The effect of child benefit on female labor supply

In 2016, the Polish government introduced a large new child benefit, called “Family 500+”, with the aim to increase fertility from a low level and reduce child poverty. Up until 2019, the monthly benefit – amounting to 500 PLN, a third of a net minimum wage - was universal for the second and every further child and means-tested for the first child.

The benefit became universal as of July 2019; therefore, our study focuses on the period directly prior to the 2016 policy implementation.

This paper looks at the impact of the new benefit on female labor supply. The transfer increased out-of-work income significantly, especially for parents with several eligible children, reducing incentives to enter the labor market through an income effect. This held particularly for lower-earning families. Furthermore, in the first 3 years of its operation, the benefit for the first child was fully withdrawn once family income rose above the eligibility ceiling. This could create an inactivity trap for singles or second earners from low-earning families, as they would need to earn quite a high wage to make up for this loss.

From a theoretical perspective, in a simple static labor supply framework, child benefits may reduce labor supply through an income effect, as they shift the consumption–leisure budget constraint (Blundell, 1995; Moffitt, 2002; Cahuc et al., 2014). In a search model framework, the “Family 500+” child benefit is likely to increase the reservation wage and thus discourage labor market participation among individuals close to the income threshold below which the benefit for the first child was paid. Women, as primary caregivers, were likely to be particularly responsive to such incentives, which was confirmed by empirical evidence for other countries (Jaumotte, 2003; Milligan and Stabile, 2009; Haan and Wrohlich, 2011). Schirle (2015) analyzed the introduction of the Universal Child Care Benefit (UCCB) in Canada in 2006 and the impact it had on the labor market. Using Canadian Labor Force Survey data for 2003–2009, she found large and significant negative income effects of the UCCB on labor supply of mothers and fathers. The effects were stronger for less-educated parents, though affecting better educated women as well. Among mothers, labor supply was decreased at both the extensive and the intensive margins. González (2013) used a regression discontinuity framework to analyze the fertility and labor supply effects of a large universal one-time benefit introduced in 2007 in Spain. She found a negative labor force participation effect a year after birth, which however disappeared by the time the child was 2 years old.

The negative effects of child benefits on female labor supply tend to be greater for women with lower potential incomes and lower levels of education (Eissa and Liebman, 1996; Immervoll et al., 2007). Moreover, marital status is likely to play a role in the impact of child benefits on female labor supply, with married women reacting more strongly to changes in income and wages. Koebel and Schirle (2016) followed up on Schirle’s (2015) study of the Canadian UCCB, finding that the benefit decreased labor supply among married women but increased labor force participation of divorced/separated women, with no impact on mothers who had never been married or those in common-law relationships. Finally, the labor supply response to child benefits differs across countries, reflecting not only the institutional differences in the design of tax-benefit systems but also the level of economic development. In particular, Scharle (2007) finds the negative effect of cash benefits on female labor force participation to be higher in Central and Eastern European countries, which may be a reflection of lower income levels in these countries.

We contribute to the current knowledge on the effects of family benefits for the labor market in three ways. First, we study the labor market effects of such transfers in the context of a catching-up economy with relatively low social and family transfers hitherto. Second, the benefit is large relative to average incomes compared to child benefits in other countries. It amounts to around 16% of the average wage (in net terms), whereas, for instance, the size of the childcare benefit introduced in Canada in 2006 amounted to around 3% of the average monthly wage in Canada at that time. Thus, we expect a higher likelihood of observing a significant impact. Thirdly, the reform can be treated as a natural experiment. The 500+ benefit was introduced quickly after it was first announced as an element of the electoral campaign by a new government, so women are very unlikely to have anticipated the introduction by changing their labor supply or their decision to have children.

At the time of the implementation of the “Family 500+” program, Poland was distinguished by a very good labor market situation on the one hand, and low female labor market participation rates on the other. The latter is related to strong family values shaped by deep-rooted Catholicism and a relatively weak, although improving, institutional childcare infrastructure, in particular in rural areas.

Given this unique institutional framework, this study can add important insights into the nature of labor supply effects of child benefits. Our hypothesis is that the new child benefits may have reinforced a longer-standing trend of labor force participation among lower-skilled women in Poland to fall, while that among higher-skilled women increased at a slower pace. The fact that the benefit for the first child was withdrawn once the per capita family income increased beyond the eligibility ceiling limited the incentives for single mothers or second earners with children to work. An unemployed single mother of two taking up a job that pays the average wage would retain <20% of her earnings as a result of taxes and benefit withdrawal. Taking childcare costs into account, which can be very high in the private sector – often, the only available option – she would actually lose money.

We use Polish Labor Force Survey data for an ex-post evaluation of the reform. Before the program’s implementation, Myck (2016) used a discrete-choice labor-supply model and Polish Household Budget Survey data to simulate the effects of the “Family 500+” benefit on labor supply. He found that the benefit could reduce labor supply in the long term by about 240,000 individuals. Based on a difference-in-differences methodology, we find that the labor market participation rates of women with children decreased significantly after the introduction of the benefit, compared to childless women, who were not eligible for the benefit. Results imply that the labor force participation rate of mothers would have been 2–3 percentage points higher in the absence of the reform. The effect set in earlier for partnered women and, within this group, it was the highest among those with lower levels of educational attainment and thus, generally, with lower incomes.

We test the hypothesis that the implementation of the “Family 500+” program led to a fall in labor force participation among mothers. To this end, we use a difference-in-differences approach (Angrist and Pischke, 2014; Lechner, 2011). To identify the effect of the introduction of the “Family 500+” benefit, we compare changes in participation rates of (1) women who were eligible for the transfer, as they had children – our treated group, and (2) women who had no children and as such were not eligible – the control group.

In the case of women with one child, many were not eligible for the benefit, because their income was too high. Yet, single women could, in principle, become eligible by withdrawing from the labor market or reducing their hours worked so that their income dropped below the eligibility ceiling, as could some partnered women – provided their partner’s income was low enough. It seems sensible to consider these women as treated, since the child benefit was potentially available to them and might thus influence their behavior. This is less clear for women whose partner’s income was so high that they could not become eligible for the benefit even by withdrawing from the labor market. Assigning them to the treated group should bias the estimated impact on participation downward, as they cannot be reasonably expected to react to the benefit. This is why we also test some alternative specifications, which are discussed later.

We use Polish Labor Force Survey data for the years 2010–2017 (and from 2007 in the placebo test). We restrict the sample to women aged 20–49 years. The analyses are run separately for single and partnered women to account for differences in their labor force participation decisions, which are likely to be influenced by the presence of a partner. Partnered women are defined as women living with a spouse or cohabiting partner in the same household.

We compare the labor force participation rates before and after the second half of 2016, as municipal offices started transferring the “Family 500+” benefits as of the end of June 2016. We study the labor market reaction in the first year after the introduction of the benefit, i.e., until mid-2017. It is safe to assume that it was not anticipated and women did not react before they actually received the money – the benefit was announced in February 2016 and formally introduced in April 2016 when the first forms were made available to fill in (the municipal offices then had 3 months to disburse the benefit).

We estimate the following equation:

where A_it is a dummy variable indicating whether individual i is active in the labor market in period t; a is a constant; X_it is a vector containing a set of individual-specific characteristics detailed in Table 1. Unfortunately, income and wage variables cannot be included as controls, as these data are unavailable (income) or too patchy (wages) in the Polish Labor Force Survey. T_i is a treatment group variable, specifying whether the woman has children (treated group) or not (control group); Post_t is a dummy variable for the period following the second quarter of 2016 when the child benefit was introduced, or the posttreatment period; ε_it is an error term; and α, β, γ, δ, and θ are parameters to be estimated. We also introduce time fixed effects to account for changes in labor market policies and the economic situation in general (Y_t is a set of half-year dummies).

We use the linear probability model to estimate Equation (1). We run the probit model as a robustness check, and the results were very similar (they are available upon request). To overcome error-term heteroskedasticity, we compute robust standard errors.

Table 1 compares the descriptive statistics for the treated and control groups in 2016, distinguishing between single and partnered women. Among the partnered women, those without children were much more likely to be employed (compared to women with children). The finding was opposite among single women, where those with children were more likely to be employed. Not surprisingly, childless women were much younger, in particular among singles. Childless single women were also already better educated and more likely to be still in education than single mothers. Among partnered women, there was a higher share of rural inhabitants in the treated group. This compositional difference may lead to different trends in labor participation between the two groups. To eliminate the impact of these compositional differences on labor force participation of women with and without children, we introduce the socioeconomic variables displayed in Table 1 as control variables in the estimated models.

2.1

Testing the common trends hypothesis

A key assumption of the difference-in-differences methodology is that – before the treatment – changes in the level of the outcome variable were the same in the treatment and control groups. We start with a visual inspection of historical trends of our outcome variable, labor force participation (see, e. g., Gebel and Voßemer, 2014; Centeno et al., 2009). Figure 1 shows that changes in participation rates for women with one or two children and those without children were indeed quite similar prior to the introduction of the child benefit in 2016, though these were not completely parallel.

We have also verified whether there have been any important, abrupt changes in coverage of childcare facilities and educational enrollment around the time the benefit was introduced, as this could be a potential confounding factor undermining our empirical strategy. Poland has experienced a steady growth in the coverage of crèches and kindergartens since the early 2010s, with no break around the reform. There were no changes in school enrollment either.

These trends, however, reflect both (1) changing probabilities of participating in the labor market among women with and without children and (2) a changing composition of these two groups (e.g., rising shares of tertiary educated women), which also impact the labor force participation rates. The prereform trend of labor force participation rate of women with three and more children was quite different; therefore, we consider that childless women are not sufficiently similar to them for a valid comparison and drop women with three or more children from our analysis.

Figure 1

To further ensure that comparing the treated and the control groups permits identification of the effect of the child benefits, we test the common trends hypothesis more formally, using two approaches. Firstly, we include – in the model – the interactions of the treatment group variable not only with the posttreatment period (treatment effect) but also with all-time dummy variables (placebo effects) to test whether the difference in the treatment and the control groups has changed at any point in time. Insignificant interaction terms would indicate that the difference between the two groups has remained stable and that the common trend hypothesis is valid.

Secondly, we vary the “Post” variable in Equation 1 so that it covers different periods, including 2009–2016, 2008–2015, 2007–2014 (i.e., the main specification moved backward by 1/2/3 years). If the coefficient of these interaction terms of the treatment group dummy with a subperiod dummy was significant, this would indicate that the difference between the treatment and the control groups has changed over time. In that case, the common trend hypothesis would not be valid.

Results for the main specification are presented in Table 2. Panel A is based on the main period of our analysis, i.e., 2010–2017, with the treatment occurring in 2016 (when the 500+ benefit was introduced) and with additional dummies for previous years. Panels B–D look at the pretreatment periods only, assuming a treatment in 2015, 2014, and 2013, respectively. All the placebo tests clearly show that there were no statistically significant effects prior to the introduction of the “Family 500+” policy. The results for other specifications also prove robust to the placebo dummies. These are available upon request.

Table 2

Placebo tests for main difference-in-differences specification

Socioeconomic variables	Partnered women	Single women
(A) Regression for 2010–2017 with all potential placebo/treatment effects
Group effect (γ)	–0.055***	0.005
Placebo treatment effect (θ) - 2010/2011	–0.012*	–0.002
Placebo treatment effect (θ) – 2011/2012	–0.005	–0.004
Placebo treatment effect (θ) – 2012/2013	–0.000	0.002
Placebo treatment effect (θ) – 2013/2014	0.007	–0.003
Placebo treatment effect (θ) – 2014/2015	0.008	0.001
Placebo treatment effect (θ) – 2015/2016	–0.007	–0.014
Treatment effect (θ) – 2016/2017	–0.023***	–0.023*
Observations	300,792	174,872
R-squared	0.119	0.316
(B) Regression for 2009–2016 as in main specification
Group effect (γ)	–0.051***	0.013**
Placebo treatment effect (θ) – 2015/2016	–0.007	–0.012
Observations	293,428	170,532
R-squared	0.120	0.310
(C) Regression for 2008–2015 as in main specification
Group effect (γ)	–0.049***	0.011*
Placebo treatment effect (θ) – 2014/2015	0.007	0.008
Observations	282,988	165,472
R-squared	0.122	0.301
(D) Regression for 2007–2014 as in main specification
Group effect (γ)	–0.045***	0.003
Placebo treatment effect (θ) – 2013/2014	0.005	0.012
Observations	269,835	158,947
R-squared	0.124	0.292

Note: Robust standard errors were computed. Significance levels: ***0.01, **0.05, and *0.1.

Source: Own calculations based on Polish Labor Force Survey data.

The results presented in this paper suggest that the introduction of child benefit in 2016 in Poland had a significantly negative impact on labor force participation and employment of eligible mothers. This finding is robust to changes in the precise outcome variable we look at (labor force participation, employment, or labor market withdrawal), to different definitions of the treated and the control groups in our difference-in-differences methodology, and to different estimation approaches. The effects are sizeable, implying that labor force participation and employment would have been 2.5–3 percentage points higher by mid-2017 in the absence of the reform. Testing for heterogeneity across different groups reveals that the effects are strongest for the lowest-educated mothers, in line with previous results in the literature.

Several advanced countries are looking for a way to improve low fertility rates and tackle the persistent poverty rates among families with children. Many of them turn to a redesigning of family support and childcare benefits. We hope the present study may be informative for the choice of policy design. Our finding of a sizeable negative effect of the Polish child benefit on female labor force participation, despite a booming labor market and increasing wages, suggests that there is a need to consider short- and long-term labor market effects in the cost–benefit analysis of public policies.

In terms of questions for further research, it will be interesting to study – at a later point in time – the extent to which the new child benefits may lengthen career interruptions of mothers and the ensuing impact on their earnings prospects when they return to the labor market. Furthermore, whether fertility is influenced positively by the new benefit introduced in Poland, as intended, would be an interesting research question for the future, as many countries struggle to alleviate demographic changes and increase the low birth rates.

The size of the effect on labor supply of the “Family 500+” benefit may be influenced by the existing tax disincentives for second earners, insufficient childcare coverage, gender pay gaps, and gendered norms. Studying how these features influence the impact of child benefits on labor supply would shed light on policies that can help alleviate any unwanted side effects of such transfers. Finally, the child benefits might also influence labor supply of men and informality, which would be interesting fields for study for the future.