• DocumentCode
    3327396
  • Title

    Study on dynamic model and demonstration analysis for urban housing purchasing power measuring

  • Author

    Li Ai-hua ; Shi Yong

  • Author_Institution
    Sch. of Manage. Sci. & Eng., Central Univ. of Finance & Econ., Beijing
  • fYear
    2008
  • fDate
    10-12 Sept. 2008
  • Firstpage
    1803
  • Lastpage
    1810
  • Abstract
    Housing purchasing power measuring is an important issue for the housing guarantee decision making, which has been studied in the static way. However, the consumption structure and income are not changeless. Thus the dynamic model for urban housing purchasing power is proposed and the main idea is as follows. First, construct the income predicting model with the previous income by the least square method. Second, construct the consumption structure prediction model with differential function. Third, the model for urban resident housing purchasing power measuring has been proposed based on the hypothesis of random walking. At last demonstration analysis has been studied with the data set in Beijing from the year 1990 to the year 2005. And the differentiation between static model and dynamic model has been discussed.
  • Keywords
    least squares approximations; management science; power consumption; power measurement; consumption structure prediction model; decision making; income predicting model; least square method; random walking; urban housing purchasing power measuring; Conference management; Economic forecasting; Energy management; Financial management; Government; Least squares methods; Power generation economics; Power measurement; Predictive models; Technology management; demonstration; housing purchasing power; least square method; measuring; random walking;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Management Science and Engineering, 2008. ICMSE 2008. 15th Annual Conference Proceedings., International Conference on
  • Conference_Location
    Long Beach, CA
  • Print_ISBN
    978-1-4244-2387-3
  • Electronic_ISBN
    978-1-4244-2388-0
  • Type

    conf

  • DOI
    10.1109/ICMSE.2008.4669150
  • Filename
    4669150