布福德英文论文---房价线性回归分析

2021年1月19日发(作者：财源滚滚)


The distribution of educational resources in
Beijing city and the housing prices


Abstract
：
House price is not only affected by national macroeconomic policy, but also affected by
the
public
facilities
and
the
environment
around.
The
equilibrium
distribution
of
education
resource result in house price fluctuation. That is not equity and widen the gap between the rich
and the poor. We research the factors affecting the house price of Bei
jing’ key schools, r
esult point
that
school
district
house
price
is
13.8%
higher
than
that
of
non-school
district
house
having
similar
conditions.
By
controlling
other
public
resources,
like
subway
station,
park
and
kindergarten, and itself property, like house age, greening rate, plot ratio, result suggest that school
district house in Haidian and Chaoyang have premium of 31%. Meanwhile, they have premium of
23% totally. The result is, different house price reflect inequality of
Beijing’s
education resources,
and
most
part
of
high
quality
resources
distribute
in
central
area.
These
spatial
pattern
is
unreasonable, reducing the utilization of high quality public resources, and resulting in sharp rise
of house price in the central area, lastly, expanding wealth gap. So the government should enhance
quality of education and improve traffic efficiency. Through these measures, we can reach these
goals: the suburbs improving its attractiveness, population density of Beijing decreasing, and more
importantly, public resources distributing equality.
Keywords
: house price; public resource; factors; inequality; population density


uction

Real estate is one of the most important parts of the economy in our country, the price rise is the
result of multiple factors. The quality of public resources is an important factor to affect the price
of housing, which is especially important in the teaching quality of residential buildings.

The
education
resources
has
always
been
an
important
impact
on
housing
prices,
for
example,
according to the study, in 2004, in the transition process from a poor school in London to a top
school, house prices have an increase of 61000 pounds. Early studies such as Oates (1969) on the
cost of real estate prices and public schools spending on each students, he found that they have a
significant positive correlation, and the negative effect of house property tax on housing prices can
be offset if they spend the money to the school, the study shows that residents tend to pay higher
prices to better public services. And Fullerton Rosen (1977) believes that the use of each student's
spending in public schools as a variable is not very appropriate, because the cost of education, and
other factors are not easy and accurate, so they use the average performance of students on behalf
of the school quality, the results show that the data and prices are significantly positive correlation.
However, it is not very good to solve the problem, in order to better quantification the quality of
school
teaching,
Lucas
Figlio
(2004)
introduced
the
school
quality
rating
report
the
state
government issued as a supplement to the students' average test score, the study shows that when




introduced
school
quality
rating
system,
the
price
will
change
significantly,
but
over
time,
this
effect is rapidly decreasing, and only in the first time, it play a greater role. Because of the impact
of
housing
prices
is
not
just
the
school
teaching
quality,
which
leads
to
missing
variables,
the
existence of this error will affect the accuracy of the results of the regression.

In
recent
years,
the
school
district
housing
phenomenon
in
China
has
become
more
and
more
noticeable
from
the
price
point
of
view,
for
example

Langya
Road
Primary
School,
Lixue
primary school, Lhasa Road Primary School are three elite schools in Nanjing,, from 2008 to April
2009 , prices rose quickly, the school district housing prices are more than 3000 yuan/m2 than the
average price, even in 2009 , housing prices generally fell 8.9%, the school district housing prices
in
April
is
still
stable.
The
mechanism
by
which
the
residents
choose
to
choose
their
place
of
residence to influence the housing price is likely to exist in China. If this mechanism exists, it will
reflect the quality of education in a part of the housing price. Regardless of the economic situation
is
good
or
bad,
the
school
district
housing
prices
will
not
follow
the
economic
law.
Research
shows
that,
some
famous
primary
school
has
a
significant
effect
on
the
school
district
housing
premium.

This
paper
focuses
on
the
impact
of
key
primary
school
on
housing
prices,
thus
revealing
the
unreasonable distribution of Beijing education resources, and from the perspective of optimizing
the
educational
space
pattern,
promoting
equal
opportunities
for
education
and
reducing
population density of Beijing city, we have discussed the problem of the development of Beijing
city.

In this paper, we have four aspects of improvement based on the previous research, 1, the
data is no longer linear distance for the parameters, but the use of the shortest walking distance to
make
the
analysis
more
close
to
reality.
2,
this
paper
studies
the
Haidian
District
Chaoyang
District,
Xicheng
District
and
Dongcheng
District,
it
is
different
from
the
common
use
of
Tiananmen
as
the
center
of
the
method
to
control
the
degree
of
prosperity.
3,
the
selection
of
primary
school
in
Beijing
City
is
the
most
famous
ones.
rather
than
the
Beijing
Municipal
Education
Commission’s
approval.
4,
the

data
is
second-hand
housing
transaction
data,
so
it
is
more reliable.

description and research methods
Based on the existing research, this paper uses the data of Beijing city housing transaction, and
using the model to control the relevant variables, we want to get a effective regression results, and


analyze the effects of education quality, transportation facilities and environmental landscape on
the house price.


division of the school district and the school district house
Compulsory education law of China established the the enrollment policy that Chinese came near
to the entrance , namely for every primary school, there is a scribe area, and within the scope of
the
scribe
area,
children
have
an
exemption
entrance
treatment.
So,
generally
speaking,
each
district
has
a
corresponding
primary
school.
This
may
has
promoted
the
equality
of
education
opportunity,
however,
there
is
a
difference
in
the
quality
of
primary
school,
relatively
speaking




some school’s quality of education is far higher t
han ordinary by the government's priority support.
Although
the
government
has
abolished
the
system
of
dividing
the
primary
school
in
2000,
the
social prestige of the primary school has been established, and the status of the primary school is
increasing.

This paper selects 19 primary schools in Beijing city as a data source, table 1 is recognized as a
key primary school list.

Table 1 list of key primary schools

Beijing first experimental primary school, Beijing No.2 experimental primary
Xicheng
District
school,
Beijing
Xicheng
District
huangchengden
primary
school,
Xicheng
District,
Peking
City,
Yu
Ming
primary
school,
Beijing
City,
Xicheng
Qu
Yuxiang
elementary
school,
Beijing
Yucai
elementary
school,
struggle
elementary school
Primary
school
affiliated
to
Beijing
Haidian
District
Experimental
Primary
Haidian
Distric
School,
Beijing,
Haidian
District,
Zhongguancun
No.1
Primary
School,
Haidian
District,
Beijing
Zhongguancun
No.2
primary
school,
Beijing,
Haidian
District,
ZhongGuanCun
the
third
willow
branch,
Beijing
Zhongguancun
No.3
primary
school
campus
in
Zhongguancun,
Renmin
University of China
The
first
Beijing
Normal
School
Affiliated
elementary
school,
Beijing
Dongcheng
District
Jingshan
School
North
Primary
School
Department,
Beijing
City
Experimental
Primary
School,
Dengshikou
primary
school,
Dongcheng
District, Beijing, Dongcheng District, Peking City, historians primary
Beijing fangcaode International School
Chaoyang
District










Figure 1 primary distribution map of Beijing City

Figure 1 is a primary distribution map of Beijing city. As shown in Figure 1, the primary school in
Beijing
is
not
in
uniform
distribution,
they
are
concentrated
in
the
comparison
of
the
city
of
Haidian District, Chaoyang District, Dongcheng District and Xicheng District. In fact, the famous
primary
schools
are
mostly
distributed
in
these
four
areas.
Beijing
Municipal
Education
Commission
in
1950s
has
announced
the
list
of
40
municipal
primary
schools,
today,
these
primary schools are still the best primary school in Beijing. And has been widely recognized by
the community, and the vast majority of these primary schools are in the above four districts.

g data
From Figure 1, we can see that the geographical distribution of Beijing city is basically a center to
the surrounding Tiananmen, from a link to the rings, are built around the Tiananmen. We collected
a total of 19 Beijing municipal key primary school district scribing a total of 120 residential and
112 non cshool district data. Variables include second-hand housing average price, , age (minus
the 2015 year built), volume rate, green rate, distance to the center of the city(in KM), distance to
the subway
station(in
KM),,
distance to
the
kindergarten(in
KM),distance
to
shopping
malls(in
KM),
distance to
thepark(in
KM),
.
And
introduce
some
dummy
variables,
such
as
a
small
primary school district is 1, otherwise the value is 0.

Table
2
is
a
description
of
the
collected
cell
data.
As
shown
in
Table
2,
the
average
price
of
second-hand
housing
is
54387,
the
mean
distance
from
the
downtown
is
7.21
km,
the
average
house age is 15.67 years, the average rate of volume is 2.68, average greening rate is 32%, and the
mean distance from the nearest subway station is 0.87 km, to the nearest kindergarten flat were




1.24 km , average distance to the nearest mall is 0.95 km, the median distance to the nearest park
is 1.22 km, the school district room price is 13267yuan/m2 higher than the average, and it is about
27.9%.


Table 2 cell description
Average price





All sample






School district room




Non school district room
Prices












54387.84












60870.37















47603.5
Downtown distance

7.21
















6.79



















7.59
Age













15.67















17.41


















13.86
Volume ratio






2.68
















2.42



















2.98
Greening rate
0.32
















0.26



















0.33
Distance

to the

subway station



0.87
















0.85



















0.89
distance to kindergarten 1.24
















1.21



















1.27
distance to the mall


0.95
















0.95



















0.95
Distance to the park
1.22
















0.99



















1.06

establishment the model
In this paper, we use the characteristic price method to analyze the house price, the following is
the log linear model used in this paper:

















（
1
）

Among them, X1i means the property of the District, including the age, the volume of residential,
greening
rate,
etc..
X2i
represent
distance
variables,
including
distance
to
the
subway
station,
distance
to
the
nursery,
distance
to
the
mall
and
the
distance
to
the
park,
Pschool
is
a
dummy
variable, used to indicate whether the district is the school district room.

cal analysis
g city house price analysis
Table
3
is
the
result
of
the
overall
regression
of
the
District
of
all
districts
in
the
city.
The
regression includes square, hospital, park, subway station, high school, elementary school, and so
on. The results show that in the 5% confidence level, the distance to the Beijing city center has a
negative effect, while the subway station and primary school have a positive effect on prices; in
the
10%
confidence
level,
the
park
is
statistically
significant,
and
square,
middle
school
and
hospital
statistics
is
not
significant.
It
is
worth
noting
that
the
hospital's
coefficient
means
a
negative effect in a certain sense, The reason why the square is not significant, it may be that as a
leisure place, such as food Square, shopping plaza , they can not provide a great attraction.

Table 3 data analysis of Beijing City
Parameter


estimate

T value
Pr(>|t|)


distance to Tiananmen

square in a mile
square in a mile
Park in a mile
Subway

in a mile
Middle school in a mile
-0.451
0.007
-0.042
0.049
0.161
-0.031
0.025
0.038
0.040
0.035
0.041
0.036
0.055
0.094
-17.498
0.186
-1.049
1.368
3.865
-0.874
3.191
122.997
< 2e-16***
0.852
0.294
0.172
0.000**
0.382
0.001**
< 2e-16***
key
primary
school
in
a
0.177
mile
Constant term
11.673
Signif. codes:

0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Multiple R-squared:

0.7013
F-statistic: 120.8 on 7 and 360 DF


In fact, table 3 is the result of the regression results of the overall data of Beijing, it can only be a
rough display of the overall situation. In fact, within the second ring even within the third ring,
most
of
the
key
primary
schools
located
in
the
vicinity
of
several
cities
around
the
city,
the
majority
of
the
properties
have
advantages
of
hospital
resources,
one
to
many
subway
stations,
many
secondary
schools
and
more
primary
schools. when
consumers
purchase
a
house,the
subway,
hospitals,
secondary
schools,
primary
schools
and
other
factors
will
be
considered,
resulting
in
a
higher
real
estate
prices.
In
order
to
further
analyze
the
role
of
the
subway station, hospital, park, middle school in promoting the rise in housing prices, we analyze
the data of each link, to observe the information of each link. In fact, the design of the Beijing link
can be seen as the Tiananmen as the center, so the link can also be seen as a symbol of the degree
of regional prosperity.

As shown in Table 4, the results show that near the park the price is 2.4% lower than estate far
away from the park, and price is 9.5% higher when it is a school district room,it is 14.4% higher
when the house is near a park from line 2 to line 3, and more than 22.4% higher when it is near the
subway station, and
13.42% higher than other properties when it is a school district room. And it
is 15.6% higher than the other properties when the house is near the park, 23.4% higher of school
district room from line 3 to line 4. And so as line 5 to line6.

Table 4 regression analysis
Parameter
Line2
Line3
Line4
Line5
Line6
Square
Hospital
Park


Estimate
0.902



0.781



0.790



0.750



0.391


0.008

-0.057
0.004
Std. Error
0.198



0.348



0.181



0.094



0.067


0.040


0.043
0.066
t value
4.552

2.242

4.348

7.920

5.782

0.199


-1.323


0.069


Pr(>|t|)


7.37e-06***

0.025*
1.81e-05***


3.30e-14***
1.66e-08***
0.842

0.186

0.944



Subway
Middle school
Primary school
Line2*park
Line2*pschool
Line3*park
Line3*subway
Line3*pschool
Line4* park
Line4*subway
Line4*pschool
Line5*park
Line5*subway
Line6*park
Line6*subway
Constant term
0.452
-0.014
0.236
-0.028
-0.141
0.139
-0.228
-0.102
0.151
-0.332
-0.004
-0.021
-0.212
0.011
-0.354
9.937

0.110


0.038
0.148
0.173
0.203
0.326


0.184
0.193
0.144
0.169
0.177
0.127
0.148
0.089
0.126
0.046
4.105

-0.362

1.596


-0.166


-0.696


0.427

-1.240


-0.530



1.052


-1.956

-0.024
-0.167
-1.437

0.133
-2.795
214.588
5.05e-05***
0.717


0.111
0.868

0.486
0.669
0.215
0.596

0.293

0.051*
0.980
0.867
0.151


0.894
0.005*
< 2e-16***
Signif. codes:

0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Multiple R-squared:

0.694

F-statistic: 34.02 on 23 and 345 DF


3.2 four district house price analysis
To
more
accurate
understanding
of
the
various
regions,
we
distinguish
between
Haidian
and
Chaoyang
as
a
group,
Dongcheng
and
Xicheng
as
a
group,
in
fact,
because
the
economic
situation
in
Dongcheng
District
and
Xicheng
District
is
more
similar,
the
same
way
Chaoyang
District and Haidian District economic conditions. From the map, the center of Beijing is indeed
Tiananmen, but the northern part of Beijing's business is more prosperous than the southern part of
Beijing,so Beijing city in this area is not symmetrical distribution.

Table 5 four area analysis

four district
Model
Variable
(
ⅰ
)
(
ⅱ
)
(
ⅲ
)
(
ⅳ
)
School

0.2684
（
14347.056
）

0.229659
（
12504.3
）

0.248
（
13373.63
）

district room
0.237777
（

12857.4
）
8.455( 8.792)
9.438
（


9.799
）

9.859
（

10.314
）

8.916
（
9.103
）

t-value
Characteristic
one
No
Yes
No
Yes
Characteristic

two
No
No
Yes
Yes
Distance
Yes
No
Yes
Yes