The educational environment affects residential mobility as a significant choice element, and the changing of educational policy has a certain level of influence on the overall housing market like the price of house, the trading volume of housing, and...
The educational environment affects residential mobility as a significant choice element, and the changing of educational policy has a certain level of influence on the overall housing market like the price of house, the trading volume of housing, and so on. Recently, various policies(selection of high school, free semester) are implemented, and these modifications of policy will be a new variable to the housing market, finally the parents who have a school age children should react sensitively.
After the execution of selection of high school 2010, the parents who have elementary and middle school age children make an effort to let their children proceed to specialized high schools or autonomous private high schools, but now the allocation of elementary and middle schools is made it a rule to short distance allocation. Thus, with the district elementary and middle school increasingly important, their children's age of which household that has a residential mobility plan for educational purpose should affect primarily to decide living quarter.
Analysis was set to binary logistic regression model to estimate the factors affecting newlyweds occupied form to account for all the independent variables.
This research is the analysis of the factors which affect on residential mobility plan for educational reasons, concentrated on the age of children and local variable. Using Data is the actual housing investigation 2014 carried by Ministry of Land, Infrastructure and Transport, on 2014, and we focus on 10,633 households, which have their children, among the 20,205 total number of subjects of family. the dependent variable is the move or not that the residential mobility plan for educational purpose, independent variable is divided to the economical characteristics of family, the characteristics of a householder, the residential characteristics, the local characteristics, and the characteristics of the children. The method of analysis is the of binary logistic regression.
The results, of which the analysis of actual proof of residential mobility plan for educational reasons, are as follows. Divided the subjects into three categories these are overall households, 1-child households, and 2 or more children households. As a result, if a subject has higher constant income, if householder of subject is the forties, and if a subject has been living rental house, the possibility of having the residential mobility plan was higher. Especially, at the local variable, the possibility to move to good middle school district is higher than others, and two or more children households have more probability to make a residential mobility plan for educational purpose than one child households. Also the younger age of their children, and the parents who have elementary school aged children, the more possibility shown to have residential mobility plan.
Therefore we should infer that the household which has the residential mobility plan for educational purpose is largely affected by constant income, the age of household, the age of children, and the area prepared for residential moving. By doing so, we are able to appraise the policies for solving the inequality of education, henceforth, we expect that this research will be a significant data for studying later policies for improving educational environment.