• 경영과정보연구
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• 제25권
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• pp.321-337
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• 2008

The house price rise suddenly is not only Economic stability but economic, mental state of a heavy burden to people. This paper is a house finance environment analyzed in this research about the rise factor of the house price and the result to present the plan to the natural disposition. The financial institute has an influence on the disguised demand extension of the house and The mortgage Lending in commercial Banks with the earnings as the stability high than the industry loaning. A house finance environment changes and will go from economic factor of the variety of the life style, the housing conditional according to the income level, a children education condition, and the population structure many this little. The disposition of the house need changes according to this and will have an influence on the house price. Necessary for a house market environment house policy of the market need which the consistency reflects so that we are suitable and is desired.

• 한국주거학회:학술대회논문집
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• 한국주거학회 2005년도 추계학술대회 논문집
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• pp.115-119
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• 2005

This study is to examine changes since autonomy of lotting-out price of apartment house and planning factors related to sale of apartment house through leaflet of sale of apartment house. Objects of the study were leaflets of sale of apartment houses through the Donga Il Bo daily newspaper from 2001 to 2003. The results of research can be summarized to three. First, traffic of locational factors in advertisement of sale of apartment house showed the highest frequency and it was found that it was an important planning factor of apartment house. Second, considering that advanced facilities and the highest finishing materials were used, quality of apartment house has been advanced. Third, considering that community space, theme park and green zone showed high occupancy in external space, there has been high increase in external space as well as in internal one since autonomy of lotting-out price.

• Soft Computing and Machine Intelligence
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• 제1권1호
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• pp.11-23
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• 2021

House price prediction is a significant financial decision for individuals working in the housing market as well as for potential buyers. From investment to buying a house for residence, a person investing in the housing market is interested in the potential gain. This paper presents machine learning algorithms to develop intelligent regressions models for House price prediction. The proposed research methodology consists of four stages, namely Data Collection, Pre Processing the data collected and transforming it to the best format, developing intelligent models using machine learning algorithms, training, testing, and validating the model on house prices of the housing market in the Capital, Islamabad. The data used for model validation and testing is the asking price from online property stores, which provide a reasonable estimate of the city housing market. The prediction model can significantly assist in the prediction of future housing prices in Pakistan. The regression results are encouraging and give promising directions for future prediction work on the collected dataset.

• 산경연구논집
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• 제11권8호
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• pp.31-38
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• 2020

Purpose: This study uses 'Autoregressive Integrated Moving Average Model' to predict the impact of a sharp drop in the base rate due to COVID-19 at the present time when government policies for stabilizing house prices are in progress. The purpose of this study is to predict implications for the direction of the government's house policy by predicting changes in house transaction prices and house rental prices after a sharp cut in the base rate. Research design, data, and methodology: The ARIMA intervention model can build a model without additional information with just one time series. Therefore, it is a time-series analysis method frequently used for short-term prediction. After the subprime mortgage, which had shocked since the global financial crisis in April 2007, the bank's interest rate in 2020 is set at a time point close to zero at 0.75%. After that, the model was estimated using the interest rate fluctuations for the Bank of Korea base interest rate, the house transaction price index, and the house rental price index as event variables. Results: In predicting the change in house transaction price due to interest rate intervention, the house transaction price index due to the fall in interest rates was predicted to change after 3 months. As a result, it was 102.47 in April 2020, 102.87 in May 2020, and 103.21 in June 2020. It was expected to rise in the short term. In forecasting the change in house rental price due to interest rate intervention, the house rental price index due to the drop in interest rate was predicted to change after 3 months. As a result, it was 97.76 in April 2020, 97.85 in May 2020, and 97.97 in June 2020. It was expected to rise in the short term. Conclusions: If low interest rates continue to stimulate the contracted economy caused by COVID-19, it seems that there is ample room for house transaction and rental prices to rise amid low growth. Therefore, In order to stabilize the house price due to the low interest rate situation, it is considered that additional measures are needed to suppress speculative demand.

• 한국건설관리학회논문집
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• 제18권6호
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• pp.89-97
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• 2017

경제발전에 따라 사람들의 생활수준이 향상되면서 새로운 주거공간을 원하고 있다. 시간이 지날수록 노후 공동주택은 늘어날 것으로 전망 되므로 공동주택 리모델링 사업에 활용 가능한 사업성 평가방법을 통해 향후 확대되는 리모델링 시장의 준비가 필요하다. 본 연구에서는 공동주택 맞춤형 리모델링 사업성 분석모델을 위해서 건축물의 공시가격에 영향을 미치는 사회적 가격형성요인을 분석하는 것이 목적이다. 수집된 표본은 127개 단지에 포함된 평형 별 350개 동을 활용하여 공시가격에 대한 다중회귀분석하였다. 중고수준, 고교수준, 총 세대수, 용적률이 추출되었고, 리모델링 사례에 적용하여 공시가격 비교 분석한 결과 기존 공시가격과 개선공시가격의 차이는 1억 4천8백만 원으로 분석되었다. 지하철역과의 접근성은 지가에 포함되었고, 맞춤형 리모델링이므로 최고층수와 향의 변화는 없다. 평가자가 공시가격요인을 일괄 적용하여 요인 추출 하는 종류에 따라 공시가격에 차이가 발생하였다. 본 연구는 향후 맞춤형 리모델링 사업성 분석 모델로 활용가능하다.

• The Journal of Asian Finance, Economics and Business
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• 제8권7호
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• pp.671-679
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• 2021

House ownership is considered as one of the important pre-conditions for marriage in China. Given that gender imbalance is a prominent issue in the country, competition for marriage partners might motivate males to look for a house and probably bigger and more expensive house. This is believed to have caused house price hikes in recent years. This study aims to investigate the impact of gender imbalance on house prices using data from 30 provinces in China for the 2000-2017 period. The results based on the generalized method of moments (GMM) estimations show that house price is strongly influenced by gender imbalance. However, there is no evidence to support differential effects across eastern and mid-western regions. One potential reason is that pre-marriage house ownership has become a common culture for the whole community and therefore it does not vary significantly across regions. There are several important policy implications. Firstly, the issues should be addressed by the policymakers at national level and not regional level. Secondly, the government should intervene to bring back gender ratio to its normal level. Finally, the government should limit the number of houses people can buy and increase the supply of houses in the market.

• 응용통계연구
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• 제4권2호
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• pp.137-148
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• 1991

전국 도시 주택가격 동향조사의 목적은 전국 주요 도시의 주택가격 변동상황을 측정하여 주택시장의 동향을 파악함으로써 주택금융 및 정책수립에 기초자료를 제공하는데 있다. 본 조사는 1981년 12월에 최초로 실시한 이후 조사체계를 확대 개선하여 1985년 9월 경제기획원으로부터 일반 통계승인을 받아 실시함으로써 각종 주택정책 및 주택금융의 기초자료로 활용되어 왔다(한국주택은행, 1988).

• 대한지리학회지
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• 제43권1호
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• pp.104-116
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• 2008

투기과열지역은 투기의 발생 가능성이 높은 지역으로, 각종 부동산대책의 주요 대상이 된다. 본 연구에서는 부동산 가격변동의 공간패턴을 모형화함으로써 투기과열지역의 공간패턴을 제안하고자 한다. 부동산 가격은 합리적 또는 적응적 소유자 수요자의 경계행위에 의해서 결정되고, 가격변동의 공간패턴은 이들의 경제행위 경향에 의해서 형성된다고 모형화하였다. 일정 지역에 적응적 소유자와 수요자가 다수인 경우, 이 지역은 타 지역에 비해 가격상승 폭이 높고 주변 부동산과 가격상승이 동시에 일어나는 가격변동 핫스팟 패턴으로 정의하였다. 투기과열지역은 최대의 미래 기대이익을 얻고자하는 적응적 소유자와 수요자에 의해서 형성되기 때문에 이 지역의 공간패턴은 가격변동 핫스팟 패턴으로 정의할 수 있었다.

• 한국건설관리학회논문집
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• 제13권2호
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• pp.128-136
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• 2012

본 연구에서는 부동산 시장뿐만 아니라 우리 생활에 많은 비중을 차지하는 주택 가격에 영향을 미치는 거시경제변수에 대해 살펴보았다. 주택 전세가격에 영향을 미칠 것으로 파악되는 거시경제변수로는 가계대출금리, 가계예금총액, 취업자 수로 분석모형을 설정하였으며, 각 변수에 대한 시계열 자료를 활용하여 다중회귀분석을 실시하였다. 분석한 결과에 따르면, 주택 전세가격은 네 가지 거시경제변수 모두에 영향을 받으며 각각의 변수가 높아질수록 전세가격 또한 상승하는 것으로 나타났다. 본 연구결과를 통해 주택 전세가격 안정화를 위한 해결책을 모색하고, 효율적이고 지속 가능한 주택시장 정책을 수립할 수 있을 것이다.

• 국토계획
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• 제54권2호
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• pp.54-66
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• 2019

This study analyzed whether a subway accessibility impact on house price is constant since its operation over time or not. The study was approached specifically to answer two research questions. One is "Are there significant temporal variations in the relationship between subway accessibility and housing price transacted after its opening?" The other one is "How the pattern of its temporal variation in housing price is formed as a function of the distance from the nearest station?" The study area is the subway station areas in the Daejeon metropolitan city, South Korea. Its first subway line has started to be opened in 2006 with 12 stations and then opened its additional 10 stations in 2007. It can be more appropriate to observe its impacts of subway accessibility on housing price because it has only one transit line with more than 10-year reaction term to its operation. The study employed alternative models to estimate yearly variation of subway accessibility on house price for the station areas with 500-meter and 1-kilometer radius respectively. While the study originally considered both a hedonic price model with interaction terms of its access distance to yearly transacted housing and a time-variant random coefficient model, the former model was finally selected because it is better fitted. Based on our analysis results, the reaction of house price to its transit line had significant temporal variation over time after opening. In addition, the pattern in its variation from our analysis results indicates that its capitalization impact on house price is over-estimated in its first several years after the opening. In addition, its positive capitalization impact is more effective in the 1000-meter station area than in the 500-meter one.