• Proceedings of the Korean Society of Computer Information Conference
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• 2023.01a
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• pp.27-29
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• 2023

불안정한 부동산 가격은 지속적인 사회 문제로 거론되고 있는데 이는 부동산 매매 가격을 예측할 수 있는 정확한 지표가 체계적이고 구체적으로 확립되지 않았기 때문이다. 본 논문은 가격변동에 주요하게 영향을 미치는 특성을 파악하여 가격 예측 지표로 활용하기 위해 머신러닝 모델을 적용하여 특성 분석을 수행한다. 이를 위해 한국부동산원에서 제공하는 2021년 10월부터 2022년 9월까지 1년간의 역 주변 500M 이내 거래 데이터 약 30만 6천 개를 어떠한 과정으로 전처리하여 머신러닝 모델에 적용하였는지 기술한다.

• Journal of the Economic Geographical Society of Korea
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• v.5 no.2
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• pp.293-302
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• 2002

China in the era of economic transition has conducted the housing reform policy over the past 20 years. Housing providing systems have changed from the free distributing housing system under the governmental planning to the monetary housing system for individual customers. The 1998 monetary housing distribution policy, which ended the 20-year Chinese housing reform, departed from the direct distribution system that had blocked housing commodification. The purpose of the housing reform was to provide and reproduce housing without the expenses of the Chinese government and work unit (danwei), which is different from Russia. In order to achieve the housing reform, the Chinese government introduced various policies, which enabled residents to purchase housing by themselves. However, it took long for residents, who had taken government's welfare system granted, to accept housing as goods. In addition, the Chinese government's efforts to reproduce housing by market systems failed because housing was closely linked to land and was expensive consumption goods, which differentiates housing from other goods that can be commodified through market prices and diverse ownerships. Accordingly, despite a political burden, the Chinese government waived the real distribution policy for housing. After the waiver, the housing commodification process excelled through the private housing markets.

• Journal of Korean Society of Transportation
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• v.19 no.4
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• pp.19-33
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• 2001

In the developed countries, traffic noise is one of most serious problems faced by people's lives. So the importance of the traffic noise is quite well recognized by the infrastructure planners as well as the people. The traffic noise is valued in monetary terms in some countries and it is reflected in estimating the net present value or benefit/cost ratio. On the contrary, the effects of traffic noise are not reflected in the assessment of infrastructure in most cases in Korea. However, as the income level has been increasing, more people have been becoming to put more importance on their living conditions. The purpose of this paper is to estimate the value of traffic noise in the Seoul metropolitan area. The housing price were surveyed to use the quasi-hedonic price technique. By this way, two housing prices at the same floor level in different 128 complexes in the Seoul metropolitan area were surveyed. the actual traffic noise level was also measured. The differences of housing prices and noise levels were analyzed using the various types of regression models. The value is quite different by size of house. The value of large house is higher than that of small house. Since the income level of people in large house is higher than that in small house. it might be said that value of traffic noise for high income people is higher than that for low income people. Moreover, the increase of 1dB(A) noise affects the house price by about 0.3% in Seoul metropolitan area.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2019.11a
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• pp.207-208
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• 2019

Currently, as the public interest for environmental issues has grown rapidly, the needs for G-SEED have also increased. However, as investment according to eco-friendly elements is inevitable to receive G-SEED certification, it is necessary to find out whether or not the sales price of apartments have increased compared to investment costs. Therefore, the objective of this study is to analyze the sales price of apartments according to G-SEED by using T-test. To achieve the objective, First, variables affecting on the sales price of apartments are selected. Second, the data are collected by using GIS(Geographic Information System). Third, after testing the normality, a comparison analysis is conducted on the sales price between G-SEED certified and non-certified apartments by using T-test. As a result, it is concluded that G-SEED certified apartments are more expensive than non-certified apartments. In the future, these findings can be utilized to develop of apartments price calculation model based on the G-SEED.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.6
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• pp.2038-2045
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• 2010

Households' monthly average income is composed of various factors. This study paper studies focuses on estimating the determinants of a households' monthly average income. The region for analysis consist of three groups, that is, the whole country, a metropolitan city(such as Busan, Daegu, Incheon, Gwangiu, Daejeon, Ulsan.) and Seoul. Analyzing period be formed over a 57 time points(2005. 01~2009. 09). In this paper the dependent variable setting up the households' monthly average income, explanatory (independent) variables are composed of the consumer price index, employment to population ratio, Index of housing sale price, the preceding composite index, loans of housing mortgage, spending rate for care medical expense and the composite stock price index. In looking at the factors which determine the monthly average income, evidence was produced supporting the hypothesis that there is a significant positive relationship between the composite index and housing loans. The study also produced evidence supporting the view that there is a significant negative relationship between employment ratios, the house sale pricing index and spending rates for care or medical needs. The study found that the consumer price index and composite stock price index were not significant variables. The implications of these findings are discussed for further research.

• 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.

• 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.

• International Area Studies Review
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• v.21 no.4
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• pp.173-194
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• 2017

The research study conducted logistics regression analysis through HLM (Hierarchical Linear Modeling) and presented the value of the outcome in order to investigate characteristic factors of demanders which influence the intention to move into public rental housing. (1) The results of the regression analysis of characteristic factors of household and housing were analyzed as having the significant effect on the intention to move in public rental housing, according to residents moving in monthly rent housing, residents' occupations, rental housing, the number of household, the location of surrounding public rental housing, monthly average income, children's educational level, the number of children, the types of housing and one's own house, in order, out of the types of housing tenure. (2) The results of the regression analysis of characteristic factors of the conditions of location were analyzed that out of the conditions of location of the top five areas in public rental rates, what influences significant effects on the intention to move in public rental housing is the location of surrounding rental housing, income, the number of household and children, children's educational level, job state, housing types, ones' own house, rent housing, monthly rent housing, in order. (3) In case of Seoul, Expanding public rental housing is inevitable in order to stabilize ordinary people's housing stability, owing to the high and rental prices of private housing. Nevertheless, an accurate analysis of the intention to move in public rental housing has not been conducted. Eventually, the research was, thus, conducted, based on the fact that the preference on public housing is low. According to the analytic results of the study, it is required for the government institutions and agencies should consider individual and local characteristics and provide an alternative that meets the real situation, in order to help ordinary citizens with low incomes stabilize housing.

• Korean Journal of Construction Engineering and Management
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• v.19 no.2
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• pp.96-106
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• 2018

The government adopted activation policy of real estate to overcome low economic growth rate. Real estate activation plan adopted by the government raised credit limit by lowering the regulation, and reduced real estate investment cost by reducing the base rate. Also, delayed transfer tax on multi-house owner to activate real estate investment and resolved purchase right resale. Relief of real estate regulate caused increase of housing sales and price increase, and the real estate market changed to overheating aspect such as premium upon completion of lot sale in a short time. Such market atmosphere greatly increased household debs as owners own houses based on 'financial debt' instead of their income. Since 2017, real estate policy was reinforced to reduce household debts and lending rate was raised due to rise of base rate, accordingly, burden of household debt is expected to increase. This research suggested a plan for the Financial Supervisory Service to efficiently manage the financial world by analyzing the cause and problem of household debs.

• Journal of the Korean Data and Information Science Society
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• v.28 no.1
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• pp.173-183
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• 2017

We investigate the factors affecting the price of apartments using the spatial and temporal data of private real estate prices. The factors affecting the price of apartment were analyzed using geographical and temporal weighted regression (GTWR) model which incorporates the temporal and spatial variation. In contrast to the OLS, a general approach used in previous studies, and GWR method which is most widely used for analyzing spatial data, GTWR considers both temporal and spatial characteristics of the house price, and leads to better description of the house price determination. Year of construction and floor area are selected as the significant factors from the analysis, and the house price are affected by them temporally and geographically.