• Land and Housing Review
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• v.7 no.2
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• pp.67-75
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• 2016

This research suggests improvement strategies for the problems of 'public housing supplied through the purchase of existing house' by understanding the situation of supply to lowest income class in Seoul where there are many demands. Due to the heavy housing expenditure burden, in spite of the fact that the needs for affordable housings are increasing, the number of 'public housing supplied through the purchase of existing house' which has been supplied to Seoul by LH & SH has decreased since 2009. It is caused by the low standard purchasing price set by government especially Seoul. Since 'the public housing supplied through the purchase of existing house' is targeted for indigenous inhabitants, different supply stocks among different regions cause equity problem. Generally regions with low income class are in short supply, on the contrary the supply is especially concentrated specific regions in outskirts of Seoul. The main reason of such new supply stagnation and regional concentration is the low standard purchasing price. Therefore, it is necessary to increase the government's standard price according to the actual transaction price. Also it is needed to associate actual transaction price's increasing rate with the government's standard price. The housing supply based on demands must be established. In addition, the provision of 'public housing supplied through the purchase of existing house' should be expanded to low-middle income inhabitants and low income youth in the regions where the supply of the affordable housing excess demands.

• The Journal of the Korea Contents Association
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• v.22 no.9
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• pp.252-259
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• 2022

In order to discuss the implications for demographic changes due to an aging society, this study sought to verify the effect of generational age with a focus on the case of the national housing scale transaction in Seoul Seocho-gu. For the result, variance and linear regression analysis, and when the analysis showed a significant correlation between age and transaction price, and corrected the trading region and year, it was also confirmed that the higher the age in most regions, the lower the trading price tendency. Based on the results of this analysis, efforts to improve the adequacy and fairness of pricing in trading cases, and the direction of policy change due to the aging of the population were discussed, and on the basis of this, we even proposed measures for the support of the policy authorities. In addition, the management condition of individual communal houses was an important factor in the sale and the lack of utilization of Internet-based platforms was expected to be the cause of the low price sale. However, due to the use of 2nd order data on real trading cases, the direction of subsequent research was presented together with respect to the limitations of not being able to control a wider variety of individual characteristics.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.1
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• pp.63-70
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• 2014

This study is to analyze impact of geography and timing on the real transactions prices of apartment complexes in Seoul using data provided by the Ministry of Land, Infrastructure and Transport. The average real transactions and location data of apartment complex was combined into the GIS data. First, the pattern of apartment real transaction price change by period and by area was analyzed by kriging, the one of the spatial interpolation technique. Second, to analyze the pattern of apartment market price change by administrative district(administrative 'Dong' unit), the average of market price per unit area was calculated and converted to Moran I value, which was used to analyze the clustering level of the real transaction price. Through the analysis, spatial-temporal distribution pattern can be found and the type of change can be forecasted. Therefore, this study can be referred as of the base data research for the housing or local policies. Also, the regional unbalanced apartment price can be presented by analyzing the vertical pattern of the change in the time series and the horizontal pattern of the change based on GIS.

• The Journal of the Korea Contents Association
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• v.15 no.6
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• pp.411-420
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• 2015

With the rapid increase in the price of house lease, a unique housing form in Korea, a serious social issue has been raised as to the use value of house lease and residence stability of the ordinary people. This study thus aimed to analyze the direct factors that affect lease guaranteed loan and market volatility in order to explore the right direction of financial policy to reduce housing burdens. To this end, the direct variables affecting house lease guaranteed loan, including lease price, transaction price and lending rate, were defined. Vector Error Correction Model (VECM), a time series analysis, was employed to dynamically explain the data. Based on the house lease prices and bank data on loans between January 2010 and December 2014, it was found that the increase in lease price was the direct result of the increase in lease guaranteed loan, not that of the decrease in lending rate or increase in housing transaction price.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.1
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• pp.43-51
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• 2012

The OLS(ordinary least squares) method is widely used in hedonic housing models. One of the assumptions of the OLS is an independent and uniform distribution of the disturbance term. This assumption can be violated when the spatial autocorrelation exists, which in turn leads to undesirable estimate results. An alterative to this, spatial econometric models have been introduced in housing price studies. This paper describes the comparisons between OLS and spatial econometric models using housing transaction prices of Busan, Korea. Owing to the approaches reflecting spatial autocorrelation, the spatial econometric models showed some superiority to the traditional OLS in terms of log likelihood and sigma square(${\sigma}^2$). Among the spatial models, the SAR(Spatial Autoregressive Models) seemed more appropriate than the SAC(General Spatial Models) and the SEM(Spatial Errors Models) for Busan housing markets. We can make sure the spatial effects on housing prices, and the reconstruction plans have strong impacts on the transaction prices. Selecting a suitable spatial model will play an important role in the housing policy of the government.

• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.111-119
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• 2024

The purpose of study is to analyze the effect of population inflow on apartment price growth. For this purpose, proxy for population structure is employed: (i) net population inflow based on 'resident registration criteria', (ii) buyer's transaction. The major findings are as followed. First, net population inflow of total and 50 over gives no significant effects on the apartment price growth in Seoul and Jeju. However, there are significant and positive effects of 50s and 60s in Seoul, and 60s in Jeju on the apartment price growth, respectively. Second, buyer's transactions of 'total and 50 over' give positive effect on apartment price growth only in Seoul. However, 60s and 50s of buyers' transaction give positive effect on the apartment price growth both in Seoul and Jeju. This study implies that more detailed population inflow like age group provide more meaningful information to the study on apartment price growth.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.95-118
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• 2017

Recent centrally the downtown area, the transaction between the row housing and multiplex housing is activated and platform services such as Zigbang and Dabang are growing. The row housing and multiplex housing is a blind spot for real estate information. Because there is a social problem, due to the change in market size and information asymmetry due to changes in demand. Also, the 5 or 25 districts used by the Seoul Metropolitan Government or the Korean Appraisal Board(hereafter, KAB) were established within the administrative boundaries and used in existing real estate studies. This is not a district classification for real estate researches because it is zoned urban planning. Based on the existing study, this study found that the city needs to reset the Seoul Metropolitan Government's spatial structure in estimating future housing prices. So, This study attempted to classify the area without spatial heterogeneity by the reflected the property price characteristics of row housing and Multiplex housing. In other words, There has been a problem that an inefficient side has arisen due to the simple division by the existing administrative district. Therefore, this study aims to cluster Seoul as a new area for more efficient real estate analysis. This study was applied to the hedonic model based on the real transactions price data of row housing and multiplex housing. And the K-Means Clustering algorithm was used to cluster the spatial structure of Seoul. In this study, data onto real transactions price of the Seoul Row housing and Multiplex Housing from January 2014 to December 2016, and the official land value of 2016 was used and it provided by Ministry of Land, Infrastructure and Transport(hereafter, MOLIT). Data preprocessing was followed by the following processing procedures: Removal of underground transaction, Price standardization per area, Removal of Real transaction case(above 5 and below -5). In this study, we analyzed data from 132,707 cases to 126,759 data through data preprocessing. The data analysis tool used the R program. After data preprocessing, data model was constructed. Priority, the K-means Clustering was performed. In addition, a regression analysis was conducted using Hedonic model and it was conducted a cosine similarity analysis. Based on the constructed data model, we clustered on the basis of the longitude and latitude of Seoul and conducted comparative analysis of existing area. The results of this study indicated that the goodness of fit of the model was above 75 % and the variables used for the Hedonic model were significant. In other words, 5 or 25 districts that is the area of the existing administrative area are divided into 16 districts. So, this study derived a clustering method of row housing and multiplex housing in Seoul using K-Means Clustering algorithm and hedonic model by the reflected the property price characteristics. Moreover, they presented academic and practical implications and presented the limitations of this study and the direction of future research. Academic implication has clustered by reflecting the property price characteristics in order to improve the problems of the areas used in the Seoul Metropolitan Government, KAB, and Existing Real Estate Research. Another academic implications are that apartments were the main study of existing real estate research, and has proposed a method of classifying area in Seoul using public information(i.e., real-data of MOLIT) of government 3.0. Practical implication is that it can be used as a basic data for real estate related research on row housing and multiplex housing. Another practical implications are that is expected the activation of row housing and multiplex housing research and, that is expected to increase the accuracy of the model of the actual transaction. The future research direction of this study involves conducting various analyses to overcome the limitations of the threshold and indicates the need for deeper research.

• Land and Housing Review
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• v.15 no.2
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• pp.89-106
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• 2024

Apartments constitute 64% of the housing type composition, representing the highest proportion among housing types. This proportion has been increasing annually. Given this trend, apartment prices are likely to have a significant impact on the national economy and people's livelihoods. This study examines the impact of the recent development of Seodaegu Station on the surrounding apartment market, with a specific focus on the effects of the educational environment. To this end, we conduct empirical analysis employing a hedonic price model and spatial autocorrelation analysis, based on actual transaction price data from the Ministry of Land, Infrastructure, and Transport. The study revealed three key findings: first, the development of Seodaegu Station positively impacted apartment prices. Second, this positive effect increases with the proximity to Seodaegu Station. Third, the enhancement of the educational environment nearby the Seodaegu Station development also positively influenced apartment prices. This study aims to serve as baseline research output for the public management of future metropolitan transportation facility development projects and for predicting apartment price trends.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.4
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• pp.75-81
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• 2016

This study focused on exploring real transaction price of apartment and spatial and temporal heterogeneity of the variables that influence real transaction price of apartment from the spatial and temporal perspective. As independent variables that are considered to influence real transaction price of apartment, transport, local characteristics, educational conditions, population, and economic characteristics were taken into account. Accordingly, the influence of independent variables and spatial distribution pattern were analyzed from the global and local aspects. The spatial and temporal changing patterns of real transaction price of apartment which is a dependent variable were analyzed. First, to establish an analysis model, OLS analysis and GWR analysis were conducted, and thereby more efficient and proper model was selected. Secondly, to find spatial and temporal heterogeneity of independent variables with the use of the selected GWR model, Local $R^2$ was used for local analysis. Thirdly, to look into spatial distribution of independent variables, kriging analysis was carried out. Therefore, based on the results, it is considered that it is possible to carry out more microscopic housing submarket analysis and lay the foundation for establishing a policy on real property.

• Korean Journal of Construction Engineering and Management
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• v.15 no.5
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• pp.147-159
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• 2014

After 2008 global financial crisis, Korean housing market has experienced stagnation. So it caused housing market problems like housing price reduction, rising rent cost and so on. For housing market normalization government announced policies but Korean housing market didn't recover from stagnation. So, to understand why Korean housing market couldn't overcome the recession and why the policies didn't be effective, this research analyzed housing market participants (home owner, housing demand) based on the law of supply and demand and the psychological effect on their transaction intention based on behavioral economics(behavioral finance). Based on the analysis this research tested the effectiveness of announced policies using System Dynamics. The result showed that the amount of transaction and mortgage loan was influenced by the length of time to draft policies.