• Journal of the Korean Data and Information Science Society
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• v.25 no.1
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• pp.65-76
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• 2014

Housing prices are influenced by external shock factors such as real estate policy or economy. Thus, the intervention effect is important for the development of forecasting model for housing price index. In this paper, we examined the degree of effective power of external shock factors for forecasting housing price index and analyzed time series models for efficient forecasting of housing price index. It is shown that intervention models are better than other models in forecasting results using real data based on the accuracy criteria.

• The Journal of the Convergence on Culture Technology
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• v.8 no.1
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• pp.435-440
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• 2022

This study analyzed the impact of changes in real estate prices on the soundness of Korean banks using multiple regression models. As a result of the analysis, changes in real estate prices significantly increase the banks' non-performing loans through the increase in loans. Among macroeconomic variables, short-term interest rates were found to have a significant effect on all soundness indicators such as BIS capital adequacy ratio, non-performing loans ratio, and liquidity coverage ratio. Among the bank characteristics indicators, the loan growth rate had a significant negative effect on BIS capital adequacy ratio, and the real estate mortgage rate had a significant positive effect. In additional, it was found that non-performing loans ratio and liquidity coverage ratio had a negative effect on BIS capital adequacy ratio.

• 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.

• Journal of the Korean Data and Information Science Society
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• v.27 no.3
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• pp.639-651
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• 2016

"Law on price announcement for real estate" which was revised as of Jan. 19, 2016 (will be enforced as of Sep. 1, 2016) decided the introduction of 'Price announcement system for non-residential property' for the first time. However, its introduction seems to be delayed based on two reasons. Firstly the methodology for introduction of non-property system is not definitized, despite many problems were brought up for current tax base of non-residential property. In addition, changes in tax base will place a burden on the government. In this regard, this study analyzed actual transaction price data throughout one year to analyze equity of taxation for non-residential property and to find major factor which affects on the tax base, in relation with the change of current public announcement system to actual transaction based system. And this is the first study that applied actual transaction price to non-residential property.

• Korea Real Estate Review
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• v.27 no.4
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• pp.63-76
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• 2017

The purpose of this study is to analyze the effect of the results of a nationwide academic evaluation of middle schools and high schools on apartment prices in Ulsan City by using a hedonic pricing model. The results of the middle school and high school achievement test, the College Scholastic Ability Test (CSAT) score for high school, the national united evaluation score, and the number of successful applicants to prestigious universities have a significant effect on the apartment price formation with a positive relationship. In addition, different kinds of academic evaluation score have asymmetric effects on apartment price determination. The results of the high school achievement evaluation are more important than the results of the middle school achievement evaluation in the apartment price determination. Among the achievement evaluation results, the ratio of the students with the higher education level is more important than the ratio of the students with the lower basic education level. Furthermore, the CSAT score for Natural Sciences is more important than the CSAT score for the Humanities course.

• Journal of the Korean Geographical Society
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• v.49 no.6
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• pp.917-934
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• 2014

Geographically weighted regression(GWR) model has been widely used to estimate spatially heterogeneous real estate prices. The GWR model, however, has some limitations of the selection of different price determinants over space and the restricted number of observations for local estimation. Alternatively, the geographically weighted LASSO(GWL) model has been recently introduced and received a growing interest. In this paper, we attempt to explore various local price determinants for the real estate by utilizing the GWL and its applicability to forecasting the real estate price. To do this, we developed the three hedonic models of OLS, GWR, and GWL focusing on the sales price of apartments in Seoul and compared those models in terms of model fit, prediction, and multicollinearity. As a result, local models appeared to be better than the global OLS on the whole, and in particular, the GWL appeared to be more explanatory and predictable than other models. Moreover, the GWL enabled to provide spatially different sets of price determinants which no multicollinearity exists. The GWL helps select the significant sets of independent variables from a high dimensional dataset, and hence will be a useful technique for large and complex spatial big data.

• Journal of the Korea Institute of Building Construction
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• v.22 no.1
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• pp.81-90
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• 2022

With apartment purchase prices rising, small and medium-sized cities have been highlighted as areas in which real estate speculation is overheated, and thus designated as target districts for adjustment. In addition, tax policy is constantly being adjusted in an attempt to stabilize real estate prices. The purpose of this study is to analyze the basic effect of tax policy on the purchase price of apartments in small and medium-sized cities. This study selected apartments in the Daejeon area that were constructed between 1990 and 2015. In addition, tax policy was divided into regulatory policy and easing policy based on tax increase and tax cut. This study analyzes the short-term difference of one year before and after the change in the purchase price of apartment houses. In addition, this study set the time when real estate policy was implemented and the actual transaction price of apartments in Daejeon as the analysis targets, and analyzed the correlation between tax policy and apartment sales prices through the NPV technique and T-test results. Through the study, it was found that most tax policies changed apartment purchase prices in the short term.

• Journal of Digital Convergence
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• v.12 no.5
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• pp.89-99
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• 2014

Correlation of KOSPI from stock market and Apartment Prices in Seoul HPPCI from real estate market has been found from this research. Furthermore, from the comparison of those indicators' flows, certain precedence was found as well. The purpose of this research is to analyze correlation and precedence among KOSPI, Apartment price in Seoul, HPPCI and CLI. As for predicting KOSPI of stock market and real estate market, it is necessary to find out preceding indices and analyzing their progresses first. For 27 years from the January 1987 to December 2013, KOSPI has been grown by 687%, while CLI showed 443%, Apartment of Seoul showed 391%, HPPCI showed 263% of growth rate in order. As the result of correlation analysis among Apartment of Seoul, CLI, KOSPI and HPPCI, KOSPI and HPPCI showed high correlation coefficient of 0.877, and Apartment of Seoul and CLI showed that of 0.956 which is even higher. Result from the analysis, CLI shows high correlation with stock and real estate market, it is a good option to watch how CLI flows to predict stock and real estate market.

• Korean Journal of Construction Engineering and Management
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• v.22 no.3
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• pp.61-68
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• 2021

This study analyzed the influencing factors for urban redevelopment projects with a relatively long project duration in the context of Seoul's increasing urbanization rate and aging. Among the business areas that have been designated since 2005 and have been approved for the management and disposal plan of the entire Seoul area, 75 business areas have been set as targets. A hedonic price model was used to analyze the project area, economic, and locational characteristics as independent variables with the project duration from designation of zones to approval of management and disposal plans as dependent variables. As a result of the analysis, the smaller the project area, the larger the area occupied per union member, the larger the land price change rate, and the smaller the KOSPI index, the shorter the required period. This study has the distinction of empirically analyzing the effect of characteristic variables considering size and economic and locational characteristics on period. It provides implications that the area of the business area, the number of union members, and economic conditions should be considered when establishing a business area.

• Korea Real Estate Review
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• v.27 no.3
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• pp.41-50
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• 2017

Previous studies, especially that by Lee (2014), showed how time series volatility models can be applied to the house price series. As the regional housing market trends, however, have shown significant differences of late, analysis with national data may have limited practical implications. This study applied volatility models in analyzing and forecasting regional house prices. The estimation of the AR(1)-ARCH(1), AR(1)-GARCH(1,1), and AR(1)-EGARCH(1,1,1) models confirmed the ARCH and/or GARCH effects in the regional house price series. The RMSEs of out-of-sample forecasts were then compared to identify the best-fitting model for each region. The monthly rates of house price changes in the second half of 2017 were then presented as an example of how the results of this study can be applied in practice.