Cross-regional connectedness in the Korean housing market

Lee, Hahn Shik; Lee, Woo Suk

doi:10.1016/j.jhe.2019.101654

Cited by 21 publications

(10 citation statements)

References 29 publications

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“…The housing policy of the Korean government has primarily Land 2021, 10, 879 2 of 21 focused on solving the housing problems in Seoul, especially the instability of housing prices. Consequently, it was inevitable that the housing policy of Gyeonggi-do would be influenced by the Seoul-centered policy direction [10]. Therefore, it can be said that Gyeonggi-do has been the subject of policies that are limited to the subordinate role of making up for the housing shortage in Seoul, despite having a much larger population (approximately 40% larger than that of Seoul) and unique characteristics as a considerable housing submarket.…”

Section: Introductionmentioning

confidence: 99%

“…The outskirts of Seoul and Gyeonggi-do have an organic relationship with each other despite their different housing market characteristics. In other words, although the administrative scope differs, there is a large spillover phenomenon in which changes in housing prices within one region affect other regions [10,11]. In particular, a number of the policies (e.g., 1st new city project, 3rd new city project, and public transportation system expansion) to solve the housing problems in Seoul have been implemented in the Gyeongeui region, which is in the northwest of Gyeonggi-do.…”

Section: Introductionmentioning

confidence: 99%

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Micro-Analysis of Price Spillover Effect among Regional Housing Submarkets in Korea: Evidence from the Seoul Metropolitan Area

Kim¹,

wonseok

2021

Land

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This study examined the price spillover effect of housing submarkets in cities in the Seoul metropolitan area in South Korea by using the Granger causality test and vector autoregressive model (VAR). We found that housing prices showed a higher spillover effect within regions with similar housing market characteristics. Additionally, the spatial spillover of housing prices revealed a difference between sales price and jeonse price. The spillover of jeonse price was characterized by mutual influence among neighboring cities, while that of sales price was characterized by the influence being transferred in one direction hierarchically. Furthermore, the effects of housing price indicated a slight difference between sales price and jeonse price. Although jeonse price was mainly affected by a neighboring area (geographic boundary), sales price was more influenced by the city with the highest housing prices. Lastly, the housing price spillover tended to be expansive around the city with the highest price. These results suggest that housing price policies targeting specific regions or areas in Korea must be differentiated according to the type of occupancy (jeonse or sales), and it is essential to consider the externalities when promoting policies in the housing market wherein externalities may be significant.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Micro-Analysis of Price Spillover Effect among Regional Housing Submarkets in Korea: Evidence from the Seoul Metropolitan Area

Kim¹,

wonseok

2021

Land

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“…the scope of risk in the studied market. The application of this approach in the housing market includes Damianov and Elsayed (2018), Lee and Lee (2019), Nguyen et al (2022), among others. The DCC-GARCH model of Engle (2002) is based on modeling conditional correlation of the univariate GARCH model.…”

Section: Related Literaturementioning

confidence: 99%

Comovements and spillovers in international commercial and residential real estate markets

Kishor

2022

JERER

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PurposeThis study aims to know to what extent do the commercial and residential estate markets move together in different economies? Do the shocks originating in one of these markets spillover to the other markets?Design/methodology/approachThe authors apply a modified version of the dynamic factor model to commercial and residential real estate prices in the Euro area, Hong Kong, Singapore and the USA. This modified dynamic factor model decomposes price growth in these two real estate markets into common, spillover and idiosyncratic components.FindingsThe results show significant heterogeneity in the relative importance of different components in the evolution of commercial and residential price growth across different economies. The findings suggest that the spillover from the residential to commercial real estate market dominates the spillover from the commercial to real estate market for all the economies in our sample. The authors also find that the common component accounts for a large fraction of the price movements in the residential markets in the European Union (EU) area and the USA, whereas spillover and common components together explain more than two-thirds of the variations in Hong Kong and Singapore. The results suggest that the role of spillover from one market to another increased significantly during the financial crisis of 2008–2009.Originality/valueThis paper contributes to the existing literature on how the transmission of shocks takes place across commercial and residential real estate markets. The transmission of shocks can take place in two directions in the proposed framework. There may be a direct spillover from a shock from one market to another. This corresponds to a shock to the idiosyncratic component affecting the other idiosyncratic component. In this paper, the authors are mainly interested in indirect spillover where the shock would transmit from the idiosyncratic factor to the common factor, and then from the common factor to the other idiosyncratic factor.

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“…The influence of London on other regional markets varies over time and housing returns in the capital are also affected by spillovers from other regions. Lee and Lee (2016) and Hwang and Sue (2018) examine spillovers between monthly regional housing market returns in Korea, over respectively 1986Korea, over respectively -2014Korea, over respectively and 2003Korea, over respectively -2017. They find relatively similar results, with spillovers accounting for about two-thirds of the system's forecast error variance over the full samples and Seoul having the strongest influence on other markets.…”

Section: Introductionmentioning

confidence: 99%

Spillovers between US real estate and financial assets in time and frequency domains

Tiwari

André

Gupta

2020

JPIF

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PurposeAssessing the strength and time variation of spillovers between returns on residential real estate, real estate investment trusts (REITs), stocks and bonds in the United States. Spillovers reduce the benefits of portfolio diversification, especially in crisis times, when asset returns tend to be more correlated.Design/methodology/approachThe Diebold–Yilmaz approach in the time domain and the Baruník–Krehlík methodology in the frequency domain are used. The latter allows distinguishing spillovers generating only short-lived volatility from those with a more persistent effect.FindingsOn average, spillovers between housing, stock and bond returns are relatively modest and shocks to stock and bond markets affect housing returns more than the other way round, even though with variations over time. Spillovers in both directions are much stronger between REITs and stocks than between REITs and housing. Shocks originating in the housing market are most persistent, particularly in the aftermath of the subprime crisis.Practical implicationsHousing provides a hedge against volatility in financial (including REITs) markets. However, hedging strategies involving housing need to take into account potential tail events such as the GFC and the investment horizon.Originality/valueTo the best of the knowledge of the authors, this paper is the first to apply the Baruník–Krehlík methodology to real estate price spillovers. Although the Diebold–Yilmaz methodology has been used in several studies on spillovers between residential real estate and financial asset returns, this paper covers a new set of variables and time span.

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Cross-regional connectedness in the Korean housing market

Cited by 21 publications

References 29 publications

Micro-Analysis of Price Spillover Effect among Regional Housing Submarkets in Korea: Evidence from the Seoul Metropolitan Area

Micro-Analysis of Price Spillover Effect among Regional Housing Submarkets in Korea: Evidence from the Seoul Metropolitan Area

Comovements and spillovers in international commercial and residential real estate markets

Spillovers between US real estate and financial assets in time and frequency domains

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