메뉴 건너뛰기
Library Notice
Institutional Access
If you certify, you can access the articles for free.
Check out your institutions.
ex)Hankuk University, Nuri Motors
Log in Register Help KOR
Subject

Operational Characteristics of Repeat Sales Price Indices Using Transaction Sales and Chonsei Prices of Apartments
Recommendations
Search

반복매매모형을 이용한 아파트 실거래지수 운영특성 분석

논문 기본 정보

Type
Academic journal
Author
Journal
Korea Real Estate Analysts Association(Kreaa) 부동산학연구 부동산학연구 제13권 제2호 KCI Accredited Journals
Published
2007.1
Pages
21 - 40 (20page)

Usage

cover
Operational Characteristics of Repeat Sales Price Indices Using Transaction Sales and Chonsei Prices of Apartments
Ask AI
Recommendations
Search

Abstract· Keywords

Report Errors
>Most of the price indices for apartments in Korea have been based on the stock price index model using offering prices for a set of survey units. However, seller's reporting of the real transaction price was mandated by law in 2006. In order to use the real transaction data newly obtainable, a new type of price indices are required. The basic choices would be between a hedonic price index and a repeat sales index. It is commonly recognized that the hedonic price index requires an extensive data set of housing and locational characteristics, while it can generate a quality controlled index. On the other hand, the repeat sales index is inefficient in using data, since it use repeatedly transacted sales data only, while it is the best in quality control. The standardized characteristics of apartments in Korea allow us to define a set of similar units as a same house. This feature of apartments allow us to overcome the inefficiency problem contained in the repeat sales index.We developed an repeat sales index using real transaction data based on some relaxed definitions of a same house. The developed repeat sales index shows earlier and more sensitive movements of prices than the conventional index.

Contents

No content found

References (12)

Add References

Recommendations

It is an article recommended by DBpia according to the article similarity. Check out the related articles!

Related Authors

Recently viewed articles

Comments(0)

0

Write first comments.