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Well-Being During the Transition from Work to Retirement

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Abstract

We investigate the consequences of retirement from work for the overall well-being of individuals aged 50 and above. Well-being is captured by two different concepts: life satisfaction and agency-freedom, i.e. the evaluation of a person’s ability to do the things s/he wants to do and be who s/he wants to be. We use three observation periods of the Survey of Health, Ageing and Retirement in Europe and include nine European countries. The sample counts 62,082 observations (38,344 individuals) of at least 50 years old. A fixed-effects estimation approach is used so that differences in (time-invariant) individual characteristics are taken into account. We control for changes in financial and health situations of the individual and the situations of the partner. When retiring, people do not immediately report (on average) a different level of life satisfaction, but after 2 years, life satisfaction decreases compared to the beginning of the retirement [identified as Atchley’s honeymoon effect (The sociology or retirement, Wiley, New York, 1976)]. If well-being is expressed as agency-freedom, well-being is immediately positively affected, and this effect does not change after 2 years of retirement. This paper also investigates several forms of heterogeneities in the transition from work to retirement. We consider partial, early and joint retirement, part-time employment and self-employment, and job quality. We find that there is no difference in overall well-being between being partially and fully retired, between being retired before or after the normal retirement age or between those who retire simultaneously with their partner and those who do not. However, for some older workers, such as those employed with a low-quality job, retirement can be a relief from their current employment status. In summary, a policy for longer working careers is, on average, not detrimental to well-being, but some specific groups need special treatment.

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Notes

  1. The Symptom Checklist-90 is a checklist for mental and physical complaints, making use of items on eight dimensions: fear, agorafobia, depression, somatic complaints, distrust, malfunctioning, problems with sleeping, and feelings of hostility.

  2. The first observation does not contain the well-being questions and the third is a special observation, focusing on people’s life history (SHARELIFE).

  3. The sample is unbalanced as not every participant has three observations. For estimations, an unbalanced panel is problematic if the missing variables are not random but selective. The SHARE project is well aware of this potential problem and keeps data attrition and non-responses as limited as possible (Börsch-Supan et al. 2013). As robustness check, we estimate the regressions also with a balanced sample (N = 33,465). The FE results are similar to the estimates in Table 3. The results are available on request.

  4. A respondent in SHARE receives pension benefits if this person receives an income from (at least) one of the following sources: (1) public old-age pension, (2) public old-age supplementary pension or public old-age second pension and/or (3) public early retirement or pre-retirement pension.

  5. The overlap with partial retirement is limited (compared to the overlap between partial and early): 15.69% of the partial retirees are jointly retired with their partner, while this is 19.04% of the full retirees.

  6. We talk about CAS when we refer to both variables because the results are similar (for CAS-internal and CAS-external). When the results are different for the two variables, we refer to the specific variable. We discuss the findings without mentioning the size nor the statistical significance of the estimates. The findings are significantly different from 0 at (at least) a 5 percent significance level. If the estimated effect is not significantly different from 0 at a 5 percent significance level, we say that there is no change in well-being.

  7. The covariance between the variables ‘employment status’ and ‘health’ is quite large. Consequently, it is difficult to determine the relative contribution of employment status and health to the explained variance of overall well-being.

  8. For example, the European Commission (2012a) classified the Netherlands in a group together with the Nordic countries as they all combine generous benefits with strict job search requirements. Esping-Andersen et al. (2001) point to similarities between the pension systems in the Netherlands and Denmark as they both “combine Beverdigean basic pensions, financed out of the general tax revenues, with a funded Bismarckian extension of earnings-related occupational pensions, which allows for a better risk diversification combined with higher rates of return” (p. 243). Following the argument of Van der Veen and van der Brug (2013) that Switzerland entails strong elements of universalism as well (and thus is rather a hybrid case than a pure liberal state) and to avoid having a country group (liberal) of only one country, we classified Switzerland among the social-democratic regimes as well.

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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: https://doi.org/10.6103/share.w2.260, https://doi.org/10.6103/share.w4.111, https://doi.org/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: No. 211909, SHARE-LEAP: No. 227822, SHARE M4: No. 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).

Funding

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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  1. Department of Economics, Faculty of Economics and Business Administration, Ghent University, Sint-Pietersplein 6, 9000, Ghent, Belgium

    Lieze Sohier, Luc Van Ootegem & Elsy Verhofstadt

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  1. Lieze Sohier
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Appendices

Appendix 1: The Rotated Factor Loadings

See Table 8.

Table 8 The rotated factor loadings
Full size table

Appendix 2: Instrumental Variable (IV) Approach

The IV approach is a two-stage estimation procedure in which in the first stage, the probability of being retired (the employment status is considered binary: employed or retired) is estimated by two instruments. In the second stage, the predicted values of the employment status from the first stage estimate the effect of the employment status on well-being. As the employment status is binary, we use Mundlak’s correction of a random-effects logit approach in the first stage of the IV. The second stage is an FE estimation. We prefer a random-effects logit estimator (to a pooled logit estimator) as it takes into account unobserved heterogeneity between (groups of) individuals. The random-effects logit estimator assumes that the (unobserved) individual effects are not correlated with the independent variables in the regression. This assumption is, however, difficult to hold as all variables are self-reported. For example, pessimistic respondents likely underrate their financial or health situation, which could lead to inconsistent estimates. We do not consider a (conditional) fixed-effects logit estimation approach, as this approach would reduce the sample severely. The estimator drops all respondents who have not made a transition from work to retirement (i.e. solution to the incidental parameter problem, see Chamberlain (1980), Greene (2012) for more information). Mundlak can satisfy the assumption of no correlation between the individual effects and the explanatory variables by adding the individual means of all time-varying variables in the regression (Mundlak 1978). In this way, the individual effects are a linear function of the individual means and the error term is normally distributed and uncorrelated with the explanatory variables.

The two instruments are both binary variables (labelled as ‘early’ and ‘normal’) and capture whether the person has reached or is over the (early) retirement age or whether the person is younger (reference category). Table 9 displays the official early and normal retirement ages for each country in the sample. The statistics are retrieved from the OECD (2009, 2011b, 2013b). Denmark and the Netherlands do not have early retirement programmes. Sweden has no mandatory retirement age. Consequently, for these countries, we have no information for one of the two instruments. We limit our sample to six of the nine countries (Austria, Belgium, France, Germany, Spain and Switzerland).

Table 9 Official early and normal retirement age.
Full size table

Table 10 displays the FE results with the limited sample (as in Table 3) and the IV results. The employment status is a binary variable (employed or retired). The IV estimates are larger than the FE estimates. In the first stage regression, the instruments are individually (p = 0.00) and jointly (χ2(2) = 69.24, p = 0.00) significant predictors of retirement behaviour. The p-value (p = 0.275) of the Hausman endogeneity test indicates that the employment status is exogenous. This means that the assumption of exogeneity for the FE estimator cannot be rejected. The endogeneity bias in the estimated effects is not significant (Tables 9 and 10).

Table 10 FE results and IV results of the effect of employment status on life satisfaction and agency variables
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Sohier, L., Van Ootegem, L. & Verhofstadt, E. Well-Being During the Transition from Work to Retirement. J Happiness Stud 22, 263–286 (2021). https://doi.org/10.1007/s10902-020-00228-6

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