IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v11y2022i12p2296-d1003388.html
   My bibliography  Save this article

The Time-Varying Effect of Interest Rates on Housing Prices

Author

Listed:
  • Cheonjae Lee

    (Global Development Partnership Center, Korea Research Institute for Human Settlements (KRIHS), 5 Gukchaegyeonguwon-ro, Sejong-si 30147, Republic of Korea)

  • Jinbaek Park

    (Real Estate Market Research Center, Korea Research Institute for Human Settlements (KRIHS), 5 Gukchaegyeonguwon-ro, Sejong-si 30147, Republic of Korea)

Abstract

This study analyzes the time-varying effect of interest rates on housing prices. As housing prices are too high for most consumers to afford with income alone, they use bank loans. Consequently, when interest rates fall, the demand for housing increases, causing prices to rise. This effect of interest rates was common in countries that implemented low-interest rates in response to the COVID-19 pandemic. Using Korean data from March 1991 to March 2022, this study examined the impact of interest rate shocks on housing prices by employing a time-varying parameter vector autoregressive model. According to the analysis, in Korea, while the impact of the interest rate shocks on housing prices was not significant before the global financial crisis, it increased dramatically afterward. Particularly, the impact of interest rate shocks was strongest relative to the past during the period of the increase in house prices from 2020 to 2021. The rise in the effects of interest rate shocks on housing prices is attributed to the increased dependence on loans for housing purchases. The results suggest that given the recent substantial increments in interest rates due to inflation, an interest rate shock would likely cause a global housing market recession.

Suggested Citation

  • Cheonjae Lee & Jinbaek Park, 2022. "The Time-Varying Effect of Interest Rates on Housing Prices," Land, MDPI, vol. 11(12), pages 1-16, December.
    • Handle: RePEc:gam:jlands:v:11:y:2022:i:12:p:2296-:d:1003388
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/11/12/2296/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2073-445X/11/12/2296/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Giorgio E. Primiceri, 2005. "Time Varying Structural Vector Autoregressions and Monetary Policy," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(3), pages 821-852.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Kyungbo Park & Hangook Kim & Jeonghwa Cha, 2023. "An Exploratory Study on the Development of a Crisis Index: Focusing on South Korea’s Petroleum Industry," Energies, MDPI, vol. 16(14), pages 1-24, July.
    2. Zarul Azhar Nasir & Noormahayu Mohd Nasir & Muhammad Adidinizar Zia Ahmad Kusairee & Siti Nur’Amalina Syeddin & Nor Zarina Mohd Salim, 2023. "Evaluating the Nexus between Monetary Sector Variables and Housing Affordability in Malaysia," Information Management and Business Review, AMH International, vol. 15(4), pages 31-40.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Drew Creal & Siem Jan Koopman & Eric Zivot, 2008. "The Effect of the Great Moderation on the U.S. Business Cycle in a Time-varying Multivariate Trend-cycle Model," Tinbergen Institute Discussion Papers 08-069/4, Tinbergen Institute.
    2. Punzi, Maria Teresa, 2016. "Financial cycles and co-movements between the real economy, finance and asset price dynamics in large-scale crises," FinMaP-Working Papers 61, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    3. Tomas Konecny & Oxana Babecka-Kucharcukova, 2016. "Credit Spreads and the Links between the Financial and Real Sectors in a Small Open Economy: The Case of the Czech Republic," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 66(4), pages 302-321, August.
    4. Florian Huber & Josef Schreiner, 2023. "Are Phillips curves in CESEE still alive and well behaved?," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue Q3/23, pages 7-27.
    5. Zsolt Darvas, 2013. "Monetary transmission in three central European economies: evidence from time-varying coefficient vector autoregressions," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 40(2), pages 363-390, May.
    6. Vincent Brémond & Emmanuel Hache & Tovonony Razafindrabe, 2016. "The Oil Price and Exchange Rate Relationship Revisited: A time-varying VAR parameter approach," European Journal of Comparative Economics, Cattaneo University (LIUC), vol. 13(1), pages 97-131, June.
    7. Luca Benati & Paolo Surico, 2009. "VAR Analysis and the Great Moderation," American Economic Review, American Economic Association, vol. 99(4), pages 1636-1652, September.
    8. Pooyan Amir-Ahmadi & Christian Matthes & Mu-Chun Wang, 2020. "Choosing Prior Hyperparameters: With Applications to Time-Varying Parameter Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(1), pages 124-136, January.
    9. Jin‐Yu Chen & Xue‐Hong Zhu & Mei‐Rui Zhong, 2021. "Time‐varying effects and structural change of oil price shocks on industrial output: Evidence from China's oil industrial chain," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 3460-3472, July.
    10. Yang Liu & Mariano Croce & Ivan Shaliastovich & Ric Colacito, 2016. "Volatility Risk Pass-Through," 2016 Meeting Papers 135, Society for Economic Dynamics.
    11. Gary Koop & Dimitris Korobilis, 2019. "Forecasting with High‐Dimensional Panel VARs," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 81(5), pages 937-959, October.
    12. Davide Pettenuzzo & Francesco Ravazzolo, 2016. "Optimal Portfolio Choice Under Decision‐Based Model Combinations," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1312-1332, November.
    13. Gruber, Lutz F. & West, Mike, 2017. "Bayesian online variable selection and scalable multivariate volatility forecasting in simultaneous graphical dynamic linear models," Econometrics and Statistics, Elsevier, vol. 3(C), pages 3-22.
    14. Francesco Bianchi, 2013. "Regime Switches, Agents' Beliefs, and Post-World War II U.S. Macroeconomic Dynamics," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 80(2), pages 463-490.
    15. Luca Benati & Paolo Surico, 2008. "Evolving U.S. Monetary Policy and The Decline of Inflation Predictability," Journal of the European Economic Association, MIT Press, vol. 6(2-3), pages 634-646, 04-05.
    16. Olawale Awe O. & Adedayo Adepoju A., 2018. "Modified Recursive Bayesian Algorithm For Estimating Time-Varying Parameters In Dynamic Linear Models," Statistics in Transition New Series, Polish Statistical Association, vol. 19(2), pages 258-293, June.
    17. Zhang, Zhikai & Wang, Yudong & Xiao, Jihong & Zhang, Yaojie, 2023. "Not all geopolitical shocks are alike: Identifying price dynamics in the crude oil market under tensions," Resources Policy, Elsevier, vol. 80(C).
    18. Coşkun Akdeniz, 2021. "Construction of the Monetary Conditions Index with TVP-VAR Model: Empirical Evidence for Turkish Economy," Springer Books, in: Burcu Adıgüzel Mercangöz (ed.), Handbook of Research on Emerging Theories, Models, and Applications of Financial Econometrics, edition 1, pages 215-228, Springer.
    19. Miranda-Agrippino, Silvia & Ricco, Giovanni, 2018. "Bayesian Vector Autoregressions," The Warwick Economics Research Paper Series (TWERPS) 1159, University of Warwick, Department of Economics.
    20. Neusser, Klaus, 2016. "A topological view on the identification of structural vector autoregressions," Economics Letters, Elsevier, vol. 144(C), pages 107-111.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jlands:v:11:y:2022:i:12:p:2296-:d:1003388. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.