Determinants Performance from Malaysian Real Estate Investment Trusts (M-REITs)

Determinants Performance from Malaysian Real Estate Investment Trusts (M-REITs)

Wan Nur Syazwina Wan Haswani, *Amir Imran Zainoddin, Basri Badyalina, Fatin Farazh Ya’acob

Department of Business and Management, Faculty of Business and Management, Universiti Teknologi MARA, Johor Branch, Segamat

DOI: https://dx.doi.org/10.47772/IJRISS.2025.905000352

Received: 11 May 2025; Accepted: 14 May 2025; Published: 16 June 2025

ABSTRACT

Real Estate Investment Trusts (REITs) is a company that owns or pays for real estate. REITs allow anyone to invest in the development of large-scale properties in the same way that they would invest in other businesses. This study seeks to investigate the determinants of performance of REITs Malaysia firms, measured by return on asset (ROA). This report offers the results of a study of 10 Malaysian Companies conducted between 2011 until 2020. The study examines the relationship between ROA and combining the following independent variables, namely long-term debt (LTD), asset tangible (TANG), sales, earnings per share (EPS) and fixed asset (FA). Panel Linear Regression (PLS) were used in the analysis. The results indicated that LTD has a positive insignificant relationship and TANG has a negative significant relationship with ROA. Meanwhile, the other independent variables which are, sales, EPS and FA shows positive and significance relationship with ROA.

Keywords: Return on asset (ROA), long-term debt (LTD), asset tangible (LTD), Sales, earnings per share (EPS), fixed asset (FA)

INTRODUCTION

Prior to 1960, the greatest way to invest in real estate was to own the property physically (Lee Kwan Hyen, 2017). Besides, according to Alias & C.Y., (2011), financial professionals can also invest in publicly listed real estate equities or land-related bond securities for quick bonds developed to grow land businesses. With the introduction of Real Estate Investment Trusts, a broad range of interest in land areas has been generated in accordance with the monetary revolution. A real estate investment trust (REIT) is a company that owns or pays for real estate (Lee Kwan Hyen, 2017).

REITs allow anyone to invest in the development of large-scale properties in the same way that they would invest in other businesses, such as through the purchase of stock or the submission of offers (Harrison et al., 2011). Investors in real estate investment trusts (REITs) receive an offer of income generated by land speculation without actually purchasing or financing any properties, in contrast to investors who benefit from owning stocks in various partnerships (Salim & Yadav, 2012). Furthermore, in order to fully benefit from this tax-free status, the REITs must have the vast majority of their benefits and wages tied to the land, and they must allocate at least 90% of their aggregate wage to financial specialists and unit holders each year. Investing in real estate investment trusts (REITs) is comparable to investing in other types of stocks (Securities Commission, 2008).

Land reserves in Malaysia were previously known as Listed Property Trusts until 2005, when they were renamed Real Estate Investment Trusts to reflect their more recent evolution. Malaysia was the first Asian country to record property confidence in the board trade, which occurred in 1989 (Lee Kwan Hyen, 2017). Several Asian countries experienced a significant shift in the development of real estate investment trusts (REITs) during the “Asian Economic Crisis Event” of 1997 and 1998. As a result of these conventions, another global standard for the development of the Islamic REITs industry was maintained, and Malaysia was given a significant role in enabling the advancement and extension of Islamic business in the International Financial System (Feng et al., 2007).

Malaysian Real Estate Investment Trusts (M-REITs) are considered to be one of the most up-to-date venture vehicles available in Malaysia, when compared to other Asian markets such as Singapore, Hong Kong, and Taiwan, it is typically considered to have a small market (Lee Kwan Hyen, 2017). Regardless, despite the fact that there are several postings on the Bursa Malaysia base, promote evaluation, particularly from individual financial specialists, is still somewhat positive. Based on Alias & C.Y., (2011), despite the fact that Malaysia was the first Asian country to launch a Listed Property Trust, the market is moving slowly. It was also stated that local structural and regulatory considerations were the primary causes of Malaysia’s listed property trusts’ delayed and poor performance. After 2005, Malaysian Listed Property Trusts were renamed or renamed to a more globally accepted word, Real Estate Investment Trusts (REITs). The Securities and Exchange Commission has announced new rules to establish a legislative foundation for enhanced oversight of newly formed REITs.

Table 1: List of Real Estate Investment Trust’s Companies listed on Bursa Malaysia

As a result, this research has produced great improvements in our understanding of the factors that influence performance in Malaysian Real Estate Investment Trusts (M-REITs). It is the goal of this research to determine whether the dependent variable, return on asset (ROA), is influenced or not by the independent variables long-term debt (LTD), asset tangible (TANG), sales, earnings per share (EPS) and fixed asset (FA). The following section of the study contains a literature review as well as the construction of the conceptual framework. The approach used is then detailed, followed by a discussion of data analysis. The final segment contains the conclusion and recommendations.

LITERATURE REVIEW

Long-Term Debt

Most of the previous study have been reached after examining the critical relationship between long-term debt (LTD) and return on asset (ROA) utilizing a variety of tools and techniques. The long-term debt ratio is a measure of financial leverage that indicates how much long-term debt a business employs to finance its assets (Cheema et al., 2017). Njagi Kirmi, (2017) using panel data from 2012 to 2016, the main goal was to evaluate the relation between capital structure and profitability of listed energy and petroleum businesses in Kenya. They found that long-term debt (LTD) has a negative insignificant with return on asset (ROA). Rohaizan et al., (2021) also found the same results. They examined the determinants of capital structure from Shariah compliant in Travel, Leisure and Hospitality using panel data from 2011 to 2020.

Tangible Asset

Tangibility refers to the ratio of fixed assets to total assets on a company’s balance sheet (Jennifer & Sward, 2015). The study asserts that such a ratio is positively related to the amount of debt owing since physical assets may be utilised as collateral by loan holders (Leon, 2013). Meanwhile, Md-Yusuf, (2017) said that The term “asset tangibility” refers to assets that can be used as collateral for loans and is often referred to as a “stability indicator” for a business since these assets may be liquidated and converted to cash when the business needs cash. Due to the danger of liquidation in the case of a default, physical assets often assist in lowering the cost of financial hardship. Given these factors, lenders are more confident and reluctant to lend to a business with a high level of physical assets on its balance sheet than they are to a business with a low level of tangible assets (Jennifer & Sward, 2015). On the other side, they claim that physical assets and leverage are negative relationship, since businesses with a high concentration of liquid tangible assets are at risk (Daud et al., 2016). Most of previous study found that asset tangible has a negative significant on return on assets. Sorana Vatavu, (2014) study over a ten-year period from 2003 to 2012 to determine the factors of financial success in 126 Romanian firms. They found that tangible asset has a negative influence on return on assets. Gharaibeh & Bani Khaled, (2020) also found the same results. They look at the impact of financial characteristic and capital structure on the profitability of all 46 services business listed on the Amman Stock Exchange from 2014 to 2018.

Sales

Sales valuation is a method of determining a company’s worth by comparing its stock price to its revenues. In other words, it is a measure of how much the financial markets assign a monetary value on each dollar of a company’s sales or revenues (Studenmund, 2020). Most of the previous study found that sales has solid and significant in conjunction with return on assets. Dada & Ghazali, (2016) investigates the capital structure and company performance information derived from Nigerian economy. They used a sample size of 100 non-financial corporations companies between 2010 and 2013. It appears from the findings that the sales variables has a favourable and positive impact on return on assets.

Earnings per Share

In the financial world, earnings per share (EPS) refers to the part of a company’s earnings that is given to each share of common stock after deducting taxes and preferred stock distributions (if any) (Islam et al., 2014). Calculating the figure is as simple as dividing net income earned in a given reporting period (which is often quarterly or annual) by the total number of shares outstanding during the same time period. The use of a weighted average is common since the number of shares in circulation can fluctuate (Islam et al., 2014). Several observations have been made using various approaches to analyse the significant relation between earnings per share and return on assets. The study from Citra Larasati et al., (2020) determine the effect of debt to equity and return on assets on earnings per share in various industrial sub-sector manufacturing companies between 2016 and 2018. Meanwhile, study conducted by Musallam, (2018) between 2009 and 2015 looked into the relationship between financial ratios and market stock performance. Both findings demonstrate that earnings per share has a statistically significant and positive association with return on asset.

Fixed Asset

In the context of business, a fixed asset is an asset that is held with the goal of being used for the purpose of producing or providing goods or services, rather than being held for sale in the normal course of operations (Lily Jade, 2019). Researchers have investigated whether fixed asset have a positive or negative relationship with return on assets. Puspita et al., (2020) investigates the relationship between fixed asset and working capital in terms of profit margins from 2014 to 2018. Next, goal of the study from Purba & Bimantara, (2020) is to investigate the impact of asset management on financial success from the years 2013 to 2017. Both of study demonstrate that the fixed assets have a positive and statistically significant effect on the return on assets. 

Conceptual Framework

The theoretical framework aims to provide a better understanding of the outputs of the selected dependent variable, return on asset (ROA), and how they are affected or not by the independent variables, long-term debt (LTD), asset tangible (TANG), sales, earnings per share (EPS) and fixed asset (FA) in Malaysian Real Estate Investment Trusts’ performance (M-REITs).

Figure 1: Theoretical framework

METHODOLOGY

The investigation is carried out using secondary data gathered from an internet database. The study looked at the performance evidence from Malaysian Real Estate Investment Trusts (M-REITs). This resulted in the selection of ten companies, which were then listed on the Bursa Malaysia. To establish the relationship between independent and dependent variables, a variety of methodologies are used, including estimating independent variables such Long-term debt (LTD), asset tangible (TANG), Sales, earnings per share (EPS) and fixed asset (FA). Additionally, the dependent variable; return on asset (ROA). Secondary data was gathered from the company’s annual reports between 2011 and 2020.

Test Consideration for Data Analysis

Correlation Analysis

A simple correlation coefficient between the explanatory variables can be used to detect severe multicollinearity, and this is one approach for doing so. When two variables are correlated, the correlation coefficient (r) is a mathematical expression that expresses the degree and direction of a linear relationship between them. Correlation between two variables is shown by the sign of r, which can be anywhere between one and one hundred percent (+1 to -1). The less digits there are, the better. The greater the distance between the absolute value of r and one, the greater the correlation between two variables (Studenmund, 2020).

If two variables are perfectly positively correlated, then r = +1

If two variables are perfectly negatively correlated, then r = -1

If two variables are totally uncorrelated, then r = 0

Serial Multicollinearity

In order to determine if the independent and dependent variables are positively connected, the approach must be utilized. The correlation coefficient (r) was employed in this study to establish whether or not there is a low degree of correlation or a high degree of multicollinearity. If the r value is less than 0.8, there is little correlation; however, if the r value is greater than 0.8, there is strong multicollinearity between the variables (Studenmund, 2020).

H₀: There is no Multicollinearity problem

H₁: There is Multicollinearity problem

Normality

It is necessary to conduct a normalcy test in order to determine the consistency of a sample     data set. If the researcher wants to draw inferences about the population based on a sample of data, he or she must verify the sample using the Jacque-Bera test, which measures the amount of kurtosis and skewness in the data set. Results will be given in the form of a histogram, and the data will be analysed at a statistically significant level (5 percent) in order to estimate its probability. In this case, the output will be normal and error-free if the skewness is equal to zero and the kurtosis is equal to three (Studenmund, 2020).

H₀: Error term is normally distributed

H₁: Error term is not normally distributed

Regression Analysis

When it comes to market research, regression analysis is one of the most often used methods available. In its most basic form, regression analysis allows market researchers to investigate the relationships between a single dependent variable and a number of independent variables. Only a few other tools, such as regression analysis, have the ability to provide additional insight into the situation. The following are some of the most significant benefits of using regression analysis:

1. Determine whether the independent variables are meaningfully related to the dependent variable.
2. Calculate the current magnitude of the effect of numerous independent variables on a dependent variable.
3. Make projections.

It is necessary to follow this approach while dealing with Panel Data. Cross-sectional and time series dimensions are present in a panel data collection, with all cross-sectional units recorded over the time period in question. When compared to repeated random selection of persons, panel data models are more “efficient” than pooling cross-sections in general because repeated observation of a single individual over time minimizes variation. The following variables are incorporated into regression models:

The unknown parameters, represented as β, which could be a scalar.

The independent variables, X.

The dependent variable, Y.

Regression model of the determinants of performance from Malaysian Real Estate Investment Trusts (M-REITs) compliant:

Y= β₁ LTD + β₂ TANG + β₃ Sales + β₄ EPS + β₅ FA + Ei

Y = Return on asset (ROA)

LTD = Long-term debt

TANG = Asset tangible

EPS = Earnings per share

FA = Fixed asset

DATA ANALYSIS AND FINDINGS

Correlation Coefficient

Table 2: Result of Correlation Coefficient using EViews software.

Based on analysis data as given in Table 2, it reveals that the value of the long-term debt (LTD) is shown moderately negative correlation with return on asset (ROA) with value of -0.042584, because the value is near to -1. The p-value of long-term debt (LTD) is 0.6740, which is higher than 5% level of significance. Meanwhile, tangible asset (TANG) shown relatively moderate negative correlation with ROA with value of -0.274331. TANG indicates negative and significant relationship between return on asset (ROA) as the p-value is less than 5% level of significance, as for tangible asset (TANG) probability value is 0.0057, which indicates that return on asset (ROA) has a positive impact on asset tangible (TANG).

Furthermore, Sales is shown relatively positive correlation value with return on asset (ROA) which is 0.200713, because the value is near to 1. Sales and earnings per share (EPS) p-value is less than 5% level of significance, which is 0.0453 and 0.0020. Meanwhile, fixed asset (FA) indicates the insignificance relationship with return on asset (ROA) because the p-value is bigger than 5% of level significance which is 0.3608. In conclusion, the independent variable that are significance relationship with the return on asset (ROA) are tangible asset (TANG), Sales and earnings per share (EPS), meanwhile, long-term debt (LTD) and fixed asset (FA) have an insignificance relationship with return on asset (ROA).

Multicollinearity Test

Based on table 2, a value of correlation is used to identify whether the independent variables have the multicollinearity problems. For return on asset (ROA), the findings reveals that all the independent variable correlation value are lower than 0.8. Long-term debt (LTD) and tangible asset (TANG) with a value of 0.269825. Long-term debt (LTD) and Sales with a value of -0.226053, long-term debt (LTD) and earnings per share (EPS) with a value of -0.021317, long-term debt (LTD) and fixed asset (FA) with a value of 0.233158. Tangible asset (TANG) and Sales with a value of -0.098176, tangible asset (TANG) and earnings per share (EPS) with a value of -0.032128, tangible asset (TANG) and fixed asset (FA) with a value of 0.168349. Sales and earnings per share (EPS) at 0.039976, sales and fixed asset (FA) at -0.107765 and last two variables are earnings per share (EPS) and fixed asset (FA) with a value of -0.125047.

Therefore, all the independent variables, long-term debt (LTD), tangible asset (TANG), Sales, earnings per share (EPS) and fixed asset (FA) has a low value of multicollinearity and there is no problem with these independents variables. Thus, null hypothesis is not rejected.

Normality Test

Table 3: Results of Normality test using EViews software.

The Jarque-Bera value is 25.01923 in table 3, and the probability value is 0.000004. Due to the probability is lower than 5%, the null hypothesis may be rejected. As a result, there is not normal distribution in the data. The skewness value is used to evaluate if the probability distribution is positive or negative in value, and whether the right or left tail of the data probability distribution is bigger. This study’s skewness value is 1.224827, indicating that the probability distribution is positive and that the right tail of the distribution is present. The value of kurtosis, on the other hand, is used to evaluate if the distribution series is more peaked or flat. If the kurtosis value is 3, the distribution channel is normal. The kurtosis is 2.938292, platykurtic since the number of kurtosis are less than 3. To summarize, the data in this study were not normally distributed since the probability was positive and lower than 5% the null hypothesis.

Regression Analysis

Table 4: Summary of regression analysis

Y= 2.292931 + 0.044259LTD – 1.547604TANG + 2.663987SALES + 2.019001EPS + 0.452144FA

Y = Return on asset (ROA)

LTD = Long-term debt

TANG = Tangible Asset

EPS = Earnings per share

FA= Fixed Asset

The overall significance f-test of this model for the independent variables of long-term debt (LTD), tangible assets (TANG), sales, earnings per share (EPS), and fixed assets (FA) is significant, based on the data provided above. Since (F-test P-value 0.05), there has been a relationship between return on assets (ROA) of Malaysian REIT businesses. This indicates that LTD, TANG, Sales, EPS, and FA all have an impact on the company’s ROA. This indicates that the chosen model is of high quality.

R² is the sum of squares explained to the sum of squares ratios. R² represents how well the generated regression equation matches the sample data. The R² value of 0.229163 indicates that the variability of the independent variables, long-term debt (LTD), tangible assets (TANG), sales, earnings per share (EPS), and fixed assets (FA), explains 22.91 percent of the variation in the dependent variable, return on assets (ROA), while the remaining 77.09 percent is explained by other factors not included in the study. Furthermore, we can reject the null hypothesis because the p-value for the f-statistic, which is used to assess the overall significance of the regression model, is 0.000149. In contrast, the corrected R² is 0.188161, which is smaller than R². This shows that the regression model is adequate and that it can be used to assess a company’s return on assets (ROA).

The p-value for long-term debt (LTD) is 0.6816, according to the Panel Least Square Regression findings, with a 95% confidence interval. Because of the p-value is more than 0.05, it shows that long-term debt is insignificant and it has a positive relationship with return on asset (ROA). The result support Cheema et al., (2017) study that there is no significant and have positive relationship between long-term debt (LTD) and return on asset (ROA) to measure company’s performance.

Next, asset tangible (TANG) shows a negative significance relationship with return on asset (ROA). The p-value for TANG is 0.0030, which is shows a significance because the value is less than 5% level of significance. Tangible asset (TANG) has a beta coefficient of negative -1.547604, which implies increase of 1 unit in TANG will reduce by 1.547604 points in return on asset (ROA). The results indicates that Tangible asset (TANG) have a negative significance relationship with return on asset (ROA), as a result, businesses that want to enhance their return on assets might expand their tangible assets (Jaishi, 2020). The findings support Gharaibeh & Bani Khaled, (2020) findings that there is significant and positive relationship between tangible asset and Return on Asset (ROA) as a performance indicator.

Furthermore, Sales has a positive significance relationship with return on asset (ROA). Sales has a beta coefficient of positive 2.663987, which means that increase 1 unit of Sales will affect ROA to decrease by 2.663987 point. The p-value for Sales is 0.0448, which is shows a significance relationship with return on asset (ROA). The findings support by Dada & Ghazali, (2016), that there is positive significance relationship between sales and return on asset (ROA).

Earnings per share (EPS) indicates a positive significance relationship with return on asset (ROA) since the level of p-value is less than 0.05 and with a beta coefficient of positive 2.019001 point from return on asset (ROA), which means that an increase in 1 unit of EPS will affect ROA to increase by 2.019001 point. Studies by Musallam, (2018); Şamiloglu et al., (2017) demonstrated a statistically significant and positive link between return on assets (ROA) and earnings per share (EPS).

Lastly, fixed asset (FA) has a statistically positive and significant relationship with return on asset (ROA). It demonstrates that a 1 unit increase in FA will results in a 0.452144 point rise in ROA. This was also validated by a study Purba & Bimantara, (2020), discovered that the independent variable, fixed asset (FA) has a positive and statistically significant effect on return on asset (ROA).

CONCLUSION

Annual data were used to evaluate the relationship between long-term debt (LTD), tangible asset (TANG), Sales, earnings per share (EPS) and fixed asset (FA) with return on asset (ROA) to determinants the performance from Real Estate Investment Trusts (REITs) Malaysia that cover the period 2011 to 2020 for ten companies listed in Bursa Malaysia. The Panel Least Square (PLS) method was employed in this study to examine the relationship between the independent variables and return on asset (ROA). The findings of the study showed that long-term debt (LTD) has a positive insignificant and asset tangible (TANG) shows a negative insignificant. Meanwhile, the remaining independent variables, which are sales, earnings per share (EPS) and fixed asset (FA) shows a positive significance with return on asset (ROA).

In addition, the results of this research shows that sales, earnings per share (EPS) and fixed assets (FA) all played a part of significant role in the return on asset (ROA) performance of real estate investment trusts (REITs) company in Malaysia. As a result, our findings are supported by the literature Dada & Ghazali, (2016); Musallam, (2018); Şamiloglu et al., (2017) shows a positive and significant relationship with return on asset (ROA). Furthermore, the positive correlation between sales and return on asset indicates that an increase in sales, while lowering the expenses, may increase the percentage of return on assets (Dada & Ghazali, 2016). According to Musallam, (2018), the positive correlation between earnings per share and return on asset indicates that a higher earnings per share indicates that the company more profitable and has more profits to distribute to shareholders.

Long-term debt (LTD), on the other hand, shows a positive insignificant relationship with return on asset (ROA). This influences in the past literature Cheema et al., (2017) have shown insignificant positive relationship between long-term debt (LTD) and return on asset (ROA). The long-term debt insignificant relationship with return on assets causes further distortions (Efendi et al., 2019). Thus, Njagi Kirmi, (2017) indicates that increasing the company’s financing expenses, hence reducing profits. In other words, the lower the debt ratio, the safer the company.

Tangible asset shows a negative significant relationship with dependent variables, return on asset (ROA). This study support by Gharaibeh & Bani Khaled, (2020) that shows negative significant relationship with return on asset (ROA). It says that tangible assets have a significant impact on business performance, return on asset, and that organizations seeking to improve their return on assets should consider expanding their tangible asset. According to Jaishi, (2020), tangible assets are valuable to businesses since they account for a large portion of the company’s value. When a business can demonstrate this value through proper documentation, the assets can be used as collateral for loans, making it easier for businesses to obtain the funding they require to continue operating.

RECOMMENDATION FOR FUTURE RESEARCH

Further study enables the discovery of ways to overcome the research’s limits, as well as parts that require further exploration. The relationship between long-term debt (LTD) and the dependent variable, return on assets (ROA), in M-REITs is statistically insignificant. According to Nathan & Hadidi, (2017), the amount of debt has a minimal impact on the company’s performance. As a result, it is advised that additional research be conducted on this topic by incorporating additional variables.  New researchers must approach the stock market with research in consideration, rather than accounting based only on company performance (Cheema et al., 2017). For instance, consider firm growth, asset growth, and corporate size to complement the efficiency of the findings. Furthermore, they must concentrate on the M-REITs’ performance analysis for both the local and international overviews in order to advise consumers on whether to invest locally or abroad. Researchers can conduct an exegetical study to better understand the performance of M-REITs. Future studies should give substantial developments and advanced property sector in Malaysia with the growth of M-REITs.

Moreover, the researchers can compared the Islamic REIT with the standard Malaysian REIT. As a result, we are able to produce relevant findings that provide investors with an understanding of each risk-return trade-off, as well as conduct studies on M-REITs as potential alternative investments. Additionally, future research can attempt to determine the success of various sectors of the M-REITs’ property types, such as healthcare, retail, diversified, or office. Consequently, it is recommended that more data be collected to ensure that the data becomes more volatile and that the independent factors are able to explain the dependent variables better.

In addition, future research should adopt more sophisticated econometric techniques, such as Fixed or Random Effects Models, or the System Generalized Method of Moments (System GMM), to better account for dynamic relationships and address potential endogeneity issues. These advanced methods allow for more robust estimations by controlling for unobserved heterogeneity, reverse causality, and simultaneity bias—common issues in panel data involving firm performance.

Moreover, incorporating qualitative dimensions such as corporate governance structures, board effectiveness, or risk management strategies could significantly enrich the understanding of what drives profitability in real estate investment trusts, particularly in emerging markets like Malaysia. Such factors can provide valuable insights into managerial practices, compliance with regulatory standards, and the strategic allocation of assets, all of which may affect the long-term sustainability and performance of REITs.

Further study enables the discovery of ways to overcome the research’s limitations, as well as areas that require deeper investigation. The relationship between long-term debt (LTD) and the dependent variable, return on assets (ROA), in M-REITs was found to be statistically insignificant. According to Nathan & Hadidi (2017), the amount of debt has a minimal impact on firm performance. Therefore, it is advised that additional research be conducted by incorporating complementary variables such as firm growth, asset growth, and corporate size, which may enhance explanatory power.

Finally, expanding the data set to include a longer time horizon and broader sample of REITs, both locally and internationally, would improve the generalizability and robustness of findings. This broader perspective is crucial for informing both local and global investment decisions in Malaysia’s evolving real estate investment landscape.

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