주택경기지수 전이효과에 대한 연구

전해정 ( Haejung Chun ) 사단법인 아시아문화학술원 2020 인문사회 21 Vol.11 No.2

본 연구의 목적은 지역별 주택경기지수를 작성하고 주택경기지수 전이효과를 FAVAR모형을 이용해 실증분석 하는 것이다. 종속변수는 주택매매가격으로, 독립변수는 주택전세가격, 소비자물가지수, 주택담보대출금, 건축물허가현황과 미분양주택수로 설정하였고 시간적 범위는 2009년 1월부터 2019년 5월까지이며 공간적 범위는 16개 광역시도로 하였다. Cholesky 분해분석결과, 대체적으로 많은 지역들이 서울의 영향을 많이 받고 또한 인접 지역의 영향을 받는 것으로 나타났다. 특히, 수도권 지역은 주택경기 상호 작용이 많은 것으로 나타났다. 본 연구결과에 따르는 정책적 시사점은 서울지역의 주택경기가 수도권을 중심으로 대부분의 지역에 영향을 미치는 것으로 나타난 바, 정부는 주택경기와 관련된 정책을 수립 집행 시에는 서울을 중심으로 한 지역 주택경기를 지속적으로 모니터링 할 필요성이 있다. 더욱 다양한 거시경제변수를 사용하고 공간적 범위를 확장하는 것은 추후 연구과제로 남긴다. The purpose of this study is to create a regional housing business cycle index and to empirically analyze the spillover effects using the FAVAR model. The dependent variable is the housing sales price, the independent variable is the housing Chonsei price, the consumer price index, the mortgage loan, the building permit and the number of unsold homes. The temporal range is from January 2009 to May 2019. The spatial range is 16 metropolitan cities. As a result of the Cholesky decomposition analysis, it was found that many regions are largely influenced by Seoul and also by neighboring regions. In particular, the metropolitan area showed a lot of interaction with the housing business cycle market. The policy implication of this study showed that the housing market in the Seoul area affects most of the region, especially in the metropolitan area. There is a need for continuous monitoring. The use of more diverse macroeconomic variables and the expansion of spatial scope remain for further study.

창조산업과 창조계급이 도시경쟁력에 미치는 영향에 관한 실증분석

전해정(Haejung Chun) 한국부동산학회 2014 不動産學報 Vol.56 No.-

1. CONTENTS (1) RESEARCH OBJECTIVES This study has analyzed the impact of creative industry and creative class on city competitiveness in an empirical analysis using a correlation analysis and granger causality test after establishing the spatial scope as city of Seoul and scope of content as the following: creative industry as cultural arts industry and information & communication technology industry; creative class (human resources) as cultural arts industry professionals, information & communication technology industry professionals, and industrial technology personnel with a masters degree or higher education; tolerance as the number of foreigners; city competitiveness as Gross Regional Domestic Product (GRDP) data. (2) RESEARCH METHOD In this study, research method was through correlation analysis and granger causality test. (3) RESEARCH FINDINGS The correlation between gross production and cultural arts industry in Seoul was relatively low, whereas all the other variables had a positive correlation with the city's gross production and the correlation was relatively high. The granger causality test confirmed that information & communication technology industry needs to be developed to boost the competitiveness of the city and the nation by implementing a creative economy. In addition, cultural arts industry needs to be intensively developed as well, as the changes in trend among global creative cities suggest that the foothold of their cultural arts industry is relatively strong. Furthermore, the creative class and human resources have a causal relationship with city competitiveness, empirically confirming the fact that producing creative industry related personnel has a profound impact on strengthening the city competitiveness. 2. RESULTS The government needs to set and execute policies that can promote information & communication technology industry and cultural industry in the medium to long term. Since the creative class has a huge influence on the city competitiveness, it is important for each city to establish an educational and living environment that facilitates producing such talents, in an effort to inspire the creative class to move into the city.

미분양주택량 결정 요인에 관한 실증분석

전해정(HaeJung Chun) 韓國不動産學會 2014 不動産學報 Vol.56 No.-

1. CONTENTS (1) RESEARCH OBJECTIVES The Fisher-DiPasquale-Wheaton(FDW) model was used for determining the unsold housing stocks. This study made an empirical analysis of the dynamic relationship of monthly unsold housing stocks, housing prices, construction cost, mortage and mortage rate in South Korea from October 2003 to May 2012 by using time series analysis. (2) RESEARCH METHOD In this study. research method was through time series analysis (VECM). (3) RESEARCH FINDINGS There was a long run equilibrium relationship between the variables, Vector Error Correction Model(VECM) was used to conduct an impulse response analysis and a variance decomposition analysis. In empirically analysis, the unsold housing Stocks in shock, the unsold housing stocks greatest positive (+) reaction, mortgage impact the unsold housing stocks is negative (-) of the reaction was. Mortgage rates and construction cost impact the unsold housing stocks is positive(+). 2. RESULTS We confirmed that thoretical models and empirical results were the same and the unsold housing stocks were affected by macroeconomic variables.

패널공적분을 이용한 거시경제변수 및 주택정책이 주택매매가격에 미치는 영향에 관한 연구

전해정 ( Chun Haejung ) 한국부동산학회 2014 不動産學報 Vol.57 No.-

본 연구에서는 거시경제변수가 주택가격 결정에 미치는 영향을 전국적 요인뿐 아니라 지역적 요인을 동시에 고려하기 위하여 지역별 패널자료를 이용한 분석하였다. 거시경제변수는 주택담보대출금, CD금리, 전세가격, 건축착공실적으로 설정하였고 정부정책의 영향력을 알아보기 위해 규제강화정책과 완화정책을 변수 선정을 하였다. 시간적 범위는 2003년 11월부터 2013년 7월까지의 월별자료로 내용적 범위는 아파트로 설정하였고 공간적 범위는 전국 16개 시도, 광역시의 자료를 이용해 횡단면 시계열을 구성을 하였다. 패널 공적분 검정결과, 모든 지역에서 변수들 간에는 장기적인 균형관계가 존재하는 것으로 나타났다. 패널 회귀분석결과, 주택담보대출금은 주택매매가격, 건축착공실적, 전세가격은 매매가격에 양(+)의 영향을 미치고 CD금리는 음(-)의 영향을 미치는 것으로 나타났다. 규제강화·완화정책은 통계적인 유의성이 없는 것으로 나타났다. 이는 글로벌금융위기 이전에 주택가격 급등현상이 지속적인 규제정책에도 불구하고 멈추지 않았고 이후기간에는 완화정책에도 주택가격이 오르지 않았던 현상을 설명해주고 있다고 판단된다. 1. CONTENTS (1) RESEARCH OBJECTIVES This study has empirically analyzed how macroeconomic variables and housing policies influence housing prices. (2) RESEARCH METHOD In this study, research method was through panel cointegration and panel regression analysis. (3) RESEARCH FINDINGS The panel regression analysis revealed that mortgage, consrtuction performance and Jeonsei prices have a positive impact on housing prices, while CD interest rates have a negative impact. Although there was no statistical significance, deregulation policies had a negative impact on housing prices, while regulatory policies had a positive impact. 2. RESULTS Since housing finance regulatory policies are effective in stabilizing housing prices, the government should properly utilize the concept, put forth Jeonsei price stabilization policy, and provide various rental houses to promote residential stability of ordinary citizens. In order for government policies to achieve their intended objectives, the officials should set and enforce policies in a systematic manner with a long-term view.

공간계량분석기법과 GIS를 이용한 주택가격모형 비교에 관한 연구?

전해정(Haejung Chun) 韓國不動産學會 2016 不動産學報 Vol.64 No.-

본 연구는 공간효과를 고려하지 않은 특성가격함수와 공간효과를 고려한 공간시차모형(SLM)과 공간오차모형(SEM)을 이용해 주택가격모형을 비교분석하였다. 종속변수는 아파트실거래가격을 독립변수는 아파트 면적, 층수, 행정동별 인구밀도, 2차선도로 직선거리, 4차선도로 직선거리, 지하철역 직선거리, 공원 직선거리로 설정하였고 시간적 범위는 2013년으로 공간적 범위는 서울시, 강남과 강북으로 하였다. 모든 지역에서 오차항의 공간적 자기상관을 고려한 SEM모형이 주택가격 추정시 가장 정확성이 높은 모형으로 나타났다. 실증분석결과, 모든 지역에서 아파트 면적이 클수록, 층수가 높을수록, 공원과의 거리가 가까울수록 그리고 역세권 일수록 거래가격이 높은 것으로 나타났으며 도로와의 가까울수록 거래가격이 낮은 것으로 나타났고 강남이 다른 지역보다 공간적 종속성이 더 크다는 것을 알 수가 있었다. 본 연구결과에 따르는 정책적 시사점은 정확한 주택가격의 추정이 국부와 가계의 부와 직결되는 매우 중요한 사항이므로 공간효과를 고려해 주택가격을 추정해 정확성이 향상시킬 필요성이 있다는 점을 정부당국자는 숙지해야 한다. 1. CONTENTS (1) RESEARCH OBJECTIVES This study, as ordinary least square (OLS) which is not considering a spatial effect, compared and analyzed the housing price model by using Spatial Lag Model(SLM) and Spatial Error Model(SEM) which are hedonic pricing model and spatial econometric analysis techniques. (2) RESEARCH METHOD The apartment real sale price is set as dependent variable and the apartment size, the number of floors, population density by administrative districts, lineal distance of two lane road, lineal distance of four lane road, lineal distance of subway station, lineal distance of park are set as independent variables. And the time range is 2013 and the spatial range is south and north of the Han river regions in Seoul. It is observed that SEM considering special autocorrelation of error terms in every region was the most suitable model. (3) RESEARCH FINDINGS According to the empirical analysis, sales price is positively correlated with the size of apartment , floors , distance to park and distance to station and sales price is negatively correlated with the distance to street and it showed that there was a higher spatial dependence in the north of the Han river area than other regions. When the size of apartment (m²) increased 1%, actual sale prices for the apartment in the south and north of the Han River regions was increased by 0.82% and 0.86% each, which means that there is a premium for large size apartment. When the number of floor of apartment increases 1%, the actual sale price for the apartment increases 0.038%, 0.035%, and 0.044% in Seoul and south and north of the Han river areas which indicate that there is a premium for higher floors than lower floors. 2. RESULTS Political implication based on the result from this study is that government officials need to be well aware of the fact that the accuracy improvement by estimating house price with considering spatial effect, for accurate estimation of housing price is very critical issue as it is tightly connected with national wealth and household economy based on the fact that 70% are houses shown in the analysis of property portfolio in Korea.

위계적 선형모형과 GIS를 활용한 도시 주거환경요인이 주택가격에 미치는 영향에 관한 연구

전해정(Haejung Chun) 한국부동산학회 2016 不動産學報 Vol.65 No.-

본 연구에서는 도시 주거환경요인이 다층구조를 가진 주택가격에 미치는 영향을 위계적 선형모형을 이용해 실증분석하였다. 종속변수는 아파트 실거래가격 자료를 사용하였고 개별수준의 설명변수는 아파트 면적, 아파트 층수, 2차선 직선거리, 4차선 직선거리, 지하철역 직선거리, 공원 직선거리로 지역수준의 설명변수는 도로율, 교육서비스 사업체수, 대학진학률, 금융 및 보험업 사업체수, 상업시 설면적과 병원수로 설정하였다. 공간적 범위는 서울시, 강남지역과 강북지역이고 시간적 범위는 2013 년 이다. 무조건부모형 분석결과, 모든 지역에서 아파트가격의 변화에 지역적 요인이 약 32% 이상의 적지 않은 영향력을 미치는 것으로 나타나 위계적 선형모형을 주택시장에 적용할 필요성을 확인하였다. 위계적 선형모형 분석결과, 지역별로 차이는 존재하나 병원수가 많을수록, 대학진학율이 좋을수록, 아파트 면적이 클수록, 아파트 층이 높을수록 2차선, 4차선 도로와 멀어질수록 지하철거리와 가까울수록 아파트 가격이 높은 것으로 나타났다. 1. CONTENTS (1) RESEARCH OBJECTIVES This study empirically analyzed the effect of urban housing environment factors on the price of multi-story house using hierarchial linear model. (2) RESEARCH METHOD Real trading price data of apartments was used as a dependent variable. The area of apartment, the number from apartment floors, straight-line distance from two-lanes, straight-line distance of four-lanes, straight-line distance to a subway station, and straight-line distance to park were set as the individual level explanatory variables; and street ratio, the number of educational service businesses, college entrance rate, the number of finance and insurance businesses, area of commercial facility, and the number of hospitals were used as the regional level explanatory variables. The spatial range is Seoul-si, Gangnam, and Gangbuk region, and temporal range is 2013. (3) RESEARCH FINDINGS As the change in apartment prices of every region is affected more by individual factor than regional factor according to the analysis result of unconditional parental type, it was identified that it is necessary to apply a hierarchical model on the housing market. The analysis result of a hierarchical linear model showed that the apartment price is higher for larger apartment area, taller apartments, more distance from two-lanes and four-lanes, and closer to subway stations. 2. RESULTS As it was observed that a hierarchical model is more appropriate in understanding the housing market than a hedonic pricing model according to the result of this study, it is necessary to analyze the housing market using a hierarchical model when government officials establish the housing policy.

도시계획적 요인이 지역 건강수준 결정에 미치는 영향에 관한 연구 - GIS와 공간계량경제모형을 이용하여 -

전해정(Haejung Chun) 한국부동산학회 2017 不動産學報 Vol.68 No.-

본 연구에서는 도시계획적 요인이 지역 건강수준에 미치는 영향을 공간계량경제모형인 GWR모형을 이용해 실증분 석하였다. 종속변수인 건강수준의 대리변수는 개인의 비만정도를 나타내는 체질량지수(BMI)로, 도시계획적 요인인 독립변수는 지역별 아파트가격지수, 시가화 면적, 자전거도로, 도로연장, 자동차수, 공원면적, 의료기관수, 공공체육시 설로 설정하였으며 공간적 범위는 서울시 25개구로, 시간적 범위는 2014년도로 하였다. 실증분석결과, 지역별로 차이는 존재하나 비만인구비율에 시가화면적, 자전거도로, 의료기관수는 음(-)의 영향을 미치고 자동차수는 양(+)의 영향을 미치는 것으로 나타났다. GWR모형의 국지적 계수를 군집화 한 결과 도시계획적 요인이 건강수준에 미치는 영향력이 지역별로 다르게 나타나고 있는 것을 알 수가 있었다. (1) RESEARCH OBJECTIVES This study aims to analyze empirically how urban planning factors influence the level of local health. (2) RESEARCH METHOD Body Mass Index (BMI) to show individual degree of obesity was the dependant variable to represent the health status; and city planning factors as the independent variables included apartments regional price index, urbanization area, bike paths, road extension, the number of cars, park area, medical facilities and public sports facilities using GWR model that is a spatial econometric model. For the study, spatial area was designated 25 Gus, Seoul; and the temporal scope was in 2014. (3) RESEARCH FINDINGS Despite regional differences, the findings show that urbanization area, bike paths and the number of medical facilities had a reduction effect on the rate of obesity while the number of vehicles had an increasing effect on it. 2. RESULTS By clustering regional coefficients of GWR model, the study provided clear evidence that urban planning factors influenced the level of local health differently by region.

수도권 아파트 경매 낙찰가율 결정요인에 관한 연구

전해정(Haejung Chun) 한국부동산학회 2018 不動産學報 Vol.72 No.-

본 연구는 수도권 아파트 경매 낙찰가율 결정요인을 종속변수는 아파트 경매 낙찰가율로 독립변수는 아파트실거래 가격 수익률, 아파트 경매 낙찰율, CD금리와 실업률로 하고 시간적 범위는 2006년 1월부터 2017년 3월까지로 공간적 범위는 서울, 경기, 인천으로 설정하여 패널 VECM을 이용해 실증분석 하였다. 충격반응 분석결과, 아파트 실거래가격 수익률은 지속적으로 아파트 낙찰가율에 정(+)의 영향을 미치고 아파트 낙찰가율도 아파트 실거래가격 수익률에 지속적으로 정(+)이 영향을 미치는 것으로 나타났다. 아파트 낙찰가율에 CD금리는 지속적인 부(-)의 영향을 미친 반면 아파트 낙찰율은 정(+)의 영향을 미쳤고 실업률은 영향력이 거의 없는 것으로 나타났다. 실증분석 결과를 종합해 보면, 패널 VECM 추정결과와 충격반응분석의 결과는 대체로 일치하는 것으로 나타났으며 아파트 낙찰가율에 부동산 시장의 상황인 아파트실거래가격 수익률과 유동성인 CD금리가 가장 큰 영향을 미치는 것을 알 수가 있었고 아파트 낙찰가율과 낙찰율의 움직임의 방향성이 동일하다는 것을 확인하였다. 1. CONTENTS (1) RESEARCH OBJECTIVES The purpose of this study is to empirically analyze determinants of housing auction price ratio in metropolitan area. (2) RESEARCH METHOD This study uses panel vector error correction model. The dependent variable is the housing auction price ratio and the independent variables are the housing transaction price yield, auction ratio, CD interest rate and unemployment rate. The temporal ranges are from January 2006 to March 2017, and the spatial ranges are Seoul, Gyeonggi, and Incheon in Korea. (3) RESEARCH FINDINGS According to the analysis results, The housing transaction price yield continues to have a positive effect on the housing auction price ratio. The housing auction price ratio also has a positive effect on the housing transaction price yield. The CD interest rate has a negative impact on the housing auction price ratio, while the auction ratio has a positive effect and the unemployment rate has little influence. According to the results of the empirical analysis, the results of the panel VECM estimation and the impulse response analysis are generally consistent, and the housing transaction price yield and CD interest rate have the greatest impact on the housing auction price ratio. It was confirmed that the direction of the movements of the housing auction price ratio and the auction ratio. 2. RESULTS If the housing market is booming, housing auction price ratio and housing transaction price yield will increase. However, if the market is in a recession, housing auction price ratio and housing transaction price yield will decrease. Therefore, housing auction price ratio can be used as an indicator of the auction market and the housing market.

서울시 임대료 대비 매매가격비율의 추세와 순환 분리

전해정(Chun, Haejung),박헌수(Park, Heonsoo) 한국부동산학회 2013 不動産學報 Vol.54 No.-

1. CONTENTS (1) RESEARCH OBJECTIVES This study separated the Cheonsei to sales ratio into trend and cycle using unobserved components model of state space models. (2) RESEARCH METHOD In this study, research method was through state space models. (3) RESEARCH FINDINGS With the empirical analysis most Cheonsei to sales ratio was explained by adopting trend and changes. However it is obvious that there exist a transit cycle change due to failure of instant adjustment and it shouldn t be ignored. 2. RESULTS The Cheonsei to sales ratio is associated with the structural and trend changes of house price, so the policy maker who is in charge of making housing policy have to monitor persistently on the data housing related and foresee the market move to reflect it to the policy.

마코프 국면전환모형을 이용한 주택시장 경기국면 변동 분석에 관한 연구

전해정(Haejung Chun) 한국부동산학회 2015 不動産學報 Vol.63 No.-

본 연구는 한국주택시장의 가격변동에서 나타나는 경기국면 특성을 2-상태 마코프 국면전환모형을 이용해 실증분석하였다. 시간적 범위는 2006년 1월부터 2014년 7월까지로 공간적 범위는 전국, 수도권, 비수도권으로 설정하였으며 내용적 범위는 아파트 실거래가격지수로 하였다. 분석결과, 지역별로 확장기, 수축기의 가격상승률이 다르게 나타났으며 수도권이 확장기, 수축기시에 가격상승률이 다른 지역보다 크게 나타나고 있음을 알 수가 있다. 또한, 모든 지역에서 수축기가 유지될 확률이 높게 나타났으며 수도권이 다른 지역에 비해 확장기가 유지될 확률이 약 10% 높게 나타났으며 유지기간도 약 3-4배 높게 나타나고 있었다. 확장기 국면의 확률분포를 살펴보면, 2008년 글로벌 금융위기 이전에는 수도권의 경우는 큰 폭의 확장기가 존재하였으나 이후기간에는 전체적으로 수축기로 나타내고 있는 반면 비수도권은 금융위기 이후 확장기가 나타나고 있다. 이에 정부는 지역별로 주택시장 경기국면이 다르게 나타나는 점을 숙지하고 지역별로 차별화된 주택정책을 수립 집행할 필요성을 있다. 1. CONTENTS (1) RESEARCH OBJECTIVES The purpose of this study is to empirically analyze the business regime of the Korean housing market. (2) RESEARCH METHOD This research analyzed the business regime reflected in the changes in price levels in the Korean housing market by using 2-state Markov regime switching model. The time frame of the analysis was between January 2006 and July 2014 and the spatial frame was classified into the whole nation, metropolitan area, and non-metropolitan areas. The research set the index of actual amount paid for purchasing and selling apartments for comparing data. (3) RESEARCH FINDINGS The results showed that the rate of price increase during the extraction, and the contraction was different according to regions, and also that the rate of price increase during extraction and contraction was much higher in metropolitan area. The results also showed that the possibility of having extraction to continue was 10% higher in metropolitan area compared to other regions and the period of maintaining that trend was 3-4 times higher in metropolitan area as well. With regards to the distribution of the rate of extraction, although there was a large-scale extraction in metropolitan area prior to the global financial crisis in 2008, there have been a contraction after the crisis. In contrast however, there have been an extraction in non-metropolitan areas after the financial crisis. 2. RESULTS The government should consider what regime housing market business regimes are when it decides housing market policies. The government should establish a differentiated policy enforcement by region.