CSIS Discussion Paper (University of Tokyo), No.121

Longitudinal trends in equity of park accessibility in Yokohama,Japan: An investigation of the role of causal mechanisms
May 3, 2013
Shinya Yasumoto* ・Andrew Jones†・Chihiro Shimizu‡
Abstract
Despite an increasing interest in issues surrounding environmental equity, muchresearch evidence to date is based on studies adopting cross-sectional approaches which
do not adequately capture the processes and mechanisms generating inequities.
Longitudinal studies may better inform policy measures to remedy inequity between
populations, but the few that have been undertaken mostly focus solely on
environmental risks, ignoring access to amenities. As a case study, we adopt a
longitudinal approach in this work to investigate the association between sociodemographic indicators and public park provision over an 18 year period in the city of
Yokohama, Japan. We show that inequities in park provision are present over the wholetime period. Hedonic modelling shows that park accessibility is positively associatedwith house and land prices in the city. Our results suggested some, relatively weak,evidence of two causal processes; new parks are located in more affluent communities,
yet also appear to subsequently encourage further move-in of affluent populations. We
suggest park provision by administrative authorities in less affluent neighbourhoods
may be required to maintain equity in access to these valuable community resources.
Economic incentives, such as subsidy provision, may have role to play to encouragepark provision by developers.

Keywords: Environmental equity; Longitudinal modelling; Hedonic
Approach; GIS
JEL Classification: C31, R31* Corresponding author: Shinya Yasumoto, Department of Human Ecology, School ofInternational Health, Graduate School of Medicine, University of Tokyo
E-mail: yasumoto@humeco.m.u-tokyo.ac.jp† Norwich Medical School, University of East Anglia.
‡ Department of Economics, Reitaku University & University of British Columbia
11. Introduction

In recent decades, there has been an increasing interest in issues surrounding
environmental equity. The concept of environmental equity particularly grew fromaction against environmental racism in the 1980s in the USA (Liu 2001), with a distinct
focus on the siting of controversial facilities such as hazardous waste dumps in areas
occupied by non-white populations (e.g. Godsil 1991). Since then the equity movement
has based its efforts on the goal of achieving planning that leads to an equal sharing ofenvironmental hazards and opportunities between communities (EPA 1992, Jones et al.
2009). Nevertheless recent findings in a range of countries suggest that inequities often
still persist and are associated with diverse factors including age, ethnicity and affluence(e.g. Liu 2001, Jones et al. 2009, Yasumoto et al. 2011, Godsil 1991).

Prior studies in the environmental equity field use mostly one of two methods (Mohai2008). A large number are cross-sectional investigations of the distribution ofenvironmental quality between different population groups (Godsil 1991, Liu 2001).
These studies are based on observations made at a single time point, generally focus on
only one outcome, and hence do not adequately capture the causes and processes
generating environmental inequities. An alternative is to take a longitudinal approach
which focuses on time-dependent changes in the relationship between environmental
qualities and population characteristics. In longitudinal studies the question of ‘Whichcame first?’ is frequently asked (Boone et al. 2009, Mohai 2008, Pastor et al. 2001). The
concept being considered here is that environmental inequity may be generated through1

two different processes. The first is that environmental risks come into already sociallydisadvantaged communities or that benefits tend to be sited in affluent areas. The
second is that disadvantaged or advantaged groups move into areas after the placementof environmental disamenities or amenities. Those two different processes can be
principally caused by two factors; unequal political power between communities andmarket mechanisms (Pastor et al. 2001), both of which may be in operation and may becomplementary to each other (Saha and Mohai 2005).

To support the argument of the first process, it has been suggested that disadvantaged
groups have limited political power to resist the disproportionate siting of disamenities,
and thus their areas attract more environmental risks (see Pastor et al. 2001, Hamilton
1993, Hamilton 1995). Conversely, more affluent or socially advantaged communities
may be more politically empowered to attract new environmental amenities such asparks (Boone et al. 2009, Talen 1998). Market mechanisms are the other potential driverof disproportionate siting since developers or authorities may chose sociallydisadvantaged areas to site controversial facilities due to cheaper land prices and lessneed to provide compensation for local people (Portney 1991). For amenity siting,market mechanisms may actually sometimes be beneficial for the sociallydisadvantaged since cheaper land prices may encourage new amenity siting by
providers, particularly for developers who have an obligation to provide amenities butwhere there is some flexibility on their location.

It has also been suggested that disadvantaged populations may be attracted into
environmentally disadvantaged neighbourhoods by low property prices (see Been 1994,
2

Saha and Mohai 2005), or partly by housing discrimination practices such as the limited
provision of social housing (e.g. Nakagawa 2001). Conversely, the affluent may beattracted into areas with good amenities, even though property prices in such areas
might be relatively high (Jones et al. 2009, Boone et al. 2009). If these processes doexist, policy makers may face a problem as policies attempting to more evenly
distribute environmental quality may backfire if consequent changes in land andproperty prices cause people to reallocate, resulting in the re-occurrence of inequity (Liu
2001).

Many hypotheses concerning people's migration associated with environmental quality
and housing prices are underpinned by the economic theory of residential sorting(Tiebout 1956, Epple et al. 2001, Calabrese et al. 2006). This theory is derived from thework of Tiebout (1956), and describes how individuals will choose to settle in acommunity that best satisfies their preference for public goods. For example, Epple etal. (2001) developed a general equilibrium model which describes how people migrate
between different areas until they find the one where they maximize their utility basedon the available mix of public goods and housing prices. However, a limitation of manystudies on residential sorting is that they rely on relatively strong assumptions abouthousehold preferences, mobility, and the cost of providing public goods. Particularissues are that it is assumed that individuals will behave rationally with respect to theirperceptions of environmental goods, and that they will have perfect information, neitherof which is likely to be the case (Liu 2001). Secondly, as most of these studies operate
at an aggregate level, there are difficulties incorporating data on housing transactions
and public good provision at a household or land parcel level. Indeed Epple et al. (2001)3

themselves have highlighted the need for future research to allow for more sources ofobserved and unobserved heterogeneity among households.

Although several longitudinal studies have been undertaken to clarify the processes
operating to generate inequities in the burden of environmental risks (e.g. Been 1994,
Saha and Mohai 2005, Pastor et al. 2001, Hamilton 1993, Hamilton 1995), very little is
known about the distribution of amenities. In this research we examine the potential
existence of the mechanisms discussed, and what the possible policy implications of
their presence may be. As a case study, we focus on the longitudinal association
between the siting of an environmental amenity, public parks, and social-demographic
characteristics in Yokohama, Japan, a country where rather little work on environmental
equity has been undertaken.

Parks are increasingly being recognised as an important component of the urban
landscape. There is good evidence that they positively affect people’s physical health,providing opportunities for recreation and physical activity (Payne et al. 1998) and moregenerally contributing to the psychological and social health of communities (Hirata
2004). Moreover large green spaces mitigate the effect of air and noise pollution (Hirata
2004). Proximity to open spaces including parks is also expected to play a vital role fornatural hazard management and protection against earthquakes and fires (Koike et al.
2010). However there is evidence from several countries that the provision of parks may
be inequitable. Jones et al. (2009) examined the distribution of access to parks between
populations in Birmingham, England, and found evidence of disparities in provision
related to socioeconomic deprivation, whilst Wolch et al (2002) and Sister et al. (2007)4both found that communities with Latinos, non-white or low income groups have worse
access to parks in American contexts.

To test the ‘which came first?’ hypothesis within framework of park provision, we
focused on the different role of two park providers: The city council (municipal
authority) and private developers. Those two providers are governed by different policy
and regulatory mechanisms, as well as being motivated by different incentives;
provision versus profit. In particular, city council parks are specified to be located inareas where provision is poor (Hirata 2004), although it is unclear if the sociodemographic characteristics of communities are often considered. On the other hand, if
an area of a planned new development plan is more than 5 ha, legislation requires that
3% of the developed area has to be public parkland, and this must be funded andprovided by the developers (Hirata 2004). As a consequence, private developers are also
important park providers (Maruani and Amit-Cohen 2011).

Whilst the primary task of local authorities is to pursue public interests, the motivationof developers is primarily profit maximization (Maruani and Amit-Cohen 2011).
Therefore developers may preferentially select areas with cheap land prices or sites thatare attractive for purchasers. They may not be strongly motivated to open parks that arelarge or of good quality, and indeed evidence suggests that developers think that targets
such as the conservation of nature are costly to achieve, and that they underestimate
value of open spaces (Bowman and Thompson 2009).

This case study of Yokohama Japan, a country where little previous equity work has
5been undertaken, was made to describe an approach to the longitudinal modelling ofpark provision. We examine both the siting and move-in hypothesises discussed above.
In order to investigate the potential causal role of market mechanisms, we then present ahedonic model which quantifies the association between park provision and land andproperty price changes. Hedonic pricing considers a land parcel or a property as a set of
attributes against which price is modelled (Hidano 2002), and our hedonic models focus
on park provision as the key attribute of interest. We conclude by presenting thestrengths and caveats associated with our approach, as well as the potential policy
implications of our findings.

2. Methodology
2.1. Study areas

The area used in this case study is Yokohama, Japan, which is located in Kanagawa
Prefecture and bounded by Tokyo Bay and Tokyo, the Japanese capital. Yokohama has
the second largest population in the country (3.6 million people in 2005), and is asignificant economic base for manufacturing, tourism and shipping. The city isundergoing substantial population growth and it acts as a dormitory town for many
people who work in the nearby Tokyo.

2.2 Data
For the purpose of this study, two main datasets were generated; a 1 km grid based on
census derived population characteristics, and a set of digital maps of park provision in6

Yokohama. Both were computed for a range of time points.

The census data was extracted from the Population Census Grid Square Statistics
published by the Ministry of Internal Affairs and Communications (MIAC 2011). The
census is conducted every five years, and for this study, the results of surveys conducted
in 1990, 1995, 2000 and 2005 were employed. This analysis focussed on two sociodemographic indicators. The first was the percentage of pensioners, defined as
individuals aged 65 years or older, in grid cells. The elderly are often regarded as asocially disadvantaged group due to their poorer health, and reduced mobility and social
activity (Sexton et al. 1993). Since our research interest is whether socially advantaged
communities attract park provision, or advantaged people move into areas after thesiting of parks, we also extracted the percentage of professional and managerial workers
as an indicator of population affluence for each cell. Ten 1 km grids were excluded fromthe analysis since their information on population characteristics were not released dueto their small population.

To measure accessibility to public parks for each 1 km census grid, we firstly generated
maps of park locations using the ArcGIS 9.3 (ESRI Inc.) Geographical Information
System (GIS). A database of urban parks was obtained from Yokohama City Council,
supplying information on the name, address, park area, and the opening year of eachpark located within the city. For the purposes of map production, we differentiatedparks which were larger than 2 ha in area from those which were less. For the larger
parks, we depicted the park boundaries on our map using outlines present in the 2005
edition of the ‘Digital Map 2500’ (1:2500) digital cartographic product produced by the7Japanese Geographical Survey Institute. Manual checking of this dataset highlighted anumber of parks which were not present, and the boundaries of these were subsequently
digitised from a local paper atlas. Small parks of less than 2 ha in area were represented
as circles with an area equal to that of the corresponding park. The circles were locatedusing address-matched latitude and longitude coordinates from on-line lookup tables
produced by the Centre for Spatial Information Science at the University of Tokyo(CSIS 2011).

Using the information on park opening dates held in the database, the mapping
procedure was repeated 18 times to produce a map of park locations for every year
between 1988 and 2005, the most recent period for which data was available. The maps
were additive because no park was recorded as being closed during this period. The cityof Yokohama also provided information on whether each park was opened by a private
developer or the city council, and this was added to the database. For each 1km gridcell for which census data was available, access to parks was measured using four
metrics; firstly the number of parks within the cell, secondly the park area, and thirdly
the park area per capita. The computation of these metrics is known as the ‘container’
method (see Talen and Anselin 1998). The fourth metric was whether or not a park was
opened in a given year. Parks provided by the city council and by private developers
were differentiated in these metrics due to the different policies governing them.

A range of covariates which were hypothesised to potentially to be associated with parkprovision were also considered (Table 1). The two population characteristics of interest,
percentage pensioners and percentage professional and managerial workers, were8

computed from census records and classified into quartile groups. Population density
was also computed based on census records, since highly populated areas may havemore demand for parks. However, since the Japanese census data is collected every five
years, it is not possible to model annual changes in population characteristics against
annual changes in park provision. Therefore, we took a time-period based approach andexamined the changes in population characteristics at a time which was as temporally
coincident as possible to that of park provision (see Saha and Mohai 2005).

As new park provision may depend on existing provision, the number of parks that werealready present within each 1 km grid was extracted from the previously described park
database. Cheaper land prices may attract park provision, and hence in order to include
a consideration of land prices in the analysis, estimated land values that are annually
published by the Ministry of Land, Infrastructure, Transport and Tourism wereconsidered. This data consists of point based estimates; for example, there were around
900 estimation points in 2005, and each point represents a specific estimated land priceproduced by professional assessors (see Hidano 2002). The land price of eachestimation point is estimated by considering actual transaction price or rent ofneighbouring land parcels which have similar characteristics. In order to estimate land
prices for each grid cell, we created Thiessen polygons (Johnston 1998) for each year
based on the locations of the points whose land price data was estimated, and these wereoverlaid with the grid cell boundaries to estimate the average land price within each
cell.

9

Table 1. Explanatory variables for the siting analysis, move-in analysis and hedonic analysis

Variable

Reference source

HypothesisedDatarelationshipsourceDescriptive statistics
Min

Mean

Max

SD

Variables for the move-in analysis (logistic regression)
Quartile groups of pensioners (%)

DEV: NS CC: NS

Census----

DEV: + CC: NS

Census----

DEV: NS CC: +DEV: + CC:－

Census

13

8612

22162

4564

DM, MP

0

5.9

22

3.8

Estimated land price (100,00 yen)

DEV:－ CC:－

ELP

9.8

41.2

773.4

50.6

Distance to Yokohama centre (km)

DEV:－ CC: NS

DM

0.4

9.7

19.8

3.9

Distance to Tokyo centre (km)

DEV:－ CC: NS

DM

17

29.1

41

6.2

-

-

-

-

-

-

-

-

Quartile groups of professional

Robinson && managerial workers (%)

Robinson (1985)

Population density (people/km2)
Number of parks pre-existingibid

Variables for the move-in analysis (multiple regression)
PEN: － P&M: +Jones et al. (2009)
DM, MP

Park provision by developers

PEN: － P&M: +DM, MP

Population density (people/km )PEN: － P&M: －Census

13

8612

22162

4564

Distance to Yokohama centre (km)PEN: －P&M: －

DM

0.4

9.7

19.8

3.9

Distance to Tokyo centre (km)PEN: －P&M: －

DM

17

29.1

41

6.2

Quartiles of pre-existing

PEN: +

Census----P&M: +

Census----DM, MP

-

-

-

-

+

RIW

13.8

136.6

991.7

64.9

+

RIW

0

80.1

1840.4

45.3

+
－

RIW

0

5.4

45.0

2.5

RIW

-

-

-

-

Park provision by city council

ibid2

pensioners (%)
Quartiles of pre-existing profess-ional & managerial workers (%)
Quartiles of park area pre-existing

variable
Variables for the hedonic analysis

Structural variables
Ground area (m2)2Floor space (m )(detached house only)
Width of front road (m)Shimizu (2004)

Private road dummy

ibid

Residential zoning dummy

+

RIW

-

-

-

-

South-facing dummy

Gao & Asami(2001)

+

RIW

-

-

-

-

Reinforced concrete dummy

Shimizu (2004)

+

RIW

-

-

-

-

(detached house only)

10Table 1. (continued)
Neighbourhood variables
Professional &Shimizu (2009)+

CensusDistance to Yokohama centre (km)Hidano (2002)－

DM

Distance to Tokyo centre (km)

ibid

－

DM

Distance to elementary school (km)Pacione (1989)－

DM, SL

Travel time to

Shimizu (2009)

－

ibid

0

5.2

22.0

3.9

0.4

9.4

20.3

4.3

16.2

29.1

42.0

6.0

0

0.4

1.4

0.2

RIW

0

12.6

38.0

4.9

－

RIW

-

-

-

-

+

DM, MP----Year 2000 dummy

－

RIW

-

-

-

-

Year 2005 dummy

－

RIW

-

-

-

-

variable

RIW

0

2.6

50.4

2.6

managerial workers (%)
Accessibility variables

closest rail station (min)Using bus dummy
Environmental variables
Quartile groups of park area
Variables related to transaction

Market reservation time (month)ibid-Hypothesized relationship with dependent variables: DEV - developers; CC - city council;
PEN - temporal change in pensioners (%); P&M - temporal change in professional andmanagerial workers (%)-Positive relationship (+) and; negative relationship (－); and no statistically significant
relationship (NS)-Key to reference and data source: RIW - Residential Information Weekly; Census - Japan
Census (Tabulation for 1 km grid) in 1990, 1995, 2000 and 2005; DM - Digital Map 2500; SL Yokohama Municipal School List of Names; and MP - Map of Parks and Green Spaces in
Yokohama

Private developers may be more likely to develop land close to city centres. Therefore,
to determine the level of accessibility to the centres of Yokohama and Tokyo (the capital
city of Japan), we calculated the Euclidean distance from the centroid point of every 1
km grid to the centres of both cities using ArcGIS.

In order to test the move-in hypothesis, we investigated the association between parkprovision and temporal changes in two demographic characteristics: the absolute change
in the percentage of pensioners and of professional and managerial workers between
two different points of time. Again, we differentiated between parks provided by the city11

council and those from developers. Another potential factor influencing population
change could be the percentage of the given population already existing in the year of
siting of parks, because a predominant population may attract more of the same owing
to the similar residential preferences, life patterns (Cutler et al. 1999), or, partly, theeffects of housing discrimination (Nakagawa 2001). Therefore, quartiles of thepercentage of pensioners and of the percentage of professional and managerial workers
at baseline were computed. Finally, if a community already has a large number of parks
or a large park area, an additional park may have little effect. Therefore, to differentiate
between the potential effect of pre-existing parks and that of a newly opened park, we
also incorporated the park area at baseline into our analysis.

For our hedonic pricing analysis, data on the prices of land parcels and detached housesin Yokohama were extracted from the Residential Information Weekly publication(RECRUIT., CO.). This weekly magazine describes the characteristics and asking prices
of both residential properties and plots of land. Although only 40% of Yokohama
residents live in detached houses, data on rents of apartments are unfortunately not
published. It was assumed that the price recorded when the property or land wasremoved from the magazine (normally at the point of sale) was the actual transaction
price, an assumption that previous empirical research has tested and found to beappropriate (Shimizu 2004). The two metrics chosen were selected to measure thecurrent (house prices) and future (land prices) potential of areas for move-in. We used
land and detached house price data from three survey years; 1995, 2000, and 2005. The
address of each transaction point was converted into a latitude and longitude and thelocation points were recorded in the GIS.
12

Although the focus of the hedonic analysis was on the association between market
prices and park provision, it was important to control for all factors that may influenceboth. Bateman et al. (2001) suggested that there are four major groups of relevance;
structural, neighbourhood, accessibility, and environmental variables. Structuralvariables are characteristics of pieces of land and the houses themselves, such as floor
space and the width of the road in front of the building. Neighbourhood variables (e.g.
population density) are characteristics of neighbourhoods that will influence desirability.
Accessibility variables are indicators of the ease by which local amenities (e.g. distances
to rail stations and schools) may be reached, whilst environmental variables encompass
measures of the quality of the surrounding environment.

The suite of variables generated is listed in Table 1. In terms of structuralcharacteristics, those computed were measures of ground area, floor space (for detachedhouses only), the width of the road in front of the property, whether the road was private
or public, whether the parcel or property fell inside a zone which was designated forresidential purposes, whether the entrance of the land parcel or property was southfacing (for good access to sunlight), and if the house was constructed from reinforced
concrete and hence more highly valued due to better earthquake resistance (Shimizu andKarato 2007) were computed.

A neighbourhood deprivation variable was generated from the Population Census Grid
Square dataset for the years 1995, 2000 and 2005. As no readily accepted index ofdeprivation exists in Japan, the percentage of professional and managerial workers was13

used a measure of area affluence. In order to capture elements of accessibility, we
created a set of variables which measured the proximity from each transaction point tothe city centres of both Yokohama and Tokyo, closest public elementary schools, andclosest railway stations. Accessibility to the centres of Yokohama and Tokyo as well as
elementary schools was computed based on Euclidean distances in the GIS. Railway
accessibility was measured considering the time required to walk to the nearest bus stopand then make a bus journey to the nearest railway station, except in cases where it was
faster to directly walk to the station, where only the walking time was considered. As
distances would differ by mode, a dummy variable representing a bus journey wasdefined, and then the cross term between it and travel time was fitted.

The key environmental variable studied, and the exposure of interest in the hedonic
study, was the accessibility of parks. To compute this, the same ‘container’ method as
described earlier was employed, this time using a 500 m circular distance buffer. Thisdistance was chosen because, in a Japanese context, Aoyama and Kondo (1986) foundthat the propensity to visit parks declined steeply amongst populations living further
than this distance away. Using the GIS we identified public parks that fell both partiallyand completely within each buffer, and then summed the total area of each park. Eachtransaction point was then classified according to the quartile of park area that fellwithin the buffer.

As the transaction dataset was collected for three time periods, dummy variables for thesurvey years were fitted into the equations to adjust effect of change in prices over time.
Next, the market reservation time was also recorded because properties or land parcels
14that had been on the market for a long time might have been so because their original
selling prices were largely unmatched with the market equilibrium price or because they
were a unique type of property (Shimizu 2009), such as one designed for handicappedpeople. Finally, to include fixed effects for unmeasured differences in outcomes
between neighbourhoods, we allocated the samples of land parcels and detached houses
to 18 wards (administrative units) in the city.

2.4. Analytical methodology
Descriptive statistics and tests for trend were initially used to examine how park accessvaried by population characteristics over the time periods analysed. For tests for trend,
Spearman’s rank-order correlation analysis was undertaken to clarify the association
between quartiles of each population characteristic and the number of parks, the park
area, and park area per capita within the census grid cells.

Next, to test the siting hypothesis, logistic regression analysis was conducted to
examine how population characteristics of each community were associated with parkprovision in each year over the 18 year-time timescale adopted. The dichotomous
dependent variable measured weather or not parks were provided in each 1km grid cellin each year. The 1990 census record was considered to examine the effect of population
characteristics on park provision between 1988 and 1992. Likewise population
characteristics extracted from the 1995 census data were used to test park provision
between 1993 and 1997, the 2000 census was used for the park siting between 1998 and
2002, and finally the 2005 census was considered for the park siting between 2003 and
2005.
15

In order to test the move-in hypothesis, multiple regression models were developed totest how park provision was associated change in population characteristics in each
census grid. The dependent variable was the absolute change in the percentage ofpensioners and of professional and managerial workers between the current andprevious modelled time points. As there would be expected to be a lag time between
park provision and population change, and the nature of that lag is not known, weinvestigated three different spans. First, we examined how changes in census
characteristics between 1990 and 2005 were associated with park provision between
1988 and 1992. Similarly, we related population change between 1995 and 2005 to parkprovision between 1993 and 1997, and population change from 2000 to 2005 to parks
built between 1998 and 2002.

Two hedonic pricing models, a land price model and a detached house price model,
were fitted to identify how additional park accessibility potentially affects both land andproperty prices. Based on the work of Doguchi and Kubo (2006), these models took theform:

lnPt = α + βit X it + δt dt + εt

Where Pt is the land price i or property price i, α is the intercept, X it is the matrix ofindependent variables and βit is the vector of parameters to be examined. δt indicates towhat extent prices change over time when all other variables are controlled. dt is adummy variable of time, and εt is an error term. All analyses were undertaken in PASW
16

statistics 18.

3. Results

Figure 1 illustrates spatial distributions of parks and population characteristics in 1990
and 2005. In 1990, as Figure 1 (c) shows, most communities with retired populations
were concentrated around the city centre, but by 2005 they had spread towards
southern-western parts. Moreover, the percentage of the population who were
pensioners doubled between 1990 and 2005. In both periods, areas with high percentage
of professional and managerial workers are situated in northern part of Yokohama,reflecting at least partially the role of the city as a dormitory town of Tokyo.

Between 1988 and 2005, the city council opened 556 parks (total park area 1702 ha),whilst developers provided 472 parks, but an area of only 212 ha. This shows that parks
built by developers are likely to be smaller than ones provided by the city authority.
Areas categorised into the most aged communities (census grids in the top quartile ofpensioners) were provided 95 parks by developers with a total area of 18 ha, whereas
developers constructed 105 (117 ha) parks in the least aged communities (lowest
quartile). For the same period, developers opened 125 parks (117 ha) in the mostaffluent communities, while in the least affluent communities only 59 parks (20 ha)
were provided. The city council opened parks almost equally between communities
regardless of the population characteristics across the 18 years.

17Figure 1. Spatial distributions of (a) public parks in 1990; (b) public parks in 2005; (c)pensioners (%) in 1990; (d) pensioners (%) in 2005; (e) professional and managerial workers(%) in 1990; and (f) professional and managerial workers (%) in 2005
18

Table 2 shows associations between park accessibility and quartiles of the two
demographic groups in Yokohama for the years 1990, 1995, 2000 and 2005. There was
no evidence of any trends in inequity associated with the percentage of pensioners at
any time period, but there was evidence of inequity in access to parks associated withthe percentage of professional and managerial workers in census grid cells, with themost affluent areas tending to have better access to parks in all time periods. The trend
is particularly apparent when the overall area of parks is considered. The mean value ofthe park area per capita shows a less clear trend, partly due to some census grids thathave small populations but large park areas and consequently high per capita values.
The median per capita values are thus more reliable.

Table 3 reports the results of multiple logistic regression analyses conducted to examine
the factors associated with park provision. After adjustment, it is evident that developers
tend to open parks in more affluent and less aged communities. Population density andthe number of parks already present also have a statistically significant and positive
association with the probability of developers opening new parks, whereas distance tothe city centre has a negative association. These factors are likely a result of the fact thatland provided by developers needs to be attractive to customers (Robinson andRobinson 1986). Meanwhile, land price has a significant and negative association. The
model thus suggests that park provision by developers is at least partially driven bymarket mechanisms.

19

Table 2. Relationship between demographic indicators and park area at different time points (1990, 1995, 2000 and 2005)
Pensioners (%)
Professional and managerial workers (%)
Park area per
Park area per
Number of parks
Park area (ha)capita (m2)
Number of parks
Park area (ha)capita (m2)
Quartiles ofdemographic
indicator
Mean Median
MeanMedian Mean Median Mean Median
MeanMedianMean Median1990 Lowest
4.5
4
11.5
2.0
114.4
2.6
2.7
2
4.8
0.4
110.6
0.9
2nd
4.7
4
8.4
1.4
25.4
1.8
4.5
4
8.1
1.8
12.3
1.8
3rd
4.8
4
8.6
1.2
14.7
1.6
5.7
6
10.1
1.5
31.3
2.2
Highest
5.1
4.5
9.1
3.0
48.9
2.3
5.9
6
13.8
2.5
53.9
3.0
－
Test for trend
+
+
+**
+**
+**
1995 Lowest
5.3
5
10.9
3.0
86.9
4.1
3.3
2
4.9
0.6
29.1
1.4
2nd
5.4
5
7.6
2.3
15.8
2.8
5.8
5
9.5
3.2
73.8
3.1
3rd
5.8
5
13.7
2.3
90.9
2.8
6.6
7
10.5
2.3
35.9
2.4
Highest
6.2
5
9.9
3.4
24.8
2.6
6.6
7
16.4
3.7
77.1
4.2
－
Test for trend
+
+
+**
+**
+**
2000 Lowest
6.2
6
11.6
3.6
62.3
5.2
3.9
3.5
9.3
2.0
393.1
2.6
2nd
6.1
5
10.1
2.4
61.6
2.8
6.8
6.5
11.3
3.5
32.0
3.8
3rd
7.0
7
13.3
3.4
21.5
3.5
7.8
8
12.2
3.3
43.2
3.0
Highest
6.9
6.5
16.2
4.9
352.1
4.6
7.0
7
17.7
4.8
83.9
5.1
－
Test for trend
+
+
+**
+**
+**
2005 Lowest
6.7
7
13.8
4.3
282.3
5.0
4.7
4
10.9
2.6
286.5
3.3
2nd
6.9
7
9.4
3.0
12.4
3.2
7.2
7
9.0
3.3
27.7
3.2
3rd
7.5
7
10.2
3.8
22.4
4.2
8.2
8
15.8
4.8
34.6
5.0
Highest
6.7
7
21.0
4.7
115.3
5.4
7.4
7
17.9
4.9
108.3
4.5
Test for trend
+
+
+
+**
+**
+**
Lowest = Least aged / affluent quartile group, Highest = Most aged / affluent quartile group
Direction of trend (+ positive – negative) **: P < 0.01 *: P < 0.05 NS: No statistical significance1

Table 3 shows no consistent association between the two demographic indicators andthe odds of parks being provided by the city council, nor were land prices associatedwith provision. The number of parks already present had a negative association withthe probability of the city of Yokohama opening a new park, illustrating that the city
council tends to provide parks in areas with fewer existing parks.

Table 3. Logistic regression model for new park provision between 1988 and 2005 by
developers and city council
Developers

City councilβ

95% CIβ

95% CI

2nd quartile of pensioners (%)

0.024

0.770 , 1.363- 0.2370.600 , 1.038

3rd quartile of pensioners (%)- 0.0650.699 , 1.256- 0.0840.700 , 1.209

4th quartile of pensioners (%)
2nd quartile of professional andmanagerial workers (%)
3rd quartile of professional andmanagerial workers (%)
4th quartile of professional andmanagerial workers (%)
Population density(100,00 people / km2)
Number of parks pre-existing
Estimated land price(100,00yen)
Distance to Yokohama centre(km)
Distance to Tokyo centre (km)- 0.446**

0.456 , 0.898- 0.0640.696 , 1.265

0.427*

1.086 , 2.162

0.331*

1.045 , 1.856

0.484**

1.150 , 2.289

0.073

0.794 , 1.456

0.455*

1.096 , 2.267

0.026

0.749 , 1.408

0.480**

1.208 , 2.162

0.334*

1.065 , 1.831

0.047**

1.016 , 1.080- 0.040*0.929 , 0.994- 0.005*

0.990 , 0.999- 0.004

0.993 ,1.000- 0.050**0.920 , 0.983

0.047**

1.016 , 1.080

0.016

0.998 , 1.034- 0.035**0.950 , 0.981

N
Cox & Snell R Square

6476
0.023

6476
0.022

95%CI = 95% confidential interval**: P < 0.01 *: P < 0.05
- 17 dummy variables measuring year (between 1989 and 2005) were incorporated into themodel, but the results of them are omitted from the table for brevity.

2

Table 4 shows the results of the model fitted to investigate changes in population
characteristics following park provision. Controlling for other characteristics, parkprovision by the city council was associated with increases in the percentage ofprofessional and managerial workers at both 10 years and 15 years following siting,suggesting the presence of move-in, although the effect sizes are small. No evidence
was found that park provision was associated with a change in the percentage ofpensioners. No associations were apparent for parks provided by developers possibly
because, as previously noted, developers’ parks are generally much smaller than thosefrom the city council.

Table 5 reports the results of the hedonic pricing models of land and property prices.
Both models illustrate that, when all other variables are controlled for, accessibility toparks has positive and significant association with land and property prices. This
provides some evidence that park provision may cause land and property prices to rise.

3

Table 4. Multiple regression analysis for changes in population characteristics after provision of parks(Constant)
Park Provision by developers
Park Provision by city council
Population density (100,00/km2)
Distance to Yokohama centre (km)Distance to Tokyo centre (km)2nd Quartile of population
characteristics (%) at baseline
3rd Quartile of population
characteristics (%) at baseline
4th Quartile of population
characteristics (%) at baseline
2nd Quartile of park area
in previous year
3rd Quartile of park area
in previous year
4th Quartile of park area
in previous year

(1988-2005)
95% CIβ0.46- 2.72, 3.65
- 0.17- 1.27, 0.93
- 1.05- 2.12, 0.02
0.26
- 1.00, 1.52
0.06
- 0.09, 0.21
0.28**
0.20, 0.36
0.28
- 1.20, 1.61

Change in pensioners (%)(1993-2005)(1998-2005)
95% CI
95% CIββ- 1.52- 4.22, 1.18 - 3.27*- 5.78, - 0.76
- 0.29- 1.26, 0.67
0.14
- 0.79, 1.07
- 0.39- 1.28, 0.51
0.46
- 0.40, 1.31
- 0.56- 1.67, 0.55
0.09
- 0.89, 1.07
0.17*
0.04, 0.29
0.26**
0.14, 0.37
0.21**
0.14, 0.28
0.10**
0.04, 0.17
1.64*
0.40, 2.88
0.56
- 0.55, 1.67

Change in professional and managerial workers (%)(1988-2005)(1993-2005)(1998-2005)
95% CI
95% CI
95% CIβββ
6.41** 4.08, 8.47
3.44** 1.72, 5.17
- 0.06- 1.26, 1.14
0.13
- 0.73, 0.98
- 0.14- 0.76, 0.49
- 0.05- 0.50, 0.40
1.31** 0.48, 2.13
0.70*
0.11, 1.29
- 0.003 - 0.42, 0.41
- 1.52** - 2.50, - 0.54 - 0.70
- 1.43, 0.03
- 0.12- 0.60, 0.35
- 0.09- 0.21, 0.03
- 0.06- 0.14, 0.02
- 0.02- 0.08, 0.03
- 0.09** - 0.15, - 0.02 - 0.08** - 0.13, - 0.04 - 0.01
- 0.04, 0.03
- 2.18** - 3.30, - 1.07 - 0.99* - 1.82, - 0.16 - 0.09
- 0.63, 0.45

0.50

- 1.82, 0.98

1.71**

0.48, 2.93

1.16

- 0.01, 2.32

- 3.65**- 4.79, - 2.50

- 1.82**- 2.65, - 1.00

- 0.58*- 1.13, - 0.03

1.26

- 3.46, 0.41

- 0.13- 1.45, 1.20

0.28

- 0.92, 1.49

- 6.69**- 7.87, - 5.52

- 3.35**- 4.24, - 2.46

- 0.70*- 1.25, - 0.15

0.20

- 1.18, 1.74

- 0.12- 1.41, 1.18

0.27

- 0.85, 1.38

- 0.98- 2.12, 0.16

- 0.04- 0.90, 0.82

0.17

- 0.38, 0.71

- 0.42- 1.01, 2.01

- 0.06- 1.32, 1.20

0.62

- 0.50, 1.73

- 0.61- 1.79, 0.57

- 0.06- 0.91, 0.80

0.12

- 0.42, 0.66

- 1.93*- 0.16, 2.69

1.27*

0.05, 2.50

0.60

- 0.49, 1.69

- 0.02- 1.16, 1.12

- 0.10- 0.95, 0.74

0.37

- 0.17, 0.90

N
Adjusted R Square
95% CI = 95% confidential interval

353
0.158

355
0.187
**: P < 0.01 *: P < 0.05

361
0.086

4

353
0.388

355
0.234

361
0.006

Table 5. Result of hedonic pricing models for natural log of land price and natural log ofdetached house price(Constant)
Ground area (m2)
Floor space (m2)
Width of front road (m)Private road dummy
Residential zoning dummySouth-facing dummy
Reinforced concrete dummyProfessional and managerial workers (%)
Distance to Yokohama centre (km)Distance to Tokyo centre (km)Distance to elementary school (km)Travel time to closest rail station (min)Cross term between bus using dummy
and travel time to closest rail station
2nd quartile of park area
3rd quartile of park area
4th quartile of park area
Year 2000 dummyYear 2005 dummyMarket reservation time (month)Land price modelβ
95% CI
3.404**
3.343, 3.466
0.001**
0.001, 0.001

Property price modelβ
95% CI3.437**
3.415, 3.458
Excluded

No Info
0.011**-0.027**0.023**
0.016**No Info
0.007**
0.002*-0.007**-0.021*-0.004**-0.002**0.003**
0.002**-0.022**0.027**
NS-0.036**0.005**
0.002**-0.004**NS-0.003**-0.001**0.003, 0.003
0.001, 0.002-0.025, -0.019
0.022, 0.031

0.003
0.013**
0.022**-0.087**-0.155**0.002**-0.001, 0.006
0.01, 0.017
0.019, 0.025-0.09, -0.084-0.158, -0.152
0.002, 0.002
26486
0.612

0.01, 0.012-0.036, -0.018
0.009, 0.036
0.005, 0.027
0.006, 0.008
0.0002, 0.004-0.008, -0.005-0.038, -0.005-0.005, -0.003-0.002, -0.001

0.021**
0.024**
0.026**-0.075**-0.14**
NS

0.012, 0.03
0.014, 0.033
0.016, 0.036-0.083, -0.067-0.148, -0.131
5828
0.651

N
Adjusted R square-0.047, -0.024
0.005, 0.005
0.001, 0.003-0.005, -0.003-0.003, -0.002-0.001, -0.001

95% CI = 95% confidential interval**: P < 0.01 *: P < 0.05 NS: No statistical significanceExcluded: excluded variables to avoid multi-collinearity

No Info: no information about the variable was available for land parcel data
- 17 dummy variables of wards were incorporated into the model, but the results of them areomitted from the table for brevity.

54. Discussion and conclusion

By conducting a case study of Yokohama, we used longitudinal modelling to identify
the processes potentially responsible for generating environmental equity in park
accessibility. First, we found that a strong association existed between inequity in park
accessibility and affluence over the past 18 years in the city. We also observed that inmore affluent communities and those with lower percentages of pensioners, developers
tended to build more parks, although they are likely to be smaller than those built by thecity authorities. Nevertheless, the long term, the cumulative effect of thedisproportionate siting of parks built by developers over several decades may increase
the disparity. Interestingly, the development of parks by the city council was found to be
associated with a subsequent rise in the affluent population in the area, although theeffect sizes were small, at least within the 15 year timespan studied. No such effect wasobserved in the case of parks built by developers. Whilst our hedonic pricing model
indicated that park provision may increase land and property prices, which may amplify
the existing inequity in park accessibility, placement of parks is thus observed to havelittle effect on subsequent change in population characteristics in the short to mediumterm.

Our original concern was that unequal political power between different social groups
may cause disproportionate park provision between communities (Boone et al 2009,
Talen 1998); however, it was evident that the city authority provides parks according topre-existing levels of park provision rather than population characteristics across areas.

6Other authors have noted that the principal motivation of developers is profit
maximization (Maruani and Amit-Cohen 2011), and indeed we found that developers
tend to build parks in socially advantaged areas, with their behavior being market driven
rather than a result of the political influence of the local people as such areas are
attractive for the consumers of development plans (Robison and Robinson 1986). In
addition, we found that developers are likely to choose areas with a cheaper land prices
to build parks, a likely consequence of the nature of their business.

Considering our results, we suggest several policy implications for remedies towards
observed inequities in park accessibility. Perhaps the most important and effective
remediation measure is the direct placement of parks by the city council in sociallydisadvantaged areas with limited parks. As we observed that park provision has little, orat least slow, effects on the reallocation of population characteristics, we suspect thiswould not act to drive out disadvantaged residents in the long-term. Nevertheless, it isimportant to remember that incorporating equity issues into the decision-making process
may increase cost of that process (Talen 1998). For example, if the city council
prioritize park provision in socially deprived communities with limited parks,
advantaged groups who are more likely to be politically empowered may take action
against them. Since private developers are motivated by profit maximization behavior,
they can be responsive to economic incentives. Policies regarding taxation and subsidies
therefore have the potential to facilitate and direct park provision from this source(Maruani and Amit-Cohen 2011, Alberini et al. 2005). The provision of bond funds andother legislation to encourage park siting by private developers in disadvantaged areas7may also have a role to play (Wolch et al. 2005).

Our study has a number of strengths and weaknesses. Some authors have mentioned thatthe limited number of longitudinal studies in the equity field is a result of the limited
availability of historical data (Mohai 2008, Saha and Mohai 2005, Liu 2001); historical
data on both population and environmental quality is sometimes not digitised orinconsistent with contemporary information, and the boundaries of spatial units forwhich it is available can change. A strength of our work is thus the use of grid-based
census data that circumvented the problems of boundary change. Furthermore theproduction of maps of park provision meant we were able to examine changes in parkprovision over a long period of time.

Although many previous studies have been conducted to investigate residential sorting
processes (see Tiebout 1956, Epple et al. 2001, Calabrese et al. 2006), which support
our migration hypothesis, the quality of data available to us compared to that used inmuch previous work is a significant strength of our study. In particular, we had adetailed and spatially referenced dataset on property and land prices and we made use ofadvanced GIS techniques in order to produce a number of novel measures of public
good provision that varied over time around individual properties.

In terms of weaknesses, this research focused on just one municipal area, the city of
Yokohama, and as a consequence, we could not incorporate the effect of different
revenue-expenditure patterns on people’s migration because residents of Yokohama pay
uniform residential tax no matter where they live within the city. Our analysis focused8

on just two social groups; the elderly and the poor. Children are another potentiallydisadvantaged group amongst whom access to parks may be particularly important(Boone et al. 2009), although we chose to focus on the elderly here as they are most
likely to be living in conditions of poverty. In addition the presence of elderly
populations is strongly negatively correlated with presence of children according to theJapanese census, making it difficult to separate out effects. We also examined measuresof percentage population composition, rather than absolute numbers of people, although
we question if an inequity affecting a greater number of individuals could ethically bedeemed ‘more serious’. Nevertheless, further work examining a wider range of
populations would be able to identify the relative contribution of the different groups tooverall inequities.

A further limitation is that, due to the availability of data, we were forced to focus on a
15 year time window for follow-up. It may be that changes in population characteristics
post park provision would take longer than this, and a more dramatic change of
population may happen within, for example, more than a half century (see Cutler et al.
1999). Consequently we could describe the process of population move-in as slow,
albeit potentially present. Our results are based on an amalgamation of years andassociations may differ over time. However, to test our findings for robustness, we ran
models separately for each year (1995, 2000 and 2005) and found that associations withpark accessibility remained positive and statistically significant in each time period.

Whilst we examined a wide range of explanatory variables we were not able to measure
all characteristics of the environment that may cause the changes in population

9

characteristics and in land and property prices we observed. For example otherenvironmental improvements may have taken place that we did not measure, and theintroduction of environmental disamenities such as hazardous waste sites, may haveoccurred. Because we have conducted a large number of statistical tests, some of thesignificant associations we observed may be due to chance. The fact that Japanesecensus data was only available for 5 year periods meant that we were not able toinvestigate changes in population at a finer temporal resolution and our analysis cannot
detect changes that occurred very shortly after parks were provided. Nevertheless, this
temporal resolution improves on many countries where only a decennial census isavailable. Finally, we focused solely on park provision, whilst other attributes of parks,
such as the facilities they provide, may also affect their value to society.

Although very little is known about environmental equity in Japan, we found evidence
inequity in park accessibility in Yokohama. This finding cannot allow us to speculate as
to whether similar disparities exist in other areas, both within Japan and internationally.
However our work presents methodological framework that can be applied in othercontexts. Furthermore, from a policy perspective, we would suggest identifying
different roles, and potential remediation measures, for both private developers andlocal authorities will be important whatever the context. To our knowledge, this study is
one of the first attempts to test the potential causal hypotheses of amenity accessibility
from an equity perspective. We hope it may assist in the development of remediation
policy, as well as improving our understanding of the underlying process that generateinequity.

10

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