CAPITAL STRUCTURE OF PROPERTY COMPANIES IN MALAYSIA BASED ON THREE CAPITAL STRUCTURE THEORIES

ISSN 2289-1560 2012 CAPITAL STRUCTURE OF PROPERTY COMPANIES IN MALAYSIA BASED ON THREE CAPITAL STRUCTURE THEORIES 1 Salwani Affandi, 1 Wan Mansor Wan Mahmood, 1 Nabilah Abdul Shukur 1 Universiti Teknologi MARA Terengganu Department of Finance, Faculty of Business and Management Universiti Teknologi MARA Terengganu ABSTRACT This study examines the capital structure determinants of 54 property companies listed in the Bursa Malaysia s property sector. Employing Fixed Effect Estimation model, the empirical results reveal that the debt-equity structure of the companies is influenced by the various firm-specific attributes and macro-economic factor. In particular, the evidence shows that property asset intensity and firm size of these property companies are significant determinants of corporate debt policy. On the other hand, profitability do not appear to suggest any significant contribution on the capital structure decision of property companies. Keywords: Capital structure, Property companies, Malaysia, Fixed Effect Estimation Model. INTRODUCTION Capital structure is the most debatable topic and continues to keep researchers pondering. Great efforts have been made to understand the determinants of capital structure after the seminal works of Modigliani and Miller (1958; 1963) MM. One of the areas that received interest among researcher is the study of capital structure of firm of various sectors of the economy such as manufacturing firm, oil and gas sector, electric-utility companies, non-profit hospitals and agricultural firms. Theoretical advancement, particularly development of capital structure models based on asymmetric information, and more recently, on product-market and corporate control considerations, have managed to shed some light on the financing behavior of corporations. For the last one decade, we see many studies that have tested the validity of the modern theory of finance such as capital structure of firms. Theoretically, a firm s capital structure deals with a mixture of different securities. Various strategies can be employed to raise its required funds, but the most basic and important financial sources are retentions, shares and debt. A firm will decide what is an appropriate level of borrowing for a given its equity capital base. To assist this decision it would be useful to know if it is possible to increase shareholder wealth by changing the gearing (debt to equity ratio) level. The present study is an attempt to examine the capital structure of properties companies in emerging economies. Specifically, the paper will explore the determinant of capital structure of properties companies in Malaysia which is still relatively new and underexplored. Currently, the understanding on how the companies choose their capital structure and what are the factors that influence their corporate financing behavior is still unclear. Moreover, the property sector is quite volatile in respond to economic condition irrespective whether in the crisis situation or otherwise. Over the year, property sector is aggressively developing in Malaysia but are still lagging behind to those of developed economies such as UK, Hong Kong or even Singapore. However, the sector is progressing fast as can be seen in the numbers of property companies been listed in the Bursa Malaysia Main Board keep increasing each year. The residential property market in Malaysia is only opened up to overseas investment at the end of 2006, yet it is already attracting high levels of interest from shrewd speculators. Malaysia is growing in significance as a centre for world trade, with low business costs encouraging multinational companies to invest. This puts the executive property market in a very strong position, with rental yields in Kuala Lumpur standing at around 7.4 to 8.7%, and new off-plan properties promising guaranteed yields of up to 10%. The organization of the paper is as follows: Section 2 reviews the related literature. Section 3 outlines the data and methodology employed. Section 4 discusses the empirical results, and section 5 concludes. LITERATURE REVIEW Numerous studies have investigated the capital structure of firms from various sectors of the economy, such as oil and gas sector (Sabir and Malik, 2012), manufacturing firm (Afza and Hussain, 2011; Long and Malitz, 1985; Titman and Wessel, 1988), construction companies (Baharuddin et al., 2011), nonprofit hospitals (Wedig,1988) and agricultural firms (Jensen and Langemeier, 1966). From the empirical studies, they conclude that industrial classification is an important determinant of capital structure. 131

ISSN 2289-1560 2012 However, the capital structure of property companies is relatively under-explored area. Ooi, (1999) and Gau and Wang (1990) are amongst the first to use the theory of capital structure directly to real estate investment decision. Gau and Wang, for example, observe that the level of debt employed in a property acquisition is directly related to the cost of investment and inversely related to the size of depreciation, tax shield, expected cost of financial distress and market interest rate. The applicability of their results to the financial context of property companies at the corporate level has not been tested. Tax trade-off theory The tax trade-off theory suggests positive relationship between tangibility and leverage. According to Ooi (1997), the positive relationship of tangibility and leverage are supported by Ferri and Jones (1979), Marsh (1982), Bradley (1984), Long and Malitz (1985) and Allen (1995). However, Buferna et al. (2005) reported that there were also researcher who did not support the trade-off theory for the tangibility and leverage. They are Booth et al. (2001), who done the study in ten developing countries and Huang and Song (2002) who done study in China reported the inverse relationship between tangibility and leverage. They were argued that inverse relationship comes from the different type of debt used by the China s companies. According to Warner (1977) and Ang and Mc Connell (1982), the traditional researcher viewed the large firm are less susceptible to bankruptcy because they do well diversified than other smaller firms. This kind of view is consistent with trade-off models of capital structure when the large firm tend to having large amount of debt in their capital structure decision as compared to the smaller firms. Bevan and Danbolt (2002), also argue the same thing because they regarded to too big to fail. According to Ooi (1997), the other researcher who argued with this theory were Maris and Elayan (1990), Bennett and Donnelly (1993) and Homaifar (1994). However Marsh (1982) and Titman and Wessels (1985) report a positive relationship between leverage and the size of firm. Pecking Order theory Myers (1984) prescribes a positive relationship between profitability and debt on the basis that successful companies do not need to depend so much on external funding. Bevan and Danbolt (2002) also agree with Myers (1984) by stating the more profitable company should have small amount of debt since the high profitability provide high level of internal funds. However, there was also the study which did not consistent with Myers or in other words we can say they support the trade-off theory with the positive relationship between profitability and debt. Ajunct et al. (2008) who investigate the capital structure of 308 UK real estate companies found positive relationship between profitability and leverage. Meanwhile, Buferna et al. (2005) reported in his determinants of capital structure study that Titman and Wessel (1988), Rajan and Zingales (1995), Bevan and Danbolt (2002) and many more were supporting the pecking order theory even though the results of his study himself supported trade-off theory when the profitability positively related to the leverage. DATA AND METHODOLOGY Data The data set comprises essentially the financial statement of 54 out of 93 property companies listed under Bursa Malaysia Main Board and are selected based on their availability in the Thomson One Banker. The data begin in year 2001 through 2008. Altogether, there are 432 firm-year observations. Descriptive Statistics Table 1 shows the summary statistics of the sample. Table I: Summary statistics based on 432 firm-year observations Variables N Mean Std. Dev Min Max Dependent: TDR 432.831465.01272199.0464432 1.238781 Independent: PROF SIZE TANG 334 432 432.4882173 6.441211.8412736.16087.7960704.1516164 -.665363 3.357489 -.8123683.8723026 8.398314 1 Notes: the summary statistics are based on the 54 firm-year observations. The dependent variable is total debt ratio (TDR). The regressors are defined as follows: property asset intensity (TANG), firm size (SIZE) and profitability (PROF). (Ln) Log transformation has been specified for these variables. Variable Used Property asset intensity (TANG) measures the tangibility of assets owned by the respective company. We hypothesize that leverage is positively associated with the firm s property asset intensity. As Booth et al. (2001) state: The more tangible the firm s assets, the greater its ability to issue secured debt. A firm with large amount of fixed asset can borrow at relatively lower rate of interest by providing the security of these assets to creditors. This is consistent with Myers (1977) arguments that tangible assets, such as fixed assets, can support a higher debt level as compared to intangible assets, such as growth opportunities. 132

ISSN 2289-1560 2012 Traditionally, researchers have taken the view that large firms are less susceptible to bankruptcy because they tend to be more diversified than smaller companies (Warner, 1977; Ang and Mc Connell, 1982). Following the trade-off models of capital structure, large firms should accordingly employ more debt than smaller firms. According to Ooi, (1999), empirical support of the predicted positive relationship is provided by Maris and Elayan, (1990), Bennett and Donnelly, (1993) and Homaifar, (1994). However, Marsh, (1982) and Titman and Wessels, (1988) report a contrary negative relationship between debt ratios and firm size. Marsh, (1982) argues that small companies, due to their limited access to the equity capital market, tend to rely heavily on bank loans for their funding requirements. Consequently, they become more heavily indebted than larger companies. Titman and Wessels, (1988) further posit that small firms rely less on equity issues because they face a higher per unit issue cost. The relationship between firm size and debt ratio is, therefore, a matter for empirical investigation and ultimately, the direction and strength of the relationship depend on which of the two opposing arguments have a stronger influence in our study sample. There are conflicting theoretical predictions on the effects of profitability on leverage. Following the pecking-order theory, profitable firms, which have access to retained profits, can use these for firm financing rather than accessing outside sources. Jensen (1986) predicts a positive relationship between profitability and financial leverage if the market for corporate control is effective because debt reduces the free cash flow generated by profitability. From the Trade-off theory point of view more profitable firms are exposed to lower risks of bankruptcy and have greater incentive to employ debt to exploit interest tax shields. Most empirical studies observe a negative relationship between leverage and profitability Affandi et al (2009), Huang and Song (2002), Booth et al. (2001), Titman and Wessels (1988), Friend and Lang (1988), Kester (1986), and Rajan and Zingales (1995) for G7 countries except for Germany). A negative relationship between profitability and leverage is expected in this study. Panel Estimations Model There are 3 competing panel estimation models which include pooled ordinary least square (OLS), fixed effects model and the random effects model. Each of the models is subject to limitations and therefore, using one method alone will not be effective. Thus, the dataset of the study is tested by using all three models. One other reason for using the three models comes from the work of Bevan and Danbolt (2004). In their paper, they noted that the OLS estimation model has widely appeared in the literature but due to the limitations of the model that is the failure to control for time invariant firm specific heterogeneity, the results are likely to be biased. However, statistically an important choice will be made between fixed effects model and the random effects model. According to the statistical rule, if the individual effects and the regressors are uncorrelated, then random effects model is used although the fixed effects still remains useful. On the other hand, if the regressors and individual effects are correlated then only fixed effects model should be used. In order to choose the correct model Hausman specification test is conducted. The general form of the model can be specified as follows; where: 133

ISSN 2289-1560 2012 In modeling capital structure decision, the firms total debt ratio is used as the dependent variable. It is the total debt divided by total assets. The independent variables employed are property asset intensity (TANG), company size (SIZE) and profitability (PROF). It has been included in the model based on priori theoretical ground to test whether industry-specific factors have any significant influence on the capital structure of property firms. The TANG is derived from total property divided by total assets. The size of the firm is the natural logarithm of total property assets held by the company. Profitability is measured by the firm s earnings before interest and taxes (EBIT). The study uses the natural logarithmic transformation to reduce the skewness of the distribution and to minimize the standard error of the regression coefficient. EMPIRICAL RESULTS Fixed Effect Estimation Model The Hausman specification test suggests that the fixed effects model is better than random effects model as the p-value is less than 0.05 for the dependent variable which imply that the random effects model should be rejected and thus the analysis is based on the fixed effects estimates. Bevan and Danbolt (2004) also compares fixed effects model with the random effects model and based their results on fixed effects model on the basis of Hausman specification test. The results of the study reported in Table IV confirm that asset structure is an important determinant of the capital structure of property companies. The property asset intensity (TANG), for example, shows significant positive relationship with debt ratio. The empirical evidence suggests that firms with higher property asset intensity employ more debt in their structure as Booth et al. (2001) state: The more tangible the firm s assets, the greater its ability to issue secured debt. A firm with large amount of fixed asset can borrow at relatively lower rate of interest by providing the security of these assets to creditors. We also find that total property assets seem to be an important determinant of the capital structure of property companies. The results report significant positive relationship with leverage. The positive coefficient is consistent with those of Maris and Elayan, (1990), Bennett and Donnelly, (1993), and Homaifar, (1994). It is also consistent with the trade-off model of capital structure where large firms seem to employ more debt than smaller one. Similar view is also obtained by traditional researchers who argue that large firms are less susceptible to bankruptcy because they tend to be more diversified than smaller companies (Warner, 1977; Ang and McConnell, 1982). The results under fixed effects model shows negative association between profitability and the dependent variable. This variable however appeared to be insignificant factor of financial behavior. The evidence is contrary to the tax trade-off models predict that profitable companies will employ more debt since they are more likely to have a high tax burden and low bankruptcy risk. However, on the other hand this result is consistent with the pecking order theory proposed by Myers, (1984) prescribes a negative relationship between debt and profitability on the basis that successful companies do not need to depend so much on external funding. Instead, they can rely on their internal reserves accumulated from past profits. Overall, our study suggests that property asset intensity (TANG) and firm size (SIZE) have more impacts on dependent variable of debt ratio (DR) than other independent variables. As for R-squared, the result show about 46% percent of the capital structure variations is explained. Results of regression on total debt ratio are presented in Table IV. Table IV: Determinants of corporate leverage Explanatory Variables Expected Sign Total Debt Ratio (TDR) TANG +.3352195 (9.41)*** SIZE + / -.0988656 (9.47)*** PROF + / - -.0107589 (-0.36) R2 F- Ratio 0.4618 14.62 Notes: Estimation results of regression on 432 firm-year observations. The dependent variable is total debt ratio (TDR). Theindependent variables include: property asset intensity (TANG), firm size (SIZE) and profitability (PROF). The absolute value of the t-statistics are give in parenthesis below the coefficient estimates.*, ** and *** indicate significance at 0.10, 0.05 and 0.01 level respectively. SUMMARY AND CONCLUSION The major contributions of this paper have been the identification of several key factors influencing the corporate debt decisions of property companies. The research results have important implications as property companies usually rely heavily on external funding to support their investment activities. Specifically the study shows that the asset intensity of property companies has a significant impact on their debt raising capacity. The empirical evidence also highlights the significance of firm size in the debt determination. However, the study shows the profitability do not contribute to any significant role in determining the debt-equity choice of property companies. 134

ISSN 2289-1560 2012 The empirical model of this study can also be expanded which can provide further empirical results. The expansion can be done by increasing the panel data set or by increasing the number of alternative indicators for the independent variables. Increasing the data set and then running the three estimation models will further enhance the credibility of the research. Moreover, as there can be two or three indicators for the same independent variables they can also be used to provide further evidences and especially for the variable of profitability which is insignificant in this study and can be explored further by using alternate proxies. Finally, given the limitations of data, industry classifications have been entirely excluded from the study but it has the potential to provide important results and can increase the r-square of the model. REFERENCES Afza, T., Hussain, A. (2011). Determinants of Capital Structure across Selected Manufacturing Sectors of Pakistan. 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