• Title/Summary/Keyword: 주택가격추정

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An Empirical Study on the long-term Relationship between House Prices and Inflation in the U.S. (주택가격과 물가의 장기관련성에 관한 실증연구 : 미국을 중심으로)

  • Lee, Young Soo
    • International Area Studies Review
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    • v.14 no.3
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    • pp.246-263
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    • 2010
  • This study examines how the long-run relations between housing price and inflation in the United Sates have changed since the year of 2000. Johansen co-integration test, estimation of long-run equilibrium equation, and Granger causality tests are conducted, based on the VECM. Data covers the period from the first quarter of 1975 to the second quarter of 2010. I adopt the recursive estimation method in which the final period of the estimation is expanded by one quarter, starting from the first quarter of 2000. The empirical results are as follows: (1) In spite of the sharp increase of housing price, the long-run relationship of house prices and inflation has been remained stable until 2007, showing that house prices are a stable inflation hedge in the long run. (2) The housing price plunge since 1997 does not seem to be related to the restore of the long-run relationship between housing prices and inflation. (3) Granger causality test results support the hypothesis that inflation granger-causes housing prices with 10% significance level, but reject the hypothesis that housing price granger-causes inflation.

How the Pattern Recognition Ability of Deep Learning Enhances Housing Price Estimation (딥러닝의 패턴 인식능력을 활용한 주택가격 추정)

  • Kim, Jinseok;Kim, Kyung-Min
    • Journal of the Economic Geographical Society of Korea
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    • v.25 no.1
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    • pp.183-201
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    • 2022
  • Estimating the implicit value of housing assets is a very important task for participants in the housing market. Until now, such estimations were usually carried out using multiple regression analysis based on the inherent characteristics of the estate. However, in this paper, we examine the estimation capabilities of the Artificial Neural Network(ANN) and its 'Deep Learning' faculty. To make use of the strength of the neural network model, which allows the recognition of patterns in data by modeling non-linear and complex relationships between variables, this study utilizes geographic coordinates (i.e. longitudinal/latitudinal points) as the locational factor of housing prices. Specifically, we built a dataset including structural and spatiotemporal factors based on the hedonic price model and compared the estimation performance of the models with and without geographic coordinate variables. The results show that high estimation performance can be achieved in ANN by explaining the spatial effect on housing prices through the geographic location.

Modelling Spatial Variation of Housevalue Determinants (주택가격 결정인자의 공간적 다양성 모델링)

  • Kang Youngok
    • Journal of the Korean Geographical Society
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    • v.39 no.6 s.105
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    • pp.907-921
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    • 2004
  • Lots of characteristics such as dwelling, neighborhood, and accessibility characteristics affect to the housevalue. Many researches have been done to identify values of each characteristic using hedonic technique. However, there is a limit to identify interaction of each characteristic and variation of each characteristic among the accessibility context. This paper has implemented the Expansion Method research paradigm to model the housevalue determination process in the city of Seoul. The findings of this paper have revealed the presence of contextual variations in the housevalue determination process. The initial model for housevalue reveals that as $F_1$ increases (i.e., larger the number of rooms/bathrooms, larger parking space) and/or $F_2$ increases (i.e., higher owner occupied housing units, higher apartment housing units) and/or $F_3$ increases, (i.e., higher the ratio of higher than college graduated households, 8 school zone, older housing units) the estimated housevalue increases. However, the above relationships drift across their respective contexts. The houses which have negative $F_1$ value, the housevalue does not fluctuate according to the distance to the city center or subcenters. However, the houses which have positive $F_1$ value, the closer to the subcenters or shorter to the river, the higher the estimated housevalues. On the other hand, in areas far from the subcenters, the estimated housevalues does not fluctuate much according to the corresponding $F_2$ level. In areas close to the subcenters, the estimated housevalues vary tremendously according to the $F_2$ value. In the residual analysis, it is revealed that large apartment which are located in Kangnam, IchongDong, MokDong are underestimated. This paper has contributed to our understanding of the housevalue determination process by providing an alternative conceptualization to the traditional approach.

Effects of Airport Noise on the Household Property Values (항공기 소음기 주택가격에 미치는 영향)

  • Lee, Sung Tae;Lee, Kwangsuck
    • Environmental and Resource Economics Review
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    • v.10 no.4
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    • pp.483-494
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    • 2001
  • 본 연구는 항공기 소음이 주택가격에 미치는 영향을 헤도닉가격기법을 적용하여 분석하고자 하였다. 국제공항이 인천으로 이전하기 전 서울지방항공청장이 소음피해지역(제1종, 제2종 및 제3종)으로 고시한 김포공항 주변의 아파트 가격을 주요 분석 대상으로 하였다. 소음측정단위로는 세계민간항공기구가 권장하는 연속적 동등소음감지단위(Weight Equivalent Continuous Perceived Noise Level: WECPNL)를 사용하였다. 2000년도 여름에 매매된 총 220가구를 대상으로 아파트의 실질거래가격과 소음측정단위, 가구속성 및 지역관련 변수를 사용하여 헤도닉 방정식을 추정한 결과 소음변수를 비롯 아파트 평수 및 방의 개수를 나타내는 변수에 대한 계수의 추정치는 통계적으로 매우 유의적으로 나타났다. 분석대상지역에 있어 항공기 소음의 한계내포가격은 평균 마이너스 340여 만 원으로 추정되었다. 이 추정치는 다시 말해 소음감지단위인 WECPNL이 한 단위 증가하게 되면 아파트의 평균매매 가격의 3.19%가 떨어지는 것을 의미하며 이 지역이 소음피해지역으로 고시되어 있는 상황을 매우 잘 나타내고 있었다.

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Fuzzy Hedonic Analysis of Airport Noise (공항 소음에 대한 퍼지 헤도닉 분석)

  • Lee, Sung Tae;Lee, Kwangsuck
    • Environmental and Resource Economics Review
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    • v.17 no.1
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    • pp.147-164
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    • 2008
  • When measuring the value of environmental attributes of housing, the conventional Hedonic Pricing Method assumes market equilibrium. Thus each attribute is believed to be implicitly valued based on the market price. The revealed preference is the basic logic in this approach. However, if the participants in the housing market are not perfectly informed or feel vagueness regarding the attributes of the housing, the conventional Hedonic Pricing Approach could not provide relevant value of the attribute in question. A Fuzzy Regression Method is suggested to handle with the lack of information or preference uncertainty problem m the Hedonic Pricing Approach. In this paper, our main concern IS given to the fuzziness effect on the airport noise in the metropolitan areas of South Korea.

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Estimation of the Value of Road Traffic Noise within Apartment Housing Prices (아파트가격에 내재된 도로교통소음가치 추정)

  • 임영태;손의영
    • Journal of Korean Society of Transportation
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    • v.19 no.4
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    • pp.19-33
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    • 2001
  • In the developed countries, traffic noise is one of most serious problems faced by people's lives. So the importance of the traffic noise is quite well recognized by the infrastructure planners as well as the people. The traffic noise is valued in monetary terms in some countries and it is reflected in estimating the net present value or benefit/cost ratio. On the contrary, the effects of traffic noise are not reflected in the assessment of infrastructure in most cases in Korea. However, as the income level has been increasing, more people have been becoming to put more importance on their living conditions. The purpose of this paper is to estimate the value of traffic noise in the Seoul metropolitan area. The housing price were surveyed to use the quasi-hedonic price technique. By this way, two housing prices at the same floor level in different 128 complexes in the Seoul metropolitan area were surveyed. the actual traffic noise level was also measured. The differences of housing prices and noise levels were analyzed using the various types of regression models. The value is quite different by size of house. The value of large house is higher than that of small house. Since the income level of people in large house is higher than that in small house. it might be said that value of traffic noise for high income people is higher than that for low income people. Moreover, the increase of 1dB(A) noise affects the house price by about 0.3% in Seoul metropolitan area.

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주택가격(住宅價格)에 내재(內在)된 대기질(大氣質)의 가격측정(價格測定) - 공간계량경제모형(空間計量經濟模型)을 이용한 접근(接近) -

  • Kim, Jong-Won
    • Environmental and Resource Economics Review
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    • v.7 no.1
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    • pp.61-84
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    • 1997
  • 본 연구는 기존의 특성가격기법(特性價格技法)(hedonic price technique)에 공간(空間)개념을 도입한 계량경제모형을 이용하여 분석하였다. 이 공간시차모형은 기존의 모형과 달리 특성변수의 변화에 따른 직(直) 간접효과(間接效果)를 동시에 포착할 수 있는 장점을 가지고 있다. 또한 공간시차모형의 회귀진단 및 가설검정 결과는 공간시차모형이 적합한 것으로 나타났다. 이 경우 공간시차를 고려하지 않은 OLS 회귀분석 결과의 계수들은 편기추정(biased)된 동시에 효율적(efficiency)이지 못하다는 것이다. 회귀분석 결과는 주택에 자본화된 대기오염에 대한 잠재가격(潛在價格)(marginal implicit price)은 주택평균가격의 약 1.5% 정도인 것으로 추정된다.

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쓰례기 매립장 기피의사 추정: 수도권 매립장의 사례

  • Kim, Gwang-Im
    • Environmental and Resource Economics Review
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    • v.5 no.2
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    • pp.303-315
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    • 1996
  • 폐기물 오염문제에 대한 국민적 인지도가 높아지면서 폐기물 처리시설에 대한 주민의 반대는 최근 커다란 사회적인 문제로 등장하고 있다. 혐오시설인 매립장의 입지를 반대하는 현상은 개인의 효용을 중시하는 경제주체의 경제행태 논리상 무시할 수 없는 현상이다. 주택가격과 주택까지의 거리와의 함수관계를 파악함으로써 주변지역주민들의 매립장 기피의사를 파악하고자 하였다. 추정결과 주택가격으로 지불하는 금액을 통해서 주민들이 매립장을 피하기 위해 부담하고자 하는 의사는 유의성이 있었다. 비용부담의사는 매립장과 가까이 거주할수록 높았고, 거리가 멀어짐에 따라 감소하는 것으로 나타났다.

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House Price Channel: Effects of House Prices on Macroeconomy (주택가격채널: 거시경제에 미치는 영향을 중심으로)

  • Song, Inho
    • KDI Journal of Economic Policy
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    • v.36 no.4
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    • pp.171-205
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    • 2014
  • This paper investigates the manner in which house prices affect macroeconomic variables through a house price channel by applying the method of Iacoviello (2005) to Korean data, and establishing a DSGE model with complementarity. This paper found that higher LTV ratio coupled with stronger complementarity results in the co-movement in both consumption and housing. For instance, the results show that when the LTV ratio and complementarity stands respectively at 50% and 0.42, an 1% rise in house prices increases consumption by 0.057%, and when the complementarity parameter increases to 0.52 with LTV remains unchanged at 50%, consumption rises by 0.047% per 1% increase in house prices. An increase in house prices leads credit constraints for borrowers to become more loose as value of a house rises as a collateral. The increase in household credit enables more consumer spending, eventually leading to increased consumption. A key link in which house prices are connected to macroeconomic variables is change in consumption. To put it simply, a rise in house prices leads to an increase in consumption, which consequently impacts the overall macro-economy. At this point, complementarity is found, in that the elasticity of intra-temporal substitution between housing and consumption is estimated at 0.42, which plays an important role in the house price channel by amplifying the effects of house prices on consumption.

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헤도닉 가격모형의 함수형태 - 시장특성을 감안한 변환함수들의 적용 및 검증 -

  • Heo, Se-Rim;Gwak, Seung-Jun
    • Environmental and Resource Economics Review
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    • v.5 no.2
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    • pp.291-302
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    • 1996
  • 환경질 개선의 편익추정에 사용되는 헤도닉 가격모형에서 제1단계 헤도닉 함수 추정시 그 함수형태에 따라 결과가 편의를 가질 수 있다. 본 논문에서는 13가지의 각기 다른 비선형 및 선형 헤도닉 함수 등을 한국 주택시장에 적용하여 그 적합성을 이론 및 실증적 방법을 병행하여 검증하였다. 그 결과, 고전적으로 종속변수만을 변환시키는 Box-Cox 함수형태나 Box-Cox 변형계수가 사전적으로 0과 1사이에 있음을 가정하는 오목한(concave) 한 함수형태가 기존 연구와는 달리 한국시장에는 적합한 함수형태가 아니라는 결과를 이끌어 냈다. 나아가 서울 주택시장에 가장 적합한 함수형태는 종속 및 독립변수를 각각 다르게 변환시키는 헤도닉 함수형태임을 보여 주었다. 아울러 본 연구는 간접적으로 헤도닉 가격모형 적용시 그 지역의 주택시장 특성에 관한 연구가 선행되어야 함을 시사하고 있다.

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