The availability of nonparental childcare may be an important factor that influences reproductive decisions. While there is still a shortage of formal childcare service in China, grandparents are one primary source of childcare for their grandchildren. However, impact evaluations regarding the contribution of grandparenting on fertility level in China are still limited; the established evaluation results are not conclusive, especially for the birth of the second child. In this paper, we provide a theoretical justification and an empirical study of the influence of grandparental childcare on the second birth. By introducing a dynamic general equilibrium (DGE) model, this study proves that intergenerational childcare plays a critical role in both boosting the fertility level and maintaining its positive tendency. Drawing on the nationally representative data from the China Migrants Dynamic Survey in 2016, we estimate the treatment effects of grandparental childcare for the first child on the second birth with the Propensity Score Matching method. After controlling the self-selection bias, the results show that intergenerational childcare can positively affect the second birth. Sensitivity analysis results show the relative robustness of our empirical estimates to potential hidden bias attributed to unobserved variables. We also draw policy implications from the analysis, calling for government policies not only to promote sustainable and healthy development of the childcare industry but also to support family life, especially grandparental childcare.
Due to decades of falling birth rates and increase in life expectancy in China, population aging, a significant obstacle to social and economic development, is becoming a pressing issue that needs to be resolved. According to the China Statistical Yearbook in 2020 [
Besides the high cost of raising a child, another critical reason that holds back the willingness of young couples to have a second child is the lack of childcare, especially for working mothers [
Different from the relatively independent family culture in Europe and America, Chinese families, which are influenced by Confucian culture, are arguably more closely knitted, which results in a closer bond between the grandparents and their offsprings. Downward intergenerational time transfers in the form of grandchild care are common in China. About 40% of elderly people in China involve in intergenerational childcare in China [
In this study, we use the nationally representative household data drawn from the China Migrants Dynamic Survey in 2016 (CMDS 2016), a large-scale survey of domestic migrant population in China, to investigate the influence of intergenerational childcare. The migrants in the CMDS refer to the population living away from their registered household residence for over one month. The domestic migrant population in 2017 was 244 million in China, according to the Report on China’s Migrant Population Development in 2018, and the fertility rate of the second child in the migrant population has a significant impact on the fertility rate in China.
Grandparenting is common in the migrant population due to the distinctive demand for nonmaternal childcare. The particularity of migrant households has a significant influence on their child-rearing modes and fertility desire. According to the different family arrangements for childcare, there are usually three ways to rear their children when both the parents work away from home. (1) When the grandparents also move with their offspring, the children are jointly raised by their parents and grandparents. (2) When only the children move with their parents, they are taken care of by their parents. (3) When the children are left behind in the hometown, they are mainly taken care of by their grandparents and are usually called left-behind children. According to the 1% National Population Sample Survey (NPSS) of China conducted in 2015, over 68 million children are left behind nationwide in 2015, and over 40 million live in rural areas. Half of the left-behind children in rural areas could only live with their grandparents or other caretakers.
A growing recent literature investigates the varied roles [
Given the existing empirical research, whether grandparental childcare is associated with higher fertility levels is still harder to answer, as the existing empirical evidence has been mixed and varies by country. For example, Tanskanen and Rotkirch [
Although many studies [
This paper conducts both theoretical analysis and empirical study to explore the impact of intergenerational childcare on the birth of the second child. To this end, we first introduce a dynamic general equilibrium (DGE) model calibrated to be more in line with the national conditions of China. The numerical simulation results show that, with the increase of life expectancy, the hours that can be invested in grandparenting and the number of births will also increase; grandparenting is an important factor that not only can boost the fertility level but also can help maintain its positive trend. Then, we conduct empirical analysis using the nationally representative data of CMDS2016, with which we mainly explore the impact of having grandparental childcare for the first child on the birth of the second child. To deal with self-selection bias in this observational study, we estimate the treatment effects by using propensity score matching (PSM) [
The remainder of this paper is organized as follows. Section
In this study, we consider the closed economy populated by perfectly rational and identical individuals and develop a DGE model consisting of individuals and firms under the market clearing assumption. Our objective is to devise a model that is not only consistent with the “trend” facts but can also replicate the cyclical properties of a household.
Based on the life-cycle theory for individuals, each individual’s life within each generation consists of three periods, i.e., childhood, young age, and old age. Individuals exclusively make economic decisions in the working and retirement periods, i.e., the young age and old age. Thus, we choose to omit childhood in the introduced econometric model. We also assume that the length of young age is one unit of time and the length of old age is
An overview of the structure of the developed OLG model for typical individuals. Intergenerational time and finical transfer, in the form of grandparenting, alimony, and inheritance, as well as intertemporal finical transfer, are considered.
At the
We further assume that each individual gives a fixed percentage
Suppose each individual has
Under the constraints of equations (
Suppose that technological progress is an exogenous variable and firms have identical Cobb–Douglas production functions.
Suppose that the total number of individuals at young age in the
The labor supply equals the labor demand when the market clears at the
Suppose that the capital is fully depreciated at the end of each period; then, the capital stock of the next period equals the total savings of the current period multiplied by the interest rate of the next period:
Since the variables
Therefore, we obtain the DGE model which consists of an individual’s maximum utility (equations (
Since the model is an intertemporal dynamic process and the current period decisions are influenced by the previous period and the next period, we could not figure out the decision variables of an individual to make personal utility to the maximum. Therefore, we will estimate the steady-state values by means of numerical simulation in Section
In order to further explore the effect of intergenerational childcare on the number of births, we also build a new OLG model without considering intergenerational childcare variable for typical individuals. Compared to the OLG model introduced in Section
Individuals make decisions about
In this section, we conduct numerical simulation to identify the effect of intergenerational childcare.
Following the parameter settings in the previous studies [
The value of old-age length
Simulation study of the DGE model with considering intergenerational childcare. (a) The association of length
Simulation study of the DGE model with/without considering intergenerational childcare (i.e., grandparental childcare). (a) The association of length
Firstly, as is shown in Figure
The DGE model in the previous section has theoretically proven the potential positive effect of grandparenting on the number of births. In this section, we further conduct empirical studies of the impact of intergenerational childcare on the birth of the second child with data from China.
For the empirical study, we draw on the data from the China Migrants Dynamic Survey in 2016 (
Since the data in CMDS 2016 were collected after the formal operation of the universal two-child policy, there are no policy barriers for the birth of the second child for almost all Chinese people. According to the 2018 Report on China’s Migrant Population Development (National Health and Family Planning Commission 2018), the number of married women of childbearing age in the internal-migrant population makes up about a quarter of that all over China mainland. Moreover, more than 80% of the married migrants choose to migrate from one place to another with their spouses. Thus, the data used for our empirical study are representative and suitable for the investigation of the second birth.
To investigate the birth of the second child, we selected a subset of data from the CMDS 2016 based on five criteria: age, marital status, the number and age of children, and living with the partner. Specifically, we select those couples who were both under the age of 45 years at the time of the interview, already have given birth to at least one child, never experienced divorce, and migrated to the same place. Remarried couples were excluded because the number of stepchildren may already be more than two. Under the universal two-child policy in China, all married couples can have no more than two children. Accordingly, 76,946 cases meet these criteria.
Moreover, we excluded 52 respondents with the first child who died, 619 respondents with twins or multiple births, and 46 respondents with missing values for crucial variables. We further excluded 15,180 respondents with the first child who was over 18 years of age or under 2 years of age at the time of the interview. Note that the recommended interbirth interval (IBI) by the WTO is at least 24 months between pregnancies. An IBI of lower than 18 months is associated with an increased risk of preterm birth. Typically, Chinese couples usually begin to have enough time to choose whether to have a second child after their first child is 2 years old. By applying these selection criteria, we obtained a sample size of 61,049.
Table
Descriptive statistics of the used sample, which is a subset of the CMDS2016. For variables with binary values, the mean indicates the proportion of the positive class.
Type | Variable | Description | Full sample | Household (two births) | Household (one birth) | |||
---|---|---|---|---|---|---|---|---|
Mean | S.D. | Mean | S.D. | Mean | S.D. | |||
Explained | Having the second birth | Yes | 0.443 | 0.497 | 1 | 0 | 0 | 0 |
Demographic | Age of the father | Continuous (years) | 34.494 | 5.102 | 35.261 | 4.875 | 33.882 | 5.195 |
Age of the mother | Continuous (years) | 32.680 | 5.098 | 33.445 | 4.922 | 32.071 | 5.153 | |
Ethnicity of the parents | Both Hans | 0.903 | 0.296 | 0.885 | 0.319 | 0.918 | 0.275 | |
Age of the first child | Continuous (years) | 8.770 | 4.372 | 10.255 | 4.115 | 7.588 | 4.207 | |
Gender of the first child | Girl | 0.466 | 0.499 | 0.577 | 0.494 | 0.377 | 0.485 | |
Primal-care provider for the first child | Parents | 0.532 | 0.499 | 0.507 | 0.500 | 0.551 | 0.497 | |
Father | 0.007 | 0.086 | 0.006 | 0.078 | 0.008 | 0.091 | ||
Mother | 0.196 | 0.397 | 0.186 | 0.006 | 0.203 | 0.402 | ||
Grandparents | 0.233 | 0.423 | 0.267 | 0.442 | 0.206 | 0.404 | ||
Other caretakers | 0.028 | 0.165 | 0.028 | 0.165 | 0.028 | 0.166 | ||
Nobody | 0.004 | 0.065 | 0.005 | 0.072 | 0.004 | 0.060 | ||
Socioeconomic | Education level of the father | Junior school and below | 0.083 | 0.276 | 0.118 | 0.323 | 0.055 | 0.228 |
Junior high school | 0.566 | 0.496 | 0.627 | 0.484 | 0.518 | 0.500 | ||
Senior high school | 0.233 | 0.423 | 0.193 | 0.395 | 0.265 | 0.441 | ||
College and above | 0.117 | 0.322 | 0.061 | 0.239 | 0.162 | 0.369 | ||
Education level of the mother | Junior school and below | 0.118 | 0.322 | 0.173 | 0.378 | 0.074 | 0.261 | |
Junior high school | 0.569 | 0.495 | 0.619 | 0.486 | 0.530 | 0.499 | ||
Senior high school | 0.214 | 0.410 | 0.162 | 0.369 | 0.255 | 0.436 | ||
College and above | 0.099 | 0.299 | 0.046 | 0.209 | 0.142 | 0.349 | ||
Family monthly income | Continuous (in log) | 8.763 | 0.536 | 8.742 | 0.556 | 8.779 | 0.519 | |
Settlement intention | Settle down | 0.622 | 0.485 | 0.597 | 0.491 | 0.642 | 0.480 | |
Return home | 0.045 | 0.207 | 0.047 | 0.211 | 0.043 | 0.203 | ||
Go to other places | 0.028 | 0.164 | 0.028 | 0.164 | 0.028 | 0.164 | ||
Uncertain | 0.306 | 0.461 | 0.328 | 0.470 | 0.288 | 0.453 | ||
Household registration (a.k.a | Both rural | 0.833 | 0.373 | 0.891 | 0.311 | 0.786 | 0.410 | |
Different | 0.075 | 0.264 | 0.053 | 0.224 | 0.093 | 0.290 | ||
Both urban | 0.092 | 0.289 | 0.055 | 0.229 | 0.121 | 0.326 | ||
The child migrates with their parents | Yes | 0.512 | 0.500 | 0.540 | 0.498 | 0.490 | 0.500 | |
The respondent participates in labor force | Yes | 0.848 | 0.359 | 0.835 | 0.371 | 0.858 | 0.350 |
S.D.: standard deviation. A hypothesis test is conducted to identify the difference between the means of the two-birth household group and one-birth household group.
As shown in Table
From Table
Our empirical study aims to identify the treatment effect of grandparental childcare for the first child on the second birth. We first identify possible determinants of having grandparental childcare for the first child with a basic regression model. Table
The propensity score model: logistic regression results of factors affecting having grandparents as the primary-care provider for the first child.
Explanatory variables | Coef. | S.E. | [95% conf. Interval] | ||
---|---|---|---|---|---|
Age of the father | −0.047 | 0.004 | −11.04 | 0.001 | [−0.055, −0.039] |
Age of the mother | −0.037 | 0.004 | −8.22 | 0.001 | [−0.046, −0.028] |
Ethnicity of the parents | |||||
(i) Both Hans | 0.287 | 0.040 | 7.10 | 0.001 | [0.208, 0.366] |
Age of the first child | 0.110 | 0.012 | 8.94 | 0.001 | [0.086, 0.135] |
Square of the age of the first child | 0.001 | 0.001 | 0.14 | 0.886 | [−0.001, 0.001] |
The first child is a girl | 0.106 | 0.0219 | 4.81 | 0.001 | [0.063, 0.149] |
Education level of the father | |||||
(i) Junior high school | 0.112 | 0.047 | 2.38 | 0.017 | [0.020, 0.204] |
(ii) Senior high school | 0.068 | 0.054 | 1.26 | 0.209 | [−0.038, 0.173] |
(iii) College and above | −0.025 | 0.068 | −0.37 | 0.713 | [−0.158, 0.108] |
Education level of the mother | |||||
(i) Junior high school | 0.010 | 0.041 | 0.24 | 0.814 | [−0.070, 0.089] |
(ii) Senior high school | −0.141 | 0.050 | −2.84 | 0.005 | [−0.238, −0.044] |
(iii) College and above | −0.148 | 0.067 | −2.22 | 0.027 | [−0.279, −0.017] |
Family monthly income (in log) | 0.185 | 0.022 | 8.44 | 0.001 | [0.142, 0.228] |
Settlement intention | |||||
(i) Return home | 1.093 | 0.049 | 22.53 | 0.001 | [0.998, 1.188] |
(ii) Go to other places | 0.727 | 0.063 | 11.55 | 0.001 | [0.604, 0.850] |
(iii) Uncertain | 0.797 | 0.024 | 33.06 | 0.001 | [0.750, 0.844] |
(i) Different | −0.131 | 0.045 | −2.93 | 0.003 | [−0.218, −0.043] |
(ii) Both urban | −0.166 | 0.044 | −3.80 | 0.001 | [−0.252, −0.080] |
The respondent participates in labor force | 0.927 | 0.037 | 24.84 | 0.001 | [0.854, 1.001] |
The child migrates with the parents | −2.402 | 0.027 | −89.13 | 0.001 | [−2.455, −2.350] |
Sample size | 61,049 | ||||
−2LL | 25818.020 | ||||
Pseudo | 0.221 | ||||
LR | 14620.810 | ||||
0.001 |
S.E.: standard errors; LL: log likelihood.
The results in Table
Given the nonexperimental observations in the CMDS, the estimation of the treatment effect of having grandparents as the primary-care provider for the first child is a challenging task because of the potential observable and unobservable biases. More specifically, in an observational study, due to the lack of randomization, statistical inferences without adjusting the
To estimate the unobservable counterfactual outcomes, we adopt propensity score matching (PSM) [
When the first child in a family is mainly taken care of by the grandparents, the potential outcome
Matching quality test: balancing property.
Explanatory variables | Matching | Mean | Bias (%) | ||||
---|---|---|---|---|---|---|---|
Treated | Controls | Bias | Reduct. | ||||
Age of the father | Before | 34.026 | 34.635 | −11.9 | — | −12.48 | 0.001 |
After | 34.026 | 34.051 | −0.5 | 96.0 | −0.40 | 0.692 | |
Age of the mother | Before | 32.291 | 32.798 | −9.9 | — | −10.40 | 0.001 |
After | 32.291 | 32.299 | −0.2 | 98.3 | −0.14 | 0.889 | |
Ethnicity of the parents | Before | 0.923 | 0.897 | 8.9 | — | 9.03 | 0.001 |
After | 0.923 | 0.922 | 0.1 | 98.3 | 0.13 | 0.894 | |
Age of the first child | Before | 8.912 | 8.727 | 4.2 | — | 4.42 | 0.001 |
After | 8.912 | 8.961 | −1.1 | 73.8 | −0.91 | 0.364 | |
Square of the age of the first child | Before | 99.386 | 95.015 | 5.1 | — | 5.36 | 0.001 |
After | 99.386 | 100.73 | −1.6 | 69.1 | −1.28 | 0.199 | |
Gender of the first child | |||||||
(i) Girl | Before | 0.477 | 0.462 | 2.9 | — | 3.04 | 0.002 |
After | 0.477 | 0.483 | −1.3 | 55.4 | −1.09 | 0.275 | |
Education level of the father | |||||||
(i) Junior high school | Before | 0.604 | 0.555 | 10.0 | — | 10.41 | 0.001 |
After | 0.604 | 0.605 | −0.2 | 97.9 | −0.18 | 0.856 | |
(ii) Senior high school | Before | 0.222 | 0.237 | −3.4 | — | −3.56 | 0.001 |
After | 0.222 | 0.220 | 0.5 | 86.4 | 0.40 | 0.689 | |
(iii) College and above | Before | 0.092 | 0.125 | −10.6 | — | −10.71 | 0.001 |
After | 0.092 | 0.092 | 0.1 | 99.1 | 0.08 | 0.935 | |
Education level of the mother | |||||||
(i) Junior high school | Before | 0.610 | 0.557 | 10.8 | — | 11.22 | 0.001 |
After | 0.610 | 0.604 | 1.3 | 88.1 | 1.09 | 0.274 | |
(ii) Senior high school | Before | 0.192 | 0.220 | −7.2 | — | −7.37 | 0.001 |
After | 0.192 | 0.192 | −0.1 | 98.1 | −0.12 | 0.904 | |
(iii) College and above | Before | 0.078 | 0.106 | −9.5 | — | −9.62 | 0.001 |
After | 0.078 | 0.077 | 0.4 | 95.4 | 0.40 | 0.690 | |
Family monthly income (in log) | Before | 8.818 | 8.746 | 13.9 | — | 14.03 | 0.001 |
After | 8.818 | 8.825 | −1.3 | 90.7 | −1.08 | 0.280 | |
Settlement intention | |||||||
(i) Return home | Before | 0.077 | 0.035 | 18.6 | — | 21.58 | 0.001 |
After | 0.077 | 0.072 | 2.2 | 88.4 | 1.58 | 0.114 | |
(ii) Go to other places | Before | 0.036 | 0.025 | 6.1 | — | 6.72 | 0.001 |
After | 0.036 | 0.038 | −1.4 | 78.0 | −1.04 | 0.299 | |
(iii) Uncertain | Before | 0.406 | 0.276 | 27.7 | — | 29.71 | 0.001 |
After | 0.406 | 0.415 | −1.9 | 93.1 | −1.53 | 0.126 | |
(i) Different | Before | 0.062 | 0.079 | −6.5 | — | −6.64 | 0.001 |
After | 0.062 | 0.062 | 0.1 | 98.3 | 0.10 | 0.922 | |
(ii) Both urban | Before | 0.073 | 0.097 | −8.7 | — | −8.75 | 0.001 |
After | 0.073 | 0.073 | 0.2 | 97.4 | 0.21 | 0.837 | |
The respondent participates in labor force | Before | 0.924 | 0.824 | 30.3 | — | 29.06 | 0.001 |
After | 0.924 | 0.922 | 0.5 | 98.2 | 0.56 | 0.578 | |
The child migrates with the parents | Before | 0.141 | 0.625 | −114.6 | — | −110.60 | 0.001 |
After | 0.141 | 0.145 | −0.8 | 99.3 | −0.78 | 0.436 |
In our experiments, PSM is performed on the explanatory variables described in the logistic model shown in Table
Density distribution of propensity scores for the treated and control groups.
Table
Propensity score matching results: average treatment effect of grandparenting on the birth of the second child.
Mean | ATT | S.E. | T-stat | ||
---|---|---|---|---|---|
Treated | Controls | ||||
Sample size | 14,213 | 46,836 | — | — | — |
Before matching | 0.509 | 0.424 | 0.085 | 0.005 | 17.93 |
After matching | |||||
(i) NNM | 0.509 | 0.455 | 0.054 | 0.008 | 6.89 |
(ii) RM | 0.509 | 0.453 | 0.056 | 0.006 | 9.65 |
(iii) KM | 0.509 | 0.453 | 0.056 | 0.006 | 9.59 |
ATT: average treatment effect on the treated; S.E.: standard errors.
To test the robustness of the matching estimators of PSM against potential hidden bias attributed to unobserved variables, we follow Rosenbaum’s procedure [
Sensitivity to unobserved biases: Rosenbaum bounds for grandparental childcare treatment effects.
Gamma | ||
---|---|---|
1.00 | <0.0001 | <0.0001 |
1.05 | <0.0001 | <0.0001 |
1.10 | <0.0001 | <0.0001 |
1.15 | 0.0002 | <0.0001 |
1.20 | 0.037 | <0.0001 |
1.25 | 0.454 | <0.0001 |
1.30 | 0.932 | <0.0001 |
1.35 | 0.999 | <0.0001 |
1.40 | 0.999 | <0.0001 |
1.45 | 1.000 | <0.0001 |
1.50 | 1.000 | <0.0001 |
To investigate possible heterogeneous results in subsets of respondents, we estimate treatment effects in different subgroups. We first investigate the treatment effects of grandparental childcare for groups of respondents with different labor-participation statuses, i.e., working and nonworking. It is noteworthy that the CMDS 2016 just collected the working information about the respondents, who may be female or male. Table
Descriptive statistics of female respondents and male respondents given different labor-participation statuses.
Female respondents | Male respondents | |||
---|---|---|---|---|
Working | Nonworking | Working | Nonworking | |
Sample size | 21,905 (65.5%) | 7,564 (34.5%) | 29,839 (94.2%) | 1,741 (5.8%) |
Primal-care provider of the first child | Percentage (%) | Percentage (%) | Percentage (%) | Percentage (%) |
(i) Parents | 55.2 | 44.9 | 53.7 | 56.1 |
(ii) Father | 0.7 | 0.6 | 0.6 | 3.3 |
(iii) Mother | 11.9 | 41.9 | 19.5 | 20.8 |
(iv) Grandparents | 28.3 | 10.7 | 23.2 | 15.8 |
(v) Other caretakers | 3.5 | 1.7 | 2.6 | 2.9 |
(vi) Nobody | 0.4 | 0.2 | 0.4 | 1.1 |
Having the second birth | 41.9 | 48.9 | 45.0 | 44.1 |
ATT estimates for subgroups of women respondents: the treatment effects of having grandparents as the primary-care provider for the first child on having the second birth.
Subgroups | Sample size | Mean | ATT | SE | T-stat | |
---|---|---|---|---|---|---|
Treated | Controls | |||||
Working | 21,905 | 0.489 | 0.410 | 0.079 | 0.012 | 6.45 |
Nonworking | 7,564 | 0.597 | 0.549 | 0.111 | 0.027 | 4.06 |
NNM is used as the matching method.
Since rural-urban migration is one of the main characters in domestic migrants in China and has always been the largest share of migration, we further investigate the treatment effects for subgroups of different
ATT estimates for subgroups of couples: the treatment effect of having grandparents as the primary-care provider for the first child on having the second birth.
Subgroups of couples | Sample size | Mean | ATT | SE | T-stat | |
---|---|---|---|---|---|---|
Treated | Controls | |||||
Both rural | 50,845 | 0.535 | 0.489 | 0.046 | 0.009 | 5.40 |
At least one urban | 10,195 | 0.339 | 0.293 | 0.045 | 0.018 | 2.56 |
NNM is used as the matching method.
In this paper, we investigated the effects of intergeneration childcare on the birth of the second child in China with both theoretical and empirical analysis. Specifically, we have developed a DGE model calibrated to match some stylized facts of China’s population. The theoretical analysis with numerical simulation has shown that, with the increase of life expectancy, hours that can be invested in grandparenting and the number of births will also increase; grandparenting is an important factor that can not only boost the fertility level but also help maintain its positive trend. Drawing on the internal-migrant data of the CMDS 2016, we conducted PSM analysis with controlling self-selection biases to estimate the treatment effect on the treated, which shows that intergeneration childcare has a statistically significant and positive effect on the birth of the second child. As a complement to the PSM estimation, we conducted sensitivity analysis based on Rosenbaum bounds, which indicates the relative robustness of our treatment estimates to moderate hidden biases attributed to unobservable variables. We also estimated treatment effects on different subgroups, i.e., the working and nonworking female respondents, and the couple groups of different
Findings from our analysis indicate that family arrangements about childcare have nontrivial macroeconomic effects. Given the limited actual effect [
The provision of childcare by grandparents is a form of downward intergenerational time transfer with emotional involvement. However, this informal child care arrangement still faces many challenges in many families. Specifically, (1) there is usually an obvious gap in the type of child-rearing between the grandparents and the parents, and the intensive parenting style followed by young couples is typically challenging to grandparents; (2) grandparents also face pressure to balance their own family and the extent of involvement in grandparenting, especially when their partners are still working; (3) despite the positive effect on fertility increase, provision of intense care to grandchildren may also have an adverse impact on grandparents’ well-being (China’s State Council, 2010; [
Currently, the role of grandparents and the stainability of grandparental childcare are still less visible on the population policy agenda of policymakers. More efforts by the government, families, and the community, such as subsidizing grandparent childcare, supporting early childhood development, and improving the well-being of grandparents that involve in childcare, should be made to support family life and ensure this informal childcare arrangement goes on wheels.
The data used to support the findings of this study are available at
The authors declare no conflicts of interest.
This research was partially funded by the National Nature Science Foundation of China (No. 71973049) and the fund of Huaqiao University (No. ZQN-PY411).