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월세, 전세, 매매 시장의 구조적 관계에 관한 실증분석

Title
월세, 전세, 매매 시장의 구조적 관계에 관한 실증분석
Other Titles
An Empirical Analysis on Structural Relationships of Monthly Rent, Jeonse Rent, and Sales Markets
Author
어경오
Alternative Author(s)
Eo, Kyoung Oh
Advisor(s)
이창무
Issue Date
2017-08
Publisher
한양대학교
Degree
Master
Abstract
일반적으로 주택시장을 매매, 전세시장으로 구분한 연구들이 다수를 차지하고 있다. 그러나 본 연구는 주택시장을 세 개의 시장, 즉 매매, 전세, 월세시장으로 구분하고 상호 연관관계에 대하여 분석하였다. 다만 주택시장은 서울시 아파트매매, 전세, 월세시장을 선정하였고, 전(全)산업생산지수(IAIP), 회사채수익율(RCB), 주거용착공면적 등 3개 자료를 외생변수로 선정 분석에 사용하였다. 기술통계량의 분석 결과, 전세가격의 상승이 매매, 월세가격에 비해 상당히 높은 것을 볼 수 있다. 이에 따르면 매매가격은 월평균 약 8bp(0.08%)가 상승하였으며, 전세가격은 월평균 46bp(0.46%)가 상승하였다. 월세가격은 월평균 약 19bp(0.19%)가 상승한 것을 볼 수 있다. 이는 전세가격의 상승이 지난 10년간 다른 가격 대비 급속하게 이루어져 왔음을 알 수 있다. 그랜저인과관계(Granger Causality Test)분석 결과, 경제와 임대료간의 인과관계 분석에서 산업생산지수가 전세가격과 월세가격에 인과관계가 있는 것으로 나타났다. 임대료와 주택가격간의 분석은 전세가격이 매매가격에 인관관계가 없는 것으로 나타났으며, 월세가격은 주택가격에 인과관계가 있는 것으로 나타났다. 이자율과 주택가격간의 분석은 회사채수익률이 매매가격에 모든 시차에서 인과관계가 있는 것으로 나타났다. 그리고 주택가격과 공급(건설)간의 분석에서 매매가격은 착공면적에 모든 시차에서 인과관계가 없는 것으로 나타났다. 이는 착공면적이 공급(건설)의 동행지표로 볼 수 있는지에 대한 의문점을 들게 하는 결과이다. 그리고 벡터오차수정모형(VECM: Vector Erroer Correction Model)을 구성 한 후 오차수정항에 대한 분석한 결과, 첫째, 서울시 아파트매매, 전세, 월세가격을 내생변수하고 회사채수익률을 외생변수로 포함 분석한 결과, 전세가격과 월세가격은 장기적으로 매매가격에 양(+)의 관계가 있는 것으로 나타났다. 둘째, 서울시 아파트매매, 전세, 월세가격을 내생변수로 하고 전산업생산지수를 외생변수로 포함하여 분석한 결과, 전세가격은 장기적으로 매매가격에 음(-)의 관계가 있으며, 월세가격은 매매가격에 장기적으로 양(+)의 관계가 있는 것으로 나타났다. 셋째, 서울시 아파트매매, 전세, 월세가격을 내생변수로 하고 주거용착공면적을 외생변수로 포함하여 분석한 결과, 전세가격은 장기적으로 매매가격에 음(-)의 관계가 있으며, 월세가격은 매매가격에 장기적으로 양(+)의 관계가 있는 것으로 나타났다. 넷째, 서울시 아파트매매, 전세, 월세가격을 내생변수로 하고 전산업생산지수, 회사채수익률, 주거용착공면적 등 세 개의 변수를 외생변수로 포함하여 분석한 결과, 전세가격과 월세가격은 장기적으로 매매가격에 양(+)의 관계가 있는 것으로 나타났다. 다섯째, 서울시 아파트매매, 전세가격을 내생변수로 하고 전산업생산지수, 회사채수익률, 주거용착공면적 등 세 개의 변수를 외생변수로 포함하여 분석한 결과, 전세가격은 장기적으로 매매가격에 음(-)의 관계가 있는 것으로 나타났다. 여섯째, 서울시 아파트매매, 월세가격을 내생변수로 하고 전산업생산지수, 회사채수익률, 주거용착공면적 등 세 개의 변수를 외생변수로 포함하여 분석한 결과, 월세가격은 장기적으로 매매가격에 양(+)의 관계가 있는 것으로 나타났다. 일곱째, 서울시 아파트매매, 전세, 월세가격과 회사채수익률 등 네 개의 변수를 모두 내생변수로 선정하고 분석한 결과, 회사채수익률은 장기적으로 매매가격과 전세가격은 음(-)의 관계가 있고, 반면 월세가격과는 양(+)의 관계가 있는 것으로 나타났다. 여덟째, 서울시 아파트매매, 전세, 월세와 전산업생산지수 등 네 개의 변수를 모두 내생변수로 선정하고 분석한 결과, 전산업생산지수는 장기적으로 매매가격, 전세가격, 월세가격은 모두 양(+)의 균형관계가 있는 것으로 나타났다. 아홉째, 서울시 아파트매매, 전세, 월세가격과 주거용착공면적 등 네 개의 변수를 모두 내생변수로 선정하고 분석한 결과, 주거용착공면적은 장기적으로 매매가격, 월세가격에 장기적으로 음(-)의 관계를 보이고, 전세가격에는 장기적으로 양(+)의 균형관계가 있는 것으로 나타났다. 충격방응분석(Impulse Response Function)에 대한 결과, 먼저 경제와 전세가격의 충격반응분석 결과, 전산업생산지수의 1단위 충격에 전세가격은 2기까지 음(-)의 영향을 보이며, 3기 이후는 양(+)의 반응을 보이고, 전산업생산지수 1단위 충격에 월세가격은 양(+)의 방향을 보이고 있다. 그리고, 임대료와 주택가격과의 충격반응분석 결과, 전세가격 1단위 충격에 매매가격은 양(+)의 반응을 보이고, 월세가격 1단위 충격에 매매가격은 음(-)의 방향을 보이고 있는 것으로 나타났다. 시장이자율과 주택가격의 충격반응분석 결과는, 회사채수익률 1단위 충격에 매매가격은 음(-)의 충격반응을 보이고 있다. 위의 결과를 종합해 보면, 주택시장에서 주택가격과 월세가격의 상관관계가 주택가격과 전세가격과의 상관관계에 비해 상당히 높음을 볼 수 있다. 이는 최근에 월세(보증금有) 거주의 급속한 증가와 관련이 있는 것으로 예상되어 진다. 또한 충격반응분석(Impulse Response Function)에서도 역시 주택시장과 경제, 이자율, 공급(건설)과 관계도 역시 이론과 실증적으로 적용되고 있는 것을 볼 수 있었다.
Generally, there are many studies which classify housing market into sales and Jeonse on a deposit basis market. However, this study classified housing market into 3 markets, i.e. sales market, Jeonse market, and monthly rent market in order to analyze correlation. The study limited housing market to sales, Jeonse, and monthly rent market of apartment houses in Seoul and an analysis was conducted using such 3 data as Index of IAIP, RCB, and construction area for residence. First, as a result of comparison between sales price of apartment houses in Seoul during the past 10 years, Jeonse/sale price rate, and monthly rent/sale price rate, there is a very high increase in Jeonse/sale price rate comparing with sales price and monthly rent/sale price. Also, the result of descriptive statistics quantity shows that increase in Jeonse price is quite higher than sales or monthly rent price. According to this, sales price increased by about 8bp (0.08%) of monthly average while Jeonse price increased by 46bp (0.46%) of monthly average. It is seen that monthly rent price increased by about 19bp (0.19%) of monthly average. This means that Jeonse price has rapidly increased during the past 10 years comparing to other prices. According to analysis result of Granger Causality Test on economy and rent, it is found that index of industrial product has a causal relationship with Jeonse price and monthly rent price. Analysis between rent and housing price shows that Jeonse price does not have a causal relationship with sales price and that monthly rent price has a causal relationship with sales price. Analysis between market interest rate and housing price shows that RCB has a causal relationship with sales price in all the time differences. And, analysis between housing price and supply (construction) shows that sales price does not have a causal relationship with construction area in all the time differences. This result gives us a question whether construction area can be considered a coincident indicator of supply (construction). VECM (Vector Error Correction Model) was formed and the results of its analysis are as follows. First, according to an analysis with sales, Jeonse, and monthly rent price of apartment houses in Seoul as an endogenous variable and with RCB as an exogenous variable, it was found that Jeonse and monthly rent price had positive relationships with sales price in the long-term. Second, according to an analysis with sales, Jeonse, and monthly rent price of apartment houses in Seoul as an endogenous variable and with IAIP as an exogenous variable, it was found that Jeonse price had negative relationships with sales price in the long-term while monthly rent price had positive relationships with sales price in the long-term. Third, according to an analysis with sales, Jeonse, and monthly rent price of apartment houses in Seoul as an endogenous variable and with construction area for residence as an exogenous variable, it was found that Jeonse price had negative relationships with sales price in the long-term while monthly rent price had positive relationships with sales price in the long-term. Fourth, according to an analysis with sales, Jeonse, and monthly rent price of apartment houses in Seoul as an endogenous variable and with 3 variables of IAIP, RCB, and construction area for residence as an exogenous variable, it was found that Jeonse price and monthly rent price had positive relationships with sales price in the long-term. Fifth, according to an analysis of sales and lease price of apartment houses in Seoul as an endogenous variable and with 3 variables IAIP, RCB, and construction area for residence as an exogenous variable, it was found that Jeonse price had negative relationships with sales price in the long-term. Sixth, according to an analysis with sales and monthly rent price of apartment houses in Seoul as an endogenous variable and with 3 variables of IAIP, RCB, and construction area for residence as an exogenous variable, it was found that monthly rent price had positive relationships with sales price in the long-term. Seventh, according to an analysis with 4 variables of sales, Jeonse, monthly rent price and RCB of apartment houses in Seoul as an endogenous variable, it was found that RCB had negative relationships with sales price and Jeonse price in the long-term while it had positive relationships with monthly rent price in the long-term. Eighth, according to an analysis with 4 variables of sales, Jeonse, monthly rent price and IAIP of apartment houses in Seoul as an endogenous variable, it was found that IAIP had positive balance relationships with sales price, Jeonse price, and monthly rent price in the long-term. Ninth, according to an analysis with 4 variables of sales, Jeonse, monthly rent price and construction area for residence of apartment houses in Seoul as an endogenous variable, it was found that construction area for residence had negative balance relationships with monthly rent price in the long-term while it had positive balance relationships with Jeonse price in the long-term. Following are results of IRF (Impulse Response Function). First, according to results of an IRF analysis on economy and Jeonse price, it was found that Jeonse price had negative effect up the 2nd phase by 1 unit impulse and positive effect after 3rd phase while monthly rent price had positive direction by 1 unit impulse of IAIP. And, according to results of an IRF analysis on Jeonse price and housing price, it was found that sales price had positive effect by 1 unit impulse of Jeonse price while sales price had negative direction by 1 unit impulse of monthly rent price. According to results of an IRF analysis on market interest rate and housing price, it was found that sales price had negative impulse reaction by 1 unit impulse of RCB. According to results of an IRF analysis on housing price and supply (construction) volume, it was found that construction area for residence had positive reaction up to the 7th phase by 1 unit impulse of sales price and then, it showed negative direction. Taking the above results together, it is seen that correlation between housing price and monthly rent price in housing market is much higher than the one between housing price and Jeonse price. This seems to be related to rapid increase in monthly rent residence (with deposit) lately. It is also seen in Impulse Response Function that it was theoretically and practically applicable to relationships between housing market, interest rate and supply (construction).
URI
http://dcollection.hanyang.ac.kr/jsp/common/DcLoOrgPer.jsp?sItemId=000000102259http://hdl.handle.net/20.500.11754/33777
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GRADUATE SCHOOL OF REAL ESTATE CONVERGENCE[S](부동산융합대학원) > REAL ESTATE(부동산학과) > Theses (Ph.D.)
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