英文论文房价线性回归分析.docx

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 Beijing’ key schools, result 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

1.Introduction

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.

2.data 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.

2.1.the 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 than 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 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
Xicheng District
Primary school affiliated to Beijing Haidian District Experimental Primary 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
Haidian Distric
The first Beijing Normal School Affiliated elementary school, Beijing Jingshan School North Primary School Department, Beijing City Experimental Primary School, Dengshikou primary school, Dongcheng District, Beijing, Dongcheng District, Peking City, historians primary
Dongcheng District
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.

2.2.housing 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

2.3.the 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.

3.empirical analysis
3.1.Beijing 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
Std.Error
T value
Pr(>|t|)
distance to Tiananmen
-0.451
0.025
-17.498
< 2e-16***
square in a mile
0.007
0.038
0.186
0.852
square in a mile
-0.042
0.040
-1.049
0.294
Park in a mile
0.049
0.035
1.368
0.172
Subway in a mile
0.161
0.041
3.865
0.000**
Middle school in a mile
-0.031
0.036
-0.874
0.382
key primary school in a mile
0.177
0.055
3.191
0.001**
Constant term
11.673
0.094
122.997
< 2e-16***
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
Estimate
Std. Error
t value
Pr(>|t|)
Line2
0.902
0.198
4.552
7.37e-06***
Line3
0.781
0.348
2.242
0.025*
Line4
0.790
0.181
4.348
1.81e-05***
Line5
0.750
0.094
7.920
3.30e-14***
Line6
0.391
0.067
5.782
1.66e-08***
Square
0.008
0.040
0.199
0.842
Hospital
-0.057
0.043
-1.323
0.186
Park
0.004
0.066
0.069
0.944
Subway
0.452
0.110
4.105
5.05e-05***
Middle school
-0.014
0