An Analysis on Factors Affecting Residential Satisfaction by Housing Price Level -Focusing on Apartment, Hanoi, Vietnam

2019 ◽  
Vol 17 (4) ◽  
pp. 43-58
Author(s):  
Jung Sun Kim
2019 ◽  
Vol 12 (1) ◽  
pp. 32-61 ◽  
Author(s):  
Maher Asal

Purpose This paper aims to investigate the presence of a housing bubble using Swedish data from 1986Q1-2016Q4 by using various methods. Design/methodology/approach First, the authors use affordability indicators and asset-pricing approaches, including the price-to-income ratio, price-to-rent ratio and user cost, supplemented by a qualitative discussion of other factors affecting house prices. Second, the authors use cointegration techniques to compute the fundamental (or long-run) price, which is then compared with the actual price to test the degree of Sweden’s housing price bubble during the studied period. Third, they apply the univariate right-tailed unit root test procedure to capture bursting bubbles and to date-stamp bubbles. Findings The authors find evidence for rational housing bubbles with explosive behavioral components beginning in 2004. These bubbles do not continuously diverge but instead periodically revert to their fundamental value. However, the deviation is persistent, and without any policy correction, it takes decades for real house prices to return to equilibrium. Originality/value The policy implication is that monetary policy designed to contain mortgage demand and thereby prevent burst episodes in the housing market must address external imbalances, as revealed in real exchange rate undervaluation. It is unlikely that current policies will stop the rise of house prices, as the growth of mortgage credit, improvement in Sweden’s international competitiveness and the path of interest rates are much more important factors.


2021 ◽  
Vol 251 ◽  
pp. 03080
Author(s):  
Tang Haoning ◽  
Liang Xin

Ship equipment maintenance fee of the single standard funds under the influence of many factors, in order to analyse the ship maintenance fee standard for each single loading factors influence the size of paper from two aspects: the ship itself and using the environment of ship cost, displacement, use fixed number of year, the price level, service environment, the use frequency of six index quantification, the factors which influence on factors affecting the characteristics of the mutual influence and mutual restriction between the measures, using the index of conflict and contrast between the strength of give attention to two or more things CRITIC method for quantitative analysis. The results show that the six influencing factors are in order from large to small: price level, service life, service frequency, service environment, ship cost, displacement.


2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Qingqi Zhang

In this paper, the author first analyzes the major factors affecting housing prices with Spearman correlation coefficient, selects significant factors influencing general housing prices, and conducts a combined analysis algorithm. Then, the author establishes a multiple linear regression model for housing price prediction and applies the data set of real estate prices in Boston to test the method. Through the data analysis and test in this paper, it can be summarized that the multiple linear regression model can effectively predict and analyze the housing price to some extent, while the algorithm can still be improved through more advanced machine learning methods.


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