• Journal of the Economic Geographical Society of Korea
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• v.17 no.1
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• pp.147-159
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• 2014

The present study was aimed to estimate the rational bubble by using the state space model and Kalman filter, of the national, capital, non-capital, Gangnam, and Gangbuk regions housing sales price from November 2003 to August 2013, for the whole period, and before and after the global financial crisis. For the whole period, Gangnam marked the highest rational bubble of 25.4%, followed by Gangbuk 21.3%, capital region 20.1%, whole country 18.9%, and non-capital region 14.3%. Prior to the global financial crisis, Gangnam showed 26.7% of bubble, which is approximately 7.4% higher than Gangbuk with 19.3%. On the other hand, after the global financial crisis, the bubble has collapsed a lot with Gangnam 13.2% and Gangbuk 10.7%; however, the non-capital region showed rather an increase of about 15% from 4.2% before the crisis to 9.0% after the crisis. The main cause of this is that the trading price has declined but the rents have risen in the capital region including Gangnam and Gangbuk, while the transaction price has gone up in non-capital region due to various positive signs like the moving of public institutions.

• 주택과사람들
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• s.168
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• pp.46-58
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• 2004

>>> 시장여건 분석 $\blacktriangleright$ 주택수급 상황 $\cdot$ 신규입주물량은 46만호로 올해보다 크게 감소하나 아파트입주물량은 32만호로 증가. 특히, 주거용 오피스텔 입주가 본격화되면서 전체적으로 공급과잉구조로 전환 $\cdot$ 가수요는 물론 실수요도 위축되면서 미분양 증가, 입주후 공가가 주요이슈로 대두 $\blacktriangleright$주택정책 여건 $\cdot$양도세,재산세 중과, 주택거래신고제, 종합부동산세 등 10.29종합대책의 후속조치가 본격화되고, 토지거래허가대상 확대 및 개발이익환수 등 2차 대책 시행가능성 상존 $\cdot$ 분양원가 공개, 후분양제 도입, 신행정수도 이전계획의 향방에 따른 불안요인도 내재 $\blacktriangleright$거시경제 전망 $\cdot$ 경기회복으로 금리가 상승세로 돌아설 경우 투자수요 위축 불가피 $\cdot$ 경제성장률이 $5\%$대로 개선되고 시중유동성도 풍부하나, 가계부실과 실업 증가로 수요증가효과는 제한적 >>> 향후 시장전망 $\cdot$ 저금리기조와 각종 개발호재에 따른 시장불안요인은 상존하나 정부의 강력한 투기억제 의지를 감안할 때 단기 조정 후 추가 하락하는 전형적인 경기후퇴국면에 진입할 전망 $\cdot$매매가격은 서울아파트가격이 크게 하락하면서 전국평균-$2\%$ 내외의 하락률을 보이고, 전세가격도 국지적 불안 가능성은 있으나 $-1\%$ 내외의 하향안정세가 이얼질 전망. 분양시장은 청약률 둔화와 미분양 증가의 침제양상이 이어지면서 주택건설실적도 각종 사업여건 악화로 50만호 안팎에 머물 것으로 예상. 지가상상률은 투기대책과 주택시장 위축으로 올해보다는 소폭 낮아지나 각종 개발 호재에 힘입어 개발예정지역을 중심으로 $3\%$ 내외의 높은 상승세가 지속될 전망

• Korean Journal of Construction Engineering and Management
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• v.17 no.3
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• pp.108-115
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• 2016

The price determinant for land investment depends on the internal information process and subjective decision making by management in general. Accordingly, the systematic frame to determine the feasibility of investment price to the public residential land for multi-housing development by private sector has not been proposed. The purpose of this study is to explore the frame to determine the investment price for public residential land from the perspectives of land attribute and apartment market factor. Multiple regression has been implemented to confirm the eligibility of proposed model. Research findings indicate that the land area, floor area ratio, coverage ratio, location have been identified as the total land cost determinant, and for the determinants for floor area land cost, the ratio of apartment, sale price, rent price, etc, have been identified. This research intends to provide the basis for land providers to predict the land value as a raw material in market and present the indicators for land buyers to review the price adequacy for the investment.

• Land and Housing Review
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• v.14 no.1
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• pp.33-46
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• 2023

This study investigated price factors for large apartment complexes in Seoul during the COVID-19 pandemic and compared Gangnam and non-Gangnam areas, which have been recognized as heterogeneous markets. We find that the change in apartment prices in large-scale complexes did not significantly affect the individual characteristics of apartments, unlike previous studies, but was affected by macroeconomic variables such as interest rates and money. On the other hand, considering the units of the interest rate and total monetary volume variables, the effects of two variables on the apartment sales price is significantly high. In addition, the Gangnam area model analysis shows that apartment prices are greatly affected by interest rates and currency volume, and, the non-Gangnam area model analysis shows that apartment prices are greatly affected by interest rates and currency volume, but the degrees are different from the Gangnam area model. Overall, our study shows that interest rates and money supply were the main factors of apartment price changes, but apartment prices in non-Gangnam areas are more sensitive to changes in interest rates and money supply.

• Journal of Cadastre & Land InformatiX
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• v.46 no.2
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• pp.283-296
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• 2016

This paper aims to analyze characteristic by the cities focused on the ratio of new apartment resale that is one of the apartment unit sale market, which has been increased recently. To do so, this study examined characteristics of population, housing, residential, and economical with 162 cities and counties and performed multiple regression analysis with dependent variable, ratio of new apartment resale. As a result. the factors affecting the ratio of new apartment resale are 7variables, regional apartment rate, population increasing rate, a mount of sell in lots, housing rent price (Jeonse price) rate compared to average apartment sale price, single-person households increasing rate, apartment subscription rate and number of buyers in the area. Thus, this study showed that the factors affecting characteristic by the regions are ordered characteristics of residential, population and rate of sale and dealing. Based on this result, this study will be basic data for policy of government and development of apartment sales system and for end user to activate resale in apartment sales market.

• The Journal of the Convergence on Culture Technology
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• v.7 no.1
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• pp.140-144
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• 2021

We humans try to pursue a better living environment along with the development of modern civilization. In particular, it is a reality that a lot of efforts are being made to improve food, clothing, and shelter. Among them, the concept of housing serves as a major function to improve the quality of life. However, the government's excessive tax rate regulation policy surrounding the sale of such houses is actually inducing annual or monthly rent expenses. Furthermore, it is a reality that even home sales are not being handled smoothly. In general, the cost of owning a house (apartment, etc.) can be divided into acquisition and possession. In addition, a lot of taxes are borne by long-term housing. Subsequently, due to the increase in the transfer tax rate due to the sale of houses, the disposal of property rights is not free. This serves as a limiting factor for market principles. If the tax rate for the transfer of multi-homed people is raised, it can cause a phenomenon that encourages yearly or monthly rent. This is a part where it seems necessary to reduce the transfer tax rate according to the multi-year retention period. If you hold it for 20 years after acquisition, you have paid a lot of taxes and returned your profits. For that reason, you should not impose a transfer tax for trading. The application of the tax-free principle for houses held for more than 20 years will respond to market principles in the future and will function effectively in annual or monthly rent policies.

• Korea Real Estate Review
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• v.24 no.1
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• pp.7-14
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• 2014

This study, as the temporal and spatial data for the real price apartment in Seoul from January 2006 to June 2013, empirically compared and analyzed the estimation result of apartment price using OLS by hedonic price model for the problem of space-time correlation, temporal autoregressive model (TAR) considering temporal effect, spatial autoregressive model (SAR) spatial effect and spatiotemporal autoregressive model (STAR) spatiotemporal effect. As a result, the adjusted R-square of STAR model was increased by 10% compared that of OLS model while the root mean squares error (RMSE) was decreased by 18%. Considering temporal and spatial effect, it is observed that the estimation of apartment price is more correct than the existing model. As the result of analyzing STAR model, the apartment price is affected as follows; area for apartment(-), years of apartment(-), dummy of low-rise(-), individual heating (-), city gas(-), dummy of reconstruction(+), stairs(+), size of complex(+). The results of other analysis method were the same. When estimating the price of real estate using STAR model, the government officials can improve policy efficiency and make reasonable investment based on the objective information by grasping trend of real estate market accurately.

• 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.

• Journal of the Economic Geographical Society of Korea
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• v.15 no.4
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• pp.585-600
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• 2012

The purpose of this study related to the liquidity impact of the housing market variables using vector auto-regressive model(VAR) and empirical analysis is to derive some policy implications. October 2003 until May 2012 using monthly data for liquidity variables mortgage rates, mortgage, financial liquidity, as the composite index and nation, Seoul, Gangnam, Gangbuk, the Apartment sales prices were analyzed. Granger Causality Test Results, mortgage rates and mortgage at a bargain price two regions had a strong causal relationship. Since the impulse response analysis, Geothermal difference there, but housing price housing price itself, the most significant ongoing positive (+) reactions were liquidity-related variables are mortgage loans is large and persistent positive (+), financial liquidity weakly positive (+), mortgage interest rates are negative (-), KOSPI, the negative (-) reacted. Liquidity and housing prices that the rise can be and Gangnam in Gangbuk is greater than the factor that housing investment was confirmed empirically. Government to consider the current economic situation, while maintaining low interest rates and liquidity of the market rather than the real estate industry must ensure that activities can be embedded and local enforcement policies should be differentiated according to the policy will be able to reap significant effect.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.2
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• pp.59-76
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• 2023

Since the COVID-19 era, the rise in apartment prices has been unconventional. In this uncertain real estate market, price prediction research is very important. In this paper, a model is created to predict the actual transaction price of future apartments after building a vast data set of 870,000 from 2015 to 2020 through data collection and crawling on various real estate sites and collecting as many variables as possible. This study first solved the multicollinearity problem by removing and combining variables. After that, a total of five variable selection algorithms were used to extract meaningful independent variables, such as Forward Selection, Backward Elimination, Stepwise Selection, L1 Regulation, and Principal Component Analysis(PCA). In addition, a total of four machine learning and deep learning algorithms were used for deep neural network(DNN), XGBoost, CatBoost, and Linear Regression to learn the model after hyperparameter optimization and compare predictive power between models. In the additional experiment, the experiment was conducted while changing the number of nodes and layers of the DNN to find the most appropriate number of nodes and layers. In conclusion, as a model with the best performance, the actual transaction price of apartments in 2021 was predicted and compared with the actual data in 2021. Through this, I am confident that machine learning and deep learning will help investors make the right decisions when purchasing homes in various economic situations.