• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.9
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• pp.6315-6324
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• 2015

This study analyses the effects of household finances on rental price of apartment in Seoul which play a major role in real estate policy. We estimate VAR models using time series data. Economy variables such as sales price of apartment in Seoul, consumer price index, hiring rate, real GNI and loan amount of housing mortgage, which relate to household finances and influence the rental price of apartment, are used for estimation. The main findings are as follows. In the short term, the rental price of apartment is impacted by economy variables. Specifically, Relative contributions of variation in rental price of apartment through structural shock of economy variables are most influenced by their own. However, in the long term, household variables are more influential to the rental price of apartment. These results are expected to contribute to establish housing price stabilization policies through understanding the relationship between economy variables and rental price of apartment.

• Journal of the Korean housing association
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• v.21 no.6
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• pp.81-90
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• 2010

The existing most studies on the apartment sales prices have been limited to relatively small size apartment complexes and have not categorized the apartment complexes based on the number of households. Some of them uses the apartment-related indices such as regional value estimates, sales unit price, and view right values. In the case of Seoul Metropolitan Area, the size of apartment complex has been growing to the level of large complex over more than 1,000 households through new town development, redevelopment and reconstruction. People prefers to choose a large scale complex instead of small complex based on their perception that a large scale apartment complex provides more conveniences in living. The result of this analysis revealed that the variables chosen as important determinants of the hedonic price model for large scale apartment complexes were square meters of apartment unit, rent/price ratio, number of bays, distance to the nearest subway station, and heating system method. This means that the sales price of apartment unit will be higher as the square meters of apartment unit increase, as the rent/price ratio decreases, as the distance to the nearest subway station increases, and as the number of bays increase.

• Environmental and Resource Economics Review
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• v.11 no.2
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• pp.261-278
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• 2002

Based on the hedonic pricing method, this paper investigates the effect of air quality on the apartment price in Seoul. The empirical results show that both the structural variables such as years of construction, heating system, and size of apartment complex and accessability variables such as distances to subway station and parks provide statistically significant effects on the price of apartment, Especially, the dendity of sulfurous acid gas ($SO_2$) and ozone ($O_3$) in the air, indicating air quality, negatively affect the price of apartment, This implies that as the condition of air quality to become worse, apartment price decreases, Therefore, when the degree of aversion of apartment residents against the air pollution affects the formation of apartment's market price, the MWPT(Marginal Willingness to Pay) in order to improve the air quality 10% has been estimated as 36,000~39,000Won per month.

• Journal of the Korean housing association
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• v.18 no.3
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• pp.63-72
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• 2007

The purpose of this study is to identify the impact of the building, site, and region characteristic factors on the annual average price rising rate of apartment housing in Seoul. The data were consisted of 272 apartment units in Seoul. A survey included checking the drawing documents and interview with apartment maintenance staffs and real estate agencies from October 2006 to February 2007. Data were analyzed with descriptives, frequency, crosstabs, and linear regression by SPSS/PC for Window. The linear regression model was employed to evaluate the price rising rate in apartment housing. Following results were obtained. The price rising rate for pyeong ($3.3m^2$) of apartment housing was determinated by the district zone, the construction company's brand name, the building age, the building stories, the floor space index, the building-to-land ratio, the green space rate, and the distance from the downtown. Especially, the district zone was the most important factor that affected the price rising of apartment housing in Seoul. Therefore, the policy has to focus to solve the imbalance between autonomous districts with the collaborated tax.

• Communications for Statistical Applications and Methods
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• v.15 no.2
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• pp.173-191
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• 2008

The goal of this paper is analyzing and modeling the trend of apartment market price in Seoul using the dynamic linear model(DLM). We use the market price per pyeong of 30-pyeong-apartment provided by "KB apartment market price database" of Kookmin bank. The data is collected from June $24^{th}$, 2003 to August $28^{th}$, 2006. The inspection of the data reveals that the trend of apartment market price in Seoul can be divided into two groups and we assume that the price is expressed by the common trend of divided groups. We try to estimate the price of apartment by DLM using the Bayesian method.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2016.05a
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• pp.249-250
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• 2016

Korean government has announced declared prices of apartment reflecting market condition each year. Therefore, on that basis, apartment owners have used as basic data trading apartments and the government has been used to calculate the tax. However, the sales prices and declared prices of apartment has occurred difference depending on the region and the brand. This study has analyzed and compared regional differences in sales price of apartments. The results of this study, we have known that sales price of apartments was a big difference depending on the region and the gross area. Especially, Seoul and Gyeonggi Province are the highest. And sales price of Southeast and urban area are the highest in Seoul. In the future, it is necessary that gap analysis between sales price and declared prices of apartment. And It is needed to develop apartment index considering the region and the gross area.

• KIEAE Journal
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• v.7 no.3
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• pp.11-20
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• 2007

The purpose of this study is to analyse the effects of the eco-friendly factors on the apartment housing price rise and to suggest the desirable way of marketing strategy for apartment housing. For the analysis, the data of apartment sites in Seoul had been collected from September 2006 to February 2007. The data consisted of 95 apartment sites in Seoul. Data were analyzed with descriptives, crosstabs, and discriminant analysis by SPSS/PC for Window. Following result was obtained. The eco-friendly apartment housing price rate in Seoul was determined by eco-friendly landscape, green space rate, house unit size, installment sale price per pyeong, floor space index, distance from subway station when it was not considered the impact of building age, construction company's brand, and autonomous districts. Findings of this research can provide valuable information for marketing strategy of housing construction company.

• 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 Cadastre & Land InformatiX
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• v.52 no.2
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• pp.211-231
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• 2022

This study attempted to identify the effects of macroeconomic variables such as the All Industry Production Index, Consumer Price Index, CD Interest Rate, and KOSPI on apartment lease prices divided into nationwide, Seoul, metropolitan, and region, and to present a methodological prediction model of apartment lease prices by region using Long Short Term Memory (LSTM). According to VAR analysis results, the nationwide apartment lease price index and consumer price index in Lag1 and 2 had a significant effect on the nationwide apartment lease price, and likewise, the Seoul apartment lease price index, the consumer price index, and the CD interest rate in Lag1 and 2 affect the apartment lease price in Seoul. In addition, it was confirmed that the wide-area apartment jeonse price index and the consumer price index had a significant effect on Lag1, and the local apartment jeonse price index and the consumer price index had a significant effect on Lag1. As a result of the establishment of the LSTM prediction model, the predictive power was the highest with RMSE 0.008, MAE 0.006, and R-Suared values of 0.999 for the local apartment lease price prediction model. In the future, it is expected that more meaningful results can be obtained by applying an advanced model based on deep learning, including major policy variables

• Journal of the Korea Institute of Building Construction
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• v.4 no.3
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• pp.117-124
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• 2004

This study aims to evaluate the feasibility of remodeling business by predicting the future price of apartment house after remodeling using Hedonic Price Model. The data concerning such 8 independent variables as location, unit size, unit plan, landscape, parking, the number of elapsed years after completion, number of units, brand per apartment unit from 25 regions in Seoul metropolitan city were collected and evaluated by established evaluation criteria. The coefficients affecting the price of apartment unit were made by way of linear multi-regression and put into Hedonic Price Model. The feasibility evaluation model for apartment was made and verified by data of remodelled apartment. The predicted results using suggested evaluation model coincide with actual apartment market situations.