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
Link To Document :
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