Housing demand forecast based on income section using model tree technique - Seon Lim, Hyoung; Hyun Choi, Sang (International Journal of Engineering and Technology, 2018)
Background/Objectives: Mankiw and Weil modified model, which is mainly used in the field of housing demand, has the problem that the added variable has no linear relationship with the age-specific house demand.Methods/Statistical analysis: In this research, we tried to complement the existing model by proposing aM-W modified model utilizing the Model tree technique. In addition, many poor people need another analysis that understands the characteristics to live in abnormal houses. And, we tried to avoid this problem by reflecting income section. We compare the performance with existing models using the 2005 and 2010 Population and Housing Cencus data.Findings: First, the error rate of the M - W modified model is greatly affected by the extreme poverty class and the low income class. Second, overall the performance of the model tree dominates, the performance has further improved to produce more of the nodes.In the middle class in which five nodes were created, the error rate decreased by 89%, and the correlation coefficient increased by 0.2566 with 0.0490.Third, it is more accurate to use the "total of income section predicted values" rather than the existing "entire section predicted value". Fourth, in order to express an accurate section error, we propose to judge "not the total of income section errors" but "total absolute value of income section error".Improvements/Applications: In this research, there is a limitation that generalization of results is inappropriate. For further research, it is considered appropriate to apply the Random forest method to generalize the results.Â