Panel Data Research Center at Keio University
DISCUSSION PAPER SERIES
DP2017-008
February, 2018

Birth Order, Gender, and the Parental Investment Gap among Children
Kei Sakata*Colin McKenzie**
Wataru Kureishi***Midori Wakabayashi****【Abstract】
Using panel data from the Japanese Longitudinal Survey of Newborns in the 21st Century, thepurpose of this paper is to examine whether birth order and gender causally matter when parents
make financial investments in their children. This paper focuses on the actual investment in thechildren in the form of financial resources. It is found that in Japan, parents spend more money on:
their first born child; their male children when they are young; and their female children when they
are old. In contrast, parents spending on educational related activities outside regular schools ishigher for boys, but there is no difference between first born and later born children. Spending on
extra-curricular activities is higher for girls and for first born children. Interestingly, girls receive
more pocket money than boys, whereas a first born child receives less pocket money compared to ahigher order child of the same age.

* Professor, Ritsumeikan University** Professor, Keio University*** National Institute of Population and Social Security Research**** Associate Professor, Tohoku University

Panel Data Research Center at Keio University
Keio University

Birth Order, Gender, and the Parental Investment
Gap among Children1
Kei SAKATAa, Colin MCKENZIEb2, Wataru KUREISHIc, and Midori WAKABAYASHIda

Ritsumeikan University, 1-1-1 Noji-higashi, Kusatsu, Shiga 525-8577, JAPAN. Email: ksakata@ec.ritsumei.ac.jpbKeio University, 2-15-45 Mita, Minato-ku, Tokyo, 108-8345, JAPAN. Tel: 81-3-5427-1831. Fax: 81-3-5427-1578.

ORCID: 0000-0001-9867-6735. Email: mckenzie@z8.keio.jpcNational Institute of Population and Social Security Research, Hibiya Kokusai Building 6th Floor, 2-2-3 Uchisaiwaicyo,

Chiyoda-ku, Tokyo 100-0011. Email: kureishi-wataru@ipss.go.jpdTohoku University, 27-1 Kawauchi, Aoba-ku, Sendai-Shi, Miyagi 980-8576, JAPAN. ORCID: 0000-0002-6516-8678.

Email: mwaka@econ.tohoku.ac.jp

1

The authors would like to thank Yasuhiro Tsukahara and participants in the 22nd Eurasia Business and Economics Society(EBES) Conference (Rome), the 16th International Conference of the Japan Economic Policy Association (Naha), the 11th
International Conference of the Thailand Econometric Society (Chiang Mai), the 12th Joint Symposium of Five Leading
Asian Universities (Singapore), and a seminar at Keio University for their helpful and constructive comments on earlier
drafts of this paper. The data used in this paper comes from the Japanese Ministry of Health, Labour and Welfare’s
Longitudinal Survey of Newborns in the 21st Century (21 seiki shusshoji judan chosa) and the Live Birth Form of Vital
Statistics (Jinko dotai chosa shusseihyo). The authors gratefully acknowledge the financial assistance provided by the Japan
Society for the Promotion of Science (JSPS) Grant in Aid for Scientific Research (B) No. 15H03363 for a project “TheImpact of Child Birth and Child Care on the Employment of Women From the Perspective of Gender Preference, Nursing
Care and Family Relationships” (Project Leader: Colin McKenzie). The funding source had no involvement in any stageof this research.
2

Corresponding author: Colin McKenzie, Faculty of Economics, Keio University, 2-15-45 Mita, Minato-ku, Tokyo, 108-

8345, JAPAN. Tel: 81-3-5427-1831. Fax: 81-3-5427-1578. Email: mckenzie@z8.keio.jp1

Abstract
Using panel data from the Japanese Longitudinal Survey of Newborns in the 21st Century, the purpose of this paper is to
examine whether birth order and gender causally matter when parents make financial investments in their children. This
paper focuses on the actual investment in the children in the form of financial resources. It is found that in Japan, parents
spend more money on: their first born child; their male children when they are young; and their female children when they
are old. In contrast, parents spending on educational related activities outside regular schools is higher for boys, but there
is no difference between first born and later born children. Spending on extra-curricular activities is higher for girls and forfirst born children. Interestingly, girls receive more pocket money than boys, whereas a first born child receives less pocket
money compared to a higher order child of the same age.
Keywords: birth order; gender; parental investment on child; random effect instrumental variable method.
JEL classification codes: J08, J13, J22

Research Highlights
・We estimate the causal relationship between birth order and gender, and parental investments in their children.
・Japanese parents spend more money on their first born children.
・Japanese parents spend more on extra-curricular activites for girls.
・Japanese parents spend more on extra-educational activities for boys.
・Daughters receive more pocket money, whereas the first born receives less.
Declarations
The authors declare they do not have any actual or potential conflict of interest in relation to this research. No ethic approval
was required for this study.

2

1.

Introduction

The purpose of this paper is to examine how birth order and gender causally matter for parental financial investments(total expenditure and some of its components including pocket money) in their children in Japan. Parent’s investments intheir children are crucial for their children’s development and the future outcomes of their children. Parents must makevarious choices about their investment in their children given their intertemporal budget constraint and their current budget
constraint if they face liquidity constraints. A number of studies suggest that parents make different distributions of theirresources across siblings (for example, Price (2008)). As theory suggests a trade-off between child quality and quantity, alarger family size can potentially reduce parental resources, and have negative effects on child outcomes. Much of theexisting research concentrates on identifying pure birth order effects after taking account of family size effects. For instance,
by using twin births as an instrument for family size, Black et al. (2005) examine the effect of family size and birth orderon the educational attainment of children, and find that birth order has a significant and negative effect on children’s
education. They also find that there is strong evidence for birth order effects for adult earnings, employment and teenage
childbearing, especially for women. Heiland (2009) examines birth order and early scholastic ability (verbal ability), andpresents empirical evidence suggesting that verbal ability of the first born is higher than middle of the birth order children.
Overall, most studies indicate that there are positive birth order effects even after controlling for family size effects, that
is, a first born child performs better (see Bjorklun and Salvanes 2011). However, due to data availability, most of theprevious studies examine the outcomes for children such as educational attainment, academic achievement, and healthstatus rather than the actual investments in the children. Studies that examine “outputs” are unable to directly answer thequestion of whether or not parents in fact change the levels of their inputs, that is, their investment in children, based on
their children’s birth order and gender.
When research has been conducted on parental investments in their children, it has typically focused on how much timeparents spend with their children. Using the American Time Use Survey, Price (2008) provides evidence that a first bornchild receives 20 minutes more parental time than a second born child of the same age in a similar family. Sakata et al.
(2018) provides evidence that Japanese parents also spend more time with their first born child. Research on the effects of3

birth order on the levels of financial inputs for example, expenditure on children and pocket money is quite rare. In the caseof expenditure, one of the key problems is obtaining expenditure spending on each child rather than the total expenditureon all children lumped together. For example, using data from the US Consumer Expenditure Survey, Kornrich andFurstenberg (2013) first identify categories of expenditure that are child related, and then analyse the factors that determine
the spending on all children. In contrast, the survey data used in this paper contains a parental estimate of their overall
expenditure on the child that is the subject of the survey, as well as expenditures on extra-educational activities, extracurricular activities, and pocket money for the child in question. These expenditures will enable us to estimate the impactof gender and birth order effects for these four expenditure variables.
Gender may matter because parents have gender preferences in relation to children and they may differ across the parents,or there may be something more fundamental differences. There is recent evidence for the United States that suggests young
boys (boys aged 5 or less) face “unique risks as a result of neurobiological and environmental factors” (Golding and
Fitzgerald 2017, p. 5; McKinney et al. 2017). Garcia et al. (2017) suggest that boys in the United States benefit from highlevel childcare whereas girls do not. Both these factors may lead to parents altering their investments in their children basedon gender. Many previous studies for countries other than Japan also show that fathers spend more time with and are more
involved with sons than daughters (Harris and Morgan 1991; Lundberg et al 2007; Mammen 2011; Yeung et al. 2001). In
contrast, Japanese fathers spread their time evenly between their sons and daughters (Sakata et al. (2018)). However,previous studies in Japan suggest that recently, there exist either mixed preference or daughter preference (Kureishi and
Wakabayashi 2011; Fuse 2013). According to National Institute of Population and Social Security Research (2011, Table
3-5), 68.7 percent of married couples prefer a daughter if they could have only one child. This may be reflected in different
patterns of investments by Japanese parents.
The

recenteconomics

literatureonpocketmoney

focuses

on

how

it

might

affect: a child's

performance at school (Barnet-Verzat and Wolff 2008); the child’s supply of labour (Wolff 2006); and teaching a child tosave (Brown and Taylor 2016), rather than what determines the amount of pocket money. The annual Halifax (2016) pocket
money survey conducted for children in the UK provides evidence that a gender ‘pay gap’ exists even for child pocket4money in that sons receive an average of £6.93 per week in pocket money, almost 12 per cent higher than the average £6.16
parents given to daughters. The Halifax (2016) survey is not concerned with birth order effects. The Financial Central
Committee (2016) reports details of a Bank of Japan survey of pocket money, but it contains no information related togender or birth order. Here, we analyse the determinants of the amount of pocket money focusing on both birth order andgender.
Using panel data from the Longitudinal Survey of Newborns in the 21st Century (21 seiki shusshoji judan chosa) that iscollected by the Japanese Ministry of Health, Labour and Welfare, this paper examines whether birth order and gender
matter for parental financial investments in their children. In order to account for the endogeneity of family size, we estimate
models for parental investment in their children using a random effect instrumental variable estimator. A key finding is thatin the allocation of financial resources within the family, it is not always the case that boys are favored. It is found that inJapan, parents spend more money in total on their first born child and female children. In contrast, parents’ spending on
extra-educational is higher for boys, but there is no difference between the first born and later born children. Spending on
extra-curricular activities is higher for girls and for the first born child. Although we cannot know whether the genderdifferences in parental investments come from the supply side (parents make a conscious choice in gender-specificinvestment in their children because of their gender preferences) or the demand side (boys and girls prefer different
activities), we observe gender-specific human capital formation resulting from parental investments at early stages in theirchildren’s development. This may partly explain why men and women differ in the types of courses they take at college,
and the type of occupation or industry they work in. Put simply, this paper suggests that siblings are unlikely to receive
equal shares of parental investment, that is, we observe a parental investment gap among their children relating to bothgender and birth order. Interestingly, girls receive more pocket money than boys, whereas the first born child receives lesscompared to a later born child at the same age. Some evidence is presented to suggest that part of the first child effect may
be attributed to the impact of gender-specific hand-me-downs.
The rest of this paper is organized as follows. Section 2 provides details of model used to analyse the determinants ofparent’s investments in their children, while the data used in this paper are discussed in Section 3. Section 4 discusses the5empirical results, and Section 5 contains the conclusions of the paper.

2. ModelFollowing previous studies such as Black et al. (2005), the following model for parental investment in a child will be
estimated.
1
where

(1)

refers to the investment by parents in the i’th household at time t in the child that is the subject of the survey.

There are four investment outcomes analysed in this paper: the total expenditure on the child surveyed; the expenditure on
extra-curricular activities of the child surveyed; the expenditure on the extra-educational activities of the child surveyed;
and the pocket money given to the child surveyed. Turning to the explanatory variables in equation (1), 1
1 dummy variable which takes the value 1 if the child is the first born3,
value 1 if the child is a boy;is a 0-is a 0-1 dummy variable which takes theis the number of siblings of child i at time t, X contains the following control

variables: the log of the household’s income; the mother’s age; a 0-1 dummy variable taking the value 1 if the mother hasa university or higher degree; the father’s age; a 0-1 dummy variable taking the value 1 if the father has a university or
higher degree; a 0-1 dummy variables which takes the value 1 if the child co-resides with at least one grandparent; the joboffers-seekers ratio for the prefecture where the child resides in time t; city size dummies; and year dummies;

is anindividual-specific random effect which is assumed to be uncorrelated with the explanatory variables in equation (1), andis a standard disturbance term. Since the children observed in the data used here are born either in January or July, we
also include as a control variable a 0-1 dummy variable which takes the value of 1 if the child is born in July. Since all thechildren surveyed are born in the same year, the year dummies essentially control for the age of the children. The key
coefficients of interest in equation (1) areand, which measure the effect of birth order of the child in question andimpact of the child’s gender on the parent’s allocation of their financial resources, respectively.
One of the hurdles in estimating the effects of birth order is that birth order is related to family size. Children who are born

3

Since this is one of the key variables of interest and it is not time dependent, we do not consider a fixed effects approach.

6later are more likely to be in a bigger family as opposed to first born children. Thus, children who are born later may receive
reduced amount of resources due to family size rather than birth order per se. As a result, it is essential to control for theendogeneity of. We follow previous studies, for example, Angrist and Evans (1998), Black et al. (2005), andAngrist and Pischke (2009), and use twins at the second birth as an instrument for family size4, so our model for the numberof sibling is:2
where 2

_

_

1

(2)

is a 0-1 dummy variable which takes the value 1 if the second born child (and the third child) is a twin,

is an individual-specific random effect which is assumed to be uncorrelated with the explanatory variables in equation(2), andis a standard disturbance term.

When family size is assumed to be exogenously determined, equation (1) is estimated using a random effects (RE)estimator (see Baltagi (2008, pp. 17-21)), and when we take into account the potential endogeneity of family size, equations(1) and (2) are estimated using a random effects instrumental variable (REIV) estimator which is also known as the error
component two stage least squares estimator (see Baltagi (2008, p. 122)).

3. Data
The data used in this paper are taken from the Longitudinal Survey of Newborns in the 21st Century, which is the firstlongitudinal survey conducted by the Japanese Ministry of Health, Labour, and Welfare. 5 This survey is a mail-in

4

As an alternative/additional instrument for family size, Angrist et al. (2010) and de Haan (2010) use variables related tothe sex composition of the children. We do not use this type of instrument since the gender of the child under investigation
appears as an explanatory variable in our equation of interest.
5

The questionnaires for the first 15 waves of the survey are available in Japanese at the following URL:

http://www.mhlw.go.jp/toukei/chousahyo/index.html#00450043 (Accessed 28 August 2017).
The Japanese Ministry of Health, Labour and Welfare has provided some information in English relating to simple analysesof the data contained in the first fourteen waves at the following URL:
http://www.mhlw.go.jp/english/database/db-hw/vs03.html (Accessed 28 August 2017).

7

longitudinal census survey which has tracked all newborn babies born in Japan in the periods of 10-17 January 2001, and10-17 July 2001 which we refer to as January babies and July babies, respectively. These new born babies were sampledfrom the Live Birth Form of Vital Statistics (Jinko dotai chosa shusseihyo). The first survey which we refer to as the ‘2001
survey’ was conducted when the babies were 6 month old, namely, on 1 August 2001 for January babies and on 1 February
2002 for July babies. The number of questionnaires delivered and responses received for the 2001 survey are 26,620 and
23,423 for January babies (a response rate 88.0%), and 26,955 and 23,592 for July babies (a response rate of 87.5%),
respectively. With the exception of 2007, this survey has been conducted every year since 2001. For the 2002 to 2006
surveys, the annual survey months continued to be August for January births and February for July babies. Since the 2008
survey, the annual survey months for January babies and July babies have been January and July, respectively. We currently
have access to each and every wave up to the 13th wave which relates to 2014.
One of the advantages of using the Longitudinal Survey of Newborns in the 21st Century is that it asks respondents (andhis or spouse) about the amount of money spent on the child that is the subject of the survey rather than the total amount ofexpenditure on all children in the family. Since the survey asks directly about the expenditure and certain categories of
expenditure for the child surveyed, we can avoid measurement error issues stemming from estimating them from the total
amount of spending spent on the children in the family. As stated in Section 2, the outcome variables used inare thetotal expenditure on the child surveyed, the expenditure on extra-curricular activities of the child surveyed, the expenditureon the extra-educational activities of the child surveyed, and the pocket money given to the child6. Information on theparent’s total expenditure on the child surveyed is available in each of the 13 waves. The survey asks the respondent how
much they spend on the child surveyed in a particular month where the expenditure includes food such as artificial baby
milk, diapers, clothing, childcare, books and toys. The extra-educational activities are educational related activities outside
regular schools, for example, cram schools, private tutoring, and correspondence/online courses. Extra-curricular activities
Sakata et al. (2015) provide a summary of this survey in Japanese. Nozaki ((2017) contains a recent analyses using thisdata.
6

Since there are zero observations for expenditure on a child and for a child’s pocket money, we added one to eachobservation before taking logs.

8include gymnastics, swimming, baseball/softball, soccer, tennis, kendo, judo, ballet, dance, English conversation, abacus,
calligraphy, music lessons, handicraft, flower arranging (ikebana), and the tea ceremony. Information on these twocategories are available for waves 8 to 12. The information on the amount of pocket money for the child surveyed isavailable for 2013 (wave 12) and 2014 (wave 13). The 2013 survey asks parents how much pocket money they give to thechild on average per month, while the 2014 survey asks the same question to the child. It should be noted that informationon the annual labour income for mothers and fathers and their other income, which is used to calculate the householdincome, is only available for waves 2, 4, 5, 7, 10, 12, and 13, and relates to the year prior to the year of the survey, so thatfor wave 13 which was collected in 2014, the income data relates to 2013.
The job-offers-seekers ratio for the prefecture is taken from Ministry of Health, Labour and Welfare’s Employment
Referrals for General Workers. The exact definitions of all variables used in the analysis are contained in Appendix 1.
Our sample selection rules are as follows: We confined the sample to those households which have 2 or 3 children, andexclude the families in the sample who have any pair of consecutive children with more than 6 years between their birthyears. Since household income is included in every equation, we only can use data from the waves where income is available.
The top 1% of values for total expenditure, expenditure on extra-educational activities, and expenditure on extra-curricular
activities are excluded from the sample. Finally, restricting the sample to those who answer the questions providing
necessary information reduces the final samples to 149,311 for the expenditure analysis, 32,427 for the analysis of theexpenditure on extra-curricular activities, 32,657 for the analysis of expenditure on extra-educational activities, and 29,117
for pocket money analysis. Table I displays some descriptive statistics for the key variables used in the regression analysis
in section 4.

[Table I around here]

Table II provides some simple evidence on how the four types of expenditure change as birth order changes when no sample
selection rules are applied and the control variables are not taken into consideration. For total expenditure, expenditure on

9extra-curricular activities and expenditure on extra-educational activities, the average spending falls as birth order increases.
In contrast, the average amount of pocket money increases as birth order increases. As will be seen in section 4, even when
account is taken of the control variables in equation (1) and the endogeneity of family size, these findings are by and large
maintained.

[Table II around here]

Table III provides some simple evidence on the gender differences for the four types of expenditure. For total expenditure,
expenditure on extra-curricular activities and pocket money, the average spending is higher for girls, whereas the averagespending on extra-educational activities is higher for boys. As will be seen in section 4, even when account is taken of thecontrol variables in equation (1), these findings are maintained.

[Table III around here]

4. Estimated Results and Discussion
All regression results reported in this section are estimated using STATA version 14 (StataCorp 2014). Table IV presents
the results of estimating equation (1) for the log of parental expenditure on the child surveyed using all the data (equations(IV-1) and (IV-2)), and using the data for prior to 2007 (equations (IV-3) and (IV-4)) and after 2007 (equations (IV-5) and(IV-6)). Using all the data, the estimated results for RE and REIV (equations (IV-1) and (IV-2)) both show that the estimatedcoefficients for the first child dummy are positive and statistically significant. The estimated coefficient for first childdummy obtained using the REIV estimator suggests that Japanese parents spend 7.6% points more on their first born thanon their second or third born child when they are of the same age. When all the data is used, the boy dummy variable isalso statistically significant in both the RE and REIV estimates. Interestingly, the signs of its estimated coefficients arenegative, which means that daughters receive more financial inputs from their parents than sons do. To be precise, based10

on the REIV estimates, parental expenditure on daughters is 1.9% points higher than the expenditure for sons. The row
labelled “2nd_twin (First Stage)” at the bottom of Table IV reports the estimated coefficients of 2nd_twin and its standard
error in the first stage REIV estimates, namely, the estimates of equation (2), and indicates that this instrument is significant
in explaining family size.
When all the data is used the sample period spans the period 2002 until 2014, so it is worth splitting the data to see if there
is any structural change in the relationship. We split the sample into observations before the children have started primaryschool (before 2007), and after the children have started primary school (after 2007), and estimate equation (1) separately
using data before and after 2007, respectively. While no change is observed in the sign of the estimated coefficient of the
1st child dummy and its significance, it is important to note that prior to 2007, that is, for younger children, spending ishigher for boys. After 2007, total spending is significantly higher for girls.

[Table IV around here]

Tables V reports the results of analyses of the three components of expenditure that are available, expenditure on extracurricular activities (equations (V-1) and (5-2)), expenditure on extra-educational activities (equations (V-3) and (5-4)), andpocket money (equations (V-5) and (5-6)), respectively. There are some interesting differences both with respect to genderand birth order effects. For first born children, spending on extra-curricular activities is significantly higher than for laterborn children, but that is not true for extra-educational activities. According to the REIV results in Tables V, parents spend
11% more on extra-curricular activities for their first born children than for later children. In contrast, later born children
receive more pocket money than a first born child when they are identical ages. Using the REIV results suggests firstchildren receive 5.9% less pocket money. One interpretation of this outcome is that the amount of pocket money the firstborn sibling receives rises with their age, and then parents may want to equalize the pocket money among children and try
to give higher order children a similar amount of pocket money to first born children. An alternative interpretation is thathigher order children negotiate the amount of their pocket money with their parents when they have elder siblings, using

11the amount paid to the elder sibling as their initial request. A third interpretation is that first born children are more likely
to have more siblings, so they appear to receive less pocket money compared to higher order children at the same age.

Examining the gender effects in Tables V, we observe that parents spend significantly more on extra-curricular activities
for girls, while they spend significantly more on extra-educational activities for boys. In fact, according to the REIV
estimates, spending on girls is 18.1% higher and 7.8% lower for extra-curricular and extra-educational activities,
respectively. It is possible that these educational related spending patterns are related to the significant gender gap for wages
in favor of men in Japan (see, for example, Abe (2010) and Chiang and Ohtake (2014)). Parents may decide to invest lessin girls in the knowledge that the return to that investment will be lower, or the decisions by parents to spend less on girls
may itself be the cause of the gender gap7. According to Table V, girls also receive more pocket money too, 3.2% moreaccording to the REIV estimates. This contrasts with the findings for the United Kingdom reported in the Halifax (2016)
pocket money survey which suggests that British boys receive more pocket money than girls. Although there is a significant
gender gap for wages in favor of men in Japan, this is not the case for pocket money.

[Table V around here]

There are several potential reasons for why parents spend more on their first born child. The first relates to learning by
doing. For their second and subsequent children, parents have some experience with raising children and so may engage inless spending. The second relates to different parental preferences between their first child and later children. Alternatively,

7

There is some conflicting evidence relating to the desires of Japanese parents in relation to educating male and female

children. The Japanese responses in Wave 6 of the World Values Survey in answer to the statement “A university education
is more important for a boy than a girl” (question v52) suggest that only 16% agree with the statement, and the majority ofJapanesedisagree

with

it.

(Accessed

10

February

2018.

Available

from

URL:

http://www.worldvaluessurvey.org/WVSOnline.jsp). National Institute of Population and Social Security Research (2017,
Table III-1-12) reports that there is at least a 10 percentage point difference in the proportion of couples who want a son to
get at least a university education compared to a daughter.

12the effect of hand-me-downs from the first to subsequent children may reduce expenditure for second and later children. In
order to investigate this last possibility a little further, it is useful to distinguish gender-specific durable goods, for example,
clothes, and gender-irrelevant goods, for example, prams. In order to pick up the possible impact of the former type ofhand-me-downs, we investigated whether there were differences in expenditure between households where the first twochildren are of the same gender and when they are of different genders. In the models for the four categories of expenditure,
we added a same sex sibling dummy, that is, a 0-1 dummy variable that takes the value 1 if the first two children have thesame sex, and also this dummy interacted with the first child dummy. The results for the key variables are presented inTable VI. For total expenditure, expenditure on extra-curricular activities and expenditure on extra-educational activities,
it is found that compared to households with children of different gender, expenditure on a child in a family with childrenof the same gender tends to be lower, but the first child in this household still receives higher expenditure. These findings
are consistent with gender-specific hand-me-downs. However, it is worth pointing out that even after taking account of thiseffect, the first child still receives more resources, so gender-specific hand-me-downs cannot explain all of the first borneffect. We do not expect gender-specific hand-me-down effects for pocket money, and the results in Table VI support thisexpectation.

[Table VI around here]

5. Concluding Remarks
This paper has examined the effects of birth order and gender on parental investment in children using the Longitudinal
Survey of Newborns in the 21st Century. Unlike previous studies which mainly examine the effects of birth order on theoutcomes of children such as educational attainment, academic achievement and health status, this paper rather focuses on
the actual investments in children, namely total expenditure, and three components of expenditure for the child surveyed.
In doing so, we provide a clearer picture of the channel between the birth order of the child and their later outcomes. Using
twin births as an instrument, we take account of the endogeneity of family size by estimating random effect instrumental

13

variable estimator. Our findings suggest that in Japan gender effects and first born effects are not the same across all typesof expenditure. For total expenditure we find that the gender effects depend on the age of the child. The finding of significant
gender effects for these four expenditure groups also implies that a gender related dummy cannot be used as an instrument
for family size in these cases. Due to data limitations, the exact cause of the gender-specific parental investments is notclear (whether it comes from the preferences of parents or the child), but our findings suggest that in a rather early stage of
their life, children receive different kinds of human capital investments according to their gender. This may partly explain
why men and women make different choices regarding human capital formation later in their lives.

Compliance with Ethical Standards:
Funding:
This study was funded by a Japan Society for the Promotion of Science (JSPS) Grant in Aid for Scientific Research (B)(Grant Number 15H03363).
Conflict of Interest:
The authors declare that they have no conflict of interest.

14

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18

Appendix 1: Definitions of Variables
Variable Name

Definition

Expenditure

Total expenditure on the child in question (1000 yen)log of expenditurelog(Expenditure)

Expenditure on extra-curricular and sporting activities, where these
activities include gymnastics, swimming, baseball/softball, soccer, tennis,
Expenditure on extra-curricular
kendo, judo, ballet, dance, English conversation, abacus, calligraphy, music
activities
lessons (piano, etc.), handicraft, flower arranging (ikebana), and the tea
ceremony. (1000 yen)log of expenditure on extracurricular activities

log(Expenditure on extra-curricular activities+1)

Expenditure on extraeducational activities

Expenditure on extra-educational activities where these are educational
related activities outside regular schools, for example, cram schools, private
tutoring, and correspondence/online courses. (1000 yen)log of expenditure on extraeducational activities

log(Expenditure on extra-educational activities+1)

Pocket Money

Pocket money given to the child. (yen)log of pocket money

log(Pocket Money+1)

1st child

0-1 dummy variable taking the value of unity if the child surveyed was thefirst born child, and 0 otherwiseBoy

0-1 dummy variable taking the value of unity if the child was a boy, and 0
otherwise.

No of siblings

Number of brothers and sisters of the child surveyed.

Household income

Sum of father's and mother's labour income and other income for theprevious year. (10,000 yen)Log of household income

log(Household income+1)

Mother's age

Age of the mother (years)

Mother's university degree

0-1 dummy variable taking the value of unity if the mother has a university
or higher degree, and 0 otherwise.

Father's age

Age of the father. (years)

Father's university degree

0-1 dummy variable taking the value of unity if the father has a university
or higher degree, and 0 otherwise.

Coresidence with a grandparent

0-1 dummy variable taking the value of unity if there is at least one grandparent co-residing with the child, and 0 otherwise.

Vacancy rate

Job offers seekers ratio for the prefecture where the child lives.

July dummy

0-1 dummy variable taking the value of unity if the child was born in July,and 0 otherwise.

2nd child is twin

0-1 dummy variable taking the value of unity if the second born (and thirdborn) child was a twin, and 0 otherwise.

City size1

0-1 dummy variable taking the value of unity if the child lives in one of the
13 largest cities, and 0 otherwise.

City size2

0-1 dummy variable taking the value of unity if the child lives in a city
other than the 13 largest cities, and 0 otherwise.

City size3

0-1 dummy variable taking the value of unity if the child lives in a ruralarea, and 0 otherwise.

Same sex siblings

0-1 dummy variable taking the value of unity if all the children have thesame sex, and zero otherwise. (Only defined for two children families).

Table I: Descriptive Statistics
Mean

Std. Dev.

Expenditure on child (1000 Japanese yen)Log of expenditure
Expenditure on extra-curricular activities (1000 Japanese yen)Log of expenditure on extra-curricular activities
Expenditure on extra-educational activities (1000 Japanese yen)Log of expenditure on extra-educational activities
Pocket money (Japanese yen)Log of pocket money

Samplesize
149,311
149,31132,42732,42732,65732,657
29,117
29,11735.755
3.360
10.1642.216
14.3632.458
1242.534
6.933

25.853
0.663
7.164
0.647
13.0400.718
786.905
0.669

1
0
0
0
0
0
0
0

213
5.361
47
3.871
84
4.443
4800
8.477

1st child

149,311

0.381

0.486

0

1

Boy

149,311

0.523

0.499

0

1

No of siblings

149,311

1.269

0.444

1

2

Household income (10,000 Japanese yen)

149,311643.924508.562

0

73000

Log of household income

149,311

6.343

0.531

0

11.198Mother's age

149,31136.6155.953

17.25061.167

Mother's university degree

149,311

0.153

0.360

0.000

1.000

Father's age

149,31138.6606.632

17.83376.583

Father's university degree

149,311

0.395

0.489

0

1

Co-residence with a grandparent

149,311

0.229

0.420

0

1

Vacancy rate

149,311

0.849

0.296

0.26

1.67

July dummy

149,311

0.505

0.500

0

1

City size1 (13 biggest cities=1)

149,311

0.226

0.418

0

1

City size2 (other cities=1)

149,311

0.640

0.480

0

1

City size3 (rural area=1)

149,311

0.134

0.340

0

1

year2001

149,311

0.096

0.294

0

1

year2002

149,311

0.100

0.300

0

1

year2004

149,311

0.139

0.346

0

1

year2005

149,311

0.152

0.359

0

1

year2008

149,311

0.117

0.322

0

1

year2011

149,311

0.137

0.344

0

1

year2013

149,311

0.130

0.337

0

1

year2014

149,311

0.129

0.335

0

1

2nd child is twin
Same sex siblings * 1st child

149,311
108,589

0.009
0.211

0.093
0.408

0
0

1
1

Same sex siblings

108,589

0.488

0.500

0

1

VariableMin

Max

Notes:(1) The top 1% of values for total expenditure, expenditure on extra-curricular activities, and expenditure on extraeducational activities are excluded from the sample. Values of total expenditure that were zero are also excluded.
(2) Since there are some zero values for expenditure on extra-curricular activities, expenditure on extra-educational
activities, pocket money and household income, one was added to every observation before the logs of these variables
were computed.
(3) $US1=110 yen.

Table II: Expenditures by Birth Order
Total Expenditure

Expenditure on
Extra-curricular
Activities

Expenditure on
Extra-educational
Activities

Birth order

Samplesize

Samplesize

MeanSamplesize

MeanSample
size

Mean

1

236,33136.3

78,488

11.7

49,94014.3

22,4551271.52

174,81232.8

56,66010.5

34,31013.2

17,0461285.7

3

53,76729.4

15,717

9.2

8,035

12.5

4,948

1317.1

4

7,905

27.5

1,839

9.5

883

12.9

671

1417.0

5

1,305

25.2

278

8.2

96

13.6

105

1489.9Mean

Pocket Money

Notes:(1) Computed by the authors using data from the Longitudinal Survey of Newborns in the 21stCentury .
(2) The units of measurement for total expenditure, expenditure on extra-curricular activities,
and expenditure on extra-educational activities are 1000 yen, while pocket money is measured inyen.
(3) No sample selection rules are applied for the computations in this Table.

Table III: Expenditures by Gender
Variable
Sex

Total Expenditure
Boys

Girls

Mean

38.2

39.2

SampleSize

248,796

230,577t-value-5.12***

Extra-curricular Activities

Extra-educational Activities

Boys

Boys

Girls

10.1

11.9

77,68875,360t-Value-31.3***

Girls

14.3

13.2

47,047

46,248t-value
9.57***

Pocket Money
Boys

Girls

1447.21470.623,99522,872t-value
1.70*

Notes
(1)Computed by the authors using data from the Longitudinal Survey of Newborns in the 21st Century .
(2) The units of measurement for total expenditure, expenditure on extra-curricular activities and expenditure on extra-educational activities
are 1000 yen, while the unit of measurement for pocket money is yen.
(3) ***, ** and * indicate significance at the 1%, 5% and 10% significance levels, respectively.
(4) t-value is a t-statistic for the null hypothesis that the expected values for boys and girls are equal.
(5) No sample selection rules are applied for the computations in this Table.

Table IV: Analysis of Total Expenditure

1st child
Boy
No of siblings
Log of household income
Mother's age
Mother's university degree
Father's age
Father's university degree
Co-residence with a grandparent
Vacancy rate
July dummy
City dummies
Time dummies
Sample size
Number of id
R-squared overall model
Hausman (1978) Test
Weak identification test (Cragg-Donald (1993)
Wald F statistic)
2nd child is twin (First Stage)All(IV-1)
RE
0.0487***[0.005]-0.0172***[0.004]-0.0837***[0.005]0.1236***[0.005]0.0017**[0.001]0.0865***[0.007]0.0028***[0.001]0.0598***[0.005]0.0246***[0.005]0.0232***[0.008]-0.0822***[0.004]
YES
YES
149,31132,1860.236-0.1259**(IV-2)
REIV
0.0763***[0.012]-0.0185***[0.004]0.0324[0.047]0.1280***[0.005]0.0022***[0.001]0.0863***[0.007]0.0026***[0.001]
0.0610***[0.005]0.0213***[0.005]0.0225***[0.008]-0.0818***[0.004]
YES
YES
149,31132,1860.23

Year<2007(IV-3)(IV-4)
RE
REIV
0.0361***0.0742***[0.007][0.018]0.0111**0.0098*[0.006][0.006]-0.0774***
0.0678[0.007][0.064]0.1215***0.1210***[0.006][0.006]0.0004-0.0002[0.001][0.001]
0.0622***0.0649***[0.009][0.009]0.0029***0.0022***[0.001][0.001]0.00190.0059[0.007][0.007]0.0550***0.0492***[0.007][0.007]0.015
0.0192*[0.011][0.011]-0.1246*** -0.1244***[0.006][0.006]
YES
YES
YES
YES
72,61072,61028,72428,7240.16
0.154-0.1529**

Year>2007(IV-5)(IV-6)
RE
REIV
0.0800***0.0947***[0.006][0.012]-0.0410*** -0.0421***[0.005][0.005]-0.0874***-0.013[0.005][0.054]0.1597***0.1619***[0.006][0.006]0.0045***0.0054***[0.001][0.001]0.1049***0.1040***[0.008][0.008]0.0027***0.0028***[0.001][0.001]0.1103***0.1105***[0.006][0.006]-0.0026-0.0054[0.006][0.006]0.0221**
0.0226**[0.009][0.009]-0.0418*** -0.0418***[0.005][0.005]
YES
YES
YES
YES
76,701
76,701
25,841
25,841
0.192
0.188-0.0767

1044.055

765.519628.8220.4260***[0.014]0.4047***[0.011]

0.5325***[0.021]

Notes:(1) Data from the surveys in 2002, 2004 2005, 2008, 2011, 2013 and 2014 are used to estimate models (IV-1) and (IV-2).
(2) The figures reported in square brackets are robust standard errors.
(3) All equations include a constant term, but details are not reported.
(4) 2nd child is twin (First Stage) provides details of the estimates and their standard errors forthe variable used in identification in the first stage regression.
(5) ***, ** and * indicate significance at the 1%, 5% and 10% significance levels, respectively.

Table V: Analysis of Expenditure on Extra-curricular Activities, Extra-educational Activities and Pocket Money

VARIABLES
1st child
Boy
No of siblings
Log of household income
Mother's age
Mother's university degree
Father's age
Father's university degree
Coresidence with a grandparent
Vacancy rate
July dummy
City dummies
Time dummies
Sample size
Number of id
R-squared overall model
Hausman (1979) Test
Weak identification test (Cragg-Donald(1993) Wald F
statistic)
2nd child is twin (First Stage)

Extra-curricular
Activities

Extra-educational
Activities

Pocket Money

(V-1)

(V-2)

(V-3)

(V-5)

RE
0.1226***[0.009]-0.1822***[0.008]-0.0788***[0.009]0.1294***[0.010]0.0103***[0.002]0.0806***[0.012]0.0004[0.001]0.1150***[0.009]-0.0139[0.010]0.011[0.021]0.0326***[0.008]YES
YES
32,427
19,8850.08280.06

REIV
0.1110***[0.019]-0.1812***[0.008]-0.138[0.086]0.1304***[0.010]0.0096***[0.002]0.0813***[0.012]0.0002[0.001]0.1142***[0.009]-0.011[0.011]0.0121[0.021]0.0322***[0.008]YES
YES
32,427
19,8850.0815RE
REIV
0.0869*** 0.0667***[0.010][0.018]0.0767*** 0.0780***[0.009][0.009]-0.0532*** -0.1684*[0.010][0.088]0.2122*** 0.2148***[0.012][0.012]0.0192*** 0.0175***[0.002][0.002]0.0447*** 0.0460***[0.014][0.014]0.0099*** 0.0096***[0.001][0.001]
0.0569*** 0.0563***[0.010][0.010]-0.0321*** -0.0275**[0.011][0.012]0.6414*** 0.6423***[0.014][0.015]-0.0821*** -0.0827***[0.009][0.009]
YES
YES
YES
YES
32,65732,657
17,04017,040
0.103
0.101
0.118

RE
REIV
-0.0437*** -0.0587***[0.009][0.019]-0.0329*** -0.0319***[0.008][0.008]-0.0290***-0.1106[0.009][0.088]0.0319*** 0.0327***[0.009][0.009]-0.0062*** -0.0073***[0.002][0.002]-0.0435*** -0.0429***[0.012][0.012]0.002
0.0018[0.001][0.001]-0.0960*** -0.0968***[0.009][0.010]0.0540*** 0.0580***[0.011][0.012]-0.0291* -0.0298*[0.017][0.017]-0.0401*** -0.0402***[0.008][0.008]
YES
YES
YES
YES
29,117
29,117
18,51818,5180.098
0.09510.0818314.838390.325

258.388

0.5927***[0.017]0.5983***[0.021]0.5452***[0.026]

(V-4)

(V-6)

Notes:(1) Data from the 2011 and 2013 surveys are used to estimate the models for the expenditure on extra-curricular activities ((V-1)
and (V-2)) and the expenditure on extra-educational activities ((V-3) and (V-4)), while data from the 2013 and 2014 surveys areused to estimate the models for pocket money ((V-5) and (V-6)).
(2) Notes (2)-(5) for Table IV apply.

Table VI: Hand-me-down Effects

Same_sex_siblings * 1st child
Same_sex_siblings
1st child
Boy
Sample size

Extraeducational
Activities

PocketMoney

Total
Expenditure

Extra-curricular
Activities

0.0214**0.0427**0.0406*

0.0266[0.010][0.020][0.022][0.020]-0.0213***-0.0536***-0.0461***-0.025[0.007][0.015][0.016][0.015]0.0233***0.0978***0.0594***-0.0584***[0.007][0.014][0.016][0.014]-0.0147***-0.2062***0.0819***-0.0341***[0.005][0.010][0.011][0.010]108,589

21,901

23,34919,985

Notes:(1) For each expenditure category, the sample is limited to households with 2 children and themodel is estimated using a random effects (RE) estimator.
(2) In addition to the explanatory variables reported in Table VI, the models contain the same
explanatory variables as In Tables IV and V with the exception of no of siblings which is
excluded.
(3) Notes (2) and (5) for Table IV also apply.