The effects of housing price on the mortgage debt in Malaysia: new evidence from FMOLS method

• Published in: International Journal of Housing Markets and Analysis
• Main Author: Hammad Ahmad Khan H.
• Format: Article
• Language: English
• Published: Emerald Publishing 2024
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85150761258&doi=10.1108%2fIJHMA-11-2022-0167&partnerID=40&md5=6be78467b5a9c524f7f7b0d0ecc2330b

Purpose: The main purpose of this study is to investigate the impact of housing price on mortgage debt accumulation while considering the structural break effects associated with the Global Financial Crisis (GFC). Design/methodology/approach: To determine the existence of a long run relationship among the variables, this study used a Johansen cointegration test. The long run model was then estimated using the fully modified ordinary least square method and reported for both the model with and without a structural break associated with the GFC. Findings: The findings demonstrate a moderate positive relationship between housing price and mortgage debt, with the impact of the GFC is positive but insignificant. The household’s lack of responsiveness to the GFC may be attributed to their optimistic expectations and confidence in the Malaysian housing market. Practical implications: Findings of this study provide some guidance to policymakers and the banking sector in predicting household borrowing behavior during future economic crises. Originality/value: The increase in housing prices and mortgage debt after the GFC has been a concern for many countries, including Malaysia. This study contributes to the literature by investigating the relationship between housing prices and mortgage debt in Malaysia and sheds light on the impact of the GFC on household borrowing behavior. The study’s contributions include providing new evidence to the underexplored topic, enhancing the robustness and reliability of the empirical results and providing insights into the importance of testing for structural breaks in time series analysis. © 2023, Emerald Publishing Limited.