A Comparative Study of Capital Structure Determinants in African-Top Gold

Mining Firm (AngloGold Ashanti) and World-Top Gold Mining Firms

Abstract: This paper seeks to compare the determinants of capital structure of one of the top-African gold mining firms

(AngloGold Ashanti) with world-top gold mining firms. Determinants of capital structure would vary in different regions

which could influence the market capitalization of a firm; therefore, a comprehensive understanding of this issue would

be helpful for the decision makers of gold mining industry. For this purpose, regressions are run for these two different

samples. Empirical results show that significant determinants of capital structure have different impacts on the leverage

ratios of AngloGold and world-top gold mining firms except profitability which affects the leverage ratios of both

samples identically. The findings of this paper provide insights for African gold mining managers and policy makers

based on empirical evidences.

Keywords: Determinants of Capital Structure, Leverage Ratio, African Gold Mining Firms, World Gold Mining Firms

1 Introduction

There are 47 countries and over 800 million people in Sub-Saharan Africa, some of the worlds largest remaining

undeveloped mineral deposits are hosted in this area. Mining industry activities play an important role in the economic

grows of the region the activities such as development of resources, ranging from coal to lead to cobalt to gold. Regarding

to natural resources a large number of the nations in SSA still perform poorly on many development indicators, which

leads to increased levels of political and economic uncertainty. Funding and developing mining projects need a powerful

foreign investment because most of SSA countries are involved with dearth of capital. Although the region remains a

medium to high-risk zone for most international banks in any capacity, European banks (the traditional lenders) is lending

and financing the new institution in mining sector recent years (Mulherin, 2012).

1.1 Review of Capital Structure Theories

In the literature of corporate finance, there are various researches which are trying to reach to a stable and scientific

method of understanding the structure of capital. The outcomes of these studies are some theories which are the

fundamentals of research in this field. It should be notified that these theories should be able to be adapted to the real-

world applications. In addition, they should be suitable for applying empirical tests in order to test different situations.

Capital structure optimization has become a wonderful field of research, since 1985, when an article has been published

by Modigliani and Miller (M&M) about the irrelevancy of capital structure.

Choosing the optimal mixture of debt and equity which is able to increase the wealth of shareholders is the basic

challenge of each financial manager. There are different supplies which are available for financing including external

financing such as debt or equity and internal financing such as retained earnings or surplus. David Duran (1952) showed

that if a firm increases its leverage ratio, the value of the firm increases and the market prices of shares show the same

behavior. Durands study is followed by one of the well-known studies in this field by Modigliani and Miller (1958).

They show that whether a firm is levered or unlevered does not affect the value of the firm supposing that arbitrage theory

is applied. Another study by M&M also shows that a firm can benefit from tax shield if it uses debt as the financing

source (1963). More precisely, they claim that debt financing gives a useful advantage to the firm in the form of interest

deduction and reduces the taxable income.

As it is known there are some fundamental differences between debt-financing and equity-financing such as tax shield,

costs of financing, risk of financing, maturities and etc. but determining of the optimal capital structure is still the

ultimate goal or researchers and managers. As Morri G and Berretta C (2008) mention, there is still a gap between

theoretical and empirical studies and none of the theories are not yet applied universally. It is not surprising that capital

structure has been an interesting field of research since many years ago because not only all theories are not tested

empirically, but also the empirical tests have resulted in different results (Amarjit Gill, 2009).

Biger, Nguyen, and Hoang (2008) indicate that collateralized assets, income tax, non-debt tax shield, corporate

profitability, firm size, and growth opportunities determine capital structure choices of the firm.

Financially, the capital structure of a firm is a combination of debt and equity which finance the firms investments or

operations (AborJ., 2005).There is not any constant formula to determine the capital structure of a firm. In other words,

financial managers decisions can vary from large proportions of debt and small proportions of equity to large proportions

of equity and small proportions of debt. Additionally, firms may choose either to arrange lease contracts and warrants or

to issue convertible bonds, forward contracts and bond swaps. Therefore, whatever the financial managers decide will

determine the final mixture of the capital structure (Abor J., 2006).

S. M. Hashemi and H. Hosseini. K (2013) studied on determinants of capital Structure in the top-five gold mining

companies. They found that profitability of a firm and tangibility of its assets are significantly affecting the leverage ratio

of top gold mining firms.

In the following section, determinants of capital structure which are believed to be important in the gold mining firms are

discussed briefly.

1.2 Determinants of Capital Structure

Because capital structure influences corporate profitability, it is important to find the important factors that influence

firms choices of leverage. A number of empirical studies have identified firm-level characteristics that affect the capital

structure of firms. Among all firm-specific characteristics are non-debt tax shield, risk, size, tangibility of assets and

growth opportunities.

1.2.1 Non-debt Tax Shield

Depreciation has the advantage of tax deductibility. Non-debt tax shield can affect income taxes mutually with debt tax

shield. However, the presence of non-debt tax shield sometimes leads to mitigation of debt tax shield (Cloyd, 1997). In

addition to depreciation, tax credits are also known as tax-saving means. DeAngelo and Masulis (1980) suggest that tax

deductibility of depreciation and tax credits can mutually cause to mitigate the benefits of debt financing. Hence, the

higher proportion of non-debt tax shields in a firm results in less tendency to use debt. In this study, non-debt tax shield is

defined as the ratio of depreciation and depletion to total assets.

1.2.2 Risk Level of a Firm

According to the related literature, risk profile of a firm is believed to be an important determinant of firms capital

structure (Kale et al., 1991). Generally, firms avoid employing a 100% debt structure because of possible bankruptcy

costs. Therefore, firms decide on their capital structure as a function of their risk profile (Castanias, 1983). Since volatile

earnings could possibly lead to operating risks, firms prefer to reduce their debt level in order to mitigate their exposure to

bankruptcy costs. In addition, an empirical research (Esperanca et al., 2003) reveals that firms risk level is related to debt

level both in long-run and short-run. In this context, risk is defined by the percentage change in earnings before interest

and tax (EBIT) in comparison with the previous year.

1.2.3 Firm Size

The firm size is known as one of the most affecting factors of capital structure decisions. It is believed that as a firm

develops, it can diversify its earnings and reduces the risks involved in the investments (Titman and Wessel, 1988). There

are also some evidences in the literature about the relationship between firm size and its leverage ratio. A study of

Norwegian companies during 1992 to 2005 by Mjos (2007) shows that size of a firm is positively related to its debt ratio.

Another similar study which is done by Frank and Goyal (2007) has investigated US firms during 1950 to 2003 shows

that larger firms have higher debt ratios in comparison with the smaller ones. This study evaluates the size of a firm by

natural logarithm of its total sales or total revenues. On the other hand, a negative relationship could exist between size

and leverage ratio because large firms may have better internal resources and easier access to financial markets and

benefit from better financial conditions on these markets when requesting new issuance of capital (Booth et al., 2001).

1.2.4 Tangibility of Assets

Mining firms, more than other industries, are dependent on their tangible or physical assets. Creditors consider tangible

assets as collaterals which have the least level of risk. Moreover, tangible assets are easier to liquidate in comparison with

intangible ones. Therefore, corporations which have higher amounts of tangible assets are potential to finance their

operations more via debt financing rather than equity financing because the former has lower costs compared to the latter

(Biger, Nguyen and Hoang, 2008).It is indicated in the literature that the type of assets have great impacts on leverage

either positively or negatively (Biger, Nguyen and Hoang, 2008).Similar studies (Frank and Goyal, 2007; Mjos, 2007)

show that as tangible assets of a firm increases, the leverage of that firm increases accordingly. In order to convert the

data for investigation, the ratio of fixed assets to total assets is calculated to be the representative of tangibility of assets.

1.2.5 Growth Opportunities

According to the pecking order theory, there should be a positive relationship between growth opportunities of a firm and

leverage. As firms tend to invest more to grow, they need more debt financing because retained earnings (internal

financing) are limited. Therefore, growth opportunities of a firm affect the leverage ratio of a firm. It is shown that firms

with higher growth opportunities are not willing to increase their debt because they are sure about future investment

opportunities. Therefore, high-growth firms tend to borrow less in order to decrease the transfer of wealth from the

shareholders to the creditors (Mayers, 1977).

1.2.6 Profitability

As profitability can influence the debt ratio of a firm in different ways, the direction of its impact on debt ratio is

conflicting. Based on the trade-off theory, if a firm earns more profits, it should employ higher debt ratios. Higher debt

ratios are associated with more tax savings and lower financial costs of bankruptcy. In addition, profitable firms are more

able to increase debt capacity because of their potential in loan repayment (Guad et al., 2005). However, the opposite

relationship between profitability and debt ratio is the representative of pecking order theory. Based on this theory,

profitable firms tend to benefit from internal funds rather than employing external funds (Myers, 1984).

2 Data and Methodology

2.1 Data

This study collected its data from Thomson Reuters DataStream database. The first sample is consisted of annual figures

for the world-top gold mining firms from 1995 to 2012 extracted from their balance sheets and income statements. As we

investigate 6 world-top large firms, there are 108 observations in the sample. The second sample concerns about the

AngloGold. Quarterly data is extracted from this companys balance sheets and income statements from 1995 to 2012 and

the sample covers 72 observations.

World-top gold mining firms are ranked based on their market capitalization in this study. The following table (Table 1)

shows the world-top gold mining firms versus AngloGold.

Table 1: World-top Gold Mining Firms versus AngloGold

Company Market Capitalization Production

Tones Headquarters

(USD Billion) (Fiscal Year 2012.)

Barrick Gold 49.0 210.4 Canada

Goldcorp

39.0 67.93 Canada

Newmont Mining

29.09 141.1 United State

Newcrest Mining 26.0 58.77 Australia

Kinross Gold 11.5 74.2 Canada

Eldorado Gold 10.59 18.69 Canada

AngloGold Ashanti 16.7 111.8 South Africa

Source: Freeport-McMoRan 2012 Annual Report (2013)

In order to investigate the relationship between the determinants of capital structure and leverage ratio, a single model is

defined (equation 1):

Leverage = F (Non-Debt Tax Shield, Profitability, Risk, Size, Tangibility, Growth) (1)

The dependent and independent variables of above equation are defined in the following table (Table 2):

Table 2: Variables Description Variables Description

Leverage Total debt divided by total assets

Non-debt Tax Shield (NDTS) Depreciation and depletion divided by total assets

Profitability (PROFITABILITY) Earnings before interest and tax (EBIT) divided by total assets

Risk Level (RISK)

Firm Size (SIZE) Natural Logarithm of Firm Sales

Tangibility of Assets (TANGIBLITY) Fixed assets divided by total assets

Growth Opportunities (GROWTH)

3 Empirical Analysis

In this section, the empirical findings of our research regarding the determinants of capital structure are presented.

3.1 Pearsons Correlation Analysis

Pearsons correlation matrix is helpful for recognizing the presence of multi-collinearity among explanatory variables in

order to avoid misleading results. In this study, for both samples Pearsons correlation analysis are done for independent

variables and the results are shown in the Table 5 and Table 6. Through the first sample (world-top gold mining

companies) as it was expected the highest correlation level exists between D (tangibility) and D (NDTS) (0. 4352). This

correlation can be interpreted that higher tangibility of assets occurs in the firms with increase in level of non-debt-tax-

shield. On the other hand, the lowest correlation coefficient in first sample (world-top gold mining companies) shows the

relationship between D (tangibility) and D (size). Based on this relationship, size of revenue and tangibility of assets are

not associated with each other significantly. In addition investigation on second sample (AngloGold) shows that, the highest

correlation level is found between D (size) and D (growth); which proofs that large size of revenue occurs in African gold

mining company with increase in level of growth opportunity. In contrast the lowest level of correlation is defined

between D (growth) and D (risk), which says that change in level of growth opportunity does not affect the level of risk in

African gold mining company, significantly. The other results of correlation analysis in both samples are following a

normal behavior.

3.2 The Estimates of OLS Regression Model

As independent variables vary in their stationary levels, different equations are used to formulate the model:

AngloGold

( )

( ) ( ) ( ) ( ) ( )

World-top

( ( ))

( ) ( ) ( ) ( ( )) ( )

( )

The outcomes of regression models for AngloGold and world-top firms are shown in the Table 3 and 4, respectively.

Table 3: Estimations of OLS Regression Model for AngloGold

Variable Coefficient Std. Error t-Statistic Prob.

DNDTS 1.606513 0.484794 3.313802 0.0016

DPROFITABILITY -0.322698 0.073199 -4.408484 0.0000

DRISK -0.003278 0.002310 -1.419085 0.1610

DSIZE 0.007653 0.025329 0.302135 0.7636

DTANGIBLITY -0.131804 0.127477 -1.033940 0.3053

GROWTH -0.004600 0.005761 -0.798510 0.4277

C 0.002835 0.003483 0.814018 0.4189

R-squared 0.435465 Mean dependent var 0.003734

Adjusted R-squared 0.379011 S.D. dependent var 0.032508

S.E. of regression 0.025617 Akaike info criterion -4.392481

Sum squared resid 0.039375 Schwarz criterion -4.162140

Log likelihood 154.1481 Hannan-Quinn criter. -4.301334

F-statistic 7.713689 Durbin-Watson stat 1.993608

Prob(F-statistic) 0.000004

The OLS regression outcomes for AngloGold show that only non-debt tax shield and profitability are significantly

affecting the leverage ratio of AngloGold; where the coefficient of non-debt tax shield is positive and the coefficient of

profitability is negative. In addition, the R-squared of this regression shows that more than 43% of changes in leverage

ratio can be explained by these 6 independent variables.

The positive effect of non-debt tax shield intensifies the importance of tax shield for AngloGold in contrast to its world-

top competitors (shown in Table 4). This behavior of world-top firms is consistent with the findings of DeAngelo and

Masulis (1980) that tax deductibility of depreciation and tax credits can mutually cause to mitigate the benefits of debt

financing.

On the other hand, the effect of profitability on the leverage ratio is not only similar to the world-top firms, but also it is

consistent with the pecking order theory. Based on this theory, profitable firms tend to benefit from internal funds rather

than employing external funds (Myers, 1984).

Table 4: Estimations of OLS Regression Model for World-Top Gold Mining Firms

Variable Coefficient Std. Error t-Statistic Prob.

DGROWTH 0.022361 0.010831 2.064528 0.0419

DNDTS 0.049086 0.111700 0.439443 0.6614

DPROFITABILITY -0.081679 0.032497 -2.513469 0.0138

DRISK 0.000196 8.74E-05 2.240853 0.0275

DTANGIBLITY 0.017355 0.009886 1.755551 0.0826

DDSIZE -0.103444 0.029901 -3.459491 0.0008

C 0.000343 0.010681 0.032138 0.9744

R-squared 0.224163 Mean dependent var 0.000646

Adjusted R-squared 0.171860 S.D. dependent var 0.113111

S.E. of regression 0.102934 Akaike info criterion -1.639341

Sum squared resid 0.942987 Schwarz criterion -1.452357

Log likelihood 85.68835 Hannan-Quinn criter. -1.563759

F-statistic 4.285809 Durbin-Watson stat 2.537527

Prob(F-statistic) 0.000769

The OLS regression outcomes for World-Top gold mining firms show that growth, profitability, risk, tangibility and size

are statistically significant. The growth opportunities and tangibility of assets of these firms have positive impacts, while

the size of the firms, their risk level and their profitability negatively affect the leverage ratio. However, the coefficient of

risk is almost zero, so its impact is not considerable. In addition, as R-squared shows, more than 22% of changes in

leverage ratios of these firms are explained by the independent variables.

As world-top gold mining firms may have a better access to financing resources, an increase in size of these firms affects

the leverage ratio negatively. Moreover, the positive impact of growth opportunities and tangibility of assets on the

leverage ratio demonstrates the presence of a positive signal for creditors.

Table 5: Correlation Matrix Results for Anglogold

GROWTH D(NDTS) D(PROFITABILITY) D(RISK) D(SIZE) D(TANGIBLITY)

GROWTH 1.000000

D(NDTS) -0.075355 1.000000

D(PROFITABILITY) 0.001162 0.107846 1.000000

D(RISK) 0.156596 -0.337579 -0.265636 1.000000

D(SIZE) 0.404042 0.114517 0.058657 0.301332 1.000000

D(TANGIBLITY) 0.007516 -0.189385 0.235069 -0.537610 -0.124662 1.000000

Table 6: Correlation Matrix Results for World-Top Gold Mining Firms

D(GROWTH) D(NDTS) D(PROFITABILITY) D(RISK) D(D(SIZE)) D(TANGIBLITY)

D(GROWTH) 1.000000

D(NDTS) -0.199791 1.000000

D(PROFITABILITY) 0.206564 -0.284182 1.000000

D(RISK) -0.406828 -0.022940 0.077626 1.000000

D(SIZE) 0.154432 0.096918 0.103024 0.149529 1.000000

D(TANGIBLITY) -0.067823 0.435292 0.063054 0.005091 0.004329 1.000000

4 Conclusions

The significant determinants of capital structure in case of AngloGold are consisted of profitability and non-debt tax

shield, while profitability, size, tangibility of assets and growth opportunities are the significant determinants of capital

structure in the world-top gold mining firms. Therefore, as the first main finding, only profitability has the same impact

on the leverage ratios of both samples. The negative relationship between profitability and leverage ratio is mentioned in

the studies of Titman S, Wessels R. (1988), Rajan RG, Zingales L. (1995), Biger N et al. (2008).

On the other hand, the second main finding of this study shows that other significant determinants of capital structure are

different in each sample. This issue may be related to the firm such as creditworthiness of company and management

priority or to some other reasons such as accessibility of funding resources, geopolitical circumstances.

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