Housing loan default in Malaysia: an analytical insight and policy implications

Abstract

Purpose The purpose of this paper is to examine the drivers of default in the Malaysian housing market in the light of various policy interventions by the country’s central bank, and the government’s expressed concern to ensure balanced growth in the market. This paper assesses the importance of considering the endogeneity of loan-to-value (LTV) in predicting housing loan default and its implications. Design/methodology/approach In this paper, the author addresses the endogeneity problem in the LTV variable using two instrumental variables (IV) in this probit regression: national residential property gains tax and the statutory reserve ratio of Bank Negara Malaysia. This study uses the instrumental variable probit model to consider endogeneity bias. This study assumes a latent (unobservable) variable (Y*), representing a borrower’s tendency to default, which is associated linearly with the borrower’s and loan characteristics and other variables (Xi). This study uses individual borrower-level information of 43,156 housing loan borrowers from the files of a well-established housing bank in Malaysia. Findings This study’s results confirm that endogeneity causes a substantial difference in the magnitude of the estimated effects of LTV on the default tendency. At the lower values of LTV, the probability of default is over-estimated, and at the higher values, the default probability is substantially underestimated. Endogeneity bias also affects the estimated coefficients of loan and borrower characteristics. The authors find that the interest rate is less relevant in predicting loan default. Other loan characteristics, such as loan age, tenure, payment amount and the built-up area, are relevant. This study’s result confirms that the borrower’s location matters, and an increase in state gross domestic product per capita and an increase in the supply of residential units reduce default probability. Research limitations/implications The present study did not explore the applicability of the “equity theory of default” in the Malaysian housing market. This study did not assess “strategic default” issues and the effect of borrowers’ characteristics, personality traits and self-control of Malaysian housing loan borrowers in the mortgage decision-making process. The evolving dynamics of the Malaysian housing market microstructure in property valuation remained unexplored in the present study. Practical implications The findings have crucial relevance in the decision-making process of commercial banks, the central bank and the government to frame policies to foster balanced growth and development in the housing market. The authors argue that striking a subtle balance between the concerns of financial stability and productive risk-taking by commercial banks in Malaysia remains a continuing challenge for the country’s central bank. The authors also argue that designing suitable taxation policies by the government can deliver its cherished goal of balanced development in the housing market. Originality/value Empirical research on the Malaysian housing market based on micro-level data is scarce due to a paucity of relevant data. This study is based on the individual borrower-level information of 43,156 housing loan borrowers from the files of a well-established housing bank in Malaysia. In this analysis, the authors find clear evidence of endogeneity in LTV and argue that any attempts to decipher the default drivers of housing loans without addressing the issue of endogeneity may lead to faulty interpretation. Therefore, this study is unique in recognizing endogeneity and has gone deeper in identifying the default drivers in the Malaysian housing market not addressed by earlier papers.

Modeling Tenant’s Credit Scoring Using Logistic Regression

“…Notice that the positive sign of the logistic coefficient indicates that the higher the x i value, the higher the probability of default and vice versa. Therefore, the male is more likely to default as compared to the female, which is similar to the finding of Lin et al (2017), Chamboko and Bravo (2019), Adzis et al (2020), andSaha et al (2021). Adzis et al (2020) recommended that the Malaysian lenders may create a new mortgage loan product specifically for female borrowers since women are more responsible in their loan repayment rather than male.…”

“…Chamboko and Bravo (2019) found gender, age, income earned, debt-to-income ratio, loan terms, and the number of past missed payments in Zimbabwe. On the other hand, Adzis et al (2020) and Saha et al (2021) concluded house equity, age, gender, ethnicity, location, the types of occupation, guarantor availability, and loan characteristics like payment-to-income (PTI) ratio, loan original balance, loan tenure, loan interest rate, and loan-to-value (LTV) ratio are the significant factors that influence loans default in Malaysia. The chance of individuals who lack credit histories getting a loan will be increased if financial institutions use non-financial data to develop the credit scoring model.…”

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

“…Specifically, a 1% increase in interest rates is expected to reduce mortgage debt by 0.2%, suggesting that households are less sensitive to interest rate changes. Consistently, a study by Saha et al (2022) on housing loan defaults in Malaysia also supports the notion that interest rates are less relevant in predicting loan defaults. Therefore, it can be concluded that monetary policy, particularly the interest rate targeting method, may not be an effective means of controlling high levels of household debt.…”

“…This suggests that households are less responsive to changes in interest rates, potentially due to positive expectations about the housing market. As a result, targeting interest rates might not be effective to address this issue (Saha et al , 2022).…”

Interdependence between foreigner housing acquisitions and housing price increase in Turkey during the COVID-19 pandemic era

“…This study obtained monthly data on the HPI and quantity of HAF, the CPI and Turkish interest rates from January 2020 to March 2022 from the TurkStat and investing.com databases, respectively. CPI and interest rates are essential macroeconomic variables influencing housing prices and acquisition (Alola, 2020; Kartal et al , 2021; Saha et al , 2022). Therefore, controlling for those variables if they are not the focus of the study is essential.…”