This paper aims to empirically illuminate the reason of the positive relationship between housing price and trading volume, one of anomalies in real estate market which cannot be explained by traditional economic theory presuming the rationality of human being, from a standpoint of bounded rationality. Based on the micro survey data on housing consumption psychology collected from the first quarter of 2011 to the second quarter of 2015, it investigates the relationship between each respondent’s recognized and predicted scales of quarterly housing price change and its difference between housing owners (potential sellers) and renters (potential buyers) as well as its difference between the periods of price increase and decrease, employing the spline regression model. Three major findings are as follows. First, a positive relationship is found between the recognized and predicted scales of quarterly housing price change, implying that adaptive expectation prevails, compared to rational expectation. Second, wishful thinking is also detected because the owners (renters) predict relatively smaller (larger) decrease in the period of price depreciation, but larger (smaller) increase in the period of price appreciation. As the result the predicted scale of the owners is higher than that of the renters in both periods of price depreciation and appreciation, but the difference is relatively much larger when the price decreases than when it increases. This is the third and the most important finding that verifies the existence of loss aversion of sellers, which causes the asymmetry characterized by small (large) trading volume coupled with price decrease (increase).
Vacant houses can have a more serious impact on residents’ quality of life when they are spatially dense or when such conditions are fixated. Accordingly, this study examines the spatial clustering of vacant and abandoned houses and the fixation phenomenon in the clustered area through the case study of Iksan. The vacant and abandoned houses formed strong spatial clusters in the inner city of Iksan, and the clustered area showed characteristics such as physical vulnerability of housing and neighborhood environment, high percentage of elderly and low-income residents, and low real estate value. Also, in the clustered area, the vacant houses became more pronounced and multiplied as the occurrence diffused into adjacent areas. To draw the factors affecting the fixation of vacant houses, binary logistic regression was conducted and as a result, the characteristics of the parcels and location of those properties and the ratio of the elderly in the neighborhood present a statistically significant influence on fixation. The fixation process of vacant houses was found to occur in several vicious circles such as vulnerability of parcel and neighborhood environment, no transaction for long, difficulty in concluding a deal with owners, vulnerability of elderly owners, and indifference and helplessness of residents. This study shows implications for management and utilization of vacant houses in urban planning and suggests a useful analysis framework and strategies for the efficient management of vacant houses in small and medium-sized cities.
This study aims to estimate land-use changes in North Korea’s city after the unification through simulation. The simulation analysis consists of exploration of urban patterns, validation of simulated results, and analysis of the land-use changes in the future. The estimation accuracy of land use change was measured by polynomial regression analysis, decision tree analysis and support vector machine analysis. On this basis, suitable methodologies were selected for the modeling of the urban pattern search. The hybrid model uses the ‘C5.0’, a kind of decision tree algorithm and the ‘RBF kernel’, a kind of support vector machine algorithm. The land use change of North Korea’s city (Nampo City) was estimated based on this model. The scenario of newly constructing roads and railroad stations, and developing new urban areas was used in the simulation. The simulated results showed that the urban sprawl impact through improvement of traffic accessibility and the development of new urban areas could be linked to the region and other regions. This study could provide a strategic guidance for policy when the unification of Korea will be on the process.
The purpose of this study is to construct a pricing model for the store residence land for residential and non-residential mixed use in Jangyu New City in Gimhae, Gyeongsagnam-do and analyzed the physical and environmental characteristics expected to act differently according to the price level through quantile regression analysis. In its analysis, the study applied quantile regression using a 2-stage regression method by the spatial lag model which is a regression model reflecting spatial dependency. As a result of the analysis, regression analysis by spatial lag model was found to give better explanation and represent inherent characteristics of land well in quantile regression. Physical factors were found to have bigger effects on the store residence land for residential and non-residential mixed use than environmental factors, especially in high-price land. Store residence land is likely to reflect the characteristics of the use of non-residential real estate more than the environmental factors of residential real estate due to its possibility of commercial use. The spatial correlations appeared higher in the middle and high price quantile of store residence land and physical characteristics were more influential in this quantile. In the related industry, it is necessary to carefully consider the characteristics of different price level, and by doing so, to supply real estate which meets the needs of customers.
During last 10 years, the government tried to make public residential development in order to supply a large number of affordable housing. Most of public residential developments were built in green belt areas. Rapid urban development would promote land cover changes and lead to increase land surface temperature (LST). The purpose of this study is to examine the effects of public residential development projects on LST in Seoul, Korea. This study investigated LST change in 7 residential and urban development areas including districts of Sinnae 3, Sinjung 4, Naegok, Segok 2, Gangnam, Ogum, and Wirye. Landsat satellite image were used to calculate variation in LST from 2007 to 2017. The results show that most of districts have increased in standardized LST change. Especially, Wirye district experienced an average relative LST increase of 2.73℃. Moreover, the LST was also high in districts where the % Impervious Surface Area (%ISA) increased over the past 10 years. It is meaningful to suggest the direction of the plan considering the environmental aspect when the public residential and urban development project is implemented in the future.