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Wage data collected by telephone interviews: an empirical analysis of the item nonresponse problem and its implications for the estimation of wage functions

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  • Alfonso Sousa-Poza
  • Fred Henneberger

Abstract

In this paper, the item nonresponse problem associated with wage data collected by telephone surveys is analysed. Using data from the 1998 Swiss Labour Force Survey (SLFS) and data on interviewers, it is shown that the response decision can only partially be explained by the chracteristics of the interview situation, the respondent, and the interviewer. This suggests that the response inclination is, to a large extent, randomly distributed amongst the underlying population. It is therefore argued that wage functions estimated using only the observed wage data are not biased by the large (wage) item nonresponse encountered in telephone interviews.

Suggested Citation

  • Alfonso Sousa-Poza & Fred Henneberger, 2000. "Wage data collected by telephone interviews: an empirical analysis of the item nonresponse problem and its implications for the estimation of wage functions," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 136(I), pages 79-98, March.
    • Handle: RePEc:ses:arsjes:2000-i-4
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    Cited by:

    1. Henneberger, Fred & Sousa-Poza, Alfonso, 2002. "Beweggründe und Determinanten zwischenbetrieblicher Mobilität: Die Schweiz in einer internationalen Perspektive (Motives and determinants of job-to-job mobility : Switzerland in an international persp," Mitteilungen aus der Arbeitsmarkt- und Berufsforschung, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 35(2), pages 205-231.
    2. Fertig, Michael & Görlitz, Katja, 2013. "Missing wages: How to test for biased estimates in wage functions?," Economics Letters, Elsevier, vol. 118(2), pages 269-271.
    3. Enrico Bolzani & Ramses H. Abul Naga, 2002. "La Distribution des Salaires en Suisse: Quelques Observations sur la Récession des Années 90," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 138(II), pages 115-136, June.
    4. Fertig, Michael & Görlitz, Katja, 2012. "Item Nonresponse in Wages: Testing for Biased Estimates in Wage Equations," Ruhr Economic Papers 333, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    5. Regina Riphahn & Oliver Serfling, 2005. "Item non-response on income and wealth questions," Empirical Economics, Springer, vol. 30(2), pages 521-538, September.
    6. Florian Zainhofer, 2007. "Life Cycle Portfolio Choice: A Swiss Perspective," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 143(II), pages 187-238, June.
    7. Miriam Rinawi & Uschi Backes-Gellner, 2020. "Firms’ method of pay and the retention of apprentices," Oxford Economic Papers, Oxford University Press, vol. 72(1), pages 269-291.
    8. Alfonso Sousa‐Poza, 2004. "Is the Swiss Labor Market Segmented? An Analysis Using Alternative Approaches," LABOUR, CEIS, vol. 18(1), pages 131-161, March.
    9. Michael Fertig & Katja Görlitz, 2012. "Item Nonresponse in Wages: Testing for Biased Estimates in Wage Equations," Ruhr Economic Papers 0333, Rheinisch-Westfälisches Institut für Wirtschaftsforschung, Ruhr-Universität Bochum, Universität Dortmund, Universität Duisburg-Essen.
    10. repec:zbw:rwirep:0333 is not listed on IDEAS
    11. Henneberger, Fred & Sousa-Poza, Alfonso, 2002. "Beweggründe und Determinanten zwischenbetrieblicher Mobilität: Die Schweiz in einer internationalen Perspektive (Motives and determinants of job-to-job mobility : Switzerland in an international persp," Mitteilungen aus der Arbeitsmarkt- und Berufsforschung, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 35(2), pages 205-231.
    12. David Dorn & Alfonso Sousa-Poza, 2005. "The Determinants of Early Retirement in Switzerland," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 141(II), pages 247-283, June.

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