ABSTRACT
Along with the reform and open-up policy，China’s economic develops rapidly. And large-scale of population flows from rural to urban and among urban. Meanwhile，the Population urbanization rate is rising from 36.09% in 2000 to 52.6% in 2012. And one of the principal goals of the urbanization is to turn migrants to new citizens，which means equalization of public services. Particularly，as one of the largest immigrant cities for new labors，Beijing encounters huge pressure in equally providing service of compulsory education to its population.
From this practical problem，this article will focus on the following two questions：
Firstly，forecast the population of basic education stage during in Beijing Municipality and its adherent districts and counties. For this reason，the method would be verified first. Secondly，evaluate the potential demand of Beijing Municipality and its adherent districts and counties for necessarily resources of basic education stage.
Forecasting methods are the premise to predict. Improved compulsory education population and educational resources demand forecasting methods will help the accuracy and scientific of the forecast. Meanwhile forecast is the basis for planning and policy making.
My study obtains original data via following channels：The data of Beijing in the fifth and the sixth national population census；the data from “Beijing Statistical Yearbook” （2000-2017）；the statistical data openly published in the official website of Beijing Municipal Education Commission，which in detail refers to the development of education in Beijing and its affiliated districts and counties during 2009-2017，and “Announcement of Financial Statement in Education of Beijing” （2000-2016）.
Cohort Component Method （CCM） is applied to measure the population of basic education stage. In projection 1，Leslie’s matrix model is further improved to the three life tables system. Meanwhile，I also argue with the concrete method in figuring life changes in birth，death，and migration. In terms of measuring the potential demanded of educational resource，I take use of scenario analysis to clarify the possible magnitude of human resources；and using average cost to predict future costs of school infrastructure；and using fixed rate to assess future expenditures which is also compared with GDP. In projection 2，I used one life table system of Leslie’s matrix model，and considered the impacts of Universal Two-child Policy.
Ultimately，I find that，firstly，in the next 10 years，the population of primary school will reach 1.025 million as its peak in 2021. The summit of preschool education comes to 552.8 thousands in 2021. Meanwhile，the summit of Junior high school comes to 494.6 thousands in 2024，and high school comes to 445.1 thousands in 2021. Compared with projections of the low fertility and high fertility scenarios，the Universal Two-child Policy has more impact on pre-school and primary school. The time to reach peak and increase level of each district are not the same，and the districts with larger increase when reach their peak should be focused.
Secondly，when comes to the allocation about educational resources：In terms of teacher demand，in the peak year，a large number of teachers should be recruited. For districts，when the demand of teachers is declining，the ratio of students to teachers can be adjusted to improve the attention of teachers to each student. In terms of the construction area of school buildings，the trend of compulsory education is basically the same as the trend of the school-age population. The peak year has a large gap between 2017. In terms of demands of education funding，in the peak year the demand of primary school is 2.1 times of the demand in 2017，and the demand for junior high school in the peak year is three times of the demand in 2017.
My study makes contributions in three aspects：Firstly，improve the methods in measuring the number of future students of compulsory education and the possible scale of needed resources，thus render the forecasting more scientific. Secondly，my measure on future students of compulsory education merely focuses on one city of Beijing and its subordinate districts and counties. Compared with previous studies concentrating into national or provincial level，my research level is not usually seen. Thirdly，combine the measure on potential students and possibly demanded resources of education together，which thus comprises a reference to similar measures of the whole country，or some other provinces，prefectures or counties.
Key words：Universal Two-child Policy；Forecasting in Education Population；Forecasting in Educational Resources Demands