Skip to main content

Advertisement

SpringerLink
Log in

Work Transitions, Gender, and Subjective Well-Being

  • Published:
Applied Research in Quality of Life Aims and scope Submit manuscript

A Correction to this article was published on 16 October 2020

This article has been updated

Abstract

We examine the gender differences in the magnitude of the effects of work transitions on subjective well-being using the United Kingdom Household Longitudinal Study data spanning from 2009 to 2016. We use the General Health Questionnaire (GHQ-12) as a measure of self-reported levels of subjective well-being and apply the propensity score matching technique combined with the difference-in-differences strategy for the analysis. Our findings suggest that men tend to experience larger shifts in subjective well-being when becoming employed or unemployed compared with women; this gender gap is larger when becoming unemployed than employed. We further test and confirm that this gender gap widens between married couples and suggest that social norms or gender roles may be the underlying reasons for the gender differences.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

Change history

Notes

  1. In this study, we use the word unemployed in a broader sense. Instead of applying the strict economic definition of unemployment, which only captures those in the labor force, we use the term to indicate individuals who are not employed or not working. Our study sample may include individuals who are not in the labor force. However, we drop observations that reported themselves as a retiree, a full-time student, long-term sick or disabled, or as an unpaid worker in family business. In our study, we apply a broader concept to capture those who are traditionally considered as an out-of-the-labor force but who are willing to and available to work in the near future. Studies have shown that the strict definition of unemployment, which imposes a relatively short job search period, is likely to underestimate the unemployed, as well as the labor force (Furstenberg and Thrall 1975; Jones and Riddell 1999; Brandolini et al. 2006). The International Labour Organization’s (ILO) recent relaxation in defining unemployment also suggests considering those who are currently not working or not seeking for a job but have arranged a new occupation that starts within the next three months as unemployed (ILO 2019). The eased, yet restrictive, definition opens up the possibility that a certain portion of those currently looking after family may indeed be in the labor force and considered as unemployed.

  2. A linear model with three treatment variables (with those who stayed employed in both t − 1 and t as a reference category) that indicate possible work transitions can be considered as an alternative model. The results from applying the linear panel data model with individual fixed effects are consistent with our main results presented in Table 2, using the DID-PSM method (see Appendix Table 7). However, Arkhangelsky and Imbens (2018) note that accounting for the group differences through additive fixed effects can be restrictive in a sense that it adjusts only for differences between groups by adjusting for the average covariate values and average treatment. They suggest using the propensity score weighting as an alternative to a fixed-effect model to adjust for general group differences. We also find that the results from the DID-PSM method are more intuitive and easier to interpret compared with the linear model that uses one of the variables as the reference group, for example, those who stayed employed in both t − 1 and t.

  3. Rubin’s B checks the absolute standardized difference of the means of the linear index of the propensity score in the treated and control groups, and Rubin’s R gives the ratio of the variances of the propensity score in the treated and control groups. Both indices are measured before and after matching, and the treatment and control groups are considered as balanced if Rubin’s B is less than 25 and Rubin’s R is between 0.5 and 2 (Rubin 2001). Results are reported in Appendix Table 8.

  4. Regional variation in the unemployment rate or social work norms may affect individuals’ well-being. For example, individuals in a reference group with a relatively high unemployment rate or weak work norms are likely to be less distressed from unemployment (Clark 2003; Stutzer and Lalive 2004).

  5. For the main results, we try different matching techniques such as one-to-one, 5:1 nearest neighbor, Gaussian kernel, and radius matching with caliper 0.01 and 0.05, and check whether differences occur in each estimation (Table 2).

  6. The final sample size is larger for women than men as the original survey sample contained more women than men (roughly 54% of the original sample and 56% of the final sample are female observations). Also, unlike the case where applying the strict definition of unemployed drops relatively more female samples than male samples, our sample keeps many female subjects as we apply a broader definition of unemployed (see footnote 1 for more detail).

  7. We conduct balance checks on each matching algorithm using Rubin’s B and R and reported the results in Appendix Table 8. The Rubin’s R value of each matching technique stays in the range of 0.5 and 2 for both employed and unemployed samples. However, the Rubin’s B is higher than 25 when kernel matching and radius matching with caliper 0.05 are applied to the employed sample, indicating that those matchings are insufficient for balancing the treatment and control groups.

  8. In our sample, married men contributed about 62.15%, on average, to the household income, and approximately 73.45% of married men earned more than 50% of the household income.

  9. Our study sample shows that individuals spend longer hours, on average, on housework per week when unemployed than when employed. However, women, in general, spend around five to eight more hours on housework per week than their male counterparts. Summary statistics on the level and change in hours per week on housework are available in Appendix Table 11.

References

  • Arkhangelsky, D., & Imbens, G. (2018). The role of the propensity score in fixed effect models (no. w24814). National Bureau of Economic Research.

  • Becker, G. S. (1965). A theory of the allocation of time. The Economic Journal, 75(299), 493–517.

    Article  Google Scholar 

  • Bird, C. E. (1999). Gender, household labor, and psychological distress: The impact of the amount and division of housework. Journal of Health and Social Behavior, 40(1), 32–45.

    Article  Google Scholar 

  • Blanchflower, D. G., & Oswald, A. J. (2004). Well-being over time in Britain and the USA. Journal of Public Economics, 88(7/8), 1359–1386.

    Article  Google Scholar 

  • Blavatskyy, P. R. (2011). Loss aversion. Economic Theory, 46(1), 127–148.

    Article  Google Scholar 

  • Boyce, C. J., Wood, A. M., Banks, J., Clark, A. E., & Brown, G. D. (2013). Money, well-being, and loss aversion: Does an income loss have a greater effect on well-being than an equivalent income gain? Psychological Science, 24(12), 2557–2562.

    Article  Google Scholar 

  • Boye, K. (2010). Time spent working – Paid work, housework and the gender difference in psychological distress. European Societies, 12(3), 419–442.

    Article  Google Scholar 

  • Brandolini, A., Cipollone, P., & Viviano, E. (2006). Does the ILO definition capture all unemployment? Journal of the European Economic Association, 4(1), 153–179.

    Article  Google Scholar 

  • Brebner, J. (2003). Gender and emotions. Personality and Individual Differences, 34(3), 387–394.

    Article  Google Scholar 

  • Clark, A. (2003). Unemployment as a social norm: Psychological evidence from panel data. Journal of Labor Economics, 21(2), 323–351.

    Article  Google Scholar 

  • Clark, A. E., & Oswald, A. J. (1994). Unhappiness and unemployment. The Economic Journal, 104(424), 648–659.

    Article  Google Scholar 

  • Coad, A., & Binder, M. (2014). Causal linkages between work and life satisfaction and their determinants in a structural VAR approach. Economics Letters, 124(2), 263–268.

    Article  Google Scholar 

  • Creed, P. A. (1999). Predisposing factors and consequences of occupational status for long-term unemployed youth: A longitudinal examination. Journal of Adolescence, 22(1), 81–93.

    Article  Google Scholar 

  • Crowley, M. S. (1998). Men's self-perceived adequacy as the family breadwinner: Implications for their psychological, marital, and work-family well-being. Journal of Family and Economic Issues, 19(1), 7–23.

    Article  Google Scholar 

  • Dolan, P., Peasgood, T., & White, M. (2008). Do we really know what makes us happy? A review of the economic literature on the factors associated with subjective well-being. Journal of Economic Psychology, 29(1), 94–122.

    Article  Google Scholar 

  • Ferreira, J. A., Reitzle, M., Lee, B., Freitas, R. A., Santos, E. R., Alcoforado, L., & Vondracek, F. W. (2015). Configurations of unemployment, reemployment, and psychological well-being: A longitudinal study of unemployed individuals in Portugal. Journal of Vocational Behavior, 91, 54–64.

    Article  Google Scholar 

  • Frijters, P., Johnston, D. W., & Shields, M. A. (2014). The effect of mental health on employment: Evidence from Australian panel data. Health Economics, 23(9), 1058–1071.

    Article  Google Scholar 

  • Furstenberg, F. F., & Thrall, C. A. (1975). Counting the jobless: The impact of job rationing on the measurement of unemployment. The Annals of the American Academy of Political and Social Science, 418, 45–59.

    Article  Google Scholar 

  • Gandelman, N., & Hernández-Murillo, R. (2013). What do happiness and health satisfaction data tell us about relative risk aversion? Journal of Economic Psychology, 39, 301–312.

    Article  Google Scholar 

  • Gebel, M., & Voßemer, J. (2014). The impact of employment transitions on health in Germany. A difference-in-differences propensity score matching approach. Social Science & Medicine, 108, 128–136.

    Article  Google Scholar 

  • Gough, M., & Killewald, A. (2011). Unemployment in families: The case of housework. Journal of Marriage and Family, 73, 1085–1100.

    Article  Google Scholar 

  • Grün, C., Hauser, W., & Rhein, T. (2010). Is any job better than no job? Life satisfaction and re-employment. Journal of Labor Research, 31(3), 285–306.

    Article  Google Scholar 

  • Harinck, F., Dijk, E. V., Beest, I. V., & Mersmann, P. (2007). When gains loom larger than losses: Reversed loss aversion for small amounts of money. Psychological Science, 18(12), 1099–1105.

    Article  Google Scholar 

  • Harryson, L., Strandh, M., & Hammarström, A. (2012). Domestic work and psychological distress – What is the importance of relative socioeconomic position and gender inequality in the couple relationship? PLoS One, 7(6), e38484.

    Article  Google Scholar 

  • Heckman, J. J., Ichimura, H., & Todd, P. E. (1997). Matching as an econometric evaluation estimator: Evidence from evaluating a job training programme. The Review of Economic Studies, 64(4), 605–654.

    Article  Google Scholar 

  • International Labour Office (2019). Quick Guide on Interpreting the Unemployment Rate. Geneva: ILO. ISBN : 978–92–2-133323-4 (web pdf). https://ilo.org/wcmsp5/groups/public/%2D%2D-dgreports/%2D%2D-stat/documents/publication/wcms_675155.pdf. Accessed 1 May 2020.

  • Jones, S. R. G., & Riddell, W. C. (1999). The Measurement of Unemployment: An Empirical Approach. Econometrica, 67, 147–162. https://doi.org/10.1111/1468-0262.00007.

    Article  Google Scholar 

  • Kahneman, D., & Tversky, A. (1984). Choices, values, and frames. American Psychologist, 39(4), 341–350.

    Article  Google Scholar 

  • Kassenboehmer, S. C., & Haisken-DeNew, J. P. (2009). You’re fired! The causal negative effect of entry unemployment on life satisfaction. The Economic Journal, 119(536), 448–462.

    Article  Google Scholar 

  • Kermer, D. A., Driver-Linn, E., Wilson, T. D., & Gilbert, D. T. (2006). Loss aversion is an affective forecasting error. Psychological Science, 17(8), 649–653.

    Article  Google Scholar 

  • Matud, M. P. (2004). Gender differences in stress and coping styles. Personality and Individual Differences, 37(7), 1401–1415.

    Article  Google Scholar 

  • Novemsky, N., & Kahneman, D. (2005). How do intentions affect loss aversion? Journal of Marketing Research, 42(2), 139–140.

    Article  Google Scholar 

  • Nyman, C., Reinikainen, L., & Eriksson, K. (2018). The tension between gender equality and doing gender; swedish couples' talk about the division of housework. Women's Studies International Forum, 68, 36–46.

    Article  Google Scholar 

  • Park, A., Bryson, C., Clery, E., Curtice, J., & Phillips, M. (eds.) (2013), British social attitudes: The 30th report, London: NatCen Social Research, available online at: www.bsa-30.natcen.ac.uk

  • Park, S., Chan, K. C. G., & Williams, E. C. (2016). Gain of employment and perceived health status among previously unemployed persons: Evidence from a longitudinal study in the United States. Public Health, 133, 83–90.

    Article  Google Scholar 

  • Poláčková Šolcová, I., & Lačev, A. (2017). Differences in male and female subjective experience and physiological reactions to emotional stimuli. International Journal of Psychophysiology, 117, 75–82.

    Article  Google Scholar 

  • Rosenbaum, P. R., & Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70(1), 41–55.

    Article  Google Scholar 

  • Rubin, D. B. (2001). Using propensity scores to help design observational studies: Application to the tobacco litigation. Health Services & Outcomes Research Methodology, 2(3–4), 169–188.

    Article  Google Scholar 

  • Schuring, M., Mackenbach, J., Voorham, T., & Burdorf, A. (2011). The effect of re-employment on perceived health. Journal of Epidemiology and Community Health, 65(7), 639–644.

    Article  Google Scholar 

  • Soobedar, Z. (2011). A semiparametric analysis of the rising breadwinner role of women in the UK. Review of Economics of the Household, 9(3), 415–428.

    Article  Google Scholar 

  • Speakman, S., & Marchington, M. (1999). Ambivalent patriarchs: Shiftworkers, 'Breadwinners' and housework. Work, Employment and Society, 13(1), 83–105.

    Google Scholar 

  • Stratton, L. S. (2012). The role of preferences and opportunity costs in determining the time allocated to housework. The American Economic Review, 102(3), 606–611.

    Article  Google Scholar 

  • Stutzer, A., & Lalive, R. (2004). The role of social work norms in job searching and subjective well-being. Journal of the European Economic Association, 2(4), 696–719.

    Article  Google Scholar 

  • Thomas, C., Benzeval, M., & Stansfeld, S. A. (2005). Employment transitions and mental health: An analysis from the british household panel survey. Journal of Epidemiology and Community Health, 59(3), 243–249.

    Article  Google Scholar 

  • Treas, J., Van der Lippe, T., & ChloeTai, T. (2011). The happy homemaker? Married Women's well-being in cross-National Perspective. Social Forces, 90(1), 111–132.

    Article  Google Scholar 

  • Unger, S., Tisch, A., & Tophoven, S. (2018). Age and gender differences in the impact of labour-market transitions on subjective health in Germany. Scandinavian Journal of Public Health, 46, 49–64.

    Article  Google Scholar 

  • University of Essex. Institute for Social and Economic Research, NatCen Social Research and Kantar Public, [producers]: Understanding Society: Wave 1-6, 2009-2015 [computer file]. 8th Edition. Colchester, Essex: UK Data Service [distributor], March 2017. SN: 6614, https://doi.org/10.5255/UKDASN-6614-8.

  • van der Meer, P. H. (2014). Gender, unemployment and subjective well-being: Why being unemployed is worse for men than for women. Social Indicators Research, 115(1), 23–44.

    Article  Google Scholar 

  • Ward, S. J., & King, L. A. (2017). Work and the good life: How work contributes to meaning in life. Research in Organizational Behavior, 37, 59–82.

    Article  Google Scholar 

  • Winkelmann, L., & Winkelmann, R. (1995). Happiness and unemployment: A panel data analysis for Germany. Applied Economics Quarterly, 41(4), 293–307.

    Google Scholar 

  • Winkelmann, L., & Winkelmann, R. (1998). Why are the unemployed so unhappy? Evidence from panel data. Economica, 65, 1–15.

    Article  Google Scholar 

  • Wulfgramm, M. (2014). Life satisfaction effects of unemployment in Europe: The moderating influence of labour market policy. Journal of European Social Policy, 24(3), 258–272.

    Article  Google Scholar 

Download references

Acknowledgements

We thank Jaesung Choi and the seminar participants at Yonsei University, 2019 Korea’s allied Economic Associations Annual Meeting, 14th Joint Economics Symposium of Six Leading East Asian Universities, and the Labor Economics Working Group (LEWG) in Korea for their generous comments. Understanding Society is an initiative funded by the Economic and Social Research Council and various Government Departments, with scientific leadership by the Institute for Social and Economic Research, University of Essex, and survey delivery by NatCen Social Research and Kantar Public. The research data are distributed by the UK Data Service. This work was supported by the Yonsei University Research Grant of 2020.

Author information

Authors and Affiliations

  1. School of Economics, Yonsei University, Seoul, Republic of Korea

    Hye Yoon Chung & Youjin Hahn

Authors
  1. Hye Yoon Chung
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Youjin Hahn
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Youjin Hahn.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendices

Appendix 1

Table 6 The following GHQ-12 Questionnaire is extracted from the official guide on the UKHLS survey questionnaire index for wave 6 offered by the Understanding Society
Full size table

Appendix 2

Table 7 FE regression results
Full size table
Table 8 Balance check by matching techniques
Full size table
Table 9 Robustness Check on Table 8
Full size table
Table 10 Robustness check on Table 2
Full size table
Table 11 Summary statistics on the Hours per week on housework variable
Full size table
Table 12 Robustness Check on Table 8 using change in GHQ-12 Likert score [t, t-2]
Full size table
Table 13 Robustness Check on Table 2 using change in GHQ-12 Likert score [t, t-2]
Full size table

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chung, H.Y., Hahn, Y. Work Transitions, Gender, and Subjective Well-Being. Applied Research Quality Life 16, 2085–2109 (2021). https://doi.org/10.1007/s11482-020-09860-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11482-020-09860-z

Keywords

Search

Navigation