Science ®Google Scholar
• Barro, R. J., & Lee, J. W. (1996). International measures of schooling years and schooling quality. American Economic Review, 86, 218–223.
   Web of Science ®Google Scholar
• Beblavý, M., Lehouelleur, S., & Maselli, I. (2013). Useless degrees of useless statistics? A comparison of the net present value of higher education by field of study in five European countries ( SSRN Scholarly Paper No. ID 2402716). Rochester, NY: Social Science Research Network.
   Google Scholar
• Bethlehem, J. (2010). Selection bias in web surveys. International Statistical Review, 78, 161–188.10.1111/(ISSN)1751-5823
   Web of Science ®Google Scholar
• Chow, G. C. (1960). Tests of equality between sets of coefficients in two linear regressions. Econometrica, 28, 591–605. doi:10.2307/1910133
   Web of Science ®Google Scholar
• Couper, M. P. (2000). Review: Web surveys: A review of issues and approaches. Public Opinion Quarterly, 64, 464–494.10.1086/318641
   PubMed Web of Science ®Google Scholar
• Das, M., Toepoel, V., & van Soest, A. (2011). Nonparametric tests of panel conditioning and attrition bias in panel surveys. Sociological Methods & Research, 40, 32–56. doi:10.1177/0049124110390765
   Web of Science ®Google Scholar
• de Bustillo, R. M., & de Pedraza, P. (2010). Determinants of job insecurity in five European countries. European Journal of Industrial Relations, 16, 5–20. doi:10.1177/0959680109355306
   Web of Science ®Google Scholar
• de Pedraza, P., Tijdens, K., de Bustillo, R. M., & Steinmetz, S. (2010). A Spanish continuous volunteer web survey: Sample bias, weighting and efficiency. Revista Española de Investigaciones Sociológicas, 109–130.
   Web of Science ®Google Scholar
• Dillman, D. A., & Bowker, D. K. (2001). The web questionnaire challenge to survey methodologists. In B. Batinic, U.-D. Reips, M. Bosnjak, & A. Werner (Eds.), Online social sciences (pp. 53–71). Seattle: Hogrefe & Huber.
   Google Scholar
• Edwards, A., Housley, W., Williams, M., Sloan, L., & Williams, M. (2013). Digital social research, social media and the sociological imagination: Surrogacy, augmentation and re-orientation. International Journal of Social Research Methodology, 16, 245–260. doi:10.1080/13645579.2013.774185
   Web of Science ®Google Scholar
• Engel, M., & Schaffner, S. (2012). How to use the EU-SILC panel to analyse monthly and hourly wages ( Ruhr Economic Paper No. 390). Duisburg: RWI – Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
   Google Scholar
• Eurostat. (2015). EU statistics on income and living conditions (EU-SILC) methodology. Luxembourg: Eurostat.
   Google Scholar
• Falk, A., & Fischbacher, U. (2006). A theory of reciprocity. Games and Economic Behavior, 54, 293–315. doi:10.1016/j.geb.2005.03.001
   Web of Science ®Google Scholar
• Fricker, R. D., & Schonlau, M. (2002). Advantages and disadvantages of internet research surveys: Evidence from the literature. Field Methods, 14, 347–367. doi:10.1177/152582202237725
   Google Scholar
• Guzi, M., & de Pedraza, P. (2015). A web survey analysis of subjective well-being. International Journal of Manpower, 36, 48–67. doi:10.1108/IJM-12-2014-0237
   Web of Science ®Google Scholar
• Heckman, J. J., Lochner, L. J., & Todd, P. E. (2006). Chapter 7 Earnings functions, rates of return and treatment effects: The Mincer equation and beyond. In E. A. Hanushek & F. Welch (Eds.), Handbook of the economics of education (pp. 307–458). Amsterdam: Elsevier.
   Google Scholar
• Kitchenham, B., & Pfleeger, S. L. (2002). Principles of survey research: Part 5: Populations and samples. ACM SIGSOFT Software Engineering Notes, 27, 17–20. doi:10.1145/571681.571686
   Google Scholar
• Kohut, A., Keeter, S., Doherty, C., Dimock, M., & Christian, L. (2012). Assessing the representativeness of public opinion surveys. Washington, DC: Pew Research Center.
   Google Scholar
• Lemieux, T. (2006). The “Mincer equation” thirty years after schooling, experience, and earnings. In S. Grossbard (Ed.), Jacob Mincer a pioneer of modern labor economics (pp. 127–145). Boston, MA: Springer US. doi:10.1007/0-387-29175-X_1110.1007/0-387-29175-X
   Google Scholar
• Lenaerts, K., Beblavý, M., & Fabo, B. (2016). Prospects for utilisation of non-vacancy Internet data in labour market analysis – An overview. IZA Journal of Labor Economics, 5, 1. doi:10.1186/s40172-016-0042-z
   Google Scholar
• Marshall, M. N. (1996). Sampling for qualitative research. Family Practice, 13, 522–526. doi:10.1093/fampra/13.6.522
   PubMed Web of Science ®Google Scholar
• Mincer, J. A. (1974). Schooling, experience, and earnings. Cambridge, MA: NBER.
   Google Scholar
• Mitra, A. (2003). Access to supervisory jobs and the gender wage gap among professionals. Journal of Economic Issues, 37, 1023–1044. doi:10.1080/00213624.2003.11506641
   Web of Science ®Google Scholar
• Mýtna-Kureková, L., Beblavý, M., & Thum-Thysen, A. (2015). Using online vacancies and web surveys to analyse the labour market: A methodological inquiry. IZA Journal of Labor Economics, 4, 1–20. doi:10.1186/s40172-015-0034-4
   Google Scholar
• O’Higgins, N. (2012). This time it’s different? Youth labour markets during ‘the great recession’. Comparative Economic Studies, 54, 395–412. doi:10.1057/ces.2012.15
   Google Scholar
• Oi, W. Y., & Idson, T. L. (1999). Chapter 33 Firm size and wages. In O. Ashenfelter, R. Layard, & D. Card (Eds.), Handbook of labor economics (pp. 2165–2214). Amsterdam: Elsevier.
   Google Scholar
• Polachek, S. W. (2008). Earnings over the life cycle: The Mincer earnings function and its applications. Foundations and Trends® in Microeconomics, 4, 165–272. doi:10.1561/070000001810.1561/0700000018
   Google Scholar
• Reips, U.-D. (2006). Web-based methods. In M. Eid & E. Diener (Eds.), Handbook of multimethod measurement in psychology (pp. 73–85). Washington, DC: American Psychological Association.10.1037/11383-000
   Google Scholar
• Reips, U.-D. (2012). Using the internet to collect data. In H. Cooper, P. M. Camic, R. Gonzalez, D. L. Long, A. Panter, D. Rindskopf, & K. J. Sher (Eds.), APA handbook of research methods in psychology (pp. 291–310). Washington, DC: American Psychological Association.
   Google Scholar
• Schonlau, M., van Soest, A., Kapteyn, A., & Couper, M. (2009). Selection bias in web surveys and the use of propensity scores. Sociological Methods & Research, 37, 291–318. doi:10.1177/0049124108327128
   Web of Science ®Google Scholar
• Sloane, P. (2014). Overeducation, skill mismatches, and labor market outcomes for college graduates. Bonn: IZA World Labor. doi:10.15185/izawol.88
   Google Scholar
• Statistics Netherlands. (2013). Final qulity report. EU-SILC 2010. The Netherlands.
   Google Scholar
• Statistics Netherlands. (2016). ICT gebruik van personen naar persoonskenmerken, 2005–2013 [ICT use of persons by personal characteristics, 2005–2013]. Amsterdam: Statistics Netherlands.
   Google Scholar
• Steinmetz, S., Raess, D., Tijdens, K., & de Pedraza, P. (2013). Measuring wages worldwide: Exploring the potentials and constraints. In N. Sappleton (Ed.), Advancing research methods with new technologies (pp. 100–119). Hershey, PA: IGI Global.10.4018/978-1-4666-3918-8
   Google Scholar
• Stieger, S., & Reips, U.-D. (2010). What are participants doing while filling in an online questionnaire: A paradata collection tool and an empirical study. Computers in Human Behavior, Online Interactivity: Role of Technology in Behavior Change, 26, 1488–1495. doi:10.1016/j.chb.2010.05.013
   Web of Science ®Google Scholar
• Thelwall, M. (2017). Social media analytics for YouTube comments: Potential and limitations. International Journal of Social Research Methodology, 1–14. doi:10.1080/13645579.2017.1381821
   Web of Science ®Google Scholar
• Tijdens, K., & Steinmetz, S. (2016). Is the web a promising tool for data collection in developing countries? An analysis of the sample bias of 10 web and face-to-face surveys from Africa, Asia, and South America. International Journal of Social Research Methodology, 19, 461–479. doi:10.1080/13645579.2015.1035875
   Web of Science ®Google Scholar
• Tijdens, K., Wetzels, C., Andralojc, M., & Michon, P. (2005). Measuring wages, and calculating hourly wages in the WageIndicator dataset. WOLIWEB Working Paper. Amsterdam: WageIndicator Foundation.
   Google Scholar
• Toepoel, V., Das, M., & Van Soest, A. (2008). Effects of design in web surveys comparing trained and fresh respondents. Public Opinion Quarterly, 72, 985–1007.10.1093/poq/nfn060
   Web of Science ®Google Scholar
• Toepoel, V., Das, M., & Van Soest, A. (2009). Design of web questionnaires: The effects of the number of items per screen. Field Methods, 21, 200–213.10.1177/1525822X08330261
   Web of Science ®Google Scholar
• van der Laan, P., & van Nunspeet, W. (2009). Modernising household surveys in the Netherlands: Design, efficiency gains and perspectives. Amsterdam: Statistics Netherlands Discussion Paper.
   Google Scholar
• Visintin, S., Tijdens, K., & van Klaveren, M. (2015). Skill mismatch among migrant workers: Evidence from a large multi-country dataset. IZA Journal of Development and Migration, 4, 1–34. doi:10.1186/s40176-015-0040-0
   Google Scholar