한국과 일본의 주택시장에 관한 연구 : 임대가격결정요인과 장기주택가격을 중심으로

송인호(Song, In-Ho) 한국부동산정책학회 2016 不動産政策硏究 Vol.17 No.2

Housing prices in Japan peaked in 1990, and both of its nominal and real prices have fallen since then, signalling continuing deflation. In the meantime, Korea’ nominal housing prices have risen consistently, that is different from Japan’s nominal housing prices. According to rental price determinants, Korea’s housing prices in 1990 were overvalued, and according to long-term housing price determinants, prices in 1990, 2002~2004 and 2007~2008 were overvalued. On the other hand, Japan’s housing prices observed in 1989~1990 were overvalued, deviating far not only from the price trend line but also from the long-term housing prices influenced by fundamental factors. The results show that in Japan, since the time it entered the aging society, the elderly population proportion has negatively affected housing prices. For Korea that is approaching to an aging society, it is too early to tell that the increasing proportion of the elderly population (aged 65 and over) brings negative impacts to the housing market. It is however worth to note that the proportion of those aged 50~64 brings statistically significant negative impacts to the housing market, implying that an increasing elderly population will affect the housing market in a longer time-series. Under this circumstance, these empirical analysis results demonstrate that housing supply policy is of greater importance than ever.

서울시 주택시장에서 주택유형별 매매가격과 전세가격의 동태적 상호관계

김우석 SH공사 도시연구원 2019 주택도시연구 Vol.9 No.3

The purpose of this study is to analyze the dynamic interrelationship between the purchase price and the jeonse price by housing type (detached houses, row houses, and apartments) in the housing market in Seoul after the U.S. sub-prime mortgage crisis. It presents the structures and characteristics of the housing market by housing type, and provides meaningful information that can help decision-making of potential housing consumers and policy formulation as well as decisions relative to stabilizing the housing market. The results of the analysis are as follow. First, there are statistically significant interrelationships between the purchase price and the jeonse price in all housing types, but in the case of detached houses and row houses, the purchase price leads the jeonse price and in the case of apartments, the jeonse price leads the purchase price. Second, the trend of housing market in Seoul is dominated by the influence of apartments rather than the level of housing prices of all housing types. Third, in the case of apartments unlike detached houses and row houses, there exists the influence of the jeonse market and the dependence on the jeonse market of the purchase market. Thus, it is necessary to closely and steadily monitor the trend of the jeonse market. In conclusion, it is necessary to spread the supply of high-quality public-type rental housing and profit-loss sharing mortgage system rather than low-interest loans of housing jeonse funds for potential housing consumers, and to strengthen progressive taxation on multi-housing owners for the downward stabilization of housing prices. 본 연구의 목적은 미국 서브프라임 모기지 사태 이후 서울시 주택시장에서 주택유형별(단독주택, 연립주택, 아파트) 매매가격과 전세가격 사이의 동태적 상호관계를 살펴보는데 있다. 이를 통해 주택유형별 주택시장의 구조와 특성을 제시하고 잠재적 주택수요자의 의사결정, 주택시장 안정화를 위한 정책 수립 및 결정에 도움이 될 수 있는 유의미한 정보를 제공하고자 한다. 분석결과, 첫째, 모든 주택유형에서 매매가격과 전세가격 사이에 통계적으로 유의한 상호관계가 존재하였으나 단독주택과 연립주택의 경우 매매가격이 전세가격을 선도하였고, 아파트의 경우 전세가격이 매매가격을 선도하여 서로 대조적인 결과가 나타났다. 둘째, 서울시 주택시장의 동향은 주택유형별 주택가격의 수준이 두루 반영되기 보다는 아파트의 영향이 지배적인 것으로 나타났다. 셋째, 아파트의 경우 단독주택과 연립주택과는 다르게 전세시장의 영향력과 매매시장의 전세시장에 대한 의존도가 매우 높은 것으로 나타나 전세시장의 동향을 지속적으로 면밀하게 관찰할 필요가 있다. 결과적으로 잠재적 주택수요자를 위해 주택전세자금의 저금리 대출보다는 양질의 공공형 임대주택과 수익·손실 공유형 모기지 제도의 공급을 확산시키고 주택가격의 하향안정화를 위해 다주택 보유에 대해 누진세를 강화할 필요가 있다.

주택유통산업에서의 주택가격과 기대주택가격간의 관계분석

최차순 한국유통과학회 2015 유통과학연구 Vol.13 No.11

Purpose – In Korea, there has been a recent trend that shows housing prices have risen rapidly following the International Monetary Fund crisis. The rapid rise in housing prices is spreading recognition of this as a factor in housing price volatility. In addition, this raises the expectations of housing prices in the future. These expectations are based on the assumption that a relationship exists between the current housing prices and expected housing prices in the real estate industry. By performing an empirical analysis on the validity of the claim that an increase in current housing prices can be correlated with expected housing prices, this study examines whether a long-term equilibrium relationship exists between expected housing prices and existing housing prices. If such a relationship exists, the recovery of equilibrium from disequilibrium is analyzed to derive related implications. Research design, data, and methodology – The relationship between current housing prices and expected housing prices was analyzed empirically using the Vector Error Correction Model. This model was applied to the co-integration test, the long-term equilibrium equation among variables, and the causality test. The housing prices used in the analysis were based on the National Housing Price Trend Survey released by Kookmin Bank. Additionally, the Index of Industrial Product and the Consumer Price Index were also used and were obtained from the Bank of Korea ECOS. The monthly data analyzed were from January 1987 to May 2015. Results – First, a long-term equilibrium relationship was established as one co-integration between current housing price distribution and expected housing prices. Second, the sign ofthe long-term equilibrium relationship variable was consistent with the theoretical sign, with the elasticity of housing price distribution to expected housing price, the industrial production, and the consumer price volatility revealed as 1.600, 0.104,and 0.092, respectively. This implies that the long-term effect of expected housing price volatility on housing price distribution is more significant than that of the industrial production and consumer price volatility. Third, the sign of the coefficient of the error correction term coincided with the theoretical sign. The absolute value of the coefficient of the correction term in the industrial production equation was 0.006, significantly larger than the coefficients for the expected housing price and the consumer price equation. In case of divergence from the long-term equilibrium relationship, the state of equilibrium will be restored through changes in the interest rate. Fourth, housing-price volatility was found to be causal to expected housing price, and was shown to be bi-directionally causal to industrial production. Conclusions – Based on the finding of this study, it is required to relieve the association between current housing price distribution and expected housing price by using property taxes and the loan-to-value policy to stabilize the housing market. Further, the relationship between housing price distribution and expected housing price can be examined and tested using a sophisticated methodology and policy variables.

A Positive Analysis of Housing Price Model in Seoul

Kyong-Hoon Kim,Yoon-Sun Lee,Byung-Ju Ahn,Jae-Jun Kim 대한건축학회 2007 Architectural research Vol.9 No.2

Our nation has a problem with discrimination of income distribution and inefficient of resources distribution caused by real estate price rising from a sudden economy growth and industrialization. Specially, in recent years, there is a great disparity of apartment price between the north and south of the Han river. Because the housing price is decided by the immanent value of a house and neighborhood effects of the regional where the house is situated, the housing price is occurred difference. The purpose of study was to analyze the influence of various factors of housing price. Also, this study tried to predict real estate market and to establish previous effective real estate policy. In this study, we analyzed the differences of housing price determinants about apartment developments between the north and south of the Han river, and found the important factors that affect the housing price using Structural Equation Modeling(SEM). As a result of this study, the older the buildings are, the more the housing price and the housing price rising ratio have increased, in Gang Nam area. This reason is that these have large possibility to be reconstructed and many convenient facilities, in this area. In the case of Kang Buk area, the increase rate of housing price are so low that they couldn’t take effect on the housing price and they were declined. So to speak, constructing the infrastructure which takes effect on the increase rate of housing price is very urgent.

주택가격 결정요인에 관한 연구

김봉호(Kim Bong Ho) 한국부동산학회 2008 不動産學報 Vol.32 No.-

  1. CONTENTS<BR>  (1) RESEARCH OBJECTIVES<BR>  The housing price stability policy has been the most important issue in Korea. The purpose of this paper is to trace the determinants of housing price. Defining the determinants of housing price will contribute to the better understanding of structural mechanism of housing price. Based on the empirical analysis, we will search for appropriate policy of housing price stability.<BR>  (2) RESEARCH METHOD<BR>  To analyze the housing price structure, regression, variance decomposition and impulse response analysis are used. Empirical analysis employed the time series data on housing price, real interest rate, expected housing price and land price.<BR>  (3) RESEARCH RESULTS<BR>  The results of this study suggest that the real interest rate and expected housing price are important factors in determining the housing price in Korea. Especially the study finds that real interest rate is more important than expected housing price and land price in determining the housing price.<BR>  2. RESULTS<BR>  The purpose of this study is to explore the cause of housing price instability by analyzing the determinants of housing price. It estimates the equation of housing price using a regression model. It also performs the variance decomposition and impulse response analysis in the VAR model with housing price and real interest rate, expected housing price, and land price variables.<BR>  The empirical results suggest that the housing price is negatively related with interest rate, and is positively related with expected housing price and land price. It is also confirmed that interest rate is the most important factor affecting housing price.

주택시장 간의 가격구조에 관한 연구

임정호(Lim Jeong Ho) 한국부동산학회 2006 不動産學報 Vol.28 No.-

1. CONTENTS (1) RESEARCH OBJECTIVES Korean tenure market has three major sectors; housing ownership market, Chonsei market, and monthly rental market. The housing stability policy has been stressed on the prices of the market directly, ignoring its structural relationship between them. The object of this study is to define the driving forces and relationship among the three different prices of tenure markets. And defining the price structure of its market will contribute the better understanding of structural mechanism for a more market oriented housing stabilization policy. (2) RESEARCH METHOD This study concentrates on two main parts; the first one is theoretical part which is study of macro and micro economic over view of Korean housing market and review of precedent papers. As a completion of the theoretical study, this study established two hypothesis; the constraints theory and the discount theory, either might explain the price structure of present Korean housing market, and the second part of the study is to prove the established hypothesis through quantitative analysis. Granger Casualty Test was adopted to define the causal relationship among the prices. The Cross Correlation Coefficient Test is for the verification and confirmation of result of Granger Casualty Test and to measure the degree of advance and postal relationship between the prices. Vector Auto Regression analysis was practiced to define the function and relativity among ownership price, Chonsei price, and monthly rental price. Due to least one cointegression vector was found, Vector Error Correction analysis was exercised. The estimation of coefficient, impulse response analysis, and decomposition analysis were done for the define relationship of the prices. Before the test, the unit root test was exercised to stabilized the time series data, and properly treated. As a result of the Granger Casualty Test, the housing price has a causual relationship to the Chonsei price, and the Chonsei price has a causual relationship to the monthly rental price. The Cross Correlation Coefficient Test showed that the housing price is advance to Chonsei price and monthly rental price, so as verifying the result of the Granger Casualty Test. The endogenity of the prices was tested through Cholesky impulse test and variance decomposition test as a part of Vector Error Correction analysis. The endogenity of the housing price is prominent to the Chonsei price and monthly rental price. The housing price can"t be explained by Chonsei price or monthly rental price, but mostly explained by its own price. The influence of the housing price is greater than the sum of Chonsei price and monthly rental price to its own price. (3) RESEARCH RESULTS As a Result of analysis, we found that housing ownership price is still the driving force to Chonsei Price and monthly rental price. So the Korean residential market is worked by the Constrained Choice theory, and result following study, like cross correlation coefficient analysis and Error Correction Model analysis, supports the result good enough but not in every case. In general, Constrained Choice theory is prevailing in housing market, and the residential housing price is major driving force and influences to Chonsei market, and monthly rental market. So the housing policy and tax policy should be concentrated on stabilizing residential ownership market. 2. RESULTS Though the Korean housing market is very composite so one theory can not define the market. Especially after the Foreign Exchange Crisis, the structural change has been experienced in residential market in Korea. So, we might be in transferring period. But in general, Constrained Choice theory is prevailing in housing market, and the residential housing pri

ARIMA 모형을 이용한 주택시장의 가격예측 분석

김동환(Kim, Dong-Hwan) 대한부동산학회 2014 大韓不動産學會誌 Vol.32 No.2

본 연구는 주택시장의 예측을 시게열분석과 ARIMA 모형을 기초로 분석했다. ARIMA 분석에 사용한 데이터는 2001년 1/4분기부터 2013년 4/4분기 데이터를 사용해서 ARIMA 모형을 구축했으며 2014년 1/4분기부터 2014년 3/4분기 데이터를 사용해서 모형의 예측력을 검증하고 2014년 4/4분기부터 2016년 3/4분기까지 예측을 수행했다. 구축된 ARIMA 모형을 확인한 결과 전국주택매매가격지수와 서울주택매매가격지수의 ARIMA 모형은 모두 (1, 1, 1)로 결정되었다. 전국주택전세가격지수의 ARIMA 모형은(2, 1, 1)로, 서울주택전세가격지수의 ARIMA 모형은 (1, 1, 2)로 결정되었다. 분석한 결과는 주택매매가격의 경우 분기별 변동률 추이를 보면 전국과 서울 모두 전체적으로 일정하게 가격을 유지하지만 약간의 등락을 계속하면서 큰 변동폭은 없는 추세를 보임으로써 2014년도 3/4분기에서 2016년도 3/4분기에 이르기까지 전체적으로 큰 등락 없이 소폭의 오름세와 내림세를 반복할 것으로 나타났다. 주택전세가격의 경우 분기별 변동추이를 보면 전국은 물론 서울의 주택전세가격의 경우 2014년도 4/4/분기에 이어서 2015년도와 2016년도 3/4분기에 이르기까지 지속적으로 오름세를 이어갈 것으로 예측되었다. 이는 주택경기를 활성화시키기 위한 정부의 주택정책에도 불구하고 주택매매시장에는 큰 변화가 없을 것으로 추측되는데 주택을 매입하기보다는 전세를 계속 유지하는 편으로 주택수요자들이 반응함에 따라서 주택전세시장은 계속적으로 상승할 것으로 추측된다. The purpose of this study is to make a model to forecasting a housing trade price and household rent price in housing market using ARIMA model. On the basis of those models, I tried to forecast the fluctuations of short-term housing trade price and household rent price in housing market. To analyze the ARIMA model, quarterly data during 2001 1/4∼2013 4/4 are used for identification, estimation, diagnosis, and prediction of the ARIMA model. Using ARIMA model, the outcome ARIMA (1,1,1) model is applied to nationwide and Seoul housing trade price in the rate of housing trade price forecasting model. ARIMA (2,1,1) model is applied to nationwide household rent price, and ARIMA (1,1,2) model is applied to Seoul household rent price in the rate of household rent price. According to the forecast result of housing trade price and household rent price of nationwide and Seoul in the ARIMA model, the housing trade price in 2015 3/4 ~ 2016 3/4 is fluctuated to be small changing portion to nationwide and Seoul, the household rent price in 2015 3/4 ~ 2016 3/4 is fluctuated to be a slight number of changing portion to nationwide and Seoul. In spite of the latest government s active involvement in the housing market, it is assumed that housing trade price is no change largely, and keeping on increasing household rent price consistently in housing market.

지역주택시장의 동태적 가격 특성 분석에 관한 연구

김주영(Kim, Ju-Young),이창원(Lee, Chang-Won) 한국주거환경학회 2012 주거환경(한국주거환경학회논문집) Vol.10 No.2

Although housing prices is one of the key variables in explaining housing cycles, prior researches focused on national housing prices. Macro based researches roots on shortages of housing market statistics and efficiency oriented government policy. The need to study regional or civic housing markets are like these. First, real estate market is naturally a local market so fluctuation of housing prices are not same those of national housing market. Second, local fundamentals tend to have greater cyclical impacts than those of national or regional fundamentals. In this study, prior studies and fundamental housing price theory was adopted to explaining housing price dynamics of each cities. According to housing price theory, it follows recent price housing price(serial correlation) and convert to its fundament housing prices(mean reversion) so housing dynamics of each cities can be explained to these theoretical concepts. This study base on these theoretical background and used empirical models of prior studies. Empirical results like these. First, There was not a patten about market value and fundamental value of each city because economic condition of each city was not same. Second, most of regional housing prices tend to have no oscillations and distribution of convergent market was about 50% percent of total market. This study has limitation in explaining housing price dynamics because time series data on regional housing market was not enough to find out empirical behavior. For example data on housing prices is not a real transaction based data but a market value of housing information company. However, this study can be a one of the first studies in this field and can be reference data understanding regional housing dynamics.

주택하부시장 특성을 고려한 신규 분양가와 입주후 가격 변화에 관한 연구

최열(Choi Yeol),김형수(Kim Hyung Soo),박명제(Park Myung Je) 대한토목학회 2008 대한토목학회논문집 D Vol.28 No.4D

본 연구는 신규 아파트 가격의 규제에 대한 결과로 나타난 신규 아파트의 분양가격과 입주 시점의 매매가격의 차이 즉 프리미엄의 원인을 규명하고자 하였다. 분석 결과를 정리하면 다음과 같다. 첫째, 부산지역 아파트 시장은 기존의 주택 형태에서 벗어나 새로운 형태의 아파트에 대한 수요가 높은 것으로 생각할 수 있다. 분석결과 아파트의 층수가 고층이고 타워형 아파트인 경우에 가격 상승이 높은 것으로 나타났으며, 주택의 형태도 더 많은 베이를 가진 아파트가 가격이 상승하는 것으로 드러났다. 둘째, 신규 아파트의 가격은 주거한 후에 평가되는 가격이 아니므로 가격상승에 대한 기대감을 높여주는 단지정보가 가격상승에 중요하게 작용하는 것으로 분석할 수 있다. 유의하게 나타난 변수는 녹지율과 아파트 세대수, 브랜드 및 도심지 접근성 등과 같은 변수였는데, 이러한 경향은 기존의 중고 아파트에 대한 연구결과와 동일한 것이다. 셋째, 신규 아파트 중에서도 대단지의 규모를 가지며 건설업도급순위 상위에 위치하는 건설회사의 브랜드 아파트가 가격 상승률이 높은 것으로 분석되었는데, 이는 지역 건설 업체의 불리한 상황에 대한 반증이기도 하다. 넷째, 변수들 중에서 가장 큰 영향을 미치는 변수는 아파트 분양가인 것으로 드러났다. 각종 선행연구들에서는 아파트 가격 상승요인으로 정부의 분영가격 규제정책을 지목하였는데, 분양가격의 규제로 인해 주택의 초기 분양가가 시장가격보다 낮게 책정되어 아파트 입주시에 가격이 상승하게 된다는 것이다. 또한 하부시장 특성에 대한 중요성을 알 수 있었는데, 중고주택시장의 상승률, 제1선호구와 제2선호구, 아파트 비율이 유의한 영향을 끼치는 것으로 나타났다. This study tried to find differences between housing lotting prices and sale prices owing to new multi-family housing price regulation. As the results of this study, they are as follows; First, this study shows housing market in Busan has a preferences of new housing which has a new housing form differing from the existing housing form. For example, the mixed-use apartment with higher stories shows steeper incline than the apartments with the existing forms. Second, the new housing prices are affected by the information that affect the price of the old existing housing. They are rates of green area of an apartment complex, the number of household, accessibility to downtown Busan and etc .. They are also confirmed factors that affect a rise of used-housing price in other studies. Third, brand value of apartments affects new housing prices. For example, if the major construction companies build the new apartment, it shows a rising trend than any other housing. Therefore, the local construction companies are expected to be put on a disadvantage places than major construction companies. Fourth, the lotting prices are the most important cause that lead to rise the new housing prices. Accordingly, the present lotting prices are expected that upward tendency the purchasing prices of the new housing will not continue, because the lotting prices have risen since the government removed lotting price regulations and exceeded the level of used-housing prices. And it denote that importance of housing sub-market which indicates rates of old existing housing market rising, frist preference Gu, second preference Gu, rate of multi-family housing.

VAR모형을 이용한 주가, 금리, 물가, 주택가격의 관계에 대한 실증연구

김재경 한국유통과학회 2013 유통과학연구 Vol.11 No.10

Purpose -This study analyzes the relationship and dynamic interactions between stock price index, interest rate, price index, and housing price indices using Korean monthly data from 2000 to 2013,based on a VAR model. This study also examines Granger causal relationships among these variables in order to determine whether the time series of one is useful in forecasting another, or to infer certain types of causal dependency between stochastic variables. Research design, data, and methodology-WeusedKoreanmonthly data for all variables from 2000: M1 to 2013: M3. First, we checked the correlations among different variables. Second, we conducted the Augmented Dickey-Fuller (ADF) test and the co-integration test using the VAR model. Third, we employed Granger Causality tests to quantify the causal effect from time series observations. Fourth, we used the impulse response function and variance decomposition based on the VAR model to examine the dynamic relationships among the variables. Results -First, stock price Granger affects interest rate and all housing price indices. Price index Granger, in turn, affects the stock price and six metropolitan housing price indices. However, none of the Granger variables affect the price index. Therefore, it is the stock markets (and not the housing market) that affects the housing prices. Second, the impulse response tests show that maximum influence on stock price is its own, and though it is influenced a little by interest rate, price index affects it negatively. One standard deviation (S.D.)shock to stock price increases the housing price by 0.08 units after two months, whereas an impulse shock to the interest rate negatively impacts the housing price. Third, the variance decomposition results report that the shock to the stock price accounts for 96% of the variation in the stock price, and the shock to the price index accounts for 2.8% after two periods. In contrast, the shock to the interest rate accounts for 80% of the variation in the interest rate after ten periods; the shock to the stock price accounts for 19% of the variation;however, shock to the price index does not affect the interest rate. The housing price index in 10 periods is explained up to 96.7% by itself, 2.62% by stock price, 0.68% by price index, and 0.04% by interest rate. Therefore, the housing market is explained most by its own variation, whereas the interest rate has little impact on housing price. Conclusions-The results of the study elucidate the relationship and dynamic interactions among stock price index, interest rate, price index, and housing price indices using VAR model. This study could help form the basis for more appropriate economic policies in the future. As the housing market is very important in Korean economy, any changes in house price affect the other markets, thereby resulting in a shock to the entire economy. Therefore, the analysis on the dynamic relationships between the housing market and economic variables will help with the decision making regarding the housing market policy.