DETERMINANTS OF CAPITAL STRUCTURE IN SRI LANKA: EVIDENCE FROM PANEL DATA PDF

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Citation: Vijayakumaran. R. and Sunitha.V., (2011). Determinants of Capital Structure in Sri Lanka. Proceedings of the international conference of Sri Ram Institute of Management Studies, India, pp. 295-305. DETERMINANTS OF CAPITAL STRUCTURE IN SRI LANKA: EVIDENCE FROM PANEL DATA Mr.R.Vijayakumaran ...

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Citation: Vijayakumaran. R. and Sunitha.V., (2011). Determinants of Capital Structure in Sri Lanka. Proceedings of the international conference of Sri Ram Institute of Management Studies, India, pp. 295-305.

DETERMINANTS OF CAPITAL STRUCTURE IN SRI LANKA: EVIDENCE FROM PANEL DATA

Mr.R.Vijayakumaran BBA, MBA, MA(Econ), MAAT(SL) Senior Lecturer, Department of Financial Management, Faculty of Management Studies & Commerce, University of Jaffna. UK Commonwealth Scholar & PhD Candidate, Durham Business School, Durham University, Durham, UK Email: [email protected]/[email protected]

Mrs Sunitha Vijayakumaran, B.Com, MA(Econ) Lecturer, Department of Management Studies, Faculty of Humanities & Social Sciences, Open University of Sri Lanka, Nawala, Nugegoda. PhD Candidate, Durham Business School, Durham University, Durham, UK. Email: [email protected]/[email protected]

Abstract This study investigates the use and the determinants of long-term leverage using the sample of 50 companies listed in Colombo Stock exchange (CSE). The panel cross sectional regression analysis was performed for 226 firm year observations over the period from 2004 to 2008. The study reveals that at an aggregate level, leverage of Sri Lankan firms is comparatively low. The size of the firms is positively significantly related to leverage while profitability is negatively significantly associated with leverage suggesting that more profitable firms tend to use less leverage. This suggests that firms tend to follow a reverse pecking order with regard to external financing: Equity is the first source of external finance on the pecking order. This study documents that the size and profitability have robust effects on long-term leverage in Sri Lanka. Key words: Capital Structure, Leverage, profitability, size, tangibility, market to book ratio.

1. Introduction Corporate capital structure remains a controversial issue in modern corporate finance. Since the seminal work by Modigliani and Miller (1958), a plethora of research has been undertaken in attempting to identify the determinants of capital structure. Firms create wealth by making investments which generate cash flows. The stream of cash flows is produced by firm‘s assets (the left hand side of the balance sheet) which are financed by sources of financing (the right hand side of the balance sheet). The mix of different sources of financing is referred to as capital structure of the firm (Panday, 2004). A firm can use infinite number of sources of combinations; however, it should use the one which

maximizes its value. The research on capital structure has focused on question whether corporate financing decisions matter at all. If financing decisions were completely irrelevant, then actual capital structures should vary randomly from firm to firm and industry to industry. Nevertheless, this is not what is observed by empirical evidence. Capital structure theories have been subjected to extensive empirical testing in the context of developed economies, particularly the United States (e.g., Harris & Raviv 1991). However, few studies report on international comparisons of capital structure determinants (e.g., Rajan & Zingales 1995; Wald 1999) and also from developing countries, for example Booth et al, (2001) analyse data from ten developing countries (Brazil, Mexico, India, South Korea, Jordan, Malaysia, Pakistan, Thailand, Turkey and Zimbabwe), Pandey (2001) utilise data from Malaysia and Omet and Nobanee (2001) use data from Jordan. Furthermore, very little empirical evidence is available from emerging markets especially in Sri Lanka. The main aim of this study is to fill this gap. Thus this study provides empirical analysis of firms‘ capital structure in Sri Lanka using a panel data and alternative model specifications. Particularly, the study attempts to answer the following research questions: a) What are the determinants of capital structure of listed companies in Sri Lanka? b) What are the capital structure theories that dominate in emerging markets?

2. Objectives of the Study The objectives of this study are: a) To identify the determinants of capital structure decisions in emerging markets a b) To identify the capital structure theories which dominate in emerging markets?

3. Literature Review The modern theory of capital structure was established by Modigliani and Miller (1958). They show the irrelevance of capital structure to the value of the firm. This implies that, there is no optimal capital structure because a firm‘s value cannot be affected by its choice of financing. Since the publication of the seminal article of Modigliani and Miller a vast theoretical literature has emerged to identify the conditions under which the irrelevance hypothesis does no longer (Harinis and Raviv, 1991; Rajan and Zngales, 1995). This theoretical literature has proven that the assumptions underlying the Modigliani and Miller theory are in general too unrealistic. However, in corporate finance, the academic contribution of Modigliani and Miller about capital structure irrelevance and the tax shield paved the way for development of alternate capital structure theories. Much attention of researchers has been placed on releasing the assumptions made by Modigliani and Miller in particular by taking into account corporate taxes (Modigliani and Miller, 1963), personal tax (Miller 1977), bankruptcy cost (Stiglits, 1972; Titman, 1984) agency costs (Jensen and Meckling 1976, Myers 1977) and information asymmetries (Myers and Mujluf, Myers 1984 ). Both, theoretical and empirical capital structure studies have generated many results that attempt to explain the determinants of capital structure. Consequently, there exist a number of determinants of capital structure derived from various theories. As Haris and Raviv (1991) demonstrate in their review article, ―the motives and circumstances could determine capital structure choices seen nearly uncountable‖. Two main theories

currently dominate the capital structure debate: the trade-off theory and the pecking order theory. 3.1 Trade-Off Theory The Trade of theory (TOT) posits that firms maximise their value when the benefits that stem from debt (the tax shield, the disciplinary role of debt, and the fact that debt suffers less from informational costs than outside equity) equal the marginal cost of debt (bankruptcy costs, and agency costs between shareholders and bondholders). The management of the firm is assumed to maintain an optimal debt/equity ratio in order to minimize the cost of prevailing market imperfections, trading off the tax shield benefits of debt finance and the agency and financial distress costs of maintaining high debt levels (Scott, 1972; Kraus and Litzenberger, 1973; Kim, 1978; Bradley et al, 1984; Harris and Raviv, 1990). Under the trade-off theory leverage is expected to be positively related to firm size (the larger the firm, the lower the costs of bankruptcy), profitability (the more profitable the firm, the greater the profits that need to be shielded from taxation and the lower the costs of financial distress), and tangibility/asset structure (the larger the assets of the firm the lower the costs of bankruptcy) 3.2 The Pecking Order Theory The pecking order theory (POT), developed by Myers and Majluf (1984) and Myers (1984), is a consequence of information asymmetries existing between insiders of the firm and outsiders (i.e. the capital market). The model leads managers to adapt their financing policy to minimise the associated costs. More specifically, they will prefer internal financing to external financing, and risky debt to equity. The pecking order theory can explain why the most profitable firms tend to borrow less; they simply do not need external funds. Less profitable firms issue debt because they do not have sufficient internal funds and because debt has lower flotation and information cost compared to equity. Debt is the first source of external finance on the pecking order. Equity is issued only as a last resort, when the debt capacity is fully exhausted. Tax benefits of debt are a second-order effect. The debt ratio changes when there is an imbalance between internal funds and real investment opportunities. Further, firms are more likely to create financial slack to finance future projects. According to the pecking order theory leverage is expect to be negatively related to the profitability of the firm (the more profitable the firm, the greater the internal financing available), and positively related to the asset structure of the firm (the greater the percentage of fixed assets possessed by the firm, the easier it would be to access collateralized debt). 3.3 Determinants of Capital Structure Tangibility: The tangibility refers to tangible assets as a proportion to total assets. There is evidence that leverage increases with fixed assets (Marsh, 1982; Long and Malitz, 1985; Friend and Hasbrouck, 1988; Friend and Lang,1988; Rajan and Zingales, 1995. A firm having a high ratio of tangible assets has more collateral and hence more borrowing capacity. Therefore, a higher tangibility is likely lead to higher leverage.

Size: This is proxied by natural logarithm of sales. There is evidence that leverage increases with size (see Harris and Raviv, 1991). One argument is that size proxies for the inverse probability of default (Rajan and Zingales, 1995). Large firms, particularly when they are diversified, have a better ability to withstand bad times than small firms, which may lead to a tendency for large firms to use more debt. Growth opportunities: This is proxied by market to book value of assets (Myers, 1977). The market value of total assets is the book value of total assets minus book value of equity plus market value of equity. The theory predicts that leverage increases with lack of growth opportunities (Jensen and Meckling 1976; Stulz, 1990), and thus a negative relationship between leverage and growth opportunities. Another argument is that highgrowth firms need more external funds to finance growth and would turn first to debt financing due to information asymmetry (Myers, 1984) and higher floatation costs associated with equity. This view predicts a positive relationship between leverage and growth. The empirical evidence is mixed; some find a reliable negative relationship (Kim and Sorensen, 1986; Rajan and Zingales, 1995) while others report a positive one (Kester, 1986). Profitability: The profitability of the firm is measured by return on assets (ROA). Empirical studies generally provide evidence that leverage decreases with profitability (see Friend and Hasbrouck, 1988; Friend and Lang, 1988; Titman and Wessels, 1988; Rajan and Zingales, 1995). Profitable firms may not have a much need for debt financing, since they can finance with retained earnings which has no information asymmetry.

4. Hypotheses Based on the above discussion of the capital structure theories and empirical findings on the determinants of capital structure, the following hypotheses are developed for testing. H1: There is a negative relationship between leverage ratio and profitability. H2: There is a positive relationship between leverage ratio and tangibility. H3: There is a positive relationship between leverage ratio and size. H4: There is a negative relationship between leverage ratio and growth.

5. The Model Specification and Estimation Methodology The study employs panel data methodology. Panel data provide the opportunity for the pooling of observations on a cross-section of units over several time periods and provides results that are simply not detectable in pure-cross sections or pure time series studies. In order to test our hypotheses, and motivated by the literature on capital structure, we estimate the following baseline model: LEVit  0  1TANit  2 SIZEit  3GROWTHit  4 PROFit  vt  v j  eit

Where: LEVit (leverage) = Long-term Debt / (Long-term Debt + Book Equity) TANit (tangibility) = Fixed Assets / Total Assets SIZEit (firm size) = log (Sales) GROWTHit (M/B ratio) = Market Value of Assets / Book value of Assets

(1)

PROFi (profitability- ROA) = Earnings Before Interest and Taxes / Total Assets

vt = time dummies vj = industry dummies eit = the regression error term where i indexes firms; t, time; j, industries We initially estimate equation (1) above using OLS without industry dummies and then with industry dummies. In addition, we estimate equation (1) using both a pooled Tobit and a random-effects Tobit specification in order to show the robustness of our findings.

6. The Sample Our sample consist of 50 companies listed in the Colombo Stock Exchange (CSE) covering seven industries namely, beverage food and tobacco, chemicals and pharmaceuticals, diversified holdings, hotels and travels, land and property, manufacturing, plantations. We excluded observations in the 1% tails for each variable in order to control outliers. In addition, we dropped firms having negative book equity since that can lead to negative leverage, which will induce a downward bias to the mean estimates of leverage. Our panel therefore comprises a total of 226 annual observations on 48 companies, over the period 2004–2008. The data were collected from published annual reports of individual companies and hand book of Colombo Stock Exchange. For the purpose of estimation, financial year ending in December of a given year, and March and June of the following year are treated as corresponding to one financial year.

7. Results 7.1 Descriptive Statistics Table 1 presents descriptive statistics such as mean, standard deviation and correlation relative to the main variables used in our regression analysis. We can see that the longterm leverage to total assets ratio is generally quite low (13 per cent) and the proportion of assets financed by current liabilities is 28%. This finding is in line with Demirgüç-Kunt and Maksimovic (1999), who show that firms in developing countries tend to depend more on short-term debt. These companies‘ average return on assets is high (9 per cent), which suggests good overall performance. Coming to the correlation, tangibility, size, market to book ratio have positive relation with long term leverage whereas profitability is negatively associated with long term leverage which are in line with our hypotheses. Traditionally, companies in Sri Lanka have mainly relied on the banking sector for their debt financing needs. For the first time in 1996 companies commenced issuing bonds to the general public through prospectus issues. Even though several companies have raised long-term debt publicly the market for long-term debt remains small and still the most popular mode is bank financing. The lack of a developed long-term debt market may be the main reason for the low use of long-term debt financing in Sri Lanka.

Table1: Descriptive statistics and Correlation metrics Mean SD Variables 1 2 3 4 5 1 Long term Leverage 0.13 0.16 Short term Leverage 2 0.28 0.18 -0.0519 Tangibility 3 0.60 0.26 0.2877 -0.4581 4 19.94 2.07 0.2056 Size 0.344 -0.0499 5 1.17 0.47 0.0563 Growth 0.034 0.1268 0.0197 6 0.09 0.07 -0.2671 -0.0174 -0.3536 0.0384 0.112 Profitability

7.2 Regression Results Table 2 and 3 present the estimates of equation (1). Columns 1 and 2 in Table 2 refer to the estimates for total leverage, obtained using the OLS. Regression estimates in column 1 in Table 1 show that tangibility, size and profitability have statistically significant relationship with leverage. However, after adding industry dummies to our model, we observe that size and profitability have statistically significant relationship with the leverage of listed companies in Sri Lanka. Table 2: OLS models for long-term leverage

OLS models (1) (2) TANit

SIZEit

GROWTHit

PROFit

Constant Year dummies

0.1267***

0.0686

(0.0391)

(0.0475)

0.0176***

0.0262***

(0.0046)

(0.0064)

0.0308

0.0327

(0.0232)

(0.0228)

-0.4649***

-0.3442**

(0.1498)

(0.1549)

-0.3167 (0.1039) yes

-0.5479 (0.1541) yes

Industry dummies

no

yes

Observations

226

226

Adjusted R-squared

0.15

0.25

Notes: The figures reported in parentheses are standard errors. See Table 1 for definitions of all variables. * indicates significance at the 10% level. ** indicates significance at the 5% level. *** indicates significance at the 1% level.

Table 3 reports the estimates for long-term leverage, obtained using pooled Tobit and random effects Tobit estimator. Once again, in both specifications, after adding industry

dummies to the models, size and profitability show statistically and economically significant impact on the leverage. Therefore, after controlling for time specific fixed effects (vt) (i.e., possible business cycle effects) and industry specific differences (vj), size and profitability remain significant determinants of capital structure decisions of listed companies of Sri Lanka. These results are in consistent with the findings of Samarakoon, (1999a) for Sri Lankan listed firms using OLS regression based on the mean value of each variable. Our results are also robust to alternative model specifications as discussed above. While our second and fourth hypotheses are rejected in Sri Lankan context, the results provide support for our first and third hypotheses. The results indicate that size of the firms has significant positive impact on long-term debt to total assets ratio. This implies that larger firms tend to use more debt capital in their capital structure than smaller firms. Another important empirical evidence that the present study finds is that a reliable negative relationship between leverage and profitability. It is interesting to find that as suggested in previous research (e.g Harris and Raviv, 1991), profitable firms may tend to use less debt since they are able to finance through retained earnings. The firm‘s ability to generate retained earnings is better captured by ROA (9%). The overwhelming importance of ROA both in terms of statistical significance and the explanatory power of regressions that supports the argument based on retained earnings. Rajan and Zingales (1995) also provide evidence of a significant negative relationship between leverage and profitability for the firms in the U.S., Japan, and Canada. Table 3: Tobit models for long-term leverage

TANit

SIZEit

GROWTHit

PROFit

Constant

Pooled Tobit model (1) (2)

Random effects Tobit model (3) (4)

0.1637***

0.0968

0.1174*

0.0510

(0.0495)

(0.0594)

(0.0681)

(0.0744)

0.0235***

0.0338***

0.0249**

0.0297**

(0.0057)

(0.0076)

(0.0100)

(0.0124)

0.0314

0.0335

0.0168

0.0165

(0.0285)

(0.0274)

(0.0172)

(0.0171)

-0.9354***

-0.8300***

-0.3996**

-0.3555**

(0.2021)

(0.2058)

(0.1704)

(0.1703)

-0.4464***

-0.6093

-0.4942

-0.4909

(0.1294)

(0.1733)

(0.2142)

(0.2813)

Year dummies

yes

yes

yes

yes

Industry dummies

no

yes

no

yes

Observations

226

226

226

226

χ2

63.27

84.63

28.14