Journal of Accounting, Finance and Economics

Vol. 3. No. 2. December 2013. Pp. 72 – 85

Theoretical Investigation on Determinants of Government-Linked Companies Capital Structure

Noryati Ahmad1 and Fahmi Abdul Rahim2

This study investigates the capital structure determinants of Malaysian Government Linked Companies (GLCs) and attempts to link the relevant capital structure theory related to GLCs. A total of 38 government linked companies listed in Bursa Main Market are analyzed covering the period from 2001 until 2010. Using pooled ordinary least square method, the results show that size has significantly positive relationship to all the dependent variables (debt ratio, long term debt ratio and short-term debt ratio). Growth is positively related to debt ratio, while liquidity is negatively related to both debt ratio and short term debt ratio. Interest coverage ratio and tangibility ratio have significantly positive relationship with long-term debt ratio, while profitability is inversely related to long-term debt ratio. A negative relationship between tangibility and short term debt ratio is found in the study. Non-debt tax shield appears not to have significant relationship with the leverage of GLCs. Generally GLCs’ capital structures are supported by both trade off theory and pecking order theory while there is little evidence to support agency cost theory. In addition GLCs with debt ratio of more than 40% is significant in explaining debt policy decision of GLCs.

JEL Codes: G30, G32 and G38

1. Introduction Incorporation of Malaysian Government Linked Companies (GLCs) started in the year 2004. The performance of Malaysian GLCs have attracted attention of various interested parties because they are directly or indirectly owned by government (through the Ministry of Finance Incorporated) or through the Government Linked Investment Company (GLIC) (Mohd-Saleh, Kundari & Alwi 2011). GLCs companies have played a vital role in Malaysia’s economy growth as they accounted for one-third of the FTSE KLCI Composite Index. Lau and Tong (2008) report that as owner of GLCs, the government has the capacity to make major decision on matters like appointment of the board of directors and top management, corporate strategy, financing, acquisition and investment. In his study, Wiwattanakantang (1999) finds that GLCs are highly leveraged because they can easily get access to secured loans. Capital structure decision of GLCs is crucial to the financial well-being of the company. Similar to other domestic companies, GLCs need to seek an ideal capital structure that could reduce the cost of capital and reach the optimal level of debt. Eriotis, Vasiliou and Ventoura-Neokosmidi (2007) state that an inappropriate debt policy decision can trigger financial distress and lead to bankruptcy. What are the determinants of such an optimal capital structure? These are the common questions asked when making financial decision relating to capital structure.

1 Associate Professor Dr Noryati Ahmad, Arshad Ayub Graduate Business School, Universiti Teknologi

MARA, Malaysia, Email: noryatia@salam.uitm.edu.my 2 Dr Fahmi Abdul Rahim, Faculty of Business Management, Universiti Teknologi, Melaka Branch

Campus, Malaysia, Email: fahmi029@melaka.uitm.edu.my

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Numerous studies have existed in an attempt to explain optimal capital structure of companies. Yet, there has been no fast rule to assist the financial manager to attain efficient mixture of equity and debt capital. Fraser, Zhang and Derashid (2006) argue that larger and more profitable firms with political patronage tend to resort to debt financing. Tahir and Miza (2009) finds Malaysian GLCs fail to optimize the use of their capital and are highly geared. In addition many researchers are attracted to investigate factors affecting capital structure decisions of company. Generally empirical results show that the choice of capital structure studies differs from sector to sector basis (Sabir and Malik 2012), between private and public companies (Ting and Lean 2011), between large and small companies and the direction of the explanatory variables on the leverage measured. For example Suhaila and Mahmood (2008) and Ting and Lean (2011) find that growth is not a determinant for capital structure in Malaysia while Dzolkarnaini (2006) and Mustapha, Ismail and Badriyah (2011) discover growth to be positively related to leverage. This setting provides an opportunity to examine and identify factors that determine the debt policy decision of Malaysian GLCs. This study also extends the research work of Ting and Lean (2011) by including additional variables like non-debt tax shield and interest coverage ratio that they have not included but have been highlighted by previous literature to be among the factors that determine firm’s capital structure. Furthermore, this study utilizes different financial leverage measurements proposed by Sheikh and Wang (2011) and Bevan and Danbolt (2004). They claim that a clearer understanding of the capital structure of a company can be derived by using long term debt and short term as proxies Last but not least this study attempts to identify the capital structure theory that would explain Malaysian GLCs capital structure decision policy. This paper is structured as follows: Section 1 provides a brief background of the study. Section 2 discusses and reviews the capital structure theories and empirical evidences. Section 3 explains the data and methodology employed. Section 4 discusses the findings and section 5 concludes.

2. Literature Review

Evolution of capital structure theories starts off with Modigliani and Miller’s (1958) study on capital structure. Also known as capital structure irrelevance theory, it argues that the capital structure of a company has no impact on its value but rather the type of investment decision made does. This theory was heavily criticized as it fails to account for other factors like the advantage of tax shield, bankruptcy costs and agency costs. The work of Modigliani and Miller prompts the development of other theories of capital structure specifically static trade-off, pecking order, and agency cost theories. Static trade-off theory explains that debt policy decision of a company is identified after the company weights the benefits and costs of using debt to finance. Optimal capital structure is achieved through the net advantage of using debt financing. It further argues that this advantage compensates the financial distress and bankruptcy costs associated with debt financing (Altman 1984; Sabir & Malik 2012). A company with a low level of debt will be able to increase the firm value if more debt financing is used. However when the firm value is already maximized then using more debt will not benefit the firm but rather incur additional costs. Hence highly profitable companies will resort to high debt financing since it can reduce agency costs, taxes and bankruptcy costs.

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Myers (1984) and Myers and Majluf (1984) were the advocates of pecking order theory. The theory explains that company will use its internal sources of financing first before seeking external financing like debt because it is cheaper to source internally and is aware that different form of capital has different costs (Myers 1984). Highly profitable company tends to prefer low level of debt financing since it has sufficient internal funds. On the other hand, company with low profitability prefers to use debt instead of equity financing because it is cheaper. In addition, if a company runs out of internal funds, then it prefers to use debt rather equity since the cost of debt is relatively cheaper. Managers are hired by stockholders to manage the company. However there may be times when managers make decision that will be at the expense of the stockholders. Consequently costs need to be borne by stockholders due to mismatch of interest between these two parties (Jensen and Meckling 1976). It is said that debt financing could reduce this conflict of interest and hence agency costs. From the agency cost theory perspective, debt financing is preferred to equity because debt investors have the right to take legal action against management who failed to pay their due interest payments. Fearing of losing his job, management will act in the interest of the organization to ensure that debt investors’ interest payments are made (Grossman and Hart 1982). 2.1 Capital Structure Determinants, Theories and Hypotheses Previous empirical findings have identified liquidity, interest coverage ratio, size, growth opportunity, tangibility of assets, profitability and non-debt tax shield as factors influencing company’s capital structure decision. The following section reviews variables identified in previous literatures relates them to capital structure theories and hypothesizes the relationship between these explanatory variables and financial leverage A company that is highly liquid would seek debt financing due to its capacity to pay any debt obligation due. As a result, a positive relationship is hypothesized between financial leverage and liquidity. This concurs with the trade-off theory. Pecking order theory tends to differ with this relationship. It is argued that if company has so much cash flow then it will use internal funds for any new investments rather than resort to debt financing. Company’s liquidity is related to short-term debt financing and is theoretically predicted to show a negative relationship (Bevan and Danbolt 2004). Among studies that are in congruent with pecking order theory are Sheikh and Wang (2011), Viviani (2008) and Mazur (2007). It is anticipated that an inverse relationship exist between GLCs leverage ratios and liquidity ratio. Interest coverage ratio is another explanatory variable to be considered in this study. Following Eriotis, Vasiliou & Ventoura-Neokosmidi (2007), the equation is expressed as net income before taxes divided by interest payment. The ratios can be calculated as expressed below: Interest Coverage Ratio equal to net income before tax interest charges. Harris and Raviv (1990) suggest that interest coverage ratio has negative correlation with leverage. They conclude that an increase in debt will increase the probability of the company to default. Therefore, interest coverage ratio acts as a proxy of default probability which implies that a lower interest coverage ratio indicates a higher debt ratio. The relationship is in support of static trade-off theory. On the other hand, Baral (2004) argues that a positive relationship between interest coverage ratio

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and leverage can exist. Hence it is expected that an increase in interest coverage ratio will affect leverage negatively. Large companies prefer to go for debt financing and are less likely to go bankrupt Due to their size, they are able to use debt financing since their earnings are more stable. Static trade off theory supports this argument. Empirical evidences by Zou and Xiao (2006), Sheikh and Wang (2011) and Huang and Song (2006) are in tandem with this theory. In contrast, Bevan and Danbolt (2004) and Chen (2004) findings support the pecking order theory where they report a negative relationship between size and leverage. A negative relationship exists due to the reason that large firms do not have serious problem of information asymmetry and therefore can afford to issue equity rather than debt instruments. Long term debt and short term debt have negative relationship with size of the company (Titman and Wessels 1988). Generally the results from previous literature are still mixed. In this study, the expectation on the effect of GLCs size on leverage is positive. Sheikh and Wang (2011) and Song (2005) find that growth is a good factor for explaining the capital structure decision of the firm. Based on the pecking order theory, when company is faced with growth opportunities, it will tend to source for debt financing rather than issuing new equity. The rationale behind such decision is that issuing new equity increases the asymmetric information related costs that could be reduced through issuing of debt. Hence pecking order theory postulates a positive relationship between growth and financial leverage. However both static trade-off theory and agency theory predict a negative relationship between financial leverage and growth opportunities. According to static trade-off theory, since growth opportunities are considered as intangible assets and therefore cannot be collateralized, company will reduce the use of debt financing. Under agency theory, management has the tendency to channel the company’s wealth to the shareholders is greater if the growth opportunities are greater. In order to mitigate the agency problems, company with high growth potential should seek equity financing rather than debt financing. Results from Eriotis, Vasiliou and Ventoura-Neokosmidi (2007) and Sheikh and Wang (2011) supported these two theories. A positive relationship between GLCs leverages ratios and growth opportunities is hypothesized. Static trade off theory states that companies will be in a position to provide collateral if they have high level of tangible assets. Companies that default on their debt can use these tangible assets as collateral and hence avoid being bankrupt. Hence it is hypothesize that there is a positive relationship between tangibility and financial leverage. Most empirical evidence in developed confirms this relationship. Wald (1999) and Viviani (2008) while those from the developing countries report either positive or negative relationship. Wiwattanakantang (1999) and Baharuddin et al. (2011) document a positive relationship while Mazur (2007) and Sheikh and Wang (2011) however find negative relationship between these two variables. Nuri (2000) explains that the inconsistency in the results is due to different form of debt being used in the studies conduct. A positive relationship exists if long-term debt is used while an inverse relationship is observed if company uses more short-term debt (Sogorb-Mira, 2005) and (Ting and Lean, 2011). This negative relationship is in line with the agency cost theory that postulates that company tends to use debt financing if it is not highly collateralized to prevent agency conflicts (Titman and Wessels 1988) and (Sheikh and Wang 2011). A positive relationship between GLCs leverages ratios and tangibility of assets is expected in this study.

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Under static trade off theory profitability is said to be positively related to financial leverage. Um (2001) explains that a profitable company is capable of higher debt capacity that results in benefitting from higher tax shields. Hence, it is expected that a positive relationship should exist between profitability and financial leverage. Besides management will choose debt financing over equity financing since debt cost is cheaper on contrary, pecking order theory suggests an inverse relationship between profitability and financial leverage because it is argued that a company prefers to source for internal funds first before going for external financing. Similar findings are documented by Sabir and Malik (2012) and Sheikh and Wang (2011). Hence, this study expects profitable GLCs to use less debt financing. The decision to increase financial leverage depends on whether the tax deductions are on depreciation and investment tax credits (DeAngelo and Masulis 1980). If major proportion of tax deduction is due to depreciation instead of borrowing then there is a negative relationship between non-debt tax shields and financial leverage (Song 2005). On the other hand, Pettit and Singer (1985) have argued that large company is inclined to seek debt financing since large company have more tax deductible items. This is in line with the pecking order theory. As a proxy for non-debt tax shield this study will use annual depreciation divided by the total assets (Song 2005). Furthermore Sheikh and Wang (2011) find inverse relationship between non-debts tax shield and short-term debt. Hence it is hypothesized that non-debt tax shield has positive relationship with GLCs leverage. In sum, although there are numerous empirical and theoretical researches investigating the determinants of company’s debt policy decision, the relationship between the explanatory variables and debt ratio are still inconclusive. Most of the studies on capital structure focus on specific industries like manufacturing, mining and extraction companies. Ting and Lean (2011) conduct a comparative study on determinants of capital structure of GLCs and Non GLCs but confined its explanatory variables to only size, cash flow, tangibility, and profitability and growth opportunities. The authors do not also highlight the capital structure theories that best explained GLCs and Non GLCs. Hence this study adds further evidence of determinants of GLCs capital structure by adding liquidity, non-debt tax shields and interest coverage ratio variables and attempts to relate the capital structure theories that best explained the debt policy of Malaysian GLCs.

3. Methodology Data The sample population of this study is Malaysia GLCs listed in Bursa Malaysia. Data is collected from the annual financial report and the period of analysis is from 2001 to 2010. Initially 44 government linked companies are identified but due to lack of information and some companies being dissolved, merged and or acquired by others companies as well as unavailability of complete data, only 38 companies are included in our sample. This study also excluded GLCs in the banking, insurance and investment sectors as their nature of business may not be comparable to the capital structure of those non-financial GLCs. The proxies use for the dependent variables and explanatory variables are based on the previous literature and are displayed in Table 1.

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Table 1 : Proxies for Dependent and Independent Variables Studied

Dependent Variables Proxies

Debt Ratio Total Debt/Total Assets

Long-Term Debt Ratio Long term debt/Total Assets Short-Term Debt Ratio Short-term debt/Total assets

Independent Variables Proxies

Liquidity (LIQi,t) Current Assets/Liabilities Tangibility (TANGi,t) Fixed assets/Total assets Profitability (PRFi,t) Return on equity ratio Firm Size (SIZEi,t) Logarithm of Total Sales

Firm Growth Opportunities (GRWi,t)

Annual percentage change in total assets

Non-debt Tax Shield (NDTSi,t)

Annual depreciation/Total assets

Interest Coverage Ratio (INCOV)

Net Income before tax/Interest Payment

Dummy Debt Ratio (D40) Debt ratio > 40% = 1 and Debt ratio < 40% = 0

Pooled ordinary least square (OLS) analysis is utilized to achieve the objectives of the study. This method is preferred as it gives more precise estimators and test statistics with more power as well as able to control for individual heterogeneity and reduce collinearity. In addition, pooled OLS regression models allow testing on all cross-section units through time which is better off than just testing all cross-section units at one point of time or one cross-section at a given point of time (Podestà 2002). Four pooled ordinary least square (OLS) regression models are estimated to analyze GLCs capital structure determinants. Model 1, 2 and 3 use debt ratio (DR), long term debt ratio (LTR) and short term debt ratio (STR) as dependent variables respectively. Model 4 includes a dichotomous variable equal to unity if GLCs have a debt ratio greater than 40% and zero otherwise. The inclusion of the dichotomous variable is to determine whether GLCs that have debt ratio of more than 40% make significant contribution in explaining GLCs debt ratio. These models are specified as follows:

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Where and are proxies for debt ratio, long term debt ratio and short

term debt ratio of at time t respectively. Liquidity ratio ( , interest coverage

ratio , size , growth rate , tangibility of assets ,

profitability a and non-debt tax shield are independent variables of

at time t. represents the error term. is the dichotomous variable as

explained in Table 1. Levin, Lin and James Chu (2002) (LLC) group and individual unit root tests, multicollinearity test, serial correlation test and heteroskedasticity test are run before four models are estimated.

4. Results 4.1 Descriptive Statistics Table 2 describes the statistics of both the dependent and independent variables in the sample of this study. On average the debt ratio of GLCs is 44% while the long-term debt ratio is 22% and short-term debt is 25% respectively. This indicates that the GLCs are almost equally financed by debt and equity. In terms of liquidity, GLCs have on average liquidity ratio of 1.7 times and interest coverage ratio of 0.8 times. The mean value of GLCs size is 8.22. The minimum value of profitability is -1.17 to a maximum value of 0.23. In relation to tangibility, fixed assets represent 50% of the total assets of GLCs. GLCs experience on average a growth rate of 18% during the period studied.

Table 2: Descriptive statistics of the variables Variables Mean Median SD Minimum Maximum

DR 0.444684 0.019159 0.277137 0.000000 2.676300

LTR 0.221270 0.179331 0.210163 0.000000 1.063000

STR 0.254584 0.226881 0.211215 0.000000 2.356967

LIQ 1.771779 1.385213 1.762410 0.000000 12.37959

INCOV 0.858262 1.062101 0.512221 0.000000 2.407551

SIZE 8.224979 8.885489 2.580289 0.000000 10.53205

GRW 0.176741 0.033747 0.771734 -0.964903 7.311859

TANG 0.508906 0.535839 0.245764 0.000000 0.945988

PROFIT 0.036432 0.041752 0.094659 -1.166284 0.225036

NDTS 0.019159 0.013601 0.023023 0.000000 0.148717

Newbold and Granger (1974) argue that if the series contain unit root then the estimated regression can provide spurious results. Hence it is essential to conduct unit root test to avoid having spurious estimation. Levin, Lin & James Chu (2002) propose to use Levin-Lin-Chu (LLC) unit root test if it is found that the pooled data (N) is larger than the time section studied (T). Result of LLC unit root test indicates all the series have no unit root (Table 3).

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Table 3: Results of Levin, Lin and Chu Group and Individual Unit Root Test Method Statistic P-value

Levin, Lin & Chu -40.6696 0.0000***

Series t-Stat P-value

DR -10.899 0.0000***

LTR -7.1491 0.0000*** STR -11.012 0.0000*** GRW -19.432 0.0000*** INCOV -11.693 0.0000*** LIQ -9.7903 0.0000*** NDTS -6.1692 0.0000*** PRF -15.306 0.0000*** SIZE -11.138 0.0000*** TANG -9.3708 0.0000***

*** denotes significance at the 1% levels

Spearman rank correlation coefficient test is used to check for multicollinearity. Sekaran and Bougie (2010) explain that correlation of 0.70 and above shows the presence of mullticollinearity. Results of correlation coefficient test indicate the absence of multicollinearity among the independent variables (Table 4).

Table 4: Spearman rank correlation test

GRW INCOV LIQ NDTS PRF SIZE TANG

GRW 1

INCOV 0.1209 1 (0.0183)** --

LIQ 0.0457 0.2014 1 (0.3737) (0.0001)*** --

NDTS 0.0721 0.0923 -0.0305 1 (0.1606) (0.0722)* (0.5521) --

PRF 0.0916 0.5117 0.0674 -0.0056 1 (0.0744*) (0.0000)*** (0.1896) (0.9123) --

SIZE 0.0393 0.4910 0.2151 0.2887 0.1436 1 (0.4440) (0.0000)*** (0.0000)*** (0.0000)*** (0.0050)*** --

TANG 0.0320 0.3145 0.0898 0.1877 0.1073 0.5928 1

(0.5335) (0.0000)*** (0.0804)* (0.0002)*** (0.0364)** (0.0000)*** --

***.** and * denotes significance at the 1%, 5% and 10% levels. ( ) indicates p-value.

The estimated equations are also tested for the presence of serial correlation and heteroskedasticity. Durbin-Watson statistics based on the initial estimation indicate that all three models have serial correlation problem. To overcome this problem, autoregressive error lag one (AR(1)) was included in all the models.The problem of heteroskedasticity can occur in a cross sectional data. In dealing with heteroskedasticity, we run the pooled OLS regression models using cross-section weights to allow for different variances for each company.

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4.2 Results of the Estimated Pooled OLS Models Table 5 displays the estimation results of the pooled OLS regression models.

Table 5: Estimated Results

***.** and * denotes significance at the 1%, 5% and 10% levels.

Size The results indicate that size is a significant determinant of GLCs capital structure for all the three models and are positively related. This implies that banks readily provide short term or long term loans to GLCs since they have more collateral than small companies. The finding appears to support the static trade off theory that suggest larger companies are less likely to face bankruptcy (Dawood et al., 2011)

Explanatory Variables

Dependent Variable

Model 1 DR

Model 2 LDR

Model 3 SDR

Model 4 DR with Dummy

Coefficient t-Statistic

p-value

Coefficient t-Statistic p-value

Coefficient t-Statistic p-value

Coefficient t-Statistic

p-value

LIQ -0.0471 -5.2531

0.0000***

0.0016 0.2864 0.7745

-0.0474 -5.0303

0.0000***

-0.0166 -2.5162 0.0119**

INCOV 0.0315 1.1017 0.2706

0.0444 2.3281

0.0199**

-0.0299 -1.3524 0.1763

0.0132 0.6560 0.5118

SIZE 0.0478 5.6867

0.0000***

0.0177 2.1566

0.0310**

0.05061 9.6852

0.0000***

0.0269 5.0586

0.0000***

GRW 0.0250 2.4100

0.0160**

0.0007 0.1860 0.8524

0.0238 2.8240

0.0047***

0.0013 0.1972 0.8436

TANG 0.1426 1.3860 0.1658

0.3592 6.3989

0.0000***

-0.2669 -3.1488

0.0016***

0.0595 0.8973 0.3696

PRF -0.2238 -1.5616 0.1184

-0.2553 -2.3637 0.0181**

0.1319 1.6076 0.1079

-0.1979 -1.8520 0.0640*

NDTS 0.9789 0.9292 0.3528

-0.1343 -0.2801 0.7793

0.7005 0.8952 0.3707

1.0898 1.3845 0.1662

DUMMY na na na 0.3029 13.569

0.0000***

C 0.0287 0.6102 0.5417

-0.1237 -2.0478 0.0406

0.0644 2.7911 0.0053

0.0166 0.8583 0.3907

AR(1) 0.5439 4.4790 0.0000

0.7208 13.082 0.0000

0.5103 2.5232 0.0116

0.3630 2.6433

0.0082***

R-squared 0.5068 0.6793 0.4790 0.6373

Adjusted R-squared 0.5065 0.6791 0.4787 0.6370

F-statistic 1668.53 3438.61 1492.81 2535.83

Prob(F-statistic) 0.0000 0.0000 0.0000 0.0000

Durbin-Watson stat 2.2846 1.9955 2.2725 2.2057

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and (Morri and Cristanziani ,2009). However the results are inconsistent with Ting and Lean (2011) in which the authors find size to be negatively related to debt ratio and short term debt ratio respectively. Liquidity Ratio The liquidity ratio variable is both negative and significant for debt ratio and short term debt ratio but insignificant for long term debt ratio. As pointed out by Bevan and Danbolt (2004) liquidity ratio variable is more relevant to short term debt than long term debt since company tends to use short term debt to finance their current assets. A significantly negative relationship exists between liquidity and short term debt ratio. This shows that GLCs will reduce short term borrowing if they have higher the liquidity ratio (Šarlija & Harc 2012). The empirical result between liquidity ratio and short term debt concurs with the pecking order theory. Interest Coverage Ratio Interestingly the coefficient on interest coverage ratio (INCOV) is significant at the 0.05 level for long-term debt ratio and positvely related. Interest coverage ratio indicates company’s capability to meet its interest payment from its operating profits. Baral (2004) explains that this relationship is possible because GLCs with higher INCOV ratio have more than enough cash flows required to service their debt and would not mind seeking more debt financing(Baral 2004). However Baral (2004) use the debt capacity theory to explain the positive relationship between interest coverage ratio and long-term debt. Another plausible reason is that since GLCs are government owned, therefore there is a tendency for these companies to deviate from the financial fundamentals when changing their long term debt levels (Ting and Lean 2011).

Profitability There are no relationships between profitability and debt ratio as well as short term debt ratio (SDR) but there is a negative relationship with long term debt ratio (LDR). The result confirms the findings of Huang and Song (2006) and Ting and Lean (2011) and is in support of pecking order theory. It appears that as GLCs become more profitability, these companies tend to raise fund through equity while decreasing the level of debt financing. A profit-making GLCs are able to attract equity investor and at the same time the ability to pay off their previous debt. Growth Opportunities Growth opportunities are significantly and positively related to both debt ratio (DR) and short-term debt ratio (SDR). This result is consistent with Myers (1984). He argues that banks willing to lend money to company that has good growth opportunities. The probable justification of such result is the most of the Malaysian GLCs have yet to achieve their optimum growth potential and will seek external financing to realized higher growth opportunities. On the other hand, growth opportunities are not significantly related to long term debt ratio for GLCs. A plausible explanation is that growth potential GLCs prefer short term financing instead of long term financing to finance investments on long-lasting assets. This finding supports both the static trade off theory and agency theory. This finding supports both the static trade off theory and agency theory. In addition, our result is in contrast with Ting and Lean (2011) that find no relationship between the two variables for GLCs but positive relationship for Non GLCs.

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Tangibility of Assets Tangibility of assets is not the determinant for GLCs capital structure, when debt ratio is used as a proxy. However when this study decomposes the leverage ratio into short term and long term debt, a significant positive relationship exists between tangiblity and long term debt. However an inverse is found for short term debt ratio. This finding is consistent with those of Bevan and Danbolt (2004), Sogorb-Mira (2005) and Ting and Lean (2011). This suggests that GLCs with higher tangible assets are more likely to use long term debt rather than short-term debt to prevent agency conflicts (Sheikh and Wang 2011). In this regard, our finding provides support for agency cost theory. Non-Debt Tax Shields Based on the theoretical discussion in the earlier section, non-debt tax shields (NDTS) is expected to have either a positive or negative relationship. However the estimated results obtained from all the three models reveal insignificant relationship. This implies that NDTS is not the capital structure determinants for Malaysian GLCs. As mentioned earlier in previous section, this study also included a dichotomous variable, D40, in our pooled OLS regression model 4 to investigate whether GLCs with debt ratio of more than 40% have significant influence on debt policy decision. Based on the estimated result, the dichotomous variable is significant implying that GLCs with 40% debt structure prefer to seek debt financing as their form of external financing.

5. Conclusion

The objective of this study is to empirically investigate the determinants of capital structure of 38 Malaysian Government Linked Companies over a 10-year period starting from 2001 to 2010. Overall results from this study indicate that several determinants affect capital structure of GLCs. Liquidity and profitability are negatively related to debt ratio while size and growth opportunities are positively related. This suggests that being large companies and have potential to grow, GLCs has the capacity to source for debt financing. The most important finding in this study is that the debt policy decision of GLCs becomes more apparent when GLCs capital structure policy is decomposed into long term debt ratio and short term debt ratio. Tangibility, size and interest coverage ratio are positively significant for long term debt ratio model. This suggests GLCs tend to seek long term financing if they have higher tangible assets and higher interest coverage ratio. In addition, investors are willing to invest in GLCs since they have more collateral than small firms. The relationship between profitability and long term debt ratio is inversely related. On the other hand, short term debt ratio has significantly negative relationship with liquidity and tangibility variables. This shows that an increase in liquidity reduces the short term borrowing of GLCs as the companies can use its current assets to pay its obligations. GLCs will also resort to short term financing rather than long term financing if they have lower tangible assets. Significantly positive relationship between growth opportunities and short term debt implies that GLCs make use of short-term financing to finance its investments. Non debt tax shield is statistically insignificant in all of the models estimated. This confirms that tax shield is not an important motivation for GLCs to use debt financing.

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It is also important to highlight that several findings from this study contradicts with those of Ting and Lean (2011) specifically for size and growth opportunities. The inclusion of liquidity, interest coverage ratio and non-debt tax shield variables have improved the adjusted R-squared for the four models estimated. This indicates that the variables are the determinants of the GLCs capital structure. Finally, this study finds that the debt structure policy of Malaysian GLCs is best explained by the both static trade off theory and pecking order theory. Future research on capital structure of GLCs could include segmenting the GLCs into different sectors to capture the industry effect. In addition, a comparative study on determinants of GLC’s capital structure from different countries can also be conducted.

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