Evaluating the Nexus between Monetary Sector Variables and Housing Affordability in Malaysia

: Housing affordability is a globally recognized and pressing issue that has prompted extensive discussions in the realms of societal discourse, academic research, and policy development. In the context of Malaysia, this issue persists, despite the government implementing a diverse array of initiatives aimed at alleviating housing affordability challenges. This study aims to explore the nexus between housing affordability and key monetary sector variables, including money supply, interest rates, inflation rates, and foreign exchange rates in Malaysia. The study employed Autoregressive Distributed Lag (ARDL) estimation techniques on a dataset comprising 52 quarterly observations from the years 2010 to 2022. The findings demonstrate the existence of a long-term cointegration relationship between money supply, inflation rates, interest rates and housing affordability. Conversely, in the short term, the analysis reveals that only money supply and inflation rates exert a statistically significant influence on housing affordability. The long-term cointegration of money supply and inflation rates with housing affordability, along with their significant short-term relationship, highlights these two monetary variables as primary drivers of housing affordability. These results underscore the critical role of monetary sector variables in determining housing affordability in Malaysia. Consequently, policymakers are encouraged to prioritize the regulation of monetary sector variables, particularly focusing on money supply and inflation rates, to effectively promote housing affordability in Malaysia.


Introduction
Housing affordability stands as a pivotal and pressing apprehension, commanding substantial deliberation within the spheres of societal discourse, academic research, and policy formulation.It is also acknowledged as a burgeoning issue on a global scale (Baker et al., 2016;Lee et al., 2022), especially prevalent within households characterized by moderate to lower income levels (Haffner & Hulse, 2021).The housing affordability problems lead to numerous adverse outcomes that emerge both on a micro level within individual households and on a broader macroeconomic scale (Galster & Lee, 2021).
From a micro perspective, issues regarding housing affordability can profoundly have an impact on individuals' well-being and satisfaction (Foye, 2017).The presence of exorbitant housing costs will result in significant societal consequences, as households are compelled to make concessions by diminishing expenditures on non-housing items and essential household needs, including education, healthcare, and food, to meet the elevated housing costs (Galster & Lee, 2021).The lack of basic housing necessities will result in notable negative externalities, encompassing deteriorations in both physical and mental well-being, in addition to limitations in educational accomplishments (Mason et al., 2013;Cattaneo et al., 2009).
From the macroeconomic standpoint, the housing affordability crisis evidently could also have impacts on socio-economic development, labor market productivity, and natural resource efficiency.Wang et al. (2012) substantiated the notion that housing affordability plays a crucial role in fostering economic development through the attraction of investments into the housing sector and the stimulation of housing consumption.Conversely, a low level of housing affordability can result in an imbalanced economic structure and a reduction in overall economic growth.Galster and Lee (2021) and Maclennan et al. (2018) further articulate that the cost of housing within employment centers is notably exorbitant and unaffordable.People are constrained to choose residences distant from their employment locations, thereby resulting in extended commuting durations, heightened traffic congestion, increased pollution, and the wasteful depletion of natural resources.Furthermore, research findings by Been et al. (2019) and Chen et al. (2019) demonstrate that the housing affordability problem carries adverse consequences for the labor market, resulting in diminished worker productivity.
In Malaysia, the government has formulated a diverse array of initiatives aimed at mitigating the housing affordability problem.These measures encompass the construction of affordable housing for individuals with lower and middle incomes, provision of financial aid to qualified first-time homebuyers, the introduction of economical rental housing targeting low-income urban households, implementation of a scheme permitting eligible individuals to lease homes with the prospect of future ownership, and establishment of collaborations with financial institutions to extend housing loan programs characterized by competitive interest rates and flexible terms.These strategic initiatives collectively underscore Malaysia's government commitment to addressing the housing affordability issue, with a resolute aim to achieve target 11.1 of the Sustainable Development Goals (SDGs).This target strives to ensure universal access to suitable, secure, and costeffective housing by the year 2030.Nevertheless, despite the initiatives undertaken by the government to address the housing affordability problem, the situation has deteriorated since the year 2000, with median housing prices consistently exceeding the affordability threshold, which is set at three times the median annual household income (Musaddad et al., 2023).
Against this background, this study was conducted to examine the dynamic interaction between housing affordability and key monetary variables in Malaysia, encompassing money supply, interest rates, inflation, and foreign exchange rates, over both short-term and long-term horizons.This paper follows a structured format with five distinct sections.In Section 2, the literature review comprehends existing knowledge.Section 3 elaborates on the methodology for empirical exploration.Section 4 presents the empirical results and subsequent discussion.Lastly, in Section 5, a conclusion is provided that summarizes the study's findings and offers recommendations.

Literature Review
What is Housing Affordability?Ezennia and Hoskara (2019) and Nwuba and Kalu (2018) note that the definition of housing affordability and its measurement concepts are continually evolving and becoming more widespread (Nwuba & Kalu, 2018;Ezennia & Hoskara, 2019).Additionally, Kallakmaa-Kapsta and Kolbre (2013) have emphasized the importance of adopting a multifaceted approach that considers diverse factors affecting housing affordability in various contexts, rather than relying solely on a single, narrowly defined concept in assessing housing affordability.In a similar vein, Ben-Shahar et al. (2020) proposed that different countries and socioeconomic groups have distinct interpretations of the meaning of housing affordability and different measurement approaches.
At a fundamental level, housing affordability is typically measured by examining the cost of housing to the disposable income of a household (Bieri, 2014;Gopalan & Venkataraman, 2015).Galster and Lee (2021) argued that a comprehensive definition of housing affordability should encompass three essential components that are the costs associated with housing and non-housing goods, the financial resources available to the household to purchase houses, and a normative standard that establishes the minimum acceptable levels of consumption for both housing and non-housing goods by the household.Paris (2007) observes that, in terms of measurement approaches, most of the past studies have employed the Median Multiple Method, also recognized as the housing price-to-income ratio (PIR), to evaluate housing affordability.This method utilizes the median household income as its benchmark.Following this methodology, The Demographia International Housing Affordability (2022) established the median house price to the median household income approach for measuring housing affordability.This approach is currently pervasive on a global scale and bears the imprimatur of esteemed international organizations such as the World Bank and the United Nations (Bank Negara Malaysia, 2016).Housing is considered affordable when this ratio remains below three times.

Monetary Sector Variables and Housing Affordability:
This section provides an overview of the findings of past literature on the relationship between monetary sector variables and housing affordability.A multitude of empirical studies have already examined the relationship between monetary sector variables with housing affordability.Nonetheless, prior research predominantly examined these monetary sector variables in isolation, resulting in disparities within research findings.This underscores the imperative for scholarly inquiry to undertake a more holistic and comprehensive framework to elucidate this intricate relationship.
In their empirical study, Liu and Liu (2010) rigorously examined the association between money supply and housing affordability across eight prominent Australian capital cities.Employing a structural vector autoregression (SVAR) model, their analysis yielded a significant empirical finding: a positive and statistically significant relationship between money supply and housing prices.However, the result of their study postulates that the response of housing price to the shock of money supply are notably more pronounced in the urban centers of Brisbane, Canberra, and Perth, relative to other major capital cities across Australia.These findings are in line with two other studies conducted by Yin et al. (2020) and Feng (2022) in mainland China.In the case of Yin et al. (2020), their study similarly identified a co-movement between housing prices and money supply, particularly in the short term, with this relationship becoming even more pronounced in the medium term.They also elucidated that the expansion of China's money supply resulted in an excess of funds, which in turn increased the demand for residential properties and consequently drove an upsurge in the price.Furthermore, Feng (2022) through the cointegration test discovered a stable and positive long-term relationship between real estate prices and the broad money supply.
Interest rates play a crucial role in addressing housing affordability issues, as interest payments constitute a substantial portion of the overall costs associated with purchasing a house (Elbourne, 2008).Fluctuations in interest rates lead to changes in the spending and saving behaviors of households, thereby influencing decisions regarding residential property purchases (Damen et al., 2016).For instance, the National Association of Realtors U.S. ( 2004) revealed that housing affordability showed improvement in 69 major cities in the United States as homebuyers experienced the advantages of declining interest rates, resulting in more manageable mortgage payments.Research conducted by Yin et al. (2020) revealed that an increase in interest rates has a positive impact on housing prices, consequently leading to a rise in the housing affordability index, which indicates that housing has become less affordable in China.Furthermore, Deb et al. (2022), in their study on housing market stability and affordability in the Asia-Pacific region, explained that an increase in inflation and interest rates creates a dual challenge for household budgets.This is because higher interest rates result in higher mortgage payments, making homeownership unattainable for the average household.Shi et al. (2014), in their investigation of how changes in central bank policies and retail mortgage rates affected real housing prices in New Zealand from 1999 to 2009, also discovered a significant and positive relationship between real interest rates and real housing prices.This finding suggests that increasing interest rates may not be an effective strategy for reducing real housing prices in New Zealand.In contrast, Januário and Cruz (2023) revealed that there is a negative relationship between interest rates and the housing affordability index.They found that lower interest rates lead to an increase in house prices and worsen the housing affordability index, indicating decreased affordability.Furthermore, Yiu (2023), who conducted a panel regression analysis across ten countries, confirmed that, after controlling factors such as GDP growth and unemployment, changes in real interest rates hurt house price growth rates.
Several studies have examined the relationship between inflation, as a monetary sector variable, and housing affordability.Kleshcheva (2021) conducted research and concluded that inflation has a direct impact on the housing affordability index in Russia.An increase in the inflation rate is an indication that housing becomes less affordable.This finding aligns with the results of a study by Yu and Zhang (2019), which utilized the ARDL bounds testing approach and an error correction model in China.Their research found that inflation positively influences housing price growth both in the short run and the long run.Nevertheless, Lee and Park (2022) provide additional insight by emphasizing that a heightened inflation rate necessitates continued adjustments to the base rate over a specified period until inflation rates converge with the target levels.This phenomenon significantly influences the purchasing capacity of households, resulting in reduced housing demand, decreased housing prices, and enhanced housing affordability.This notion is reinforced by Demary (2009), who succinctly summarizes that when inflation surpasses its long-term average and the central bank reacts by increasing interest rates, a cascading effect ensues.This effect diminishes housing demand and affordability, ultimately resulting in a decrease in housing prices.
An exchange rate refers to the value of one currency when exchanged for another in international transactions (Jamil et al., 2023).Numerous research studies have highlighted the interrelationship between exchange rates and the housing market due to their close intertwining.In their work, Jack, et al. (2019) elucidated that the nexus between real estate prices and foreign exchange rates has consistently held significance.This importance stems primarily from apprehensions regarding the potential influence of foreign exchange rate fluctuations on the prices of commonly traded goods and services in countries that heavily rely on imports.A study conducted by Tatarstan et al. (2021) substantiated that housing affordability is directly affected by multiple factors, including the national currency exchange rate.The national currency exchange rate plays a crucial role in determining the costs of imported building materials and subsequently affects the final pricing within the new housing market.The depreciation of a domestic currency would lead to increased costs for imported building materials, consequently raising house prices and exacerbating housing affordability issues within a country (Kok et al., 2018).However, a study conducted by Zulkarnain and Nawi (2023), which employed a hedonic pricing econometric model, discovered an insignificant impact of the exchange rate on property prices.

Research Methodology
This section encompasses a comprehensive discussion of the data collection methods, procedures and techniques that were utilized to address the research objectives.The measurement of both dependent and independent variables is succinctly presented in Table 1.Housing affordability, serving as the dependent variable, is determined by dividing the overall house price by GDP per capita.As for the independent variables, the interest rate is approximated through the overnight policy rate, the money supply is represented by M3, the exchange rate is quantified by the Malaysian Ringgit against the US dollar and inflation is proxied by the consumer price index.The data for the overall house price was extracted from the Malaysian Housing Price Index Report published by the National Property Information Centre (NAPIC), GDP per capita was derived from the Department of Statistics Malaysia (DOSM), while the data for other monetary sector variables was obtained from Bank Negara Malaysia (BNM) monthly highlights and statistics.The time series data utilized consists of quarterly data, comprising 52 observations spanning from the first quarter of 2010 to the fourth quarter of 2022.All the data have been transformed using the natural logarithm to mitigate the potential heteroscedasticity problem.(2001).
The model specifications are encapsulated in Equation 1, where nHA signifies the l housing affordability and represents the log of money supply, lnR denotes the interstate, lnINF sands for a log of inflation, and lnEX signifies the log of foreign.  =  0  1    2    +  3   +    +   -----(Equation 1) The analysis of time series data necessitates adherence to specific procedures to ensure the validity and reliability of results.The initial step involves conducting stationarity tests using the Augmented Dickey-Fuller (ADF) and Phillips-Perron (PP) unit root tests.It is important to note that the ARDL technique can only be applied when all variables are stationary at levels, first differences, or a combination of both.It is not applicable if any of the variables are stationary at the second difference level (Pesaran et al., 2001).
Subsequently, the diagnostic tests are conducted to assess the goodness of fit of the econometrics model.The evaluations encompass several various tests including the Jarque-Bera test, which examines the normality of data distribution and Lagrange Multiplier Serial Correlation (LMSC) tests to detect and address the existence of autocorrelation problems within the dataset.Breusch-Pagan-Gdfrey (BPG) test I employed to identify and mitigate any potential issues of problems.Furthermore, the Ramsey Regression Equation Specification Error Test (Ramsey RESET) is utilized to examine and rectify any function from misspecification.
In addition, the Cumulative Sum (CUSUM) and Cumulative Sum of Square (CSUMSQ) tests are so conducted to examine the stability of the model parameters.Finally, Autoregressive Distributed Lag (ARD -run and long-run relationship between the dependent variable and all the independent variables.The estimation of the ARDL model, in the long run, using Equation 2 is presented below 2) The equation that represents the short-run relationship can be expressed as in Equation 3:

ADF and PP Unit Root Test Results:
Based on the results of the ADF and PP unit root test conducted at a 5 percent significance level as presented in Table 2, all variables were identified as non-stationary at the level.However, all variables were found to be stationary at the first difference level at a 5 percent significance level.Consequently, the cointegration test can be performed through the utilization of the ARDL estimation method.

Co-integration Test Result:
The results of the ARDL cointegration test, as displayed in Table 3, reveal an F-statistic value of 6.518.This value exceeds the critical bound of 4.01 at a 5 percent significance level, signifying the presence of a long-term relationship between the dependent variable, housing affordability, and all independent variables, including interest rate, money supply, employment rate, and inflation rate.With the establishment of cointegration among all tested variables, the subsequent step entails the estimation of the ARDL model in both the long run and short run.ARDL Short-run and Long-run Analysis Results: Table 4 presents the results of the short-run and long-run analyses examining the relationship between monetary sector variables and housing affordability in Malaysia.The findings reveal that money supply has a positive and significant influence on housing affordability in Malaysia, with a 5 percent significance level, both in the short run and the long run.More specifically, a 1 percent increase in money supply leads to a 3.212 percent increase in the housing affordability index in the long run and a 1.154 percent increase in the short run.This aligns with the results obtained by Feng (2022), who identified a stable and positive long-term correlation between real estate prices and the broad money supply.Furthermore, Yin et al. (2020) elucidated that the expansion of the money supply led to an excess of funds, thereby increasing the demand for residential properties, and ultimately driving an upsurge in prices, exacerbating housing affordability issues in Malaysia.In the long run, it is observed that the interest rate has a positive and statistically significant impact on the housing affordability index, as indicated by a probability value of 0.009, exceeding the commonly used significance level of 0.05.Specifically, the 1 percent increase in the interest rate will result in a 0.768 increase in the housing affordability index in the long run.This phenomenon can be attributed to the research conducted by Deb et al. (2022), which highlights that higher interest rates result in higher mortgage payments, thereby making housing less affordable for households.In the short run, the interest rate is identified as having a positive impact, but it is statistically insignificant in influencing housing affordability.This conclusion is drawn from the p-value, which stands at 0.512, a value higher than the significance level of 0.05.
Additionally, inflation is found to exert a substantial influence on housing affordability in Malaysia, as indicated by a statistically significant negative effect at a 5 percent significance level in both the short-run analysis (with a p-value of 0.001) and the long-run analysis (with a p-value of 0.035).In the long run, a 1 percent increase in inflation results in a significant 9.326 percent decrease in the Malaysian housing affordability index, while in the short run, a 1 percent inflation increase leads to a 3.588 percent reduction in the Malaysian housing affordability index.According to the study by Lee and Park (2022) and Markus (2009), a higher inflation rate requires the implementation of a restrictive monetary policy by the central bank, leading to a corresponding escalation of interest rates.The escalation of interest rates, particularly within the housing sector, leads to an increase in borrowing costs, thereby reducing the purchasing power of households.Consequently, people are discouraged from borrowing and spending, resulting in a decline in housing demand, a decrease in housing prices, and, ultimately an improvement in housing affordability.
In terms of foreign exchange rates, the findings suggest a positive relationship with housing affordability in the long run, but a negative relationship in the short run.However, the foreign exchange rate is found to be statistically insignificant in influencing housing affordability in Malaysia in both the short and long run.This is evidenced by the probability value of the foreign exchange rate in the long-run (0.155) and short-run (0.704) that exceeds the 5 percent significance level leading to the failure of rejection of the null hypothesis.
The estimated Error Correction Term (ECT) for the model utilized in this study exhibits a negative sign and is statistically significant at the 5 percent level.The ECT coefficient is -0.379, signifying that around 37.9 percent of the disequilibrium is corrected, resulting in closer to its long-run equilibrium within a one-year timeframe.This aligns with the criteria outlined by Dhungel (2014) for an ideal model, which states that the model should be statistically significant and have a negative ECT coefficient, with its value falling within the range of 0 to -1.

Diagnostic Test Results:
The diagnostic test results, as depicted in Table 5, confirm the reliability and validity of the model estimated in this research.This is substantiated by the fact that all the p-values for the tests exceed the predetermined 0.05 percent significance level.Specifically, the Jarque-Bera test, designed to assess normality, yields a p-value of 0.488, signifying that the data conforms to a normal distribution.Furthermore, the Breusch-Godfrey Test, employed to assess the presence of autocorrelation in the original equation, returns a p-value of 0.169, indicating the absence of autocorrelation.Next, the BPG test displays a pvalue of 0.356, leading to the rejection of the null hypothesis of homoscedasticity, which hypothesizes that the variance of the residuals in a regression model is constant across various levels of the independent variables.Following that, the Ramsey RESET test indicates that the functional form of the model is accurately specified, as evidenced by the p-value (0.212), which exceeds the predetermined significant level.

Conclusion
In summary, this study uses Autoregressive Distributed Lag (ARDL) estimation techniques on quarterly data, encompassing 52 observations from the first quarter of 2010 to the fourth quarter of 2022, to examine the long-and short-run impacts of monetary sector variables on housing affordability in Malaysia.
The findings reveal that, firstly, money supply has a positive and significant impact on housing affordability in both the short and long run in Malaysia.The increase in money supply leads to an excess of available funds for the public, thereby increasing the demand for residential properties and consequently driving up housing prices and the housing affordability index in Malaysia.A higher housing affordability index, as indicated by the overall house price relative to GDPP, signifies a worsening of housing affordability issues in Malaysia.Secondly, inflation was observed to have a short and long-run significant impact on housing affordability in Malaysia but in a negative direction.A higher inflation rate necessitates the implementation of a contractionary monetary policy by the Central Bank of Malaysia.This, in turn, leads to an increase in interest rates that discourage the public from borrowing and spending.Consequently, this results in decreased housing demand, and lower housing prices, and ultimately contributes to an improvement in housing affordability in Malaysia.Thirdly, the interest rate does not exert a short-run impact on housing affordability in Malaysia; its effect becomes evident only in the long run.The higher interest rates result in higher mortgage payments, thereby making housing less affordable for households.The long-term cointegration of money supply and inflation rates with housing affordability, along with their significant short-term relationship, highlights these two monetary variables as primary drivers of housing affordability.These results underscore the critical role of monetary sector variables in determining housing affordability in Malaysia.Consequently, policymakers are encouraged to prioritize the regulation of monetary sector variables, particularly focusing on money supply and inflation rates, to effectively promote housing affordability in Malaysia and therefore achieve the Sustainable Development Goals, or SDGs.
For future research, it is recommended that researchers explore how monetary sector variables influence housing affordability across a spectrum of socioeconomic groups, encompassing low-income households, middle-class families, and high-income individuals.By gaining insight into the diverse impacts of monetary variables on housing affordability within distinct socio-economic segments, policymakers can formulate more finely tailored strategies including targeted monetary policies, housing subsidies, and housing market regulations to ensure housing affordability for all.

Table 3 : Result of ARDL Bound Test for Cointegration
ARDL model selected based on Akaike info criterion (AIC) and *** denotes 1% of significant levels.