• 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.

• Korean Journal of Construction Engineering and Management
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• v.16 no.6
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• pp.3-11
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• 2015

The current real estate market is in a state that is considerably shrink due to the recession and long-term reduction of trading. In response, the government recently announced an innovative way for the middle-class residential housing and it is taking the lead to activate the real estate market. Meanwhile, the domestic housing market is entering a transition period, including structural changes of household structure, changes from joeonse to rent increasingly. Also single-member households will rise steeply, so that makes the high demand of small houses. In addition, the domestic construction industry is interested in new technology called Modular building. The Modular construction is an off-site construction system that shorten construction period, eco-friendly building technology and mobility etc, which can be used in various field. Overall, there are two major issues of the current market, one is the change of the real estate market, and the other is the modular construction. This study will propose modular business model in the rental market through the analysis the profitability of the modular business scenarios and IRR analysis.

• East Asian Journal of Business Economics (EAJBE)
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• v.8 no.1
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• pp.57-69
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• 2020

Purpose - This study examines what are the asset market fluctuations in Europe and how each economic variable affects major variables, and explore the dynamics of housing and stock market through Greece. The variables under consideration are balance on current account (BCA), index of stock (STOCK), gross domestic product (GDP), housing price indices (HOUSING), M3, real rate of interest (IR_REAL) and household credits (LOAN). We investigate the functional and causal relationships between housing and stock market. Research design, data, and methodology - Vector error correction model (VECM) is used to figure out the dynamic relationships among variables. This study also contains the augmented Dickey-Fuller unit root, cointegration, Granger causality test, and impulse response function and variance decomposition analysis by EViews 11.0. Results - The statistical tests show that all variables under consideration have one unit root and there is a longterm equilibrium relationship among variables for Greece. GDP, IR_REAL, M3, STOCK and LOAN can be considered as causal factors to affect real estate market, while GDP, LOAN, M3, BCA and HOUSING can bring direct effects to stock market in Greece. Conclusions - It can be judged that the policy that affects the lending policy of financial institutions may be more effective than the indirect variable such as monetary interest rate.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.4
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• pp.228-234
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• 2021

Real estate market participants need to have a sense of predicting real estate prices in decision-making. Commonly used methodologies, such as regression analysis, ARIMA, and VAR, have limitations in predicting the value of an asset, which fluctuates due to unknown variables. Therefore, to mitigate the limitations, an artificial neural was is used to predict the price trend of apartments in Seoul, the hottest real estate market in South Korea. For artificial neural network learning, the learning model is designed with 12 variables, which are divided into macro and micro factors. The study was conducted in three ways: (Ed note: What is the difference between case 1 and 2? Is case 1 micro factors?)CASE1 with macro factors, CASE2 with macro factors, and CASE3 with the combination of both factors. As a result, CASE1 and CASE2 show 87.5% predictive accuracy during the two-year experiment, and CASE3 shows 95.8%. This study defines various factors affecting apartment prices in macro and microscopic terms. The study also proposes an artificial network technique in predicting the price trend of apartments and analyzes its effectiveness. Therefore, it is expected that the recently developed learning technique can be applied to the real estate industry, enabling more efficient decision-making by market participants.

• Land and Housing Review
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• v.15 no.3
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• pp.113-127
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• 2024

This study explores shifts in real estate investment sentiment using media reports from 2012 to 2022, segmenting the market dynamics into three distinct cycles based on housing and land transaction indices. Leveraging 54 BigKinds media sources, we investigates 3,387 headlines and 8,544 body texts using LDA topic modeling. The results show that the first cycle (2012-2015 ) centered on apartment pre-sales, where policy changes influenced sentiment but did not consistently affect investment decisions. The second cycle (2016-2018) was characterized by interest rate hikes and rising property prices in Seoul, resulting in significant fluctuations in transaction volumes. The third cycle (2019-2022) encompassed the effects of COVID-19, market instability, and policy failures, leading to distorted and weakened investment sentiment. Each cycle demonstrated that policies, interest rates, and economic events significantly shaped investor sentiment, as reflected in media reports.

• Journal of the Korean Regional Science Association
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• v.36 no.1
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• pp.37-50
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• 2020

Estimating investment profits of real estate is critical to understand real estate markets and create relevant policy as real estate market and capital market combines closely. Thus, this study applied the concept of Tobin's Q to estimate investment profits for apartments as well as row-houses and multi-family homes in Seoul from 2010 to 2018. Investment profits were estimated by two approaches: subtracting the replacement cost from the transaction price and calculating ratio of the transaction price to the replacement cost, respectively. The spatio-temporal changes in investment profits were apparent in apartments compared with row-houses and multi-family homes. As a result of analyzing the spatial econometrics models, the investment profit was higher in the area with high density and new developments regardless of the housing types. The framework and key findings would be the effective reference to understand residential investment behavior, create relevant housing policy, introduce value capture of windfall, measure regional competitiveness, and estimate housing bubble.

• The Journal of Information Technology
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• v.6 no.3
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• pp.53-64
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• 2003

The purpose of this study is to examine the valuation models and valuation factors for the valuation of real estates. In Korea, the weak market conditions prevented investors from the sound investing the real estates. To develop the real estate investment market, we need the information of sale prices, volume, vacancy rates, and regulatory policies to the various types, and areas of the real estates. In addition, we have to develop the indirect investing methods such as REITs.

• International Journal of Human Ecology
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• v.7 no.2
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• pp.53-62
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• 2006

The purpose of this study is to examine the changes in financial structure of the self-employed brought on the economic crisis in Korea.. We use financial ratio analysis, such as income to expenditure ratio, liquidity ratio, debt ratio, and capital accumulation ratio to analyze financial well-being of self-employed households. This study used a 1997 and 1998 Korean Household Panel Study collected by Daewoo Economic Research Institute. The average amount of holding of each type of asset showed that the investment of self-employed households decreased in the banking industry and the stock market in 1998 compared to 1997. On the other hand, asset allocation in bond and real estate increased, which implied preference for a stable type of asset with the increase in uncertainty of the future and economic instability. Devaluation of real estate allowed households to easily obtain real estate and increase preference for asset allocation in real estate after the crisis. The changes in financial ratio for the year 1998 shows that such ratios as income to expenditure, liquidity, and capital accumulation, decreased compared to the year 1997. Among those ratios, the income to expenditure ratio showed the biggest decline because of reduced income of self employed households. The results implied that the income structure of the self-employed is unstable, thus the self-employed were likely to be greatly affected during the economic downturn. Earners have more average income and net assets than the self-employed. However, using financial ratios, it was found that self-employed households were more stable than employees. The results shows that the financial ratio analysis is better tool to estimate households financial status. Implications for financial educators, counselors, and planners are offered. The results will provide implications for policy makers to establish appropriate policies for the self-employed and help them financially survive.

• Information Systems Review
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• v.22 no.3
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• pp.15-30
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• 2020

In the real estate industry, the latest changes in the Fourth Industrial Revolution, such as big data analytics, machine learning, and VR (virtual reality), combine to bring about industry change. Proptech is a new term combining properties and technology. This study aims to derive and analyze from a comprehensive perspective the quality factors (systems, services, interfaces, information) for mobile real estate brokerage services that are well known and used in the domestic market. The surveys in this study were conducted online and offline and a total of 161 samples were used for statistical analysis. As a result, all hypotheses were approved to except system quality and service quality. The results show that the domestic proptech companies who are mostly focused on real estate brokerage services, peer-to-peer lending, advertising platforms and apartments need to grow in various fields of proptech business of other countries including Europe, USA and China.

• 주택과사람들
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• s.224
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• pp.32-32
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• 2008

2009년 부동산 시장이 밝았다. 하지만 현 부동산 시장 상황은 10년 전, 1998년으로 되돌아간 듯하다. 헐값으로 나온 오피스 빌딩을 외국계 자본이 노리고 있고, 양도세 일시 감면 투기 지역 투기과열지구 해제 등 각종 부동한 규제책들이 무장 해제되고 있다. 지난달 부동산 시장의 단면들을 담은 주요 이슈들을 정리했다.