서울 아파트 경매 매각가율에 미치는 영향 요인 연구 : 부동산 시장 심리 지수를 중심으로 = A study on factors affecting the auction winning price ratio of apartments in seoul : focusing on the real estate market sentiment Index

다국어 초록 (Multilingual Abstract)

This study aims to empirically identify factors influencing apartment auction success rates based on apartment auction data from Seoul Metropolitan City between January 2020 and December 2024. Previous studies on the auction market tended to focus on macroeconomic variables such as interest rates, inflation, and economic indicators, or on the physical and legal characteristics of individual properties. In contrast, this study analyzes how publicly available market indicators encountered daily by auction participants, particularly various apartment market sentiment indicators provided by KB Real Estate, affect the auction success rate. This aims to verify whether a micro-level approach based on sentiment indicators is also valid for the auction market. The study covers the entire Seoul metropolitan area, subdivided into Gangnam 3 Districts, the Han River Belt, and other regions to reflect spatial characteristics. This division considered the possibility that the intensity of market sentiment responses might differ across regions. Research data utilized Seoul auction winning bid data, market sentiment indicators provided by KB Real Estate, and Real Estate 114 indicators. Analytical methods included descriptive statistics, one-way analysis of variance (ANOVA), and multiple regression analysis. First, analyzing trends in Seoul's apartment auction market from 2020 to 2024 revealed that the number of successful bids and the bid-to-list price ratio showed distinct annual changes due to the impacts of Covid-19, interest rate fluctuations, and economic contraction. Particularly after 2023, as interest rates eased and the market recovery phase began, the auction success rate showed an upward trend, with this recovery appearing relatively quickly in the Gangnam 3 Districts and the Han River Belt area. The regression analysis, the core methodology of this study, confirmed that the KB Market Price Change Rate, KB Transaction Price Index, KB Transaction Price Outlook Index, and KB Buyer Advantage Index exert a statistically significant positive (+) influence on the overall auction price ratio for Seoul apartments. This indicates that, similar to the actual transaction market, market participants' expectations and sentiment play a crucial role in the price formation process within the auction market as well. Specifically, as market optimism or demand dominance intensifies, auction bidders also tend to project future prices more positively, leading to higher auction success rates. Regional analysis revealed that psychological indicators exerted a particularly strong influence in the Gangnam 3 Districts and the Han River Belt area. This aligns with these regions being representative investment hotspots in the general sales market, characterized by high price volatility and rapid psychological response speeds. Conversely, other regions showed relatively greater susceptibility to external market factors like macroeconomic variables and transaction volume. These results demonstrate that regional market structures and demand characteristics are directly reflected in the auction market. This study empirically demonstrates the explanatory power of market sentiment indicators, which previous auction market research overlooked, confirming that publicly available indicators with high information accessibility actually influence auction participants' decision-making processes. Particularly, the fact that the KB indicator—which intuitively reflects market sentiment—showed a high correlation with the winning bid rate underscores the necessity of utilizing sentiment indicators in future auction market analysis and policy design.
Ultimately, this study demonstrates that auction market analysis can be expanded beyond a simple focus on appraised value and physical characteristics to a multidimensional analytical framework that incorporates micro-level factors like market sentiment. It provides empirical foundational data enabling a more realistic and timely approach to auction investment strategies and policy decisions.

목차 (Table of Contents)

• 제1장 서론 1
• 제1절 연구의 배경 및 목적 1
• 1. 연구의 배경 1
• 2. 연구의 목적 3
• 제2절 연구의 범위 및 방법 4
• 1. 연구의 범위 4
• 2. 연구의 방법 6
• 제3절 연구의 구성 및 체계 7
• 제2장 이론적 고찰 및 선행연구 검토 10
• 제1절 부동산 경매 10
• 1. 부동산 경매의 개념 10
• 2. 부동산 경매의 특성 11
• 3. 부동산 경매의 절차 13
• 4. 부동산 경매시장 현황 16
• 5. 부동산 경매 매각가율의 의의 23
• 제2절 부동산 가격 결정 이론 28
• 1. 부동산 가격 형성요인 28
• 2. 내재가격 결정이론 30
• 3. 거품가격이론(Bubble Price Theory) 34
• 4. 효율적 시장가설(EMH) 35
• 제3절 부동산 지수에 대한 고찰 37
• 1. 한국부동산원 37
• 2. 국토연구원 38
• 3. KB부동산 39
• 4. 부동산114 40
• 제4절 선행연구 검토 및 연구의 차별성 41
• 1. 아파트 매각가격 결정요인 선행 연구 41
• 2. 아파트 경매 매각가율 결정요인 선행 연구 49
• 3. 선행연구와의 차별성 58
• 제3장 연구모형의 설계 및 분석방법 61
• 제1절 분석 자료 61
• 제2절 분석방법 고찰 62
• 1. 상관관계 분석 62
• 2. 분산분석(ANOVA) 64
• 3. 다중회귀분석 모형 66
• 제3절 변수 고찰 68
• 1. 물리적 특성 변수 68
• 2. 경매 절차적 특성 변수 72
• 3. KB 부동산 지수 특성 변수 74
• 제4절 연구모형 및 가설 설정 78
• 1. 변수설정 및 연구 모형 78
• 2. 연구 가설 82
• 제4장 분석 결과 85
• 제1절 기술통계 분석 85
• 1. 전체모형 기술통계량 86
• 2. 강남3구모형 기술통계량 89
• 3. 한강벨트 기술통계량 91
• 4. 기타지역 기술통계량 93
• 4. 모형별 기술통계량 비교 95
• 제2절 상관관계분석 결과 95
• 제3절 회귀분석 결과 97
• 1. 전체 모형 분석결과 97
• 2. 강남3구 모형 분석결과 100
• 3. 한강벨트 모형 분석결과 103
• 4. 기타지역 모형 분석결과 106
• 제4절 소결 108
• 제5장 결론 113
• 제1절 연구결과 요약 및 시사점 113
• 제2절 향후 연구의 방향 및 과제 116
• 참고문헌 118
• ABSTRACT 123