주택가격 변동의 지역 연관성 분석에 관한 연구 : 서울 및 6대 광역시를 중심으로 = (A) study on the relationship between the housing price changes and regions : a case study of Seoul & 6 other metropolitan cities in Korea

다국어 초록 (Multilingual Abstract)

This study is to analyze the relationship between the regions and their housing prices with the price indexes of Seoul and 6 other metropolitan cities. Firstly, what kinds of interrelation exist among the entire country, Seoul and other main cities? Secondly, does a causal relationship exist between housing prices and regions? If so, how does it happen? Finally, how and how much does the housing price change in one region affect the ones in other regions? Impulse Response Function and Variance Decomposition have been done with correlation analysis, Grander causality and VAR.
The sale prices of APT have increased by 3.7 times, whereas the consumer prices have escalated by 2.8 times during 23 years from 1986 to 2009. The cities with the rates of APT price higher than their consumer prices are Seoul, Incheon and Busan, while the actual housing prices of other cities have descended. In terms of housing lease market, all the cities except Ulsan have shown higher security deposits than consumer price index.
For the correlation coefficient of the nation, Seoul has shown 0.945 and all analyzed cities have revealed over 0.5. In the correlation coefficient with Seoul's housing price, the highest was Incheon which is adjacent to Seoul, while Busan, Taegu and Ulsan were also over 0.5. The correlation coefficients between the security deposits and the cities are highest in Seoul and lowest in Ulsan. In addition, for the cross correlation coefficient of security deposits and sale prices in the cities, the security deposits have preceded the volatility of sale prices.
As a result of Granger causality evaluation on housing price, the prices of Seoul, Busan and Taegu are meaningful within 10% significance level. It also represents that Seoul's housing deal price has strongly affected other cities' housing deal price after foreign exchange crisis than before it. Seoul has most strongly been influencing on the whole country's house lease market, too. As for the security deposits the mutual causality among the cities has greatly been decreased after the exchange crisis more than before the crisis. As a result of Granger causality evaluation on security deposits and sale prices, both of the security deposits and sale prices appear to be interactively influenced to each other in most cities. But after the foreign exchange crisis the mutual effects has apparently been decreased and there has hardly been causality between security deposits and sale prices.
VAR Model has been established with 8 parameters. The nation's APT price has been set up with the function of the nation's APT price only, and 7 main cities including Seoul have been set up with the function of price variances of 7 cities except the entire country. Each city's housing price can be explained with its past housing price value and unexpected price change which cannot be explained with past price value during t period. The unexpected price change is under the assumption of the nation's and region's impact only. The region impact was limited to the impact of the city itself, Seoul and its adjacent cities. The 3 models assumed of the relationship between impact vector and aberration are the one ① between the Country and the city itself impact, ② among the country, Seoul and the city itself impact, ③ among the country, adjacent cities and the city itself impact.
In the sale market, the presumed index on each model has matched to the expectancy. Considering the nation's impact, Seoul has most largely responded while the adjacent city's impact as regional impact has shown pure impact, but substitution effects come out. The price influence of Seoul and Incheon has been increased since the foreign exchange crisis. According to the analysis in the lease market the large local cities had stronger influences before foreign exchange crisis, but the influencing power of Seoul and Incheon has increased after the crisis.
In Reviewing the Variance decomposition results, most cities have relatively considerable effects from the impacts of each city and the nation. However, the nation factor has decreased, whereas each city factor has increased after the foreign exchange crisis, compared to its earlier times.

목차 (Table of Contents)

• Abstract --------------------------------- ⅺ
• 제1장 서론 -------------------------------- 1
• 1. 연구의 배경 및 목적 --------------------------- 1
• 2. 연구의 범위 및 방법 --------------------------- 3
• 3. 선행연구 개관 -------------------------------- 6
• 제2장 우리나라 주택시장의 현황 -------------- 15
• 1. 시장의 형성과 발전 --------------------------- 15
• 가. 아파트 시장의 형성 --------------------------------- 15
• 나. 선분양 제도와 아파트 청약제도 ------------------------ 29
• 다. 전세제도와 주택시장 -------------------------------- 31
• 2. 우리나라 주택시장의 특성 ---------------------- 38
• 가. 주택시장과 주택건설 -------------------------------- 38
• 나. 거시 경제변수와의 관계 ------------------------------ 46
• 다. 수도권 집중화 -------------------------------------- 49
• 라. 가계자산과 주택 ------------------------------------ 52
• 3. 우리나라 아파트 시장 추이 --------------------- 57
• 가. 아파트 매매시장 ------------------------------------ 57
• 나. 아파트 전세시장 ------------------------------------ 64
• 제3장 데이터 및 2변량 분석 ------------------ 71
• 1. 데이터 ------------------------------------- 71
• 가. 시계열자료의 종류와 특성 ---------------------------- 71
• 나. 계절조정과 단위근 검정 ------------------------------ 76
• 2. 상관관계 분석 ------------------------------- 82
• 가. 아파트 매매가격의 상관관계 -------------------------- 82
• 나. 아파트 전세가격의 상관관계 -------------------------- 85
• 다. 전세가격과 매매가격의 상관관계 ----------------------- 88
• 3. 인과관계 검정 ------------------------------- 90
• 가. 그랜저 인과 검정 ----------------------------------- 90
• 나. 아파트 매매가격의 인과성 검정 ------------------------ 91
• 다. 아파트 전세가격의 인과성 검정 ------------------------ 98
• 라. 아파트 전세가격과 매매가격의 인과성 검정 ------------- 105
• 제4장 벡터자기회귀모형 분석 ---------------- 108
• 1. VAR 모형의 설정 ---------------------------- 110
• 2. 아파트 매매가격의 VAR 분석 ------------------ 118
• 가. 식별결과 ----------------------------------------- 118
• 나. 충격반응함수 및 분산분해 --------------------------- 123
• 3. 아파트 전세가격의 VAR 분석 ------------------ 136
• 가. 식별결과 ----------------------------------------- 136
• 나. 충격반응함수 및 분산분해 --------------------------- 141
• 제5장 결론 ------------------------------ 156
• 1. 연구결과의 요약 ----------------------------- 156
• 2. 정책적 시사점 ------------------------------- 163
• 3. 향후 연구과제 ------------------------------- 166
• 참고문헌 -------------------------------- 168
• 감사의 글 ------------------------------- 174