Abstract
Many European countries are facing the challenge of increasing the effective retirement age. Increasing the effective retirement age also requires that older employees are voluntarily willing to continue working. A worker who is willing to retire but is not allowed to retire might experience a negative impact on his or her well-being. This articles studies the determinants of the willingness to retire: the job, health, and financial situation of the older worker, and other socio-demographic characteristics. To do this, the micro data of the Survey of Health, Ageing and Retirement in Europe are used, which contains a binary question about willingness to retire. Based on the random effects logit estimator, we find that the job situation of the worker and the retirement of the partner are important drivers of the willingness to retire. Specifically, those willing to retire are more frequently employed in jobs that are mentally and physically demanding. They also feel less appreciated by the management or their colleagues and report to have fewer opportunities to get promotion. The willingness to retire is higher if the older worker has a retired partner. In the countries with the lowest rates of willingness to retire, the workers have better working conditions and are more easily able to make ends meet.
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Notes
Austria, Belgium, Denmark, France, Germany, Netherlands, Spain, Sweden, and Switzerland. This study used the first (2004–2005), second (2006–7), fourth (2011) and fifth (2013) observation period of the SHARE data.
Using a fixed effects logit regression is no solution as the estimates of the individual effects are biased and poorly estimated when the number of time periods is small. This problem is known as the incidental parameter problem. The poor estimates of the individual effects then contaminate the rest of the coefficients estimated through the maximum likelihood estimation procedure (Greene, 2004). A solution is to eliminate the individual effects by conditioning the probability of the dependent variable for each respondent on the number of observations for which the respondent is willing to retire (Chamberlain, 1980; Greene, 2012). In this way, the conditional probability does not include individual effects and therefore they are no longer estimated when the resulting conditional likelihood estimator is estimated. One important drawback of this method is that it drops respondents that are willing to retire in each observation. These respondents do not provide any information as the conditional probability is one. In this way, only the older workers who made the transition from not willing to retire to willing to retire and the reverse transition are included in the estimated sample. This reduces the sample size severely.
The third observation period (2008–9) is special as it focuses on people’s life history (SHARELIFE).
Changing jobs could be an alternative option but older workers change jobs less frequently than younger workers. The number of jobs people have declines with age, workers change jobs more often between 25 and 35 than towards the end of their career. Charni (2022) shows that employment opportunities decrease with age and that older workers experience longer unemployment spells. It might also be harder for older employees to find a new job due to age discrimination. See e.g. Baert et al., 2016) for Belgium and Albert et al. (2011) for Spain. Lain et al. (2019) provide another reason. They argue that older workers are in a precarious situation, due to the fact that they know they have to work longer. This might have the consequence that they aim less for changing jobs out of fear for having to accept a lower quality job out of necessity.
The odds are based on a ratio calculation. It expresses the probability of being willing to retire divided by the probability of being not willing to retire. The odds ratio (OR) is the ratio of two odds. The odds ratio (OR) expresses the odds for having a more physically demanding job (‘not agree’) divided by the odds for having not a physically demanding job (‘agree’).
The estimations including the interactions are available on request.
An example is the points system that has been proposed by the Belgian Commission for Pension Reform 2020–2040 (Academische Raad van Pensioenen, 2017). In this system, each working year is equal to one point. Workers with a higher income than average or with a physically demanding job are receiving more than one point. At the end of the working career, the points are accumulated and multiplied by the value of the point and by a conversion coefficient.
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Acknowledgements
This paper uses data from Survey of Health, Ageing and Retirement in Europe (SHARE) Waves 2, 4 and 5 (DOIs: 10.6103/SHARE.w2.260, 10.6103/SHARE.w4.111, 10.6103/SHARE.w5.100). The SHARE data collection has been primarily funded by the European Commission through the FP5 (QLK6-CT-2001-00360), FP6 (SHARE-I3: RII-CT-2006-062193, COMPARE: CIT5-CT-2005-028857) and FP7 (SHARE-PREP: N°211909, SHARE-LEAP: N°227822, SHARE M4: N°261982). Additional funding from the U.S. National Institute on Aging (U01_AG09740-13S2, P01_AG005842, P01_AG08291, P30_AG12815, R21_AG025169, Y1-AG-4553-01, IAG_BSR06-11, OGHA_04-064), the German Ministry of Education and Research and from various national funding sources is gratefully acknowledged (see www.share-project.org).
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This research is supported by the Special Research Fund of Ghent University and the National Bank of Belgium, both granted to Lieze Sohier.
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Sohier, L., Defloor, B., Van Ootegem, L. et al. Determinants of the Willingness to Retire of Older Workers in Europe. Soc Indic Res 164, 1017–1041 (2022). https://doi.org/10.1007/s11205-022-02991-w
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DOI: https://doi.org/10.1007/s11205-022-02991-w