Silviase/jgov_v1.4_full_ann huggingface dataset:
# The expenditure on children in Japan $ ^{\dagger} $

Masahiro Hori

Hitotsubashi University, and Economic and Social Research Institute, Cabinet Office

## 1 Introduction

Japan is facing a demographic crisis due to declining fertility rates coupled with rising longevity. While fewer than three workers currently support a retiree in Japan, this ratio is projected to drop to two workers for every aged dependent by 2025. Although Japan’s has been successful thus far in maintaining a relatively generous social security system, maintaining this system will be increasingly difficult, given the inevitable shrinking of the working population. The solution to Japan’s aging crisis appears to be straightforward but not easy to implement: increase the participation of women and the elderly in the workforce; reform the pension system; raise taxes to pay for the cost of social security; and encourage society to be more supportive of child rearing in order to boost fertility.

This study focuses on the last of these issues, namely ways to provide greater support for child rearing, by attempting to estimate the average family expenditure on children in Japan. Based on the perception that the cost of child rearing is a key factor in a married couple’s decision to have a baby (at least from the viewpoint of economics), there have been several recent attempts to examine expenditures on children, including Rosenbaum and Ruhm (2007) for the United States, Bargain and Donni (2010) for France, Bargain, Donni, and Gbakou for Ireland (2010), and Menon and Perali (2009) for Italy. Among others, the U.S. Department of Agriculture has provided annual figures on expenditures on children since 1960, $ ^{1} $ and its child rearing expense estimates are often used in determining state child support guidelines and child care payments. Despite the importance of this issue for a country experiencing a decline in fertility, there are few empirical studies
investigating how much parents in Japan spend on their children. A few studies using equivalence scales to examine child rearing costs in Japan do exist (see Suruga, 1993, and Oyama, 2006), but they focus only on a relatively short period in the past and the estimates are likely to be too outdated to provide a reliable assessment of the present situation. $ ^{2} $

The present study seeks to address this dearth of research by estimating the average expenditure on children by families in Japan over the past quarter of a century, using the rich information on household expenditures and demographics available from the Family Income and Expenditure Survey (FIES). Instead of using equivalence scales, which, although widely used in the literature, rest on debatable assumptions, this study tries to calculate average child rearing expenditure by individual household members, taking into account their age, sex, and several other attributes, in order to arrive at average household child rearing expenditures. The results of our simple regression analysis indicate that average total cumulative expenditure (excluding housing expenses) for the first child from birth through age 18 was approximately 16.5 million yen in the period 2004–2008. Furthermore, when there are two or more children in a household, the average expenditure per child is substantially lower; for example, in households with two children, it was approximately 11 million yen, partly reflecting economies of scale in child rearing activity. Note that there is no significant gender-based difference in the total child rearing expenditure. Further, the estimated average total expenditure per child shows a clear upward trend not only in absolute terms but also relative to what parents spend on themselves.

The rest of the paper is organized as follows. The next section describes the dataset and empirical strategy used. Section 3 presents the results of a preliminary estimation obtained by simply applying the methodology employed here to the total consumption expenditure by individual households; in addition, the section highlights a few problems that need to be addressed to make the estimates more reliable. Section 4 then reports the main estimates of the expenditure on children for the period 2004–2008. Next, Section 5 considers historical trends in child rearing costs in Japan since the mid-1980s. Finally, Section 6 concludes.
## 2 Data and Methodology

### 2.1 Data Source

To estimate the expenditure on children in an average Japanese household, the household-level data from the Family Income and Expenditure Survey (FIES) from the mid-1980s is used. The FIES provides detailed monthly information on household income and expenditure, and household members' characteristics (sex, age, relationship to the household head, etc.) for a nationally representative sample of 8,000–9,000 households. The monthly data is compiled from a diary collected twice a month, and each household is surveyed for six months before being replaced.

Another source of detailed household expenditure data for Japan is the National Survey of Family Income and Expenditure (NSFIE), which is implemented every five years and covers a larger sample of more than 50,000 households. However, the NSFIE data are not suitable for the purpose of the analysis here, since the survey period is only from September to November and the data may therefore be highly susceptible to expenditure seasonality. $ ^{3} $

The analysis in this study focuses on observations for households of two or more persons (with/without children). Moreover, in order to ensure a sufficiently large number of observations is available for the regression analysis, which employs an exceptionally large number of independent variables, expenditure patterns for three selected five-year intervals (instead of each year), namely 1984–1988, 1994–1998, and 2004–2008 are examined. The number of observations for each of the three intervals is approximately 480,000 $ (8,000 \times 12 \times 5 = 480,000) $ . In order to improve the estimates, the sample will be restricted to households without large remittance expenditures, $ ^{4} $ since remittances are expenses for relatives who live away from the household head and cannot be assigned to a specific family member listed in the FIES. $ ^{5} $ Even after the exclusion of households
with large remittances, there are more than 440,000 observations for each interval.

In addition to the total of households' monthly consumption expenditure, expenditure on the following 10 broad categories of consumption is examined: (1) food; (2) housing; (3) fuel, light, and water charges; (4) furniture and household utensils; (5) clothes and footwear; (6) medical care; (7) transportation and communication; (8) education; (9) culture and recreation; and (10) other consumption expenditures. Summary statistics of the key variables are shown in Table 1.

Given that the aim of the study is to examine expenditure on children, the central explanatory variables of the analysis are those concerning household demographic structure. Specifically, the analysis starts with a comparison of the expenditure patterns of married couples without children and married couples with at least one child to examine the effects that having a child or children on the consumption behavior of a couple. In the sample of households without large remittances, roughly two-thirds of households have at least one child, while the share of households with children has been declining in recent years. In addition to the presence/absence of children, the analysis in this study employs information on the age and sex of all household members (and not only the household head) – something that has not been done in earlier studies. Figure 1 shows the age-sex pyramid of the population included in the dataset (the observations in the three five-year intervals aggregated together) as well as the pyramid for each of the five-year intervals. Unfortunately, the age-sex pyramids based on the FIES data appear not to follow the pattern for the national population as a whole; that is, young adults seem to be underrepresented in the age-sex pyramids based on the FIES data. The reason is the way that household members are defined in the FIES, i.e., children are counted as household members only when they live with the household head. However, thanks to the large sample size of the FIES, it is possible to obtain a sufficiently large number of observations for all age-sex brackets, including for young adults. The changing demographics resulting from the aging of the Japanese population are well mirrored in the changing shape of the FIES pyramids.

### 2.2 Methodology

Household expenditures are made either on shared goods, such as housing, or on individually
consumed goods, such as food, and it is usually impossible to directly observe expenditures on behalf of a specific household member, for example, a child. Therefore, it is necessary to use an indirect approach to assign household expenditures to a specific household member and to estimate household expenditure on children. A relatively widely used approach is the marginal cost method, which measures expenditures on children as the difference in expenses between families with children and equivalent families without children. However, there is no generally accepted equivalency measure in the economics literature, and it is known that estimates vary substantially depending on the choice of equivalency measure. In addition, the marginal cost method does not allow for the possibility that parents change expenditure on themselves after a child is added to the household.

Given this, this study aims to simply calculate, through multiple linear regressions, the average expenditure on a household member of a specific age, sex, and other attributes. More concretely, adopting the method developed by Mankiw and Wail (1989) to examine the impact of demographic changes on the U.S. housing market, consumption expenditure by a household is modeled as an additive function of the expenditure on its members:

$$ C(i;j,t)=\sum_{k=1}^{N_{j}}c(i;k,j,t), $$

where $ q(i;k,j,t) $ is the consumption expenditure (on category i goods/services) on the kth member in household j during year t, and $ N_{j} $ is the total number of persons in household j. Expenditure on each individual is considered to be a function of age, sex, and household structure (or family type). Each age-sex combination is allowed to have its own expenditure parameter. The age-sex combination parameters differ depending on whether the individual has at least one child (if the individual is an adult) and whether the child is the firstborn child (if the individual is a child). Therefore, category i goods/services expenditure on an individual household member is given by

$$ \begin{align*}c(i;k,j,t)=&\quad\sum_{sex=male}^{female}\sum_{age=20}^{85over}\sum_{child=no}^{yes}\alpha_{p}(i;sex,age,child,t)D_{p}(sex,age,child,k,j,t)\\&+\sum_{sex=male}^{female}\sum_{age=0}^{23}\sum_{first=yes}^{no}\alpha_{c}(i;sex,age,first,t)D_{c}(sex,age,first,k,j,t),\end{align*} $$

where $ D_{p}(sex,age_{0},child/nochild,k,j,t)=1 $ if the individual $ (k,j,t) $ is the head of the household or its spouse, who is aged $ age_{0} $ , and has at least one child/no children.
$ D_{c}(sex_{1},age_{1},first/nofirst,k,j,t)=1 $ if the individual $ (k,j,t) $ is a household head's dependent child, whose sex is $ sex_{1} $ , whose age is $ age_{1} $ , and who is the firstborn (or eldest) child in the household. The parameter $ \alpha_{p}(i;sex_{0},age_{0},child/nochild,t) $ indicates the category i goods/services expenditure on a household head/spouse of age $ age_{0} $ , with at least one child/without children at time t. $ \alpha_{c}(i;sex_{0},age_{0},first/nofirst,t) $ is the expenditure on a son/daughter of age $ age_{0} $ that is the firstborn child/non-firstborn child in the family. Combining (1) and (2) gives the equation for expenditure on category i goods/services by household j at time t:

$$ \begin{align*}C(i;j,t)=&\quad\sum_{sex=male}^{female}\sum_{age=20}^{85over}\sum_{child=no}^{yes}\alpha_{p}(i;sex,age,child,t)\sum_{k=1}^{N_{j}}D_{p}(sex,age,child,k,j,t)\\&+\sum_{sex=male}^{female}\sum_{age=0}^{23}\sum_{first=yes}^{no}\alpha_{c}(i;sex,age,first,t)\sum_{k=1}^{N_{j}}D_{c}(sex,age,first,k,j,t),\end{align*} $$

In the next section, equation (3) is estimated for a preliminary analysis to obtain $ \alpha_{p}() $ s and $ \alpha_{c}() $ s for the total consumption expenditure by an individual household in the sample from the 2004–2008 FIES. As the regression does not include variables such as income and assets, key items in standard theories of consumption, the estimated $ \hat{\alpha}() $ s cannot be taken as structural parameters. Instead, they should be understood as effective calculations of average expenditures on goods/services i at time t on a household member of a specified age, sex, and other attributes (i.e., with/without children for the household head and his/her spouse, and first/non-first for children).

It is additionally assumed that $ \alpha_{p}(i;sex,age,first,t) $ and $ \alpha_{c}(i;sex,age,first,t) $ vary with the month, reflecting consumption seasonality, but are constant over the years in the five-year interval from 2004 to 2008, since economic growth (and inflation) were roughly zero in that period. Based on these assumptions, the average annual expenditure on goods/services i for the period on an individual of a specified age, sex, and other attributes can be calculated as

$$ \begin{aligned}&C(i,sex_{0},age_{0},child_{0})=\sum_{month=1}^{12}\hat{\alpha}_{p}(i;sex_{0},age_{0},child_{0},month)\quad for parents,and\\&C(i,sex_{1},age_{1},first_{1})=\sum_{month=1}^{12}\hat{\alpha}_{c}(i;sex_{1},age_{1},first_{1},month)\quad for children.\\ \end{aligned} $$

If we were interested in consumption expenditures over some specific age interval in the course of a person’s life, say from age $ a_{0} $ to $ a_{1} $ , the average consumption over the period could be calculated as

$$ C(i,sex_{1},a_{0}a_{1},first_{1})=\sum_{age=a_{0}}^{a_{1}}C(i,sex_{1},age,first_{1})=\sum_{age=a_{0}}^{a_{1}}\sum_{month=1}^{12}\hat{\alpha}_{c}(i;sex_{1},age,first_{1},month) $$
As the aim of this study is to estimate the expenditure on child rearing in a typical household in Japan, (5) is calculated over the age interval from birth through age 18. Although expenditure on children often continues beyond the age of 18, the estimation here focuses on expenditures up until this age. The reason is that expenditures on children aged 19 and older differ considerably across households and, more crucially, the FIES definition of household members, which excludes children living separately from their parents, makes it impossible to estimate expenditures on such household members, since children aged 19 and over often start to live separately to attend college. Therefore, although the following sections also report the expenditure on college-aged children (i.e., aged 19 to 23), these estimates should be treated with caution. $ ^{6} $ In addition, for reference, the average expenditure by parents on themselves is reported to gain a sense of the relative magnitude of child rearing expenditures. Such estimates are also useful for examining how the consumption behavior of the household head and his/her spouse are affected by having children.

## 3 Tentative Application to Total Consumption Expenditure

To illustrate the methodology introduced above, this section presents a simple application to total consumption expenditure by an individual household (in the sample period 2004–2008). Although this simple application is useful for revealing several interesting facts about household expenditure on children in Japan, it also turns out that there are a number of aspects that need to be improved to obtain more reliable estimates.

### 3.1 Preliminary Findings

The results of the simple application of the methodology, i.e., equations (5) and (4), to total consumption expenditure are shown in Table 2 and Figure 2, respectively. Beginning with Table 2.1 and Figure 2.1, the results reveal a number of interesting facts about child rearing expenditure in Japan. First, there are hardly any gender-based differences in the expenditure on children. Annual expenditure per child (for the first child) is slightly less than 1 million yen for children up to their early teens and 1.5 million yen for children of high school age. Total expenditure on the firstborn
child from birth through age 18 is around 19 million yen. Second, when there are two or more children in a household, the increases in expenditure due to the second or later children are much smaller than that for the first child. The average expenditure per child (cumulated over the age interval from birth through age 18) in households with two children falls to approximately 11 million yen, suggesting partly that there are economies of scale in child rearing activities and that families with two children have less money to spend on each child. Third, consumption expenditure by the household head and the spouse in households with at least one child is substantially lower than in households without children.

Given that remittances, which fall into the “other consumption expenditure” category, represent an expenditure on those living outside the household, and therefore cannot be assigned to a specific household member listed in the FIES household questionnaire, expenditures were re-estimated after removing remittances from household consumption (Table 2.2 and Figure 2.2). While the estimate of the total expenditure on the first child (cumulated from birth through age 18) decreases to around 17 million yen, and the rise in expenditure on a middle-aged childless wife (observed in Figure 2.1) disappears in Figure 2.2, the overall patterns in the expenditure on children are not very different from those found in the first regression, before excluding remittances.

### 3.2 Problems Found in the Estimates on Subcategories

Although the findings above suggest that the methodology employed for estimating the expenditure on each household member is useful, the estimates need to be treated with caution. Space constraints mean that it is not possible to discuss the reasons here in full, but essentially some flaws emerge when the same methodology is applied to the subcategories of consumption. In theory, exactly the same results should be obtained for average per capita expenditure (on a household member of a specific age, sex, and other attributes) regardless of whether total expenditure or the sum of the estimates for the subcategories are used. Therefore, similar regressions were performed for the 10 broad subcategories and these show that at least for a few items, the estimates contain obvious biases. They include the following:

1. housing expenses are estimated to decrease as household members become older (see Figure
3.1);

2. educational expenses for a female parent with at least one child are estimated to be negative, probably causing an overestimation of the cost of education for children (see Figure 3.2); and

3. the estimates of other consumption expenditures on children become large negative values; moreover, the estimates for this category appear to be considerably affected by remittances (see Figures 3.3 and 3.4).

The problem regarding housing expenses probably arises because the FIES does not regard mortgage repayments by homeowners as housing expenditure. The counterintuitive estimates indicate not only that housing expenditure by homeowners is not well captured, but also that estimating housing expenditure is difficult, as it is strongly affected by the behavior of homebuyers. The second problem regarding the education category probably indicates the presence of multicollinearity due to the large number of independent variables. As education expenses by adults without children appear to be almost zero, better estimates can probably be obtained by restricting education expenses by parents to be also zero. A similar multicollinearity underlies the third issue concerning “other consumption expenditures” and, unlike the multicollinearity regarding education expenses, presents a much more substantial problem for the analysis in this study. More specifically, the “other consumption” category contains remittances, which make up a sizable share but which represent consumption expenditures on somebody (including relatives) not included in the FIES households, and therefore the methodology employed here cannot (and should not) allocate such expenditure to reported members in the FIES households. In a nutshell, the information available from the FIES household questionnaires is insufficient to identify the number of children in each household, especially when the household makes large remittances, which may or may not be for a child (or children) aged 19 or older and living separately, e.g., to attend college.

### 3.3 Remedies

In order to overcome the problems discussed above, the following strategy is adopted in the subsequent sections. First, to ensure that any of the problems described in the previous section are avoided, the expenditure on children in each subcategory is first estimated and the total is then
calculated as the sum of the category estimates. Second, given the difficulties in dealing with remittances, only observations on households without large monthly remittances are used, as already noted in the data section. Excluding observations on households with large monthly remittances not only avoids the problem of how to assign remittances to a specific member in a household, but also mitigates the problems resulting from the incomplete coverage of household members in the FIES. Third, given the problems regarding housing expenditure and remittances mentioned above, expenditure on children is calculated excluding these two subcategories. $ ^{7} $ Fourth, given the multicollinearity observed for education expenditures and other consumption expenditures, zero restrictions are imposed on some of the parameters to reduce the number of independent variables. More specifically, it is presumed that education expenses are for dependent children (from birth through age 23) and that other consumption expenditures are for adult members in each household. $ ^{8} $

## 4 Estimates by Consumption Category

This section presents the estimates of the expenditure on children following the procedure discussed in the previous section; that is, the expenditure on children for each consumption category is estimated and the total is then calculated as the sum of the category estimates.

#### 4.1 Food (Figure 4.1 and Table 3)

Notwithstanding the finding in the previous section that there appear to be no differences in the total expenditure on male and female children, when age-consumption profiles for individual consumption categories are examined, differences in expenditures on boys and girls can be observed. As for food expenditure, this is greater for boys than for girls and the gender gap in consumption becomes most evident during adolescence. The increase in food expenditure due to a