• Title/Summary/Keyword: 전세(田稅)

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전세(傳貰)의 경제적(經濟的) 효과(效果)와 개선방안(改善方案)

  • Park, Won-Am;Kim, Gwan-Yeong
    • KDI Journal of Economic Policy
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    • v.15 no.1
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    • pp.87-116
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    • 1993
  • 전세제도(傳貰制度)는 공공임대주택(公共賃貸住宅)이 존재하지 않고 제도금융권의 주택금융이 미약한 상황에서 유지되어 온 우리나라 특유의 주거점유형태(住居占有形態)이다. 그러나 불완전한 우리의 주택시장 여건하에서 전세임대차(傳貰賃貸借)에 따르는 위험부담이 임차자(賃借者)에게 전가되는 등 불필요한 사회적 비용을 초래하고 있다. 따라서 현존의 전세제도(傳貰制度)를 개선하기 위하여 공공임대주택(公共賃貸住宅)을 늘리고 월세전환(月貰轉換)으로의 유인책을 제공하여야 한다. 아울러 20조(兆)원이 넘는 전세보증금(傳貰保證金)을 주택부문 자금으로 쓸 수 있도록 전세기금(傳貰基金)을 설치하는 등 전세제도(傳貰制度)를 개선하여야 한다. 종국적으로 전세제도(傳貰制度)가 사라지더라도 사회 일각에서 우려하는 저축감소효과는 거의 없을 것이다.

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A Factor Analysis and Regression-Based Prediction Model of Security Deposit Scam Amount for Preventing Rental Scam (부동산 전세사기 예방을 위한 요인 분석 및 회귀 분석 기반 전세보증사고 금액 예측 모델)

  • Seo Jung Ha;Se Hyeon Oh;Soh Jung Ban;Ji Youn Lee;Hyon Hee Kim
    • Annual Conference of KIPS
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    • 2024.05a
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    • pp.554-555
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    • 2024
  • 전세 사기로 인한 피해가 해마다 증가하고 있다. 본 연구에서는 부동산 가격과 대출 데이터를 통해 전세 사기의 원인을 분석하고, 이에 대한 대처방안을 제시하였다. 데이터 분석 결과, 주택 가격의 상승과 부동산 정책의 변화가 전세사기에 주요한 영향을 미친다는 것과, 전세사기 사건 수와 부동산 가격 상승 사이에 높은 상관관계가 나타남을 확인했다. 또한, 회귀분석을 사용하여 연도에 따른 전세보증사고 금액 예측 모델을 구축하였다. 이를 토대로 부동산 시장 안정화와 함께 개인 및 정부 차원의 협력이 강화된다면 전세사기 피해를 줄일 수 있을 것이라 기대된다.

The Spillover Effect of Public Hosing Policy on Rental Housing Market: The Case of Seoul, Korea (공공임대주택이 주변 전세시장에 미치는 효과: 서울시 장기전세주택(SHIFT)의 경우)

  • Yang, Jun-Seok
    • Journal of the Economic Geographical Society of Korea
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    • v.20 no.3
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    • pp.405-418
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    • 2017
  • SHIFT is public rental housing policy introduced by Seoul Metropolitan in 2007, which works as Chonsei(korean unique deposit rental system). This paper examines the effect of SHIFT on Chonsei prices of neighborhood apartments. To estimate the change in prices of Chonsei after the provision of SHIFT, I collect data on Chonsei prices of apartments within a 5km radius from the SHIFT housings. Summary of main results are following. Chonsei prices of the apartments within a 2-3km radius decreased by 4.4% after the provision of SHIFT housings. In contrast, when it comes to apartments within a 1-2km radius, I can't find the stochastic relationship between the provision of SHIFT hosing and price changes. This results can be explained by "Offset effects" caused by real estate development. Provision of SHIFT can sequentially induce nearby area's development, which plays a factor in the effect of price increases. And this offset effects varies in each apartment complex depending on demand for Chonsei and supply of the SHIFT.

The Effects of Expected Rate for Housing Sale Price on Jeonse Price Ratio - Focused on Markets in Seoul - (매매가격에 대한 기대상승률이 전세가격비율에 미치는 영향 - 서울시를 중심으로 -)

  • Lee, Ji-Young;Ahn, Jeong-Keun
    • Journal of Cadastre & Land InformatiX
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    • v.45 no.2
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    • pp.203-216
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    • 2015
  • This study focuses on the relationship between housing sale prices and Jeonse prices, amid a recent surge of Jeonse price and Jeonse-to-housing sale price ratio. There are many studies about the relationship between house prices and Jeonse, but they couldn't fully explain what makes them spike up. In addition to this relationship, this paper deals with the difference of Jeonse system on regions and price levels. Using Granger causality and Spearman's Correlation Coefficient, the outcome is drawn. As the result, the expected rate for housing sale prices effects on the Jeonse-to-housing sale price ratio. The higher on sale price, the lower the Jeonse-to-housing sale price ratio regarding the region difference.

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.

A study on the Ratio of jeonse to purchase price for apartment after IMF (IMF이후 아파트 전세가율에 관한 연구)

  • Ko, Pill-Song;Kim, Dong-Hyun
    • The Journal of the Korea institute of electronic communication sciences
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    • v.8 no.2
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    • pp.301-306
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    • 2013
  • The Ratio of APT jeonse to purchase price was still rising. The interaction of APT Purchase and Jeonse price indices by region analysis in order to analyze this phenomenon, and results were summarized as follows. First, because the regional APT purchase and jeonse prices appears the rise and fall differently by region, regional polarization was deepening. Second, the recently real estate market was analyzed the province's booming real estate and the downturn of the metropolitan area. So, the ratio of APT jeonse to purchase price was continued to rise. Finally, the Ratio of APT jeonse to purchase price changing rate is (+) increased if the APT purchase price changing rate is larger then the APT purchase price changing rate and smaller then is (-) decreased.

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

강남.강북의 전세 가격 양극화

  • 송복규
    • 주택과사람들
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    • s.221
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    • pp.60-63
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    • 2008
  • 강남권에서 전셋값이 크게 하락하고 있다. 주된 원인은 대규모 재건축 아파트 입주가 시작되면서 공급이 크게 증가했기 때문이다. 반면, 강북 지역 전셋값은 천정부지로 치솟고 있다. 전세난을 겪고 있는 서울 지역 전세 시장의 해결책은 무엇일까?

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올 봄 전세 시장 안정이 집값 안정의 시금석

  • Cha, Hak-Bong
    • 주택과사람들
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    • s.201
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    • pp.42-45
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    • 2007
  • 올 봄에도 이사철이면 어김없이 나타났던 '고질병'인 전세난이 재현될 거라는 염려가 커지고 있다. 수요가 몰리는 수도권 입주량이 지난해보다 감소할 전망이어서 수급 불균형에 다른 전세난은 불가피하다는 게 관련 업계의 전망이다. 이에 따라 정부에서는 중장기적으로 얼마나 큰 영향력을 발휘할 수 있을 지 의문이다.

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A Study on the Effect of Chonsei Price Increase on the Index of Financial Industry (전세가격상승이 금융산업 생산지수에 미치는 영향에 관한 연구)

  • Jo, I-Un;Kim, Bo-Young
    • The Journal of the Korea Contents Association
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    • v.15 no.10
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    • pp.457-467
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    • 2015
  • Despite the recent phenomena of Chonsei price increase, low interest rate and low growth, the indexes of financial and insurance industry production showed the results contrary to the common belief that the financial industry is sensitive to such financial crises. This is because the index of financial industry has continuously maintained a certain level of increase as opposed to the index of all industry production. Thus, this study aimed to analyze the dynamic correlation between the index of financial industry production and Chonsei price increase. A vector autoregression (VAR) model, which doesn't have a cointegrating relationship, was used to define the Chonsei price index and the indexes of all industry production and financial and insurance industry, which are macro economic variables, and describe the data. The results of the analysis on the time series data of 183 months from January 2000 to May 2015 showed that Chonsei price increase was not directly derived from the index of financial industry, but the finance industrial index affected Chonsei price increase.