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Analyzing Dynamic Connectedness in Korean Housing Markets

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  • So Jung Hwang
  • Hyunduk Suh

Abstract

This study investigates regional housing market connectedness among the 16 first-tier administrative divisions in Korea and 25 districts in Seoul, the capital city. Time-varying parameter vector autoregressive model is used to capture time-varying nature of Diebold and Yilmaz (2014) connectedness network. Rapid increases in connectedness during the sample period are mostly associated with housing booms rather than downturns. The connectedness cycles for the whole country and for Seoul seem to diverge after the global financial crisis. During the 2006 and 2018 connectedness surge episodes, when housing booms were driven by the Seoul metropolitan area, Seoul and the surrounding Gyeonggi province had a strong influence on the whole country network. However, their impact was much weaker in 2010–2011 when the housing boom arose outside Seoul. The influence of Gangnam-3 districts in Seoul’s connectedness network is low overall, but tends to lead the total connectedness index by a few months.

Suggested Citation

  • So Jung Hwang & Hyunduk Suh, 2021. "Analyzing Dynamic Connectedness in Korean Housing Markets," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 57(2), pages 591-609, January.
    • Handle: RePEc:mes:emfitr:v:57:y:2021:i:2:p:591-609
    DOI: 10.1080/1540496X.2019.1649653
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    Cited by:

    1. Molina-Muñoz, Jesús & Mora-Valencia, Andrés & Perote, Javier, 2025. "Dynamic volatility spillovers among commodities, bitcoin, and emerging markets," Emerging Markets Review, Elsevier, vol. 69(C).
    2. Huifu Nong, 2024. "Integration and risk transmission across supply, demand, and prices in China’s housing market," Economic Change and Restructuring, Springer, vol. 57(3), pages 1-28, June.
    3. Aviral Kumar Tiwari & Christophe André & Rangan Gupta, 2020. "Spillovers between US real estate and financial assets in time and frequency domains," Journal of Property Investment & Finance, Emerald Group Publishing Limited, vol. 38(6), pages 525-537, April.
    4. Lu, Yunzhi & Li, Jie & Yang, Haisheng, 2021. "Time-varying inter-urban housing price spillovers in China: Causes and consequences," Journal of Asian Economics, Elsevier, vol. 77(C).
    5. Lee, Hahn Shik & Lee, Woo Suk, 2019. "Cross-regional connectedness in the Korean housing market," Journal of Housing Economics, Elsevier, vol. 46(C).
    6. James E. Payne & Xiaojin Sun, 2023. "Time‐varying connectedness of metropolitan housing markets," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 51(2), pages 470-502, March.

    More about this item

    JEL classification:

    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies
    • R31 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Housing Supply and Markets

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