CSIS Discussion Paper No. 114

Access to childcare and the employment of
women with preschool-aged children in Tokyo*

Mizuki Kawabata†

September, 2012

Abstract
This paper presents a geographical and empirical study on childcare accessibility and theimportance of access to childcare in attaining preferred employment among women withpreschool-aged children. The study area is the Tokyo’s ward area, which has a large numberof children on childcare waiting lists. Visualized accessibility reveals a considerable
geographic mismatch between childcare center supply and demand, especially for children
aged 2 years or below. Empirical results show that access to childcare is closely associatedwith a higher probability of attaining preferred employment among women withpreschool-aged children. The association is remarkably strong when a woman has a very
young child aged 0–2 years and when the childcare center is one that is desired. Adequate
childcare provision, particularly for children under age 3, would increase active female
participation in the labor market.

*
This work was supported by the Grants-in-Aid for Scientific Research [20330045, 22510140] from the Japan Society
for the Promotion of Science. The author is grateful to the Bureau of Social Welfare and Public Health of the Tokyo
Metropolitan Government, local municipalities, and individual childcare centers for the valuable childcare data they
provided for this study. The author would like to thank Yukiko Abe, Yukako Ono, and participants in conferences,seminars, and workshops for their valuable suggestions. Any errors in this paper, however, are my sole responsibilities.
†
Associate Professor, Faculty of Economics, Keio University, Visiting Researcher, Center for Spatial Information
Science, The University of Tokyo. e-mail: mizuki@econ.keio.ac.jp

11. Introduction
With the increasing participation of women in the labor market, work-life balance has
become an important policy issue in many countries (Crompton and Lyonette, 2006;
OECD, 2008). Families attempting to balance their work and family life face numerous
challenges and one of these is to find appropriate childcare for their children while theywork. If adequate childcare is unavailable, many parents may abandon the employment
they prefer. Other parents may have no choice but to use undesirable (e.g., distant andlow quality) childcare out of necessity, which can hamper not only the work-life balance
but also children’s well-being and development. The lack of adequate childcare isreported to be a problem in various areas around the world (Apps and Rees, 2005; Blau,
2001; Del Boca and Vuri, 2007). Apps and Rees (2005) argue that childcare shortage isa result of market failure, representing a strong case for public intervention.
The lack of access to childcare arises not only because of a supply shortage but
also because of a geographical mismatch between supply and demand for childcare.
Even when a slot in a childcare center is available, that opening may remain
inaccessible unless the center is located within a reasonable distance from home.
However, the geographic mismatch of childcare arising from considerations of areasonable distance from home has not been sufficiently examined, perhaps due to data
limitations. Childcare accessibility, often termed childcare availability, has been
examined for relatively large geographic areas such as counties and regions (Davis andConnelly, 2005; Gordon and Chase-Lansdale, 2001; Kreyenfeld and Hank, 2000). 1
Webster and White (1997) use a more detailed geographic area—a circular area with aradius of 800 meters—when measuring accessibility of childminders. However, there is1
Gordon and Chase-Lansdale (2001) use data at the zip-code level; however, the supply-demand mismatch ispresented at the metropolitan level.

1only limited research that addresses the accessibility of childcare centers, taking into
account not only the supply but also the demand that spatially competes for the supply(i.e., spatial competition). Moreover, very few studies differentiate children’s ages inmeasuring childcare accessibility, although the level of childcare services can differ
considerably by age.
In many countries, considerably more women with young children wish toparticipate in the labor market than actually do. In most EU countries, among couples
with children under the age of 6, more women express a desire to participate in the labor
force than actually do (Jaumotte, 2003). A national survey in Japan shows that among
women with preschool children aged 4 or 5, the majority (72%) wish to work, but lessthan half of that figure (37.4%) actually work (Gender Equality Bureau Cabinet Officeof Japan, 2007). The large disparities between desired and actual employment patterns
indicate substantial potential for the promotion of female labor force participation.
There is a large body of literature suggesting that the lack of access to childcare is aproblem affecting the balance between work and family. Thus far, however, the extent towhich access to childcare is important in the attainment of preferred employment is anempirical question that has not been fully explored.
The objective of this research is to shed new light on these under-researchedaspects of childcare access and work-life balance. Specifically, this study addresses thefollowing two questions. First, does a geographic mismatch exist between the supply of,and demand for, childcare centers, and does it differ according to the age of children?
Second, is access to childcare centers important in attaining preferred employment
among women with preschool-aged children?
To answer the first question, the accessibility of childcare centers incorporating2the geographic mismatch of their supply and demand was calculated and visualized foreach infant age group. Unlike previous childcare studies, this research takes into
account spatial competition in the accessibility, incorporating a concept of reasonabledistance for childcare trips. The accessibility is calculated at the block level—a microarea—using detailed spatial data and a geographic information system (GIS). With
regard to the second question, probit models are estimated using a unique survey dataset
on balancing work and child rearing and accessibility to childcare centers. This study
also examines whether the importance of access to childcare differs according to thefollowing three variables: status of preferred employment (full-time versus part-time),
age of youngest child (younger versus older preschool child), and type of childcare(desired versus other-than-desired). The study area is Tokyo’s 23 wards, which have alarge number of children on childcare waiting lists.
The remainder of the paper is organized in the following manner. A review ofthe literature is presented in Section 2 and Section 3 describes the study area and the risein demand for childcare in Tokyo. The methodology is described in Section 4, and theresults are presented in Section 5. The findings and policy implications are discussed in
Section 6.

2. Childcare access and preferred work-family balanceThis section reviews the literature on access to childcare and work-family balance andclarifies the research questions raised in this paper. First, I discuss why the geographic
mismatch of childcare may is important in balancing work and family; I then describe
why access to childcare may be significant in attaining preferred employment among
women with young children.
32.1 Geographic mismatch of childcare
A geographic mismatch of childcare bespeaks an imbalance between the locations ofchildcare facilities (childcare supply) and childcare users or seekers (childcare demand).
The geographic mismatch matters since the location of childcare facilities is importantfor many families who rely on childcare to reconcile work and family life (Tivers, 1988).
Travel to childcare facilities adds substantial time to work commutes. In addition to
reduced mobility with young children, a parent has to take the child to childcare in one
place and then travel to another place to work. Thus, it is not surprising that proximity
to home is often an important consideration when selecting childcare, particularly
among women (Hanson and Pratt, 1990; Kawabata, 2010).
Two theories can explain why the geographic mismatch of childcare may
impede work-family balance. First, the geographic mismatch is a factor that contributes
to the creation of childcare waiting lists, which may negatively affect the attainment ofwork-family balance. Certain areas have childcare waiting lists, which reflect excess
demand in those areas. Placement on a waiting list is likely to have a negative impact on
attaining preferred work-life balance, although empirical evidence is limited.
Second, the geographic mismatch of childcare may be a significant hindrance
to job access. For many families, access to childcare is a prerequisite for access to jobs
(Kwan, 1999: van Ham and Büchel, 2006; van Ham and Mulder, 2005). The geographic
mismatch creates areas where childcare is scarce, which may place severe constraints on
job search and employment options. As the distance to childcare increases, the job
search cost is likely to be higher and job opportunities are likely to become fewer. The
constraints of travel to childcare are likely to be stronger for women than for men
4

(Kwan, 1999; Pickup, 1988), since mothers are most likely the primary carers inhouseholds (de Meester et al, 2011; Schwanen et al, 2007). Indeed, many employed
women work closer to home or the local labor market and their commutes are shorter
than those of men (Pickup, 1988).

2.2 Childcare access and work-family balance
While work-life balance is an important policy in many countries, a large discrepancy
between preferred and actual employment persists, particularly among women withyoung children (Jaumotte, 2003). Studies suggest that a lack of adequate childcare is amajor barrier to attaining preferred employment among women with preschool-aged
children. For example, a number of studies find that greater availability of childcare
increases female participation in the labor market (Gordon and Chase-Lansdale, 2001;
Herbst and Barrow, 2008; Stolzenberg and Waite, 1984; van Ham and Büchel, 2006;
van Ham and Mulder, 2005; Webster and White, 1997). Surveys in the UK and US
indicate that many more women would work or work longer hours if satisfactorychildcare was available (Presser and Baldwin, 1980; Tivers, 1988).
Some literature suggests that the problem of childcare shortage may besignificantly greater for full-time rather than part-time employment, younger rather thanolder children, and desired rather than less-desired childcare. For example, inadequate
childcare spending is found to be more of a constraint for full-time participation in thelabor market than for part-time participation (Jaumotte, 2003; Powell 1998). It is widely
recognized that constraints on women’s employment due to children are stronger for
younger than older children (Leibowitz et al., 1992; Stolzenberg and Waite, 1984).
Several studies report that when desirable childcare centers are unavailable, many5

women with young children do not work or work lesser number of hours (Kawabata
2010; Presser and Baldwin, 1980). Thus, the importance of access to childcare in theattainment of preferred employment may significantly differ between full-time andpar-time employment, younger and older children, and desired and less-desired
childcare.

3. Study area and rise in childcare demand in Tokyo
The study area comprised Tokyo’s 23 wards, which encompass the central and densely
populated area of Tokyo Metropolis, a metropolitan prefecture in Japan (Figure 1). The
study area covers 622 square kilometers with a population of 8.5 million people in 2009.
In the remainder of this paper, this area will be referred to as the “Tokyo ward area,”
while “Tokyo” will indicate the entire Tokyo Metropolis.

Tokyo

Japan

Tama  area

Ward  
area

N

Tokyo
0

5

10 km

Tokyo’s  ward  area

Basic  unit  block  (Kihontaniku)
Ward  (Ku)

Figure 1. The study area.

6

For more than a decade, the Japanese Government has strived to increasechildcare services to eliminate waiting lists at childcare centers throughout the country.
In 2001, the Cabinet endorsed the ‘Zero Wait Listed Children Strategy,’ and in 2008, thegovernment implemented the ‘New Zero Wait Listed Children Strategy.’ Nonetheless, therise in demand has far outpaced the increase in supply; during fiscal year 2009,
childcare waiting lists in Japan grew by 891 children, even though the total supply ofchildcare slots increased by approximately 26,000 (MHLW, 2010).
Childcare waiting lists are an urban problem in Japan. As of April 2010, most
waiting lists were found in urban areas, with Tokyo alone accounting for 32% of thetotal number of children on childcare waiting lists nationwide (MHLW, 2010). Between
2005 and 2010, Tokyo has witnessed a dramatic increase in licensed daycare waiting
lists (Figure 2), data for which were obtained from the Bureau of Social Welfare andPublic Health of the Tokyo Metropolitan Government (TMG). The total number ofchildren on waiting lists rose by 62% (from 5,221 to 8,435), with the period 2008–2009,in particular, showing a remarkable increase. The rise in demand among younger children
aged 0–2 years is noteworthy. Between 2005 and 2010, waiting lists for children ages 0, 1,
and 2 years grew by 199%, 109%, and 36%, respectively, whereas the lists decreased by
26% for age 3 years and 65% for ages 4 years and above. Consequently, the proportion of
0- to 2-year-olds on waiting lists rose from 76% to 91%. The 1-year-old group was
predominant, accounting for almost half the total number on waiting lists in 2010.

7

Number of children by age

4,000

1 Yr old
3 Yrs old
Total

9,000

(As of April each year)

8,000

3,000

7,000

2,000

6,000

1,000

Total number of children

0 Yr old
2 Yrs old
4 Yrs and older

5,000

0

4,000
2005

2006

2007

Note: The number s are based on the new definition.

2008

2009

2010
Year

Figure 2. The number of children on waiting lists for licensed daycare centers in Tokyo,
2005–2010.

Note that the actual demand for childcare centers is likely to be much greaterthan indicated by the waiting list numbers in Figure 2, as suggested in Zhou and Oishi(2005). This is due to a number of reasons. First, waiting list data are available only forlicensed daycare centers, and the relevant figures for other types of childcare centers are
not included. Second, the publicly available numbers do not include licensed daycare
applicants who are enrolled in non-licensed centers receiving public agency support orapplicants who requested a single licensed daycare center (as opposed to multiple
selections) in their applications for desired facility. Since many users of non-licensed
daycare centers also apply for licensed daycare centers, the eliminations of those
applicants results in demand from the perspective of users being underestimated. Third,
licensed daycare waiting lists released are usually as of April, when the lists tend to be
shortest. Since most licensed daycare facility enrollments are made at the start of the8fiscal year in April, the waiting lists tend to grow toward the end of the fiscal year.
Finally, many people do not apply for positions on waiting lists, put off by the difficultyin enrolling in licensed daycare centers. Licensed daycare centers use rigorous selection
standards, prioritizing applicants employed full-time over part-time workers and job
seekers, for instance. Thus, the potential demand not reflected by publicly released data
may be enormous.
Increasing the number and capacity of childcare centers is a pressing policy
issue in Japan. In order to resolve the problem of childcare waiting lists, the TMG isaiming to increase childcare capacity by 22,000 spots over three years from 2010 (TMG
Bureau of Social Welfare and Public Health, 2011).

4. Method
This study uses a two-part methodology. The first part examines the geographic
mismatch between childcare center supply and demand, and the second part analyzes
the importance of access to childcare centers in the attainment of preferred employment
among women with preschool-aged children. Each part will be described below.

4.1 Geographic mismatch of childcare centers: accessibility and data
In order to examine the geographic mismatch between childcare center supply anddemand, accessibility is calculated for each basic unit block (kihontaniku). The basic
unit block is the smallest geographic unit for which census population data are available.
There are 115,501 basic unit blocks within the study area (Figure 1). Accessibility ismeasured in various ways depending on its purpose (Handy and Niemeier, 1997; Morris
et al., 1979). In order to meet the goals of this study, I measured accessibility in a9manner that can indicate not only the mismatch between childcare supply and demand
but also their geographic mismatch, using the following measurement:
a
i

A

¦

j:d ij  d 0

S aj

¦r P
a

k :d kj  d 0

a
k

,

(1)

where a is the age of children; Ai is the accessibility for a resident zone i; Sj is the supply
of a childcare center j; dij and dkj are the respective distances by road between resident
zones i and k, on the one hand, and a childcare center j, on the other; d0 is the thresholddistance for commuting to childcare centers; r is the ratio of those requiring childcare
centers to the entire population; and Pk is the population in a resident zone k.
An important point is that the accessibility measurement takes into accountspatial competition, as described in Harris (2001); the proposed measurement
incorporates not only the spatially accessible supply but also the demand spatiallyaccessible to the supply. This accessibility measurement is similar to the two-step floatingcatchment area method employed by Luo and Wang (2003) and Wang and Luo (2005),
among others, in that the measurement combines the following two steps: 1) at eachlocation of a childcare center, the ratio of supply to its surrounding demand (within athreshold distance to the childcare center) is calculated; and 2) at each demand(residential) location, the ratios (derived in the first step) surrounding (within the same
threshold distance from) the demand location are summed. Therefore, an accessibility
value, in essence, represents the supply-demand ratio; accordingly, an accessibility valueof 1 represents a supply-demand balance, whereas a value of greater or less than 1
indicates excess supply or demand. An accessibility measurement that allows suchinterpretation is intelligible and useful for policy making. Note that the10population-weighted average of accessibility for the whole area equals the
supply-demand ratio for the whole area. It should be pointed out that not taking into
account the supply and demand outside the study area can distort the supply-demand ratio,
particularly around the border of the study area; however, this is unlikely to be a major
problem in this study, since most childcare centers prioritize applicants living in the sameward or Tokyo.
There are various types of childcare in Tokyo. This analysis focuses on three
types of childcare centers: licensed daycare centers (ninka-hoikujo), TMG-certified
daycarecenters(Tokyo’sninsyo-hoikujo),

andauthorizedchildcarecenters(nintei-kodomoen). These three types of centers were selected for the following reasons:their quality and affordability are ensured at certain levels by national or TMG
standards, 2 they are the major providers of childcare services in Tokyo, and relevant,

data on the other non-licensed childcare centers were unavailable. Quality and cost areoften the primary concerns in countries where childcare services are provided in theprivate sector such as the US (Blau, 2001; Blau and Robins, 1988), whereas availability
seems to be more of an issue in countries where most childcare services are publicly
subsidized, such as Germany, Japan, and the Netherlands (Del Boca and Vuri, 2007;
Kreyenfeld and Hank 2000; van Ham and Mulder, 2005).
Data on the three types of childcare centers categorized by age were obtained
from the Bureau of Social Welfare and Public Health of the TMG, ward offices, andindividual childcare centers. Spatial data on basic unit blocks in the 2005 census were
provided by the Statistical Bureau of Japan. For the supply of childcare centers (Sj), I used2
The costs of the three types of childcare centers are regulated so that their maximum monthly fees are set atapproximately 80,000 yen (about $1,000 at JPY/USD80). Fees for licensed daycare centers are determined dependingon family income and the age of the child, from no fee at all (for welfare recipients, for example) to approximately
80,000 yen per month. Suzuki (2010) estimated that the average monthly fee paid for licensed daycare centers is
20,000–30,000 yen (approximately $250–$375).

11the capacity, as of April 2009, of the three types of childcare centers. Capacity tends tobe smaller for younger children. The total capacity for children aged 0 is 10,158 spots,
aged 1 is 18,592 spots, aged 2 is 21,876 spots, aged 3 is 22,954 spots, and aged 4 andabove is 45,885 spots.
The distance by road between basic unit blocks and childcare centers (dij and dkj)
are calculated using the 2009 road network data and GIS. Here, locations of basic unit
blocks are the centroids of those blocks, and locations of childcare centers are the spatial
points created using the detailed address matching service of the Center for Spatial
Information Science at the University of Tokyo.
The ratio of those requiring the three types of childcare centers to the population(r) is set at 20% for infants aged 0 and 35% for children aged 1 year and older. 3 The
population by basic unit block (Pk) for each age was estimated using 2009 population databy age for each subdivision (chocho-aza) of a city. The subdivision, which is larger than abasic unit block but smaller than a ward, is the smallest geographic unit for which
population data by age were available for the year 2009. The data for subdivisions weredisaggregated into the data for basic unit blocks on the basis of the proportional
distributions of the 2005 census population at the basic-unit-block level, which were
provided by the Statistics Bureau of Japan.
Figure 3 shows maps visualizing the spatial distributions of childcare centersand estimated numbers of preschool-aged children by basic unit block. Both childcare
3

These figures are based on the 2009 ratios in the Tokyo ward area that were estimated on the basis of available data,using the following equation:ra( Sla  Staa  Qla  Etaa ) / P a,(2)
where a denotes the age of children, Sl the number of children enrolled in licensed daycare centers, Sta the capacity of
TMG-certified and authorized childcare centers (since the number of children enrolled in these two types of centerswere not obtainable), Ql the number of applicants for licensed daycare centers minus the number of applicants admitted,
Eta the number of children in Ql but enrolled in TMG-certified or authorized childcare centers, and P the population.
The estimated ratios are 17% (for age 0), 34% (1 year), 37% (2 and 3 years), and 35% (4 and 5 years).

12

centers and preschool-aged children are widely distributed in the Tokyo ward area,
except for nonresidential areas such as rivers and parks. Note that the dots in the figure
indicate the locations of the total of 1,477 childcare centers, and the number of thelocations is smaller for a particular age group.

1  dot  =  5  children
Ward0                    5                10  kmLicensed daycare  center
TMG-­‐certified  daycare  center
Authorized  childcare  center(Population  as  of  January  1,  2009)

Figure 3. Spatial distributions of childcare centers (a) and preschool children (b) in theTokyo ward area, 2009.

For the threshold distance to childcare centers (d0), I used 500, 750, and 1,000
meters, given that over 90% of travel times to childcare facilities in Tokyo areapproximately 15 minutes or less (Miyazawa, 1998; Kawabata, 2010). Assuming awalking speed of approximately 50 meters per minute with young children in tow(Segawa and Sadahiro, 1996), the three thresholds are approximately 10, 15, and 20
minutes on foot, respectively. 4
The calculated accessibility measurements are then visualized using GIS. The
visualization is effective for identifying the geographic mismatch, particularly when the
4

In the Tokyo ward area, the most common means of traveling to childcare centers is by bicycle on days when weather
permits but by foot on days with inclement weather (Kawabata, 2010). Pinch (1984) and Webster and White (1997)
use a similar threshold, about 800 meters (half a mile), which Pinch considers a reasonable duration given travel
challenges on bad weather days.

13

study area consists of a large number of locations (blocks).

4.2 Childcare access and attaining preferred employment: the model and data
The importance of access to childcare centers in attaining preferred employment by
women with preschool-aged children is examined by estimating probit models. With
regardtopreferred

employment,

this

study

addresses

two

employment

statuses—full-time and part-time employment. It is assumed that preferred employment
is attained if a woman who prefers to work full-time is working full-time or if a woman
who prefers to work part-time is working part-time. The sample is from a uniqueInternet-based questionnaire survey on balancing work and child rearing andaccessibility to child-care centers, which was conducted over the period November
20–25, 2009. The survey data include answers from 311 respondents among 650 womenwith preschool-aged children living in the Tokyo ward area. The respondents are widelydistributed across the 23 wards and their basic demographic statistics are not very
different from the 2005 census data. 5 The survey data indicate a considerable
discrepancy between preferred and current employment status. Of the 311 women, 263(85%) prefer to work and are the population of interest, while less than half of
that—113 (36%)—are actually working. Among those who prefer to work, part-time ispreferred to full-time employment. Our models use 261 women who prefer to work andanswer all the relevant question items. Of the 261 women, 71 (27%) prefer full-time
employment while the rest, 190 (73%), prefer part-time employment.
The probit models take the following form:P( y 1 | X , Acc, Acc  D)

5

) (D  EX  JAcc  GAcc  D) ,(3)

Details regarding the survey are documented in Kawabata (2010).

14where y is the binary response variable 1 if preferred employment is attained, and 0
otherwise. X is a set of individual and neighborhood characteristics—age, number ofchildren, presence of a very young child, presence of full-time husband or partner,
working experience, and female unemployment rate, which are likely to be relevant towomen’s employment outcomes based on the labor market literature. Acc comprises thevariables on access to a childcare center, and D denotes either a dummy indicating
preference for working full-time or a dummy indicating the presence of a child aged 0–2
years.
Table 1 explains variable descriptions and descriptive statistics. The four
variables on access to childcare centers are (i) access to a childcare center (acc1), (ii)
access to a desired childcare center (acc2), and (iii) access to an other-than-desired
childcare center while unable to have access to a desired childcare center (acc3), and(iv) the accessibility of childcare centers at the ward level for the youngest child (acc4).
The variables acc2 and acc3 are used to examine whether the importance of childcare
centers differs between desired and other-than-desired childcare centers. The
accessibility variable, acc4, is at the ward level, larger than the basic unit block level,
since the residential information of the sample is limited to the ward level. Theinteraction terms, AccD, are introduced in order to examine two further
aspects—whether the importance of access to a childcare center differs by the type ofpreferred employment (full-time and part-time) and the presence of a very young childaged 0–2 years.

15

Table 1. Variable descriptions and descriptive statistics.
Variable

Description

Mean

Attained preferred
employment
Age 30-34 years
Age 35-39 years
Age  40 years
2 or more children

1 if preferred employment attained; 0otherwise
1 if between 30 and 34 years old; 0 otherwise
1 if between 35 and 39 years old; 0 otherwise
1 if 40 years old or older; 0 otherwise
1 if living with 2 or more children; 0 otherwise

0.31

Child age 0-2 years

1 if child is aged 0–2 years; 0 otherwise (childaged 3–5 years)
1 if living with a husband or partner who is
working full-time as a regular employee; 0
otherwise
1 if working up to (less than one year before)
birth of the youngest child; 0 otherwise
1 if preferring to work full-time; 0 otherwise(preferring to work part-time)
1 if using childcare center for the youngest
child; 0 otherwise
1 if using desired childcare center for the
youngest child; 0 otherwise

0.55

1 if using other-than-desired childcare centerfor the youngest child because unable to use
desired childcare center; 0 otherwise
Population-weighted average of accessibilityof childcare centers using the 750-meter
threshold, for the youngest child, at the ward
level (value×100)
Female unemployment rate (%), at the ward
level

0.07

Full-time partner

Work experience before
childbirth
Full-time work preference
Access to childcare center(acc1)
Access to desired childcare
center (acc2)
Access to other-than-desired
childcare center (acc3)
Accessibility of childcare
centers, ward-level, 750m,
value×100 (acc4)
Female unemployment rate
(ward level, %)Number of observations

s.d.

0.35
0.38
0.16
0.55

0.85

0.56
0.27
0.32
0.25

97.5

20.9

4.96

0.81

261

5. Empirical results
First, I present the results of the geographic mismatch between childcare center supply
and demand. Next, the importance of access to childcare centers in attaining preferred
employment for women with preschool-aged children is explained.

16

5.1 Geographic mismatch of childcare centers
Figure 4 shows visualized results of the accessibility of childcare centers by basic unit
block for the commuting threshold of 750 meters. The maps reveal a considerable
geographic mismatch in childcare center supply and demand. It is striking that many
blocks have accessibility values below 1 (excess demand, or childcare shortage),particularly for younger children aged 0–2 years. A closer examination with the spatial
distributions of preschool-aged children and childcare centers (Figure 3) reveals thatblocks with low accessibility have the following three patterns in general. First, there are
no childcare centers nearby (within the commuting threshold). Second, centers nearby do
not provide care for a particular age group. Third, demand exceeds supply for a particularage group, although centers nearby do provide care for that age group.
The sensitivity to the two alternative commuting thresholds of 500 and 1,000
meters was examined. When the 500-meter threshold was used, the number of blocks
with considerably low accessibility values below 0.25 increased substantially,
particularly for children aged 0, for whom both the number and capacity of childcare
centers are limited; many blocks do not have childcare centers within the 500-meter
threshold. On the other hand, when the 1,000-meter threshold was used, the number ofblocks with considerably low accessibility decreased because many blocks havechildcare centers within 1,000 meters. However, there were still many blocks withaccessibility below 1. This result indicates that even when parents can travel a distanceto a childcare center, many areas still have childcare shortage. Thus, although alternative
thresholds led to different spatial variations in accessibility, the finding that low
accessibility exists in many blocks was consistent.

17

Accessibility  value
0.00
0.01-­‐0.24
0.25-­‐0.49
0.50-­‐0.74
0.75-­‐0.99>=1.00(a)  0  to  5-­‐year-­‐old  children(d)  children  aged  2(b)  children  aged  0(e)  children  aged  3

N

0    

5  

10  km (c)  children  aged  1(f)  children  aged  4–5

Figure 4. Accessibility of childcare centers in the Tokyo ward area (commuting
threshold of 750 m), 2009.

18

The considerable geographic mismatch for younger children appears to berelated to the large numbers on childcare waiting lists for younger children (Figure 2). I
investigated this relationship by using simple linear regression models relating theaccessibility measurement to the number on the waiting list in 2009 at the ward level foreach age group. Here, since the smallest spatial unit for which waiting list numbers
were available was the ward, the population weighted-average accessibility at the ward
level was used for the regression. Regression estimates are summarized in Table A2(Appendix). As expected, poorer accessibility was significantly associated with a larger
waiting list for children under the age of 3 years, and the most significant association
was found for the 1-year-old group for which the waiting list was the largest. On theother hand, the association for children 3 years and older was smaller in magnitude andinsignificant. The weak association for the children 3 years and older may be related to
the fact that they can be accommodated in kindergartens, which reduces childcare
waiting lists.

5.2 Childcare access and attaining preferred employment
Table 2 presents the estimation results of probit models examining the importance ofaccess to a childcare center in attaining preferred employment by women withpreschool-aged children. The five models using different sets of variables were
estimated to examine whether the importance of access to a childcare center differs
between (1) a desired childcare center and an other-than-desired childcare center, (2) awoman preferring to work full-time and a woman preferring to work part-time, and (3) awoman with a very young child aged between 0–2 and a woman whose youngest childis in the age group of 3–5 years.
19Model 1 examines the importance of access to childcare center in attaining
preferred employment. Access to a childcare center is significantly associated with ahigher probability of attaining preferred employment. The estimated marginal effect (atthe mean) indicates that the probability of attaining preferred employment is 38.7
percentage points higher when an otherwise-average woman has access to a childcare
center. Model 2 divides childcare centers into desired and other-than-desired. Bothaccess to a desired childcare center and access to an other-than-desired childcare center
have positive and significant associations with the attainment of preferred employment.
In Model 3, an interaction term is included in order to examine whether the
association between access to a childcare center and the attainment of preferred
employment differs between full-time and part-time as the preferred employment. The
results indicate that the association does not differ significantly according to the statusof preferred employment. Model 4 includes an interaction term to examine whether the
association differs by the presence of a very young child in the age group of 0–2 years.
Indeed, the association is greater for a woman with a very young child in the age groupof 0–2 years than for a woman whose youngest child is in the age group of 3–5 years.
For an otherwise-average woman with a very young child in the age group of 0–2 years,
the probability of attaining preferred employment is 40.8 percentage points higher when
she has access to a childcare center. On the other hand, when the youngest child is in theage group of 3–5 years, the difference is much smaller—26.3 percentage points. Model
5 divides childcare centers into desired and other-than-desired centers and adds twointeraction terms to examine whether the association between access to each of the two
types of centers and the attainment of preferred employment differs by the presence of avery young child in the age group of 0–2 years. A significant difference emerges when20the childcare center is the desired center. For an otherwise-average woman whose
youngest child is in the age group of 0–2 years, the probability of attaining preferred
employment is 61.9 percentage points higher when she has access to a desired childcare
center, whereas for a woman whose youngest child is in the age group of 3–5 years, thedifference is much smaller, 23.5 percentage points. When the childcare center is another-than-desired center, the association is not made significantly different by thepresence of a child in the age group of 0–2 years.
It should be noted that the estimated results cannot prove the causality due topotential bias arising from endogeneity between access to childcare centers andemployment. However, the estimated results do offer evidence suggesting at least thataccess to childcare and the attainment of preferred employment are strongly associated.
In all the models, the ward-level accessibility of childcare centers using thecommuting threshold of 750 meters shows weak and insignificant association with theattainment of preferred employment. The insignificant result holds true when alternative
accessibility with the threshold of 500 or 1,000 meters is used. The results may bepartially due to using accessibility measurements at the ward level rather than at thebasic unit block level (Figure 4), on account of the limited residential area informationof the sample. The particularly tight childcare market (excess demand) might also play apart in the insignificant result. In a tight market, a woman might put extra effort inovercoming the spatial barrier by finding other childcare help or moving residence.
Other variables that are significantly associated with the probability of
attaining preferred employment in all the models are discussed below. Living with two
or more children is positively associated with the attainment of preferred employment,
which might suggest that having more than one child causes a greater financial need to21

work. The presence of a very young child (under the age of 3) is negatively associatedwith the attainment of preferred employment. Living with a husband or partner who is
working full time is also negatively associated with the attainment of preferred
employment. Working experience before childbirth is related to a higher probability of
attaining preferred employment. These results are reasonable given the existing labormarket literature.

22

Table 2. Probit estimates of attaining preferred employment.
Model 1
Age 30-34 years
Age 35-39 years
Age 䍹 40 years
2 or more childrenChild age 0-2 years
Full-time partner
Work experience before childbirth-0.077(0.349)0.129(0.353)-0.287(0.406)0.512**(0.208)-0.430*(0.235)-0.779***(0.243)0.669***(0.217)[-0.025]

1.123***(0.196)[0.387][0.042][-0.086][0.161][-0.140][-0.282][0.207]

Model 2-0.076(0.349)0.130(0.353)-0.284(0.407)0.514**(0.209)-0.429*(0.235)-0.780***(0.243)0.670***(0.217)[-0.024][0.042][-0.085][0.162][-0.139][-0.282][0.208]Full-time work preference
Access to childcare center (acc1 )Access to desired childcare center (acc2 )Access to other-than-desired childcare center (acc3 )Full-time work preference × acc1
Child age 0-2 years × acc1

1.111***(0.213)1.160***(0.335)Model 3Model 4Model 5-0.069 [-0.022](0.349)0.138[0.045](0.353)-0.298 [-0.089](0.408)0.505** [0.158](0.208)-0.457* [-0.148](0.238)-0.756*** [-0.273](0.246)0.644*** [0.199](0.219)0.158[0.059](0.303)
1.066*** [0.373](0.238)-0.117 [-0.036](0.358)0.069[0.022](0.361)-0.320 [-0.092](0.411)0.560*** [0.171](0.213)-0.874*** [-0.277](0.304)-0.835*** [-0.299](0.248)0.653*** [0.197](0.221)-0.057 [-0.018](0.363)0.124[0.040](0.366)-0.332 [-0.099](0.418)0.471** [0.149](0.218)-0.936*** [-0.199](0.310)-0.902*** [-0.330](0.250)0.594*** [0.186](0.223)0.691***(0.258)[0.230][0.395]0.605**(0.270)1.234**(0.536)[0.433]0.065[0.408]a(0.420)[0.359]b0.983**[0.514]c(0.392)[0.263]d[0.474][0.453]23

(Cont’d)Model 1Model 2Model 3Model 4Model 5

Child age 0-2 years × acc2

1.321*** [0.619]c(0.440) [0.235]dChild age 0-2 years × acc3

-0.033[0.419]c(0.705)[0.454]d[0.001]0.001[0.000][0.023](0.006)0.126(0.138)[0.041]

Accessibility of childcare centers, ward-level, 750m,
value×100 (acc4 )0.004

Female unemployment rate (ward level, %)(0.006)0.050(0.129)Number of observations
Percentage correctly predicted

261
78.9

261
78.9

261
79.3

261
77.4

261
79.3

Log-likelihood value
McFadden's pseudo R-squared-118.90.26-118.90.26-118.50.26-115.70.28-114.10.29[0.001]0.004[0.016](0.006)0.047(0.131)[0.001]0.004[0.015](0.006)0.035(0.131)[0.001]

0.003[0.011](0.006)0.074(0.132)

Constant is not reported. Standard errors are in parentheses. Statistical significance is indicated as follows: ***p < 0.01; **p < 0.05; and *p < 0.10.
Marginal effects at the mean of the sample are in brackets; marginal effects for dummy variables are for discrete changes from 0 to 1. Marginal effects
for interaction variables are for discrete changes from 0 to 1 in variables related to access to childcare centers when a) full-time work preference is 1; b)full-time work preference is 0; c) child age 0–2 years is 1; and d) child age 0–2 years is 0.

24

6. Conclusion
In this study, visualized accessibility at the block level has revealed the existence of aconsiderable geographic mismatch between childcare center supply and demand,
particularly for younger children aged 2 years or below. For these children, lower
accessibility of childcare centers was significantly associated with a longer childcare
waiting list. Key findings from the probit models are summarized in the following threepoints. First, access to a childcare center was significantly associated with a higher
probability of attaining preferred employment among women with preschool-aged
children. Second, the association was not significantly different according to the statusof preferred employment—full-time versus part-time. Third, access to a childcare center,particularly a desired center, was significantly more important in attaining preferred
employment for a woman with a child in the age group of 0–2 years than for a woman
whose youngest child is in the age group of 3–5 years old.
The findings of this study have important policy implications. First, resolving
the geographic mismatch for children in the age group of 0–2 years helps to reduce thenumber of childcare waiting lists. The placement of childcare centers within a city andthe extent of the development of these centers are questions that no evident policy has
addressed. The accessibility measurement for spatial micro areas can be a usefulindicator in the development of such policy. For example, developing childcare centersin low-accessibility areas with high demand could be an effective approach to reducing
the number of waiting lists.
Second, providing adequate childcare helps women attain their preferred
employment while raising children. Such provision could encourage women’s active
25

participation in the labor market. It would be beneficial in areas experiencing childcare
shortage (excess demand) as well as promoting female labor market participation. Thereis great potential here, as indicated, for example, by the substantial gap between current
and preferred employment statuses.
Third, providing quality and affordable childcare for very young children(under the age of 3) is particularly valuable for women’s attainment of preferred
employment. There is a substantial number of women who need childcare in order tocontinue working while raising children. The lack of access to reliable childcare can not
only discourage such women from continuing working but also deteriorate their future
employment prospects, since gaps in work history are a disadvantage for those who
attempt to re-enter the labor market. In fact, the probit results show that continuous work
experience is an important factor in the attainment of preferred employment. The probit
results also suggest that for women with very young children, access to quality andaffordable childcare are of particular importance for continued working. As is evident,
the positive association between access to a desired childcare center and the attainmentof preferred employment was significantly greater for a woman with a very young childin the age group of 0–2 years than for a woman whose youngest child is in the agegroup of 3–5 years. The survey data employed in this study could provide answers
regarding the most desirable childcare service. Among women with children in the agegroup of 0–2 years, a strong majority (73%) selected licensed daycare centers, which
provide relatively high quality and affordable childcare.
The results of this study warrant further research. The first direction is to refine
the models to examine causal relationships between access to childcare and employment,
which are likely to be endogenous. The second direction is to use, in the models, more26

spatially micro-level data on the accessibility of childcare. Results that are moresignificant might emerge if sufficiently spatially detailed accessibility were incorporated
into the models. The third direction is to incorporate fathers’ roles in the analysis, asmany countries attempt to encourage fathers’ participation in childrearing (OECD,2007). Further research in these directions would contribute to the literature on
childcare access and work-life balance.

References
Apps, P. and Rees, R. (2005) Gender, time use, and public policy over the life cycle,
Oxford Review of Economic Policy, 21(3), pp. 439-461.
Blau, D. M. (2001) The Child Care Problem: An Economic Analysis. New York: The
Russell Sage Foundation.
Blau, D. M. and Robins, P. K. (1988) Child-care costs and family labor supply, The
Review of Economics and Statistics, 70, pp. 374-381.
Crompton, R. and Lyonette, C. (2006) Work-life ‘balance’ in Europe, Acta Sociologica,
49, pp.379-393.
Davis, E. E. and Connelly, R. (2005) The influence of local price and availability on
parents’ choice of child care, Population Research and Policy Review, 24, pp.
301-334.
de Meester, E., Zorlu, A. and Mulder, C. H. (2011) The residential context and thedivision of household and childcare tasks, Environment and Planning A, 43, pp.
666-682.
Del Boca, D. and Vuri, D. (2007) The mismatch between employment and child care in
Italy: the impact of rationing, Journal of Population Economics, 20, pp. 805-832.
27

Gender Equality Bureau Cabinet Office of Japan (2007) Report of Survey on Support
for Women’s Life Planning, Cabinet Office, Japan.
(http://www.gender.go.jp/danjo-kaigi/kansieikyo/raifupuran1903.pdf) (in Japanese)
Gordon, R. A. and Chase-Lansdale, L. (2001) Availability of child care in the UnitedStates: a description and analysis of data sources, Demography, 38, pp. 299-316.
Handy, S. L. and Niemeier, D. A. (1997) Measuring accessibility: an exploration ofissues and alternatives, Environment and Planning A, 29, pp. 1175-1194.
Hanson, S. and Pratt, G. (1990) Geographic perspectives on the occupationalsegregation of women, National Geographic Research, 6(4), pp. 376-399.
Harris B. (2001) Accessibility: concepts and applications, Journal of Transportationand Statistics, 4(2/3), pp. 15-30.
Herbst, C. M. and Barnow, B. S. (2008). Close to home: a simultaneous equations
model of the relationship between child care accessibility and female labor force
participation, Journal of Family and Economic Issues, 29(1), pp. 128-151.
Jaumotte, F. (2003) Labour force participation of women: empirical evidence on therole of policy and other determinants in OECD countries, OECD Economic Studies,37, pp. 51-108.
Kawabata, M. (2010) Survey report on balancing work and child rearing andaccessibility to child-care centers, CSIS Discussion Paper 102, Center for Spatial
Information Science, The University of Tokyo, pp. 1-39. (in Japanese)
Kreyenfeld, M., and Hank, K. (2000) Does the availability of child care influence theemployment of mothers? Findings from western Germany, Population Researchand Policy Review, 19, pp. 317-337.
Kwan, M.-P. (1999) Gender and individual access to urban opportunities: a study using28

space-time measures, Professional Geographer, 51, pp. 210-227.
Leibowitz, A., Klerman, J. A. and Waite, L. J. (1992) Employment of new mothers andchild care choice: differences by children’s age, The Journal of Human Resources,27(1), pp. 112-133.
Luo, W. and Wang, F. (2003) Measures of spatial accessibility to health care in a GIS
environment: synthesis and a case study in the Chicago region, Environment andPlanning B, 30, pp. 865-884.
Ministry of Health, Labour and Welfare of Japan (MHLW), 2010. About
Childcare-Center and Other Conditions (as of April 1st, 2010).
(http://www.mhlw.go.jp/stf/houdou/2r9852000000nvsj.html) (in Japanese)
Miyazawa, H. (1998) Investigating time-space constraints on accessibility to day
nursery facilities in Nakano Ward, Tokyo, Geographical Review of Japan, 71A-12,
pp. 859-886. (in Japanese)
Morris, J. M., Dumble, P. L. and Wigan, M. R. (1979) Accessibility indicators fortransport planning, Transportation Research A, 13, pp. 91-109.
Organisation for Economic Co-operation and Development (OECD) (2007) Babies andBosses: Reconciling Work and Family Life: A Synthesis of Findings for OECDCountries. Paris: OECD.
Organisation for Economic Co-operation and Development (OECD) (2008) Babies andbosses: balancing work and family life, Policy Brief July 2008.
Pickup, L. (1988) Hard to get around: a study of women’s travel mobility, in: J. Little, L.
Peake and P. Richardson (Eds) Women in Cities: Gender and the Urban
Environment, pp. 98-116. Houndmills, England: Macmillan Education.
Pinch, S. (1984) Inequality in preschool-aged provision: a geographical perspective, in:29

A. Kirby and S. Pinch (Eds) Public Service Provision and Urban Development, pp.
231-282. New York: St. Martin’s Press.
Powell, L.M. (1998) Part-time versus Full-time work and child care costs: evidence formarried mothers, Applied Economics, 30(4), pp. 503-511.
Presser, H. B. and Baldwin, W. (1980) Child care as a constraint on employment:
prevalence, correlates, and bearing on the work and fertility nexus, American
Journal of Sociology, 85(5), pp. 1202-1213.
Schwanen, T., Ettema, D. and Timmermans, H. (2007) If you pick up the children, I'll
do the groceries: spatial differences in between-partner interactions in out-of-homehousehold activities, Environment and Planning A, 39, pp. 2754-2773.
Segawa, S. and Sadahiro, Y. (1996) A decision-making support system for child carefacilities using GIS, Theory and Applications of GIS, 4, pp. 11-18. (in Japanese)
Stolzenberg, R. M. and Waite, L. J. (1984) Local labor markets, children and labor force
participation of wives, Demography, 21, pp. 157170.
Suzuki, W. (2010) Inconvenient Truth about Social Security Services: Thinking Child
Rearing, Medical Care, and Pension in Economics. Tokyo: Nikkei Publishing.
Tivers, J. (1988) Women with young children: constraints on activities in the urban
environment, in: J. Little, L. Peake and P. Richardson (Eds) Women in Cities:
Gender and the Urban Environment, pp. 84-97. New York: New York University
Press.
Tokyo Metropolitan Government (TMG), Bureau of Social Welfare and Public Health(2011) 2011 Social Welfare and Public Health in Tokyo.
(http://www.fukushihoken.metro.tokyo.jp/joho/koho/tokyo_fukuho_e11/files/2011fukusi_eigo_1.pdf)
30

van Ham, M., Büchel, F. (2006) Unwilling or unable? Spatial and socio-economic
restrictions on females’ labour market access, Regional Studies, 40, pp. 345-357.
van Ham, M. and Mulder, C. H. (2005) Geographical Access to Childcare and Mother’sLabour-Force Participation, 7LMGVFKULIWYRRU(FRQRPLVFKHHQ6RFLDOH*HRJUD¿H,
96(1), pp. 63-74.
Wang, F. and Luo, W. (2005) Assessing spatial and nonspatial factors for healthcare
access: towards an integrated approach to defining health professional shortage
areas, Health & Place, 11, pp. 131-146.
Webster, C. J. and White, S. (1997) Childcare services and the urban labour market.
Part 2: modelling the relationships between childcare service accessibility andlabour-market participation, Environment and Planning A, 29, pp. 1675-1695.
Zhou, Y. and Oishi, A. (2005) Underlying demand for licensed childcare services inurban Japan, Asian Economic Journal, 19, pp. 103-119.

31

Appendix
Table A1. Basic demographic statistics of the survey and 2005 census.
Survey respondents
Number2005 census population of women withpreschool children in Tokyo ward area
Percent
Number
Percent

Age
under 25
3
1
25–29
28
9
30–34
115
37
35–39
116
37
40–44
42
14
45 and older
72
Number of children living together
1
145
47
2
142
46
3 and more
24
8
Age of youngest child
0
57
18
1
66
21
2
58
19
3
59
19
4
34
11
5
37
12
Working
Housewives

114
175

Full sample size

311

37 a)
57 a)

8,380
40,080105,200
94,12032,720
3,700

3
14
37
33
12
1

138,170
113,740
32,29049
40
1158,56057,82049,33044,70038,25035,540

21
20
17
16
13
13

96,260
181,020

34 b)
64 b)

284,200a) The proportions of those whose answers are valid (308). b) The proportions of those whose labor
force statuses are determined (281,250).
Note: The census statistics were calculated using the order-made summary statistics provided by the
National Statistics Center of Japan; the census statistics are different from the data created and madeavailable by the administrative agencies.

32

Table A2. Regression estimates of the number of children on childcare waiting list.
Age 0

Age 1

Age 2

Age 3

Age 4 and older Total

Accessibility
500m

750m

1,000m-68.04**-334.66***-116.46**-24.45-1.80-380.04*(32.07)(120.97)(56.39)(16.61)(4.52)(196.02)-68.00**-373.28***-123.01**-24.74-2.37-410.80**(32.83)(119.07)(58.85)(17.34)(4.65)(196.27)-71.68**-388.21***-121.80**-22.68-2.07-392.49*(35.66)(126.83)(59.26)(17.63)(4.65)(202.14)

Adjusted R-squared
500m

0.14

0.23

0.13

0.05

-0.04

0.11

750m

0.13

0.29

0.13

0.04

-0.03

0.13

1,000m

0.12

0.28

0.13

0.03

-0.04

0.11

Standard errors are in parentheses. *, **, and *** denote significance at the 10, 5, and 1 percent level,
respectively. The number of observations is 23 for each model.

33