• Title/Summary/Keyword: 주택 전세가격

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A Effect Analysis of the Housing Policy on the Housing Price (주택 ${\cdot}$ 부동산정책이 주택가격에 미치는 영향분석)

  • Noh, Jin-Ho;Han, Suk-Hee;Kim, Bong-Sik;Ko, Hyun;Kwon, Yong-Ho;Kim, Jae-Jun
    • Proceedings of the Korean Institute Of Construction Engineering and Management
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    • 2006.11a
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    • pp.665-668
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    • 2006
  • After foreign exchange trouble, Korean government became effective an economy-invigorating policy that to raise the housing demand and transaction. In result, the rate economic growth kept up a high growth rate and the market recovered. But an economy-invigorating policy of continuance caused an excessive boom of housing market in the second half of 2001. Therefore Korean government enforced a speculation-restraint policy. But it caused a instability of economics. This study is to analyze the effect between the housing policy and the housing cost and is to apply the basis data of the next housing policy.

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The Effect Factors affecting Lease Guaranteed Loan on Lease Market Fluctuation by Time Series Analysis Model (시계열 분석 모형을 이용한 전세시장 변동에 따른 전세보증대출 영향 요인에 관한 연구)

  • Jo, I-Un;Kim, Bo-Young
    • The Journal of the Korea Contents Association
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    • v.15 no.6
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    • pp.411-420
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    • 2015
  • With the rapid increase in the price of house lease, a unique housing form in Korea, a serious social issue has been raised as to the use value of house lease and residence stability of the ordinary people. This study thus aimed to analyze the direct factors that affect lease guaranteed loan and market volatility in order to explore the right direction of financial policy to reduce housing burdens. To this end, the direct variables affecting house lease guaranteed loan, including lease price, transaction price and lending rate, were defined. Vector Error Correction Model (VECM), a time series analysis, was employed to dynamically explain the data. Based on the house lease prices and bank data on loans between January 2010 and December 2014, it was found that the increase in lease price was the direct result of the increase in lease guaranteed loan, not that of the decrease in lending rate or increase in housing transaction price.

주택경기전망

  • 한국주택협회
    • 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

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A Study on the Effect of Macroeconomic Variables on Apartment Rental Housing Prices by Region and the Establishment of Prediction Model (거시경제변수가 지역 별 아파트 전세가격에 미치는 영향 및 예측모델 구축에 관한 연구)

  • Kim, Eun-Mi
    • 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

A Study of the Price Determinants for Public Residential Land Investment - From the Perspective of Land and Market Factors - (택지지구 공동주택용지의 투자가격 결정요인에 관한 연구 - 토지특성 및 시장요인 관점에서 -)

  • Choi, Kiheon;Lee, Sangyoub
    • 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.

A Study on the Influence of Macroeconomic Variables of the ADF Test Method Using Public Big Data on the Real Estate Market (공영 빅데이터를 활용한 ADF 검정법의 거시경제 변수가 부동산시장에 미치는 영향에 관한 연구)

  • Cho, Dae-Sik
    • The Journal of the Korea institute of electronic communication sciences
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    • v.12 no.3
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    • pp.499-506
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    • 2017
  • Consideration of influential factors through division of capital market sector and interest rate sector to find and resolve the problems in current housing market and leasing market will become an important index to prepare measures for stabilization of housing sales market and housing lease market. Furthermore, a guideline will be provide you with preliminary data using Big Data to prepare for sudden price fluctuation because expected economic crisis, stock market situation, and uncertain future financial crisis can be predicted which may help anticipate real estate price index such as housing sales price index and housing lease price index.

Influence of Liquidity on the Housing Market before and after Macroeconomic Fluctuations (거시경제변동 전후 유동성이 주택시장에 미치는 영향 분석)

  • Lee, Young-Hoon;Kim, Jae-Jun
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.17 no.5
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    • pp.116-124
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    • 2016
  • In the past, once apartments were built by housing construction companies, their presale went smoothly. Therefore, the developer and construction companies in Korea were extremely competitive in the housing market. However, when the 1997 foreign exchange crisis and 2008 global financial crisis occurred, the quantity of unsold new housing stocks rapidly increased, which caused construction companies to experience a serious liquidity crisis. This paper aims at analyzing the influence of Liquidity on the Housing Market before and after Macroeconomic Fluctuations using VECM. The periods from September 2001 to September 2008 and from October 2008 to October 2015, which were before and after the Subprime financial crisis, were set as Models 1 and 2, respectively. The results are as follows. First, it is important to develop a long-term policy for the housing transaction market to improve household incomes. Second, due to the shortage in the supply of jeonse housing, structural changes in the housing market have appeared. Thus, it is necessary to seek political measures to minimize the impact of transitional changes on the market.

부동산시장의 자금흐름에 관한 실증적 연구

  • Kim, Jong-Gwon
    • Proceedings of the Safety Management and Science Conference
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    • 2008.11a
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    • pp.441-455
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    • 2008
  • 본 논문은 단기 및 장기간에 걸쳐 부동산시장의 동태적 자금흐름과 수익률 분석에 초점을 맞추고 있다. 본 논문에서는 부동산시장의 실증적 동태적 자금흐름과 수익률 분석은 VAR모형을 사용하였으며 다양한 금융 및 경제관련 변수들을 연구에 포함시키고 있다. 실증적 분석 결과에 따르면 우리나라에서도 기존의 미국 연구 사례에서와 같이 금융시장의 자금흐름을 통하여 부동산시장의 동태적 자금흐름을 예측할 수 없다는 점을 파악할 수 있다. 또한 Granger 인과성 검정 결과에 따르면 통화정책 및 증권시장 변수 모두 전국아파트 매매가격, 전국 단독주택 매매가격, 전국 전세아파트 매매가격 실질상승률 등의 부동산관련 변수에 통계적으로 유의한 영향이 크지 않음을 알 수 있다. 그러나 분산분해 결과에 따르면 전국아파트 및 전국전세아파트 매매가격 실질상승률에 대한 움직임에 코스피수익률의 영향력이 증대될 수 있음을 알 수 있다.

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The Empirical Analysis about Structural Characteristics of the Housing Jeonse Price Change in Seoul (서울시 주택전세가격 변동양상에 대한 실증분석)

  • Jung, Yeong-Ki;Kim, Kyung-Hoon;Kim, Jae-Jun
    • Journal of The Korean Digital Architecture Interior Association
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    • v.12 no.1
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    • pp.89-98
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    • 2012
  • While the housing transaction price of Seoul tends to be stagnant or declining in line with the housing market recession since 2007, the jeonse price keeps continual increase. Such flow of jeonse price change has a serious influence on ordinary person's housing stability seriously. Therefore, it is very meaningful in terms of social policy to analyze the trend of recent jeonse price change. This study aims to have an empirical analysis of structural characteristics of the trend of recent jeonse price change. After the review of various previous studies, this study selected housing jeonse price index, non-sold house quantity, jeonse vs. transaction price rate, and housing construction performance as analytical variables, and employed monthly time series resources from January 2007 to April 2011. As a result, when the housing supply reduced, the potential quantity for jeonse market reduced that occurred unbalance of supply and demand in jeonse market. In turn, it caused the increase of jeonse price. And, in case of jeonse vs. transaction price rate change, the rate increased which means the increase of required rate of return of invested demand. As such, the increase of market risk degenerates the investment sentiment which caused the reduction of quantity for jeonse market as a submarket.

Comparison of the forecasting models with real estate price index (주택가격지수 모형의 비교연구)

  • Lim, Seong Sik
    • Journal of the Korean Data and Information Science Society
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    • v.27 no.6
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    • pp.1573-1583
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    • 2016
  • It is necessary to check mutual correlations between related variables because housing prices are influenced by a lot of variables of the economy both internally and externally. In this paper, employing the Granger causality test, we have validated interrelated relationship between the variables. In addition, there is cointegration associations in the results of the cointegration test between the variables. Therefore, an analysis using a vector error correction model including an error correction term has been attempted. As a result of the empirical comparative analysis of the forecasting performance with ARIMA and VAR models, it is confirmed that the forecasting performance by vector error correction model is superior to those of the former two models.