The impacts of home care vs. day care of young children

The second half of the 20th Century involved some massive social change in Western countries. One of those changes was the rapid increase in female labour force participation, including an increase in labour force participation among mothers of young children. As mothers have increasingly gone to work, fathers have in the main not compensating by decreasing their work time. So, childcare has become increasingly important over time. On top of that, there is a lot of tension (and judgment) associated with the decision by mothers to return to work or not.

A useful question to consider, then, is what is the impact of mothers working on their child's outcomes, compared to the mother staying out of work to care for the child. That is essentially the question addressed in this 2023 NBER Working Paper (ungated version here) by Jonathan Gruber (MIT), Tuomas Kosonen (VATT Institute for Economic Research), and Kristiina Huttunen (Aalto University School of Economics). They look at the case of Finland, where they look at the effects of:

...the Finnish Home Care Allowance program (HCA). This program provides substantial payments to mothers who stay home with their children from age ten months through 3 years old, rather than placing the children in formal child care, which is almost exclusively publicly-financed and of relatively high-quality in international comparison. The HCA program has a long tradition in Finland. It was introduced in 1985 and more than 80% of mothers in Finland utilize the HCA. As a result, the share of children in formal child care is much lower in Finland than in other Nordic countries...

Gruber et al. exploit variations in the value of HCA across municipalities, because each municipality could provide a supplement to the HCA, and many have done. The value of these supplements changes over time, and that is the variation that is key to assessing the impact on mothers and children. Essentially, they look at how differences in the amount of HCA assistance affect mothers' work, and children's outcomes, using linked data from the Finnish population register, birth registry, tax and benefits records, early childhood data from clinical assessments of children's readiness for school, and education and youth crime records for when the children were older. The early childhood data are interesting:

The individual tests we consider for four years olds (from 2010 onwards) are Cross (needing to draw a cross, where the two lines intersect), Ask (the child is able to ask following types of questions: when and where?), Details (the child is able to explain details from a specific picture), and Colors (the child is able to identify three out of four main colors from a color card). The tests for five years old (prior to 2010) are Circle (the child can cut a circle from a paper with scissors), Square (the child is able to draw a square on paper), Human (the child can draw human that has at least head, body and limbs come out of body, not from head), and Instruct (the child is able to follow three-part instructions).

Gruber et al. apply a difference-in-differences approach with a continuous treatment variable (the amount of HCA assistance received), which essentially estimates how a 100-Euro change in the HCA supplement amount affects outcomes between the years before and after the supplement changes. The results in terms of mothers' employment are summarised in Figure 1 in the paper:

Notice the big drop in employment that occurs at Time 0, which is when there is a 100-Euro increase in the HCA supplement. However, eyeballing the figure, while the point estimates are negative, it looks like they are not statistically significant (at the 5 percent level). When they move to a more standard difference-in-differences (rather than a dynamic DID approach), the results are statistically significant. Nevertheless, for this analysis Gruber et al. note that:

Maternal labor supply then falls by about 1.5% for each 100 euro increase in the homecare allowance and remains at that level in the municipalities that increased their supplement amount. So supplements are clearly reducing maternal work in favor of at home care, and the effect corresponds to about 5 percent reduction when compared with mean share of employment of mothers of one-year-old children.

Gruber et al. also show that the HCA supplement leads to a decrease in maternal labor income, but an increase in total income." Interestingly, they go on to show that their:

...estimates are large enough to explain the entire difference between the Finnish and (for example) Danish levels of short run child penalties of 20%.

Turning to children's outcomes, they find that:

...children become more likely to fail the cognition test at age four or five when their parents were eligible for higher HCA supplements at child’s age 1...

After an increase in supplement when one year old, enrolling to academic high school declines and committing a youth crime increases.

Needless to say, these are all bad outcomes for children. Gruber et al. then move onto a standard DID approach in order to better quantify the effects, and find that:

...the impact of receiving a 100 euros per month supplement when the eligible child is one year old is to reduce the employment of mothers by -1.27 percentage points, which is a roughly 5% decline in the odds of working... the impact on annual labor earnings is –194 Euros. Given the increase in HCA of 273 Euros... this suggests an almost three-quarters “crowdout” of the income benefits of HCA; that is, for every dollar of HCA received, mothers offset 72 cents through lower labor earnings... the effect of supplement on all income including earnings and taxable income transfers (including HCA and supplements). The effect on this outcome is 237 Euros.

So, mothers work less, earn less labour income, but receive higher total income as a result of the HCA supplement. In terms of child outcomes though:

...a 100 euro per month increase in the supplement leads to a statistically significant 1.78 percentage point increase in the odds of failing a test; the effect size represents about 7% increase from the baseline failing rate...

...higher HCA in form of supplements when the child is one year old leads to -.6 percentage point decline in the odds of enrollment in an academic high school, which is about 1 percent of the sample mean...

...each 100 euros per month of supplement leads to a rise in youth criminal sentencing of .22 percentage points, off a mean of 4 percentage points, a roughly 6% effect...

All of those effects are statistically significant. And they all point to the homecare supplement having negative impacts on children's short-term and long-term outcomes. Perhaps that is uniquely due to the homecare supplement? Gruber et al. go on to investigate a daycare reform in 1997 that unified daycare fees across the country. As a result, some families ended up paying higher daycare fees, while others paid lower fees. A 100-Euro increase in daycare fees should have a similar (but opposite direction) effect to a 100-Euro increase in the HCA supplement. Indeed, Gruber et al. find an effect of the daycare fee change that is of a similar magnitude, but in the opposite direction, to the HCA supplement results.

That they find similar effects based on changes in HCA supplement and daycare fees should provide some confidence in the results. However, we should treat them with a little bit of caution for at least a couple of reasons. First, as I noted in this post, the 'two-way fixed effects' approach that they have adopted has recently attracted a lot of criticism (which is nicely outlined in two posts on the Development Impact blog, here and here, as well as this post). The short version is that the two-way fixed effects approach is likely to lead to biased estimates of the treatment effect. Gruber et al. do try a few ways of dealing with this, and the results are robust to the approaches they adopt, but given that their dynamic DID results are statistically insignificant, this still leaves me concerned. Second, Finland is somewhat unique in the pervasiveness of homecare. As they note in the paper, 80 percent of mothers make use of the homecare allowance, which is a high take-up rate. It's not clear that similar effects would be observed in other countries.

This external validity problem is the biggest issue for me. Mothers are essentially choosing between homecare, where they look after the children and teach them the basics required to prepare them for school (with whatever resources and support they have available to them), or they send the children to a daycare service, which employs professionally-trained early childhood educators to perform the task. There are pros and cons either way, but in terms of school readiness, the daycare may have the edge. On top of that, Finland has a high-quality, publicly funded daycare system, which further tilts the balance in favour of daycare. In countries where the daycare system is of lower quality, the negative impacts on child outcomes are likely to be smaller, or perhaps absent entirely.

Gruber et al. conclude that:

...there may be limits to general international lessons from such policy analyses, and that conclusions are best drawn on a country-by-country basis.

Given the issues of external validity I've noted above, I'd say that further research in other countries is imperative, before we definitively conclude that homecare of children is bad for them.

[HT: Marginal Revolution, last year]

Teenage daughters and divorce

Sociological research has shown that couples with daughters are more likely to divorce than couples with sons. However, there are a number of competing (and complementary) theoretical explanations for this observed relationship, and it has been difficult to disentangle the different mechanisms that might be at work. In a recent article published in The Economic Journal (sorry I don't see an ungated version online, but there is this conference presentation), Jan Kabatek (University of Melbourne) and David Ribar (Georgia State University) use comprehensive data from the Netherlands to investigate. Specifically, they use:

...administrative data that cover the near universe of marriages and registered partnerships that began in the country between October 1971 and December 2015. The data include nearly 3 million marriages and partnerships, allowing us to estimate effects precisely and consider how effects vary with children’s ages, parities, and conditional on parents’ backgrounds. The data are highly accurate with the exact dates of weddings, births, and divorces.

This is the sort of research that can only be done with population register data like this, because the sample size is enormous and sample selection is less of an issue. However, first let's take a step back. Kabatek and Ribar outline the various competing theories for why couples with daughters may be more at risk of divorce:

Consider an overarching preference for boys over girls. Such a preference would raise the value of the marriage-specific capital for couples with sons, thereby lowering their incentives to divorce... Similar effects would occur if fathers prefer spending time with sons more than spending time with daughters...

The constraint-based explanations posit that daughters are more costly to raise than sons... Another possibility is that boys are more susceptible to developmental problems if parents divorce, which would lower the value of parents’ alternatives to marriage... It is also possible that parenting interactions are more strained with girls than boys and that these strains lower the match-specific quality.

...it is also possible that the association is not causal. Hamoudi and Nobles (2014) described how girls in utero have survival advantages under conditions of stress relative to boys. They found that mothers who reported high levels of relationship conflict prior to their children’s births were more likely to give birth to girls. This means that the gender-related divorce disparities may result from sex-selection into live birth.

Kabatek and Ribar use what is referred to as a complementary log-log (cloglog) discrete-time hazard model. When what you are modelling is really a type of survival analysis, cloglog provides a better fit than a logistic regression, and it deals with low-probability events better. Anyway, enough of that. In the headline results, they find that:

...having a daughter increases the risks of divorce among Dutch couples - the first robust finding of this association for a European country. An even more novel and intriguing result is that the increased risks of divorce only appear when daughters are teenagers (aged 13-18) - there is no detectable gender difference at earlier or later ages. We observe this pattern among both firstborn and subsequent children. We also find the same age pattern in analyses of the 1980, 1985, 1990, and 1995 US Current Population Survey Marriage and Fertility Supplements (CPS-MFS).

The divorce risks for couples with firstborn daughters aged between 13 and 18 are about 5.5% higher, on average, than the risks for couples with firstborn sons. However, because there are no differences at younger or older ages, the cumulative effect of the child’s gender on parental divorce is modest. For instance, the cumulative divorce rates of couples with firstborn sons and daughters aged 19 only differ by 1.8% (0.36 percentage points).

So far, so consistent with the sociological literature, except for the fact that the result is largest for teenage daughters. Kabatek and Ribar then go further:

The ‘teenage daughter effect’ is at odds with many possible explanations, including: (i) overarching, time-invariant preferences for sons, (ii) sex-selection into live birth, and (iii) rational forward-looking behaviours based on age-specific differences in preferences for or costs of raising sons and daughters. This is because each of these explanations predicts that gender disparities would also appear earlier in the child’s life. Instead, the precisely-estimated pattern of zero effects during childhood and non-zero effects during the teenage years leads us to consider explanations based on unexpected changes in parents’ valuation of marriage during children’s adolescence. We give special consideration to family conflicts that might arise from differences in family members’ gender-role attitudes. These differences can become a more salient source of conflict as girls mature, and conflict in this dimension of family life may spill over to the parents’ marital relationship.

Additional analyses of Dutch administrative data support this explanation. We find that the excess divorce risks associated with having teenage daughters are higher for couples whose gender-role attitudes are likely to differ from those of their daughters (for example, for less-educated couples and immigrant couples), and that the risks are exacerbated further for couples in which the two spouses are likely to hold different gender-role attitudes (for example, for parents with different immigration backgrounds or different levels of education). In a further analysis, we examine the gender composition of the parents’ siblings and find that the teenage daughter effect only appears among fathers who grew up without sisters. In contrast, we find no differences with regard to the gender composition of the mother’s siblings, which suggests that the father’s experiences are critical.

It appears that the effect of daughters on divorce arises from conflict between parents in terms of their beliefs in gender roles. This only becomes problematic when the daughter is older and presumably better able to assert themselves. It is particularly interesting that there is a difference here between fathers with sisters and fathers without sisters, suggesting that having sisters may affect fathers' beliefs about gender roles, and reduce conflict with their daughters. Kabatek and Ribar use additional survey data to support these explanations.

Some would not doubt argue that these results fall short of a definitive causal explanation. The gender of children is mostly distributed randomly, but there may be some concerns about sex selection, especially for more recent children. Kabatek and Ribar test for differences between couples with first-born sons and couples with first-born daughters, and there are few statistically significant differences. However, couples who are both immigrants are more likely to have a first-born son, and parents wait slightly longer before having a second child after a first-born son. The number of siblings is also higher for couples with a first-born son, but the difference is tiny (0.003 children, on average). Those variables are all controlled for in the analysis, but there might still be unobservable differences between those couples that are correlated with the chance of divorce.

However, despite that caveat, this is the best analysis we have to date on why couples with daughters are more likely to divorce than couples with sons.