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Children, unhappiness and family finances

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Abstract

The common finding of a zero or negative correlation between the presence of children and parental well-being continues to generate research interest. We consider international data, including well over one million observations on Europeans from 11 years of Eurobarometer surveys. We first replicate this negative finding, both in the overall data and then for most different marital statuses. Children are expensive: controlling for financial difficulties turns our estimated child coefficients positive. We argue that difficulties paying the bills explain the pattern of existing results by parental education and income and by country income and social support. Last, we underline that not all children are the same, with stepchildren commonly having a more negative correlation with well-being than children from the current relationship.

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Notes

  1. China, India, Israel, Japan, Mexico, New Zealand, the Philippines, South Africa, Surinam and Taiwan.

  2. Clark et al. (2018) discuss a number of results from the existing literature, available in Online Annex 5 at http://cep.lse.ac.uk/origins/onlinematerial.pdf. These broadly show a divergence of findings in the cross-sectional literature, with negative estimated coefficients in, for example, Aassve et al. (2015), Alesina et al. (2004), Deaton and Stone (2014) and Stanca (2012), but small positive correlations in Aassve et al. (2012) and Cetre et al. (2016). Fixed effect analysis tends to produce more positive findings: see Clark et al. (2008), Stutzer and Frey (2006) and Figure 5.6 in Clark et al. (2018).

  3. The length of the SOEP panel does allow Myrskylä and Margolis (2014) to consider the relationship between parental life satisfaction and a small number of children up to teen ages. They find a positive life satisfaction effect around childbirth, but no significant relationship thereafter.

  4. A similar point applies to the instrumental variable analysis in Costa-Font et al. (2018), which relies on a 2007 parental leave reform in Germany. The children here are all fairly young.

  5. We in addition use cross-sectional data, where there may be a bias from happy people being more likely to have children in the first place (as in Cetre et al. 2016): even so, the correlation between children and parental well-being without controlling for financial difficulties is negative.

  6. See also Stanca (2012) for evidence from the World Values Survey.

  7. The regressions here, and in the rest of the paper, are OLS. We have checked that all of our main results hold in ordered logit and ordered probit regressions.

  8. This standard series is augmented by Special and Flash Eurobarometers on specific issues.

  9. These are the forty-two Eurobarometer surveys we use—2009 = #71.3; 2010 = #73.4; #74.2; 2011 = #75.3; #75.4; #76.3; 2012 = #77.4; #78.1; 2013 = #79.3; #79.4; #80.1; #80.2; 2014 = #81.1; #81.4; #81.5; #82.3; #82.4; 2015 = #83.1; #83.2; #83.3; #83.4; #84.2; #84.3; #84.4; 2016 = #85.2; #86.1; #86.2; #86.3; 2017 = #87.1; #87.3; #88.3; #88.4; 2018 = #89.1; #89.3; #90.1; #90.2; #90.3; #90.4 and 2019 = #91.2; #91.3: #91.5 and #92.1

  10. The labour force status categories in the Eurobarometer are Working; Responsible for ordinary shopping and looking after the home, or without any current occupation, not working; Student; Unemployed or temporarily not working; and Retired or unable to work. The schooling categories are up to 15 years, 16–19 years, 20+ years, Still Studying and No full-time education.

  11. The presence of any children in the household rises from 49% at age thirty to a peak of 75% at age 42 and then falls rapidly to 58% at age 50. As we only know about children who live in the household, we miss out adult children who have left home. This is another reason to split the sample by age, as under 45s who do not currently live with children are more likely never to have had any.

  12. We are grateful to an anonymous referee for suggesting this analysis.

  13. In our European data, we thus do not find that the children-happiness gap is correlated with family benefit scores. This is contrary to Glass et al. (2016). Note that our analysis uses different data covering only European countries and over a longer time period.

  14. The ISSP (www.issp.org) is a cross-national collaboration programme, conducting annual surveys on diverse topics relevant to social sciences. Established in 1984 by its founding members Australia, Germany, Great Britain and the USA, the ISSP has since included members covering various cultures around the globe. Its institutional members, each of them representing one nation, consist of academic organizations, universities or survey agencies.

  15. In Tables 8 and 9, the ISSP labour force status categories are In paid work, Unemployed and looking for a job, In education, Apprentice or trainee, Permanently sick or disabled, Retired, Domestic work, In compulsory military service or community service and Other. The schooling categories are in terms of Highest completed education level: No formal education; Primary school (elementary education); Lower secondary (secondary completed that does not allow entry to university: end of obligatory school); Upper secondary (programs that allows entry to university); Post secondary, non-tertiary (other upper secondary programs towards the labour market or technical formation); Lower level tertiary, first stage (also technical schools at a tertiary level); Upper level tertiary (Master, Doctor); and Cannot choose.

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Acknowledgements

We thank the Editor, five anonymous referees, Ed Diener, Carol Graham, Anthony Lepinteur and participants at the Age Well Accounts workshop in Vienna and the Demographic Aspects of Human Wellbeing Conference for their helpful comments.

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Authors and Affiliations

  1. Department of Economics, Dartmouth College, Hanover, NH, USA

    David G. Blanchflower

  2. GLO, Bloomberg and NBER, New York, NY, USA

    David G. Blanchflower

  3. Paris School of Economics – CNRS, Paris, France

    Andrew E. Clark

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  1. David G. Blanchflower
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  2. Andrew E. Clark
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Correspondence to David G. Blanchflower.

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Appendix

Appendix

Table 10 Life satisfaction by European country, 2009, 2015, 2019 and change 2019–2009
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Table 11 Detailed marital status and children information in the Eurobarometer
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Table 12 Marital status, children and life satisfaction across Europe: 2009–2019
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Table 13 Difficulty paying bills: Europe 2009–2019
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Table 14 Age, years of schooling and difficulties paying bills in the Eurobarometer
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Table 15 Life satisfaction, difficulty in paying bills, broad marital status and children: Europe 2009–2019
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Table 16 Life Satisfaction in the 2017 ISSP
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Table 17 Financial Difficulties in the 2017 ISSP
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Table 18 Unhappiness in the 2017 ISSP
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Blanchflower, D.G., Clark, A.E. Children, unhappiness and family finances. J Popul Econ 34, 625–653 (2021). https://doi.org/10.1007/s00148-020-00798-y

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