This is the subtitle of a study by Rebaudo et al. (2024) that aims to examine how different factors impact individual willingness to provide caregiving. The study is focused on potential caregivers in Germany. Before we get to the statistical analysis, first some background:

Informal Caregiving in Germany

The article provides a nice summary of informal long-term caregiving in Germany.

In 1995, Germany introduced a long-term care insurance (LTCI) system…employees and their employers jointly contribute 3.4% of the individual gross wage to finance expenditures for care needs. Care needs were redefined in 2017, distinguishing five care levels….As of 2019…benefits in cash ranged from 316 euros monthly for care level 2 to 901 euros for care level 5.

The article also notes that in addition to cash payments, benefits can also be paid in kind.

What factors influence caregiving?

On the one hand, there is a sense of duty to care for family members. Other factors include “intrinsic motivation, avoidance of guilt, or even bequests and intergenerational exchange.” On the other hand, financial incentives may play a role including opportunity costs (wage caregiver could earn in a paid occupation) as well as potential state reimbursement for caregiving. Moreover, an individual’s own health and physical status also would play in a role in deciding whether or not to provide caregiving.

Data and Statistical Specification

The authors use data on potential caregivers from the German Socio-Economic Panel (SOEP). The survey contains information on personal economic circumstances, employment, preferences and personal background covering ~30,000 individuals (~20,000 households). The authors focus on individuals aged 18-65. The key independent variable is ‘How many hours do you spend on care and support for persons in need of care on a typical weekday, Saturday, and Sunday?‘ The authors used a mixed logit model with random coefficients where the key outcome is whether they patients provide >1 hour of caregiving per week. The utility function assumes individuals utility depends on leisure, consumption, and informal care hours and the utility function varies by factors such has demographics, income level.

Results

In short, higher wages, reduced likelihood of caregiving.

On average, a 1% increase in gross wages leads to an increase of labor force participation of 0.05% points, and a 0.1% increase of working hours…
The elasticity of care is negative and statistically significant for both the subgroup with below and above median wages, for women and for those above 50 years of age. For men, the estimated elasticities for care are insignificant

Conversely, more financial incentives increase the likelihood of caregiving, but some individuals are unwilling to provide care even if care hours are fully compensated.

Overall, the reform increases participation in informal care by about 18% points…However, a large proportion of about one half of potential carers remains unwilling to provide informal care, even when informal care hours are fully compensated as paid work. This reflects the importance of non-financial factors in the caregiving decision.

…for the group with above median wages, the impact on informal care is about 12% points larger than in the lower wage group. Thus, among higher earners, more potential caregivers are induced to participate in informal caregiving when they receive financial compensation. However, considering the lower participation in caregiving among higher earners before the reform…there is also greater potential to increase participation in this group. 

You can read the full paper here.