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Does Quality of Work Life Affect Men and Women’s Retirement Planning Differently?

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Abstract

Population ageing in most western countries involves an increase in public expenditures and the risk of labour shortage. One way to meet these challenges is to retain older workers in the labour market by improving their work life. This article assesses whether quality of work life measures differ in importance for male and female workers in their retirement planning. This study applies samples of workers and retirees born in 1940 and 1945 drawn from Danish panel surveys in 1997 and 2002 and merged with longitudinal register data. Results suggest that male and female workers’ retirement plans are affected differently by various aspects of the job. Indeed, job demands lower planned retirement age, while increases in earnings, work hour satisfaction, and the opportunity to use skills on the job increase this age for men and women. Nevertheless, the impact of earnings is largest for men, and only male workers attach importance to job control and job security. These gender differences suggest, first, that men are more influenced than women by the quality of job dimensions in their retirement planning and, second, that an employer-initiated effort directed towards retaining older workers at the workplace will not necessarily be as effective for female as for male workers.

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Notes

  1. In 2005, the labour force participation rate for men aged 50–59 years was 88.7% (OECD 2007).

  2. In 2005, more than 218,000 60- to 66-year olds received VERP benefits corresponding to 48% of the age group (Department of Unemployment Insurance 2007).

  3. At the moment where survey and register data were merged, register data from 2002 were not available.

  4. Table 3 of Appendix shows exactly which variables were merged in from register data.

  5. Correlation coefficients are not shown but are available on request.

  6. Further, the standard decomposition between income effect and substitution effect of earnings on retirement age is confirmed by the fact that, in general, no wealth effect is shown.

  7. For further discussion of gender differences with respect to job control, see Blekesaune and Solem (2005).

  8. These results are not shown but are available on request.

  9. I do not model the jointness of couples’ retirement decisions, as do Hurd (1990), Gustman and Steinmeier (2000), and Christensen and Datta Gupta (1994) because this issue is beyond the scope of this paper.

  10. Information on work-related factors is obtained from the first wave for these individuals.

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Acknowledgement

This work is part of the research of the Graduate School for Integration, Production and Welfare. Financial support from the Danish Social Science Research Council is gratefully acknowledged.

I am grateful for comments by Peder Pedersen, Paul Bingley, Michael Rosholm, Torben Tranæs, Nabanita Datta Gupta and two anonymous referees. Thanks also to the participants at the 4th International Research Conference on Social Security 2003 in Antwerp, the PhD Workshop at the Graduate School for Integration, Production and Welfare 2003 in Odense and the Workplace and Gender Workshop 2005 in Copenhagen. All remaining errors are my own.

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  1. SFI—The Danish National Centre for Social Research, Herluf Trolles Gade 11, DK-1052, Copenhagen K, Denmark

    Mona Larsen

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Appendix. Selection of sample

Appendix. Selection of sample

In 1997, a representative sample of individuals born every fifth year from 1920 to 1945, consisting of 5,864 individuals, were interviewed in their homes. The response rate was 70%. In 2002, the same respondents were contacted primarily by phone for a second interview. Seventy-nine percent of the first wave respondents participated in the second wave. Thus, 4,634 individuals form part of both waves.

To minimize sample selection due to retirement, I limit my sample to individuals born in 1940 and 1945, i.e. people aged about 52 and 57 years in 1997. This number corresponds to 2,658 individuals. I also restrict my sample to wage earners (or those temporarily unemployed) in 1997. Consequently, one source of potential sample selection is omission of already retired individuals and individuals who were self-employed. However, as key information on quality of work life measures and many relevant economic characteristics are unavailable for these individuals, including them in the analysis is not possible. Restricting the sample to be representative for wage earners thus results in a sample of 1,836 individuals, corresponding to 69% of the original sample for the two birth cohorts.

A large part (86%) of the selected sample of 1,836 individuals participated in the second wave in 2002. I extend the sample with observations for 2002 for these individuals who are wage earners (or temporarily unemployed) in the second wave. I also include observations for those who retired between the two waves, as I have full information on all covariates on these individuals.Footnote 10 Planned retirement age is set equal to the actual retirement age (reported in the survey) for this group. Including observations from the second wave leaves a sample of 3,360 person-wave observations.

Finally, since the dependent variable is planned (or actual) retirement age, I am only able to include person-wave observations for individuals who report a given age in the wave in question when asked about planned (or actual) retirement age. Unfortunately, in 20% of the cases, the answer was ‘don’t know’ or ‘as long as possible’. While it is feasible to set ‘as long as possible’ to a maximum of, say, 75 or 85 years as in some previous studies (e.g. Dwyer and Mitchell 1999), I hesitate to do so, as this latter group of individuals turns out to be a very heterogeneous group whose characteristics do not generally resemble those individuals who cite a high retirement age. When I throw out person-wave observations without information about an exact planned (or actual) retirement age, I end up with a sample consisting of 2,704 person-wave observations.

Table 2 Quality of work life measures, wording and creation of variables
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Table 3 Descriptive statistics, men and women (SD in parentheses)
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Table 4 Pooled OLS estimates of the effect of job demands measures on planned retirement age for men and women
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Table 5 Pooled OLS estimates of the effect of job control measures on planned retirement age for men and women
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Larsen, M. Does Quality of Work Life Affect Men and Women’s Retirement Planning Differently?. Applied Research Quality Life 3, 23–42 (2008). https://doi.org/10.1007/s11482-008-9045-7

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