Detection and Prediction of House Price Bubbles: Evidence from a New City

Hanwool Jang, Kwangwon Ahn, Dongshin Kim, Yena Song

Research output: Chapter in Book/Report/Conference proceedingConference contribution

14 Citations (Scopus)


In the early stages of growth of a city, housing market fundamentals are uncertain. This could attract speculative investors as well as actual housing demand. Sejong is a recently built administrative city in South Korea. Most government departments and public agencies have moved into it, while others are in the process of moving or plan to do so. In Sejong, a drastic escalation in house prices has been noted over the last few years, but at the same time, the number of vacant housing units has increased. Using the present value model, lease-price ratio, and log-periodic power law, this study examines the bubbles in the Sejong housing market. The analysis results indicate that (i) there are significant house price bubbles, (ii) the bubbles are driven by speculative investment, and (iii) the bubbles are likely to burst earlier here than in other cities. The approach in this study can be applied to identifying pricing bubbles in other cities.

Original languageEnglish
Title of host publicationComputational Science – ICCS 2018 - 18th International Conference, Proceedings
EditorsJack Dongarra, Haohuan Fu, Valeria V. Krzhizhanovskaya, Michael Harold Lees, Peter M. Sloot, Yong Shi, Yingjie Tian
PublisherSpringer Verlag
Number of pages14
ISBN (Print)9783319937120
Publication statusPublished - 2018
Event18th International Conference on Computational Science, ICCS 2018 - Wuxi, China
Duration: 2018 Jun 112018 Jun 13

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10862 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference18th International Conference on Computational Science, ICCS 2018

Bibliographical note

Publisher Copyright:
© 2018, Springer International Publishing AG, part of Springer Nature.

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science


Dive into the research topics of 'Detection and Prediction of House Price Bubbles: Evidence from a New City'. Together they form a unique fingerprint.

Cite this