Informal care and long-term labor market outcomes☆
Introduction
The effects of informal care provision on caregiver's labor force outcomes have been subject to a large literature in the previous two decades. Labor supply reactions (of females, mostly) have been studied by, e.g., Carmichael and Charles (1998), Heitmueller (2007), Ciani (2012), Casado-Marín et al. (2011), Bolin et al. (2008), Ettner, 1995, Ettner, 1996, Crespo and Mira (2014), Heger (2014), Meng, 2012a, Meng, 2012b, where the effects range from small to very large (up to 30 percentage points) reductions in the probability to work for pay.2 The effect on working hours, as studied by, e.g., Wolf and Soldo (1994), Casado-Marín et al. (2011), Bolin et al. (2008), Ettner (1996), Johnson and Sasso (2000), and Van Houtven et al. (2013) are quite mixed, while wage penalties are more consistently found (Van Houtven et al., 2013, Carmichael and Charles, 2003, Heitmueller and Inglis, 2007).
All of these studies have in common that they look at the contemporaneous effect of caregiving on labor market outcomes. As many societies aim at increasing female labor force participation, one often reported policy implication is to set up more flexible work-arrangements to facilitate informal caregiving while keeping the job (Heitmueller, 2007). However, one might argue that negative short-term effects do not pose severe problems – both for the caregivers and societies as a whole – if they are not persistent. Caregiving spells typically last only a couple of years and as soon as caregivers who put their labor force participation on hiatus return to the labor market after cessation of their caregiving spell, the life-time opportunity costs of caregiving might not be too large. However, caregivers are often in the age of 50+ and might have problems to return into the labor force once they left it – either because they voluntarily decide to stay absent or because they cannot return due to labor market frictions.3 This would imply negative consequences that potentially add up over many years after their caregiving period. Thus, to draw conclusions about the holistic costs of care, it is necessary to turn to a longer-run perspective since the cost of caring might be more complex than forgone income for the time spent caring.
This study looks at longer term labor market effects up to eight years after care provision. Evaluating the persistence of effects is the main contribution of this paper. As far as we are aware, only three papers explicitly move away from the contemporaneous perspective. Fevang et al. (2012) use Norwegian data to study labor market outcomes up to around 10 years before and 5 years after the death of a lone parent and do find notable effects on labor market participation (for women, not for men) around the death which, however, are not persistent. On the other hand, reliance on social assistance increases persistently for men. Although the authors do not observe actual care provision these effects can largely be ascribed to informal care obligations. Skira (2015) explicitly takes into account the dynamic effects on labor supply as one of the first papers in this literature. She estimates a dynamic discrete choice model that is underpinned with a theoretical framework. Her results highlight existing labor market frictions for caregivers as their reduced labor supply in the US due to caregiving persists over time. Michaud et al. (2010) also estimate a structural model in order to look at dynamic effects of caregiving on employment. Yet, the authors do not explicitly look at long-run effects and effects beyond three periods after caregiving are not reported.
We use a representative German data set to assess short- and longer-term effects of care provision on labor market outcomes such as the probability to work full-time, to be in the labor force, the number of weekly working hours (conditional on working) and hourly wages. In Germany, the largest European economy, there were 2.6 million people in need of care in 2013 (Statistisches Bundesamt, 2015) and this number is estimated to increase steadily to outnumber 3.4 million people demanding care services by 2030 (Augurzky et al., 2013). Even according to these official – and probably underestimating – numbers, 1.9 million received care in their private home and 1.3 exclusively received informal care (typically by close relatives) making this the most important pillar of the German long-term care system. Thus, not only due to its size as the largest European labor market, Germany is an interesting country to study: it is rapidly aging and already now has a large informal care sector which is even going to increase in the future.
Apart form the longer-term perspective we, as another contribution to the literature, also take the dynamic nature of caregiving spells into account and use sequential inverse probability weighting (IPW) estimators as suggested by Lechner (2009) and Lechner and Miquel (2010) to estimate effects of up to three consecutive years of care provision. A further, if minor, contribution comes from the methodological side where we offer an identification strategy that relies on less functional form assumptions than the previous literature on short-run effects but also than Skira (2015) and Michaud et al. (2010).4 Our strategy rests on (sequential) conditional independence assumptions (CIA) which we justify by exploiting cross-sectional but also longitudinal information from our rich household survey, the German Socio-Economic Panel (SOEP). In auxiliary analyses, we relax the CIA to identify effect bounds under weaker assumptions. Other sensitivity tests such as placebo regressions imply that remaining time-invariant unobservables are unlikely to lead to an upward bias of our estimates.
Our main finding is that female caregivers reduce the probability to work full-time by 4 percentage points (at a baseline probability of 35 per cent). The effect is persistent over a period of eight years and seems to be mainly driven by switches to part-time work. High care intensities and longer episodes, however, also increase the long-run probability to leave the labor force. When we move away from point identification to effect bounds, the reduction in full-time work changes to an interval of 2.4–5.0 ppts. As another finding, wages seem to be unaffected contemporaneously but are significantly lower 8 years after the start of a care episode.
The paper proceeds as follows. Section 2 gives a brief introduction into the German long-term care system. Section 3 presents the data and how we exploit the panel structure. Section 4 lays out the estimation strategy and reports results of the baseline (static) model. Section 5 scrutinizes the identifying assumptions and allows for deviations. Results of the dynamic model are reported in Section 6, while some alternative specifications are carried out in Section 7. Section 8 concludes.
Section snippets
Institutional background
The German social long-term care insurance system was introduced in 1995 as a pay-as-you-go system.5 It is financed by a mandatory pay payroll tax deduction of currently 2.35 per cent of gross labour income (2.6 per cent for employees without children). In order to qualify for benefits, individuals need to be officially defined as care recipients and be classified into one of now four care levels. In care level one
Sample selection
We use data from the German Socio-Economic Panel (SOEP) which is an annually repeated representative panel survey on households and persons living in Germany (Wagner et al., 2007). Since 1984 it covers many questions on different life domains such as work, health, time use and education. On average, the survey contains about 22,000 individuals. We use data from the waves 2001 to 2013 as these include information on informal care provision.
Informal care is defined by the answer to the following
Empirical strategy I – a static design
We are interested in the effect of caregiving on labor market outcomes, both contemporaneously and up to eight years later. Fig. 3 describes the basic design. In period 1, individuals receive the binary treatment D1 (for all random variables to come, subscripts denote time in years), which could either be care provision (D1 = 1 and a green circle in Fig. 3) or no care provision (D1 = 0 and a red circle).11
Sensitivity analysis
So far we interpreted our estimates as causal conditional on the validity of our identifying assumption (the CIA) and found, in particular, considerable and persistent negative effects on full-time employment. We justified the identifying assumption by fully exploiting the panel information in the SOEP and using many observable characteristics to match on. As we also match on pre-treatment outcomes, time-constant unobserved heterogeneity that probably explains a lot of the willingness and
Empirical strategy II
The previous approach answers a relevant question: given that a women provides care today, what effects can she expect for her labor force status today, in one year, in eight years? Given that the treatment is defined in year 1 only, this effect is a mixture of different care provision paths later on. The treatment group consists of individuals that provide only one year of care but also of those who care for two consecutive years, three years and any other care spell (like care, no care, care,
Alternative specifications of the treatment variable
An important question is how sensitive the effects are with respect to the care intensity. In the baseline specifications, we defined the treatment to be at least one hour of care per day. In the following we vary this definition by restricting the treatment to at least two hours or three hours per day. The number of observations in the treatment group is then reduced from 2186 to 847 for two hours of care per day and to 380 for three hours. Fig. 10 – which returns to the static version due to
Conclusion
In this paper we assessed labor market outcomes as an important part of the implicit costs of informal care provision. In order to identify these costs we use matching techniques and inverse probability weighting. We exploit the panel information and a large set of individual controls (including measures of personality traits) to justify the identifying assumptions but also relax the assumptions in sensitivity analyses. We compare effects of providing care in a certain year on contemporaneous
References (51)
- et al.
Your next of kin or your own career? Caring and working among the 50+ of Europe?
J. Health Econ.
(2008) - et al.
The labour market costs of community care?
J. Health Econ.
(1998) - et al.
The opportunity costs of informal care: does gender matter?
J. Health Econ.
(2003) Informal adult care and caregivers’ employment in Europe?
Lab. Econ.
(2012)The chicken or the egg? Endogeneity in labour market participation of informal carers in England
J. Health Econ.
(2007)- et al.
The earnings of informal carers: wage differentials and opportunity costs?
J. Health Econ.
(2007) - et al.
A dynamic analysis of informal care and employment in England?
Lab. Econ.
(2010) - et al.
Short- and medium-term effects of informal care provision on female caregivers’ health
J. Health Econ.
(2015) - et al.
The effect of informal care on work and wages?
J. Health Econ.
(2013) Should instrumental variables be used as matching variables?
Res. Econ.
(2016)
The career costs of children?
J. Polit. Econ.
Selection on observed and unobserved variables: assessing the effectiveness of catholic schools?
J. Polit. Econ.
Pflegeheim Rating Report 2013 - Ruhiges Fahrwasser erreicht
Inference on treatment effects after selection among high-dimensional controls?
Rev. Econ. Stud.
Do instrumental variables belong in propensity scores?
Int. J. Stat. Econ.
Variable selection for propensity score models?
Am. J. Epidemiol.
Income comparisons and non-cognitive skills
SOEPpapers No. 441
Informal care and labour force participation among middle-aged women in Spain?
SERIEs
Two economists’ musings on the stability of locus of control?
Econ. J.
Caregiving to elderly parents and employment status of European mature women?
Rev. Econ. Stat.
Persoenlichkeitsmerkmale im Sozio-ökonomischen Panel (SOEP) – Konzept, Umsetzung und empirische Eigenschaften
The impact of “parent care” on female labor supply decisions?
Demography
The opportunity costs of elder care?
J. Hum. Resour.
Labor supply in the terminal stages of lone parents’ lives?
J. Popul. Econ.
Long-term and spillover effects of health shocks on employment and income?
J. Hum. Resour.
Cited by (73)
Informal caregiving and the allocation of time: implications for opportunity costs and measurement
2023, Social Science and MedicineInstrumental variable estimates of the burden of parental caregiving
2023, Journal of the Economics of AgeingDoes caring for others affect our mental health? Evidence from the COVID-19 pandemic
2023, Social Science and MedicineDoes retirement (really) increase informal caregiving? Quasi-experimental evidence from Australia
2023, Journal of Health EconomicsHeterogeneity in informal care intensity and its impact on employment
2022, Journal of Health EconomicsCitation Excerpt :I define two measures of caregiving intensity, respectively based on hours of care in a typical week and total months of care in the two-year period leading up to the survey year. A broad range of hours cut-offs have been used to identify intensive caregivers, from 1 to 35 h per week (e.g., Carmichael and Charles, 2003; Jacobs et al., 2017; Leigh, 2010; Schmitz and Westphal, 2017). Despite this substantial variation, certain cut-offs have been used relatively more frequently, including 10 and 20 h per week.
The impact of informal care from children to their elderly parents on self-employment? Evidence from China
2022, Economic ModellingCitation Excerpt :This result is consistent with our hypothesis and supports the following view: After controlling for the inter-generational support effect, caring for elderly parents is an opportunity cost of self-employment and reduces the probability of entering the labor market in the form of self-employment. Our finding is also in line with Liang et al. (2018), Schmitz and Westphal (2017), and Carmichael et al. (2010). Column (6) shows that providing pension subsidies for the elderly parents has an 8% lower likelihood of becoming self-employed compared to those who do not provide pension subsidies when other determinants are equal.
- ☆
Financial support by the Fritz Thyssen foundation (Project: 10.12.2.096) is gratefully acknowledged. We thank two anonymous referees for many constructive and helpful comments. We are also grateful for comments by Emanuele Ciani, Peter Eibich, Daniel Kamhöfer, Thorben Korfhage, and Nicolas R. Ziebarth as well as participants of the Unpaid Care Seminar at the LSE, the research seminar at the University of Duisburg-Essen, ESPE, the SOEP User conference, and the annual meeting of the German Economic Association.
- 1
RGS Econ: Ruhr Graduate School in Economics, Paderborn University, Warburger Strasse 100, 33098 Paderborn, Germany.