• Land and Housing Review
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• v.11 no.2
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• pp.33-46
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• 2020

As the fastest growing office transaction volume in Korea, there's been a need for development of indicators to accurately diagnose the office capital market. The purpose of this paper is experimentally calculate to the office price index for effective benchmark indices in Seoul. The quantitative methodology used a Case-Shiller Repeat Sales Model (1991), based on actual multiple office transaction dataset with over minimum 1,653 ㎡ from Q3 1999 to 4Q 2019 in the case of 1,536 buildings within Seoul Metropolitan. In addition, the collected historical data and spatial statistical analysis tools were treated with the SAS 9.4 and ArcGIS 10.7 programs. The main empirical results of research are briefly summarized as follows; First, Seoul office price index was estimated to be 344.3 point (2001.1Q=100.0P) at the end of 2019, and has more than tripled over the past two decades. it means that the sales price of office per 3.3 ㎡ has consistently risen more than 12% every year since 2000, which is far above the indices for apartment housing index, announced by the MOLIT (2009). Second, between quarterly and annual office price index for the two-step estimation of the MIT Real Estate Research Center (MIT/CRE), T, L, AL variables have statistically significant coefficient (Beta) all of the mode l (p<0.01). Third, it was possible to produce a more stable office price index against the basic index by using the Moore-Penrose's pseoudo inverse technique at low transaction frequency. Fourth, as an lagging indicators, the office price index is closely related to key macroeconomic indicators, such as GDP(+), KOSPI(+), interest rates (5-year KTB, -). This facts indicate that long-term office investment tends to outperform other financial assets owing to high return and low risk pattern. In conclusion, these findings are practically meaningful to presenting an new office price index that increases accuracy and then attempting to preliminary applications for the case of Seoul. Moreover, it can provide sincerely useful benchmark about investing an office and predicting changes of the sales price among market participants (e.g. policy maker, investor, landlord, tenant, user) in the future.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.35 no.9
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• pp.131-142
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• 2019

The purpose of this study was to find out the characteristics of housing policies and apartment designs by comparison of supplying and remodeling apartments between France and Korea. The literature review was used in Korea cases and the literature review, site investigation, and expert interviews were used in France cases. At first, by reviewing the related literatures about the apartment developments and regenerations in France and Korea, twelve remodeling cases were represented respectively in Ile de France and Seoul. As a result, in housing policy, the Korean housing market had a shortage of low-priced houses related to biased apartment developments by private sector dependence. Consequently, the living in Korea generally required the high price in low quality houses. But in France, the housing policies were very successful in housing quantity, quality, and expense. It is involved in balances between the public housing supply and the activation of a private housing market based on the government support policy. Nevertheless, in the success of the apartment as a house type, apartments in France means the social elimination because of the supply method problems and the management failures of HLM institutions. However, in Korea, the apartment implies the successful life of the middle class population because of the competitive evolutions during 40 years as a market housing. Secondly, In the characteristics of remodeling, the remodeling in Korea was for property value improvements. It mainly executed to expand the size of a house by expansion of living space. However the remodeling in France was for social mixes and connections with the surrounding area. It mostly performed by various design methods such as vertical merging houses, partial removal, reconstruction, and construction of a local community centers and mixed-use residential buildings. This study shows the simultaneously remodeling features of those two countries. These findings can be used in developing effective strategies for the public housing regenerations in Korea and other countries.

• Spatial Information Research
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• v.10 no.2
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• pp.215-232
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• 2002

Variables representing neighborhood quality should be included in hedonic price models to control lfor the influences of negative or positive externalities from the quality of neighborhood on urban housing prices. This study proposes a GIS-based method to effectively measure the neighborhood quality variable when data on the neighborhood quality are aggregated by census sub area. This study also tests the superiority of the proposed neighborhood quality variable created by intensive use of GIS operations to a neighborhood variable not based on GIS operations in explaining the housing price variations by using Seoul＇s apartment sales data. The results from this study show that the neighborhood quality variable based on GIS-based operations shows better performance in explaining the urban housing price variations in Seoul＇s housing market. The implication from the results is that the potentials of GIS-based spatial operations in creating neighborhood quality variables should be well acknowledged by the researchers in the area of urban housing market study and GIS-based spatial operations should be more actively applied to generate better neighborhood quality variables for hedonic price models.

• Journal of Cadastre & Land InformatiX
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• v.50 no.1
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• pp.125-141
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• 2020

This study investigated the time-series relationship between housing consumer sentiment and housing prices in the five major districts in Seoul and also analyzed the effect of the housing consumer sentiment on housing prices using Granger Causality and VEC (Vector Error Correction) models. To describe the key results, first of all, housing consumer sentiment and regional housing market prices were closely related to each other, and the consumer sentiment strongly affected the change of housing prices. Second, the housing consumer sentiment was confirmed to have a discriminatory effect on the housing prices among the districts in Seoul in the short term. Specifically, the housing price of the east southern district (ESD) was the main reason for the change in housing consumer sentiment in Seoul, and that the resulting impact was transferred to other districts. Third, it was analyzed that regions other than the ESD would increase the housing prices in the long term as the housing consumer sentiment turned positive, but that the ESD would see a steady tone. Fourth, in the case of relative influence by district, housing (apartment) price fluctuation in a district was generally found to be most affected by adjacent or competitive districts. Through these findings, this study confirmed that there is a clear causality between housing consumer sentiment and housing prices in each district of Seoul and that there is a discriminatory influence on housing consumer sentiment among the districts.

• Journal of the Korean housing association
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• v.23 no.5
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• pp.103-111
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• 2012

This study empirically investigates the degree of physical exclusiveness of multi-family housing estates and its socioeconomic effects. By combining various physical elements devised to blockade and control the entrance to the estate as well as housing units, it constructs the index to quantify the degree of physical exclusiveness for the multi-family housing estates of more than 300 households in Seoul. The statistics reveal that the degree of physical exclusiveness has increased over time and therefore, as a representative example, two-thirds of the estates are now equipped with barricade at the entrance, which often symbolizes 'gated community'. The estimation result of hedonic price model show that physical exclusiveness has a significant positive effect on housing price. The household survey data for the case study estates also demonstrate that the residents in the estate of higher degree of physical exclusiveness put a higher housing value on socioeconomic 'prestige' as well as 'community', beyond physical 'security', and have closer neighborhood relationship with the residents inside the estate. However, there is no significant difference in neighborhood relationship with the outside residents depending upon the degree of physical exclusiveness.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.3D
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• pp.477-487
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• 2011

The modified repeat-sales model is employed in this study in order to identify differentiating impacts of time-varying accessibility characteristics on housing price. The results demonstrate that accessibility measures have very differential impacts on housing price over time. The improvement of accessibility through newly built facilities and apartment complex has either increased or decreased housing price. For example, the new subway line 9 has positive impact on housing price nearby, therefore price gap between subway access area and the other parts has been increased. The impact of the wide area facilities such as shopping center and hospital are decreased because they can be used more easily by the new subway line before. However, the small service area facility such as elementary school doesn't lose their impact even though subway accessibility extremely increased. The results imply that new facilities in existing residential site can affect not only housing price but also the other facilities' impact of housing price.

• Journal of agricultural medicine and community health
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• v.49 no.1
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• pp.59-70
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• 2024

Objectives: This research analyzed and compared housing transaction prices and depression rates according to housing types before and after the COVID-19 pandemic. Methods: Data on housing transaction prices and depression rates from 2018 to 2022 in 25 districts of Seoul, South Korea, were utilized. Dummy variables were employed to account for potential confounders influencing the relationship between the variables. Statistical analysis was conducted using R, and the relationship between depression rates and housing transaction prices was examined through Ordinary Least Squares (OLS) and panel data regression analysis. Results: The results of OLS and one-way random effects models indicated a significant relationship between apartment (p<.05) and officetel (p<.001) transaction prices and depression. However, detached/semi-detached and row/townhouse transaction prices did not exhibit a significant relationship with depression. Conclusion: It was observed that as apartment and officetel transaction prices increased in Seoul before and after the COVID-19 pandemic, depression rates also increased. Considering that changes in housing prices by housing type in South Korea may impact the mental health of local residents, it is deemed necessary to consider healthy housing and housing prices as comprehensive determinants of mental health.

• The Journal of Bigdata
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• v.6 no.1
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• pp.91-113
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• 2021

Despite the influence of real estate in the Korean asset market, it is not easy to predict market trends, and among them, apartments are not easy to predict because they are both residential spaces and contain investment properties. Factors affecting apartment prices vary and regional characteristics should also be considered. This study was conducted to compare the factors and characteristics that affect apartment prices in Seoul as a whole, 3 Gangnam districts, Nowon, Dobong, Gangbuk, Geumcheon, Gwanak and Guro districts and to understand the possibility of price prediction based on this. The analysis used machine learning algorithms such as neural networks, CHAID, linear regression, and random forests. The most important factor affecting the average selling price of all apartments in Seoul was the government's policy element, and easing policies such as easing transaction regulations and easing financial regulations were highly influential. In the case of the three Gangnam districts, the policy influence was low, and in the case of Gangnam-gu District, housing supply was the most important factor. On the other hand, 6 mid-lower-level districts saw government policies act as important variables and were commonly influenced by financial regulatory policies.

• International Journal of Advanced Culture Technology
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• v.10 no.1
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• pp.274-283
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• 2022

Korea is facing a number difficulties arising from rising housing prices. As 'housing' takes the lion's share in personal assets, many difficulties are expected to arise from fluctuating housing prices. The purpose of this study is creating housing price prediction model to prevent such risks and induce reasonable real estate purchases. This study made many attempts for understanding real estate instability and creating appropriate housing price prediction model. This study predicted and validated housing prices by using the LSTM technique - a type of Artificial Intelligence deep learning technology. LSTM is a network in which cell state and hidden state are recursively calculated in a structure which added cell state, which is conveyor belt role, to the existing RNN's hidden state. The real sale prices of apartments in autonomous districts ranging from January 2006 to December 2019 were collected through the Ministry of Land, Infrastructure, and Transport's real sale price open system and basic apartment and commercial district information were collected through the Public Data Portal and the Seoul Metropolitan City Data. The collected real sale price data were scaled based on monthly average sale price and a total of 168 data were organized by preprocessing respective data based on address. In order to predict prices, the LSTM implementation process was conducted by setting training period as 29 months (April 2015 to August 2017), validation period as 13 months (September 2017 to September 2018), and test period as 13 months (December 2018 to December 2019) according to time series data set. As a result of this study for predicting 'prices', there have been the following results. Firstly, this study obtained 76 percent of prediction similarity. We tried to design a prediction model of real estate transaction price with the LSTM Model based on AI and Bigdata. The final prediction model was created by collecting time series data, which identified the fact that 76 percent model can be made. This validated that predicting rate of return through the LSTM method can gain reliability.

• Journal of the Korean association of regional geographers
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• v.11 no.2
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• pp.169-186
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• 2005

This paper has focused on the geographical patterns of migrations and the influence of housing value(apartment) per pyung on the migrations within the one city(Seoul) for 1995$\sim$2003. The migration flows which are composed of the origin, the destination and the number of migrants, are examined at the administrative gu and dong level. As most migrations occur among adjacent gus and dongs, short-distance migration is prominent But there is a tendency for the short-distance migrations to occur between specific regions. Since the economic crisis of 1997 out of which Korea was rescued by IMF, differentiation of housing price is so evident that residental relocation is selective among dongs. It seems that the differentiation of housing price has begun to facilitate the relocation of households. Certain social groups are excluded from high-quality residences, as they cannot afford the high price. The number of migrants between dongs is closely related to the variation of the housing value per pyung within dongs. The short-distance migration may reflect this phenomena simultaneously. It seems that the intra-urban migrations in Seoul play a important role to produce and reinforce the residential segregation.