주택가격과 거래량의 동태적 인과관계에 관한 연구

• 영문명: A Study on the Dynamic Causal Relationship between Housing Price and Housing Trading Volume
• 발행기관: 한국주거환경학회
• 저자명: 오윤경(Oh, Yun Kyung)
• 간행물 정보: 『주거환경(한국주거환경학회논문집)』住居環境 제18권 제1호 (통권 제47호), 21~33쪽, 전체 13쪽
• 주제분류: 사회과학 > 지역개발
• 파일형태: PDF
• 발행일자: 2020.03.30

영문 초록

The purpose of this study is to examine the characteristics of the housing market that differs by region by analyzing the correlation between the housing prices and the transaction volume of seven major cities including Seoul. For the analysis, apartment transaction volume and sales price index of Seoul, Busan, Daegu, Incheon, Gwangju, Daejeon, and Ulsan were used. The data was monthly data released by the Korea Appraisal Board and from January 2006 to December 2019. Analytical methods were performed by Granger causality tests, impulse response analysis and variance decomposition analysis. The empirical results of the study can be summarized as follows. First, it is possible to confirm that the sale price and the volume of the house are operating in a positive correlation, but differs depending on the characteristics of the housing market in the area. This suggests that, as suggested in the previous study, price fluctuations affect trade volume fluctuations and trade volume fluctuations have mutual causal effects on price fluctuations. However, only Daegu and Incheon are identified as two-way correlations. Second, an increase in sales prices leads to an increase in trading volume in the short term, while the increase in trading volume is not significant for fluctuations in sales price. Third, as a result of variance decomposition analysis, that the impact of price on the volume of trade is relatively higher than the impact on price on volume. In areas where trade prices and volume have a mutual influence on trade volume change, explanatory power increased from short to long term.

목차

Ⅰ. 서 론

Ⅱ. 선행연구 분석

Ⅲ. 주택시장현황 및 분석방법

Ⅳ. 실증분석

Ⅴ. 결론

참고문헌

키워드

비주택가격 주택거래량 그랜저인과관계 VAR모형 Housing Price Housing Trading Volume Granger Causality Vector Auto Regresion model