Housing demand forecast based on income section using model tree technique

  • Authors

    • Hyoung Seon Lim
    • Sang Hyun Choi
    2018-06-08
    https://doi.org/10.14419/ijet.v7i2.33.13883
  • Housing Demand Forecast, Mankiw and Weil, Model Tree, Income Section, Population and Housing Cencus.

  • Abstract

    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.

     

  • References

    1. [1] http://kostat.go.kr/portal/korea/index.action.

      [2] Mankiw, N. G., & Weil, D. N., The baby boom, the baby bust, and the housing market. Regional science and urban economics, 1989, 19(2), pp. 235-258.

      [3] Swan, C, Demography and the demand for housing A reinterpretation of the Mankiw-Weil demand variable. Regional Science and Urban Economics, 1995. 25(1), pp. 41-58.

      [4] Chung Eui-Chul, Cho Sung-Jin, Demographic Changes and Long-term Housing Demand in Korea,Journal of Korea Planning Association, 2005, 40(3), pp. 37-46.

      [5] Choi Seong-ho, Lee Chang-moo, Non-Linear Mankiw-Weil Model on Housing Demand -The case of Seoul Metropolitan Area -, Journal of the Korea Real Estate Analysis Association, 2009,15(2), pp. 117-130.

      [6] Kim Mikyoung, Lee Changmoo, Forecasting Distribution of Dwelling Size Using Quantile Regression Model, Journal of the Korea Real Estate Analysis Association, 2015, 21 (3), pp. 45-62.

      [7] Quinlan, J. R., C4. 5: Programming for machine learning, Morgan Kauffmann, 1993, 38.

      [8] Wang, Y., & Witten, I. H., Induction of model trees for predicting continuous classes, 1996.

      [9] Hong In-ok, Housing actual condition and support plan of housing poor, Korea Research Institute For Human Settlements, 2004,PLANNING AND POLICY, pp. 32-40 http://www.dbpia.co.kr/Article/NODE01168209.

      [10] http://www.molit.go.kr/portal.do.

      [11] McDonald, J. F., Moffitt, R. A, The uses of Tobit analysis. The review of economics and statistics, 1980, pp. 318-321.

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  • How to Cite

    Seon Lim, H., & Hyun Choi, S. (2018). Housing demand forecast based on income section using model tree technique. International Journal of Engineering & Technology, 7(2.33), 196-190. https://doi.org/10.14419/ijet.v7i2.33.13883

    Received date: 2018-06-08

    Accepted date: 2018-06-08

    Published date: 2018-06-08