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Archives of Business Research – Vol. 9, No. 9
Publication Date: September 25, 2021
DOI:10.14738/abr.99.10094. Nyamita, M. O., & Dorasamy, N. (2021). The Drivers of Debt Financing Within State-Owned Corporations in South Africa. Archives
of Business Research, 9(9). 240-257.
Services for Science and Education – United Kingdom
The Drivers of Debt Financing Within State-Owned Corporations
in South Africa
Micah Odhiambo Nyamita
Lecturer
Tom Mboya University College, P.O. Box 199, 40300 Homa Bay Kenya
Prof. Nirmala Dorasamy
Professor: Public Administration
Department of Public Management and Economics
Faculty of Management Sciences, Durban University of Technology
41-43 M L Sultan Road, Durban, 4001, P.O. Box 1334, Durban 4000
South Africa
ABSTRACT
The public sector financial management reforms being adopted by many countries,
such as South Africa, have encouraged the adoption of private-sector management
style, such as debt management, within the state-owned corporations. The reform
agenda on debt financing is that state-owned corporations should face competitive
conditions regarding access to finance. To highlight on the achievements of these
reforms, this study explored the questions as to whether the drivers of debt
financing within state-owned corporations in South Africa are similar to those of
private-sector corporations. Applying a hybrid of cross sectional and longitudinal
quantitative surveys, a panel data regression model was used to analyse data from
26 income-generating state-owned corporations in South Africa for the eight-year
period 2007-2014 using the generalized method of moments (GMM). The results
identified the main determinants of debt financing within the state-owned
corporations in South Africa to include asset tangibility, corporation’s growth and
liquidity.
Keywords: Debt financing, State-owned corporations, Debt management, Public financial
management, drivers of debt financing
INTRODUCTION
State-owned corporations are believed to be less efficient than their private counterparts
(Ramstetter & Ngoc, 2013, p. 28). The managers of state-owned corporations are constantly
tempted to base decisions, including debt financing, on political rather than market criteria, and
strategic state investment may be misdirected because of simple miscalculation ((Fukuyama,
1995, p. 96); (MacCarthaigh, 2011, p. 215)). The financing decisions of state-owned
corporations are unique compared to the private-sector corporations. The decisions are made
by the Chief Executive Officers (CEO) with technical advice from the finance managers or
officers. If the intended borrowing involves a large amount, then the financing strategy must be
approved by the Board of Directors or the Cabinet Secretary or Minister in charge of the state- owned corporation ((Palcic & Reeves, 2013, p. 121); (OECD, 2005, p. 21)).
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Nyamita, M. O., & Dorasamy, N. (2021). The Drivers of Debt Financing Within State-Owned Corporations in South Africa. Archives of Business Research,
9(9). 240-257.
URL: http://dx.doi.org/10.14738/abr.99.10094
Most state-owned corporations get their financial resources from foreign governments, from
the private sector, from the revenue generated internally and from their own governments in
the form of bona fide loans (Gantt & Dutto, 1968, p. 115). In addition to these sources of finance,
some of them also get central government or international grants which they treat as increase
in equity. The financing practice of state corporations also varies from one country to another
and from one corporation to another. Adamolekum (1999, p. 40), argued that financing within
state-owned corporations has also been a critical issue in most countries, particularly because
of the strong linkage between finance and autonomy. This study therefore, attempted to
identify the major drivers of debt financing within state-owned corporations in a developing
country like South Africa.
In South Africa, public-sector management reforms towards a responsive, accountable and
transparent state, including the state-owned corporations, were declared by the African
National Congress (ANC) leadership about a decade ago (Wenzel, 2007, p. 50). However,
Wenzel (2007, p. 50) argued that, in practice, anticipation is narrowed to consultation or simply
information dissemination and propaganda. He observed that the shift from a traditional
bureaucratic model to the market model of governance, including debt financing, was based on
the belief that private-sector financial-management methods are generally superior.
Further, the public sector financial management reforms, being adopted by many countries,
such as South Africa, have encouraged the adoption of private-sector management style, such
as debt management, within the state-owned corporations (Koppell, 2007, p. 255). The reforms
are geared towards the improvement of financial performance of state-owned corporations
from emerging economies, like South Africa. The reform agenda on debt financing is that state- owned corporations should face competitive conditions regarding access to finance (OECD,
2005, p. 21). Their relations with state-owned banks, state-owned financial institutions and
other state-owned companies should be based on purely commercial grounds. The state-owned
corporations should further be subject to the same high quality accounting and auditing
standards as listed companies. To achieve the objectives of these reforms, this study explored
the questions as to whether the drivers of debt financing within state-owned corporations in
South Africa are similar to those of private-sector corporations.
LITERATURE REVIEW
Theories of debt financing
In one of his early studies, Myers (2001, p. 81) argued that there is no universally accepted
theory of debt-equity choice and there is no reason to expect one. Nevertheless, he assents to
the fact that there are a number of conditional theories which have been established. The
accepted theories start with the celebrated capital structure irrelevance proposition by
Modigliani and Miller (1958, p. 268), developed in 1958. They argued in their first proposition
that the market value of any firm is independent to its capital structure and is given by
capitalizing its expected return at the rate appropriate to the risk class. Simply put, the debt
financing level of the firm has no effect on the value of the corporation. The proposition was
theoretically very sound but was based on the assumptions of perfect capital market and no tax
world, which are not valid in reality.
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The Modigliani and Miller paper inspired serious research dedicated to challenging the
irrelevance proposition as a matter of theory or as an empirical matter. These consequential
researches have shown that the Modigliani–Miller theorem does not apply under a selection of
conditions (Frank & Goyal, 2005, p. 140). The most frequently adopted conditions include
consideration of taxes, transaction costs, bankruptcy costs, agency conflicts, adverse selection,
lack of division between financing and operations, time-varying financial market opportunities,
and investor clientele effects.
Since so many different conditions that may affect debt financing levels within a corporation
are available, it is not surprising that many different theories have been proposed after the
Modigliani and Miller proposition. Most corporate finance literature point to the “trade-off
theory”, in which taxation and deadweight bankruptcy costs are taken into consideration
(Frank & Goyal, 2009, p. 1). Myers (1984, p. 581) proposed the “pecking-order theory” in which
there is preference of retained earnings, debt and then equity. Frank and Goyal (2009, p. 1)
argued that the idea that firms engage in “market timing” has also become popular, especially
for publicly-traded corporations. Finally, the “agency theory” lurks in the background of much
of the theoretical discussion. Agency concerns are normally included in the trade-off
framework when deduced broadly. Each theory, however, has tried to explain the reasons
behind the choice between debt financing and other forms of financing within corporations.
Drivers of debt financing
There are extensive studies on factors influencing debt financing within private-sector
corporations. However, very few or none has been applied entirely on state-owned
corporations, more so from Kenya. The few studies, such as Majumdar and Chhibber (1999, p.
291); Dewenter and Malatesta (2001, p. 320); King and Santor (2008, p. 2426); Huang and Song
(2006, pp. 16-17) and Lim (2012, p. 191), that have attempted to look at the factors influencing
debt-financing decisions within state-owned corporations, have only concentrated on stock
exchange-listed corporations, which included some state-owned corporations which are listed
in the stock exchange.
The empirical results from most studies on private-sector corporations have identified
different factors depending on the industry and the economic environment of the country
(Mokhova & Zinecker, 2014, p. 534). The previous studies have identified the specific factors of
corporations, such as profitability, corporation size, asset tangibility, corporation growth,
corporation risk, corporation tax, liquidity, probability of bankruptcy and corporation age. In
addition, macroeconomic factors, such as gross domestic product, inflation and interest rates,
have also been identified as factors influencing debt-financing decisions within corporations.
Profitability
Some studies have identified that profitability influences debt-financing decisions negatively
within corporations, under the pecking order theory (Baltacı & Ayaydın, 2014, p. 54; Bassey,
Arene, & Okpukpara, 2014, p. 43; Lemma & Negash, 2013, p. 1083; Moosa & Li, 2012, p. 10).
Other studies also identified a positive influence of profitability on debt-financing decisions
within corporations, in support of the trade-off theory (Chakraborty, 2013, p. 117;
Gungoraydinoglu & Öztekin, 2011, p. 1467; Kouki & Said, 2012, p. 221).
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Nyamita, M. O., & Dorasamy, N. (2021). The Drivers of Debt Financing Within State-Owned Corporations in South Africa. Archives of Business Research,
9(9). 240-257.
URL: http://dx.doi.org/10.14738/abr.99.10094
Corporation size
Further, in line with the trade-off theory, many studies have identified corporation size to have
a positive influence on debt financing of corporations (Baltacı & Ayaydın, 2014, p. 53; Bassey et
al., 2014, p. 44; Dang, 2013, p. 180; Forte, Barros, & Nakamura, 2013, p. 362; Jõeveer, 2013, p.
306; Kouki & Said, 2012, p. 221). Some studies also observed a negative influence of corporation
size on debt financing of corporations, confirming the proposition of the pecking order theory
(Chakraborty, 2013, p. 118; Gaud, Hoesli, & Bender, 2007, p. 206; Majumdar 2012, p. 21; Smith,
2012, p. 144).
Asset tangibility
The pecking order theory recognizes a negative relationship between the asset tangibility and
debt-financing level, whereas the trade-off theory supports a positive one (Baltacı & Ayaydın,
2014, p. 50). Some studies like Smith (2012, p. 144); Dang (2013, p. 179); Drobetz,
Gounopoulos, Merikas, and Schröder (2013, p. 51); Lemma and Negash (2013, p. 1104);
Antonczyk and Salzmann (2014, p. 145) and Bassey et al. (2014, p. 44) have reported a positive
relationship between tangibility and debt financing. Other studies, like Öztekin and Flannery
(2012, p. 107); (Kouki & Said, 2012, p. 222); Lemma and Negash (2013, p. 1104); Jõeveer (2013,
p. 306) and Baltacı and Ayaydın (2014, p. 54), reported a negative relationship, especially when
more than one measure is used for debt-financing levels.
Corporation growth
The expected theoretical relationship between corporation growth opportunities and debt is
negative in line with the trade-off and agency theories since the growth of corporations
increases financial distress and the agency costs of debt (Deesomsak, Paudyal, & Pescetto, 2004,
p. 393). Most observations have supported the negative relationship between a corporation’s
growth opportunities and its debt financing level (Chakraborty, 2013, p. 117; Dang, 2013, p.
180; Lemma & Negash, 2013, p. 1104; Mateev, Poutziouris, & Ivanov, 2013, p. 43). On the other
hand, some observations, like Cortez and Susanto (2012, p. 129); Forte et al. (2013, p. 362);
Alzomaia (2014, p. 61); Antonczyk and Salzmann (2014, p. 145) and Bassey et al. (2014, p. 44),
have shown a positive relationship.
Corporation risk
Studies, like Lim (2012, p. 197); Drobetz et al. (2013, p. 51); Forte et al. (2013, p. 364); Alzomaia
(2014, p. 61) and Baltacı and Ayaydın (2014, p. 54), have found a negative relationships
between corporation risk and debt financing. On the contrary, Gaud, Jani, Hoesli, and Bender
(2005, p. 63); Foster and Young (2013, p. 7) and Lemma and Negash (2013, p. 1109)found both
positive and negative relationships when they used different measures of debt-financing level.
Corporation tax
Few studies that have found some reasonable results for taxation, like Huang and Song (2006,
p. 32); Antoniou, Guney, and Paudyal (2008, p. 73); De Jong, Kabir, and Nguyen (2008, p. 1961);
Foster and Young (2013, p. 6) and Jõeveer (2013, p. 306), have established a negative
relationship. Conversely, Antonczyk and Salzmann (2014, p. 146), studying corporations across
different countries, identified a positive relationship and Lemma and Negash (2013, p. 1104)
observed both a positive relationship, for some countries in Africa, and a negative relationship
for others within the continent.
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Liquidity
Empirically, studies such as Deesomsak et al. (2004, p. 398); Smith (2012, p. 157) and Mateev
et al. (2013, p. 43) confirmed the expected negative theoretical relationship between liquidity
and debt financing of corporations. On the contrary, Gungoraydinoglu and Öztekin (2011, p.
1467), looking at some new international evidence, found a positive relationship between
liquidity and debt financing.
Non-debt tax shield
Studies, such as Cortez and Susanto (2012, p. 130); Lim (2012, p. 197) and Lemma and Negash
(2013, p. 1105), found a negative influence of non-debt tax shield on debt financing of
corporations. On the contrary, studies like Kouki and Said (2012, p. 221); Chakraborty (2013,
p. 117); Dang (2013, p. 179) and Antonczyk and Salzmann (2014, p. 145), found a positive
relationship between non-debt tax shields and debt financing.
Probability of bankruptcy
Trade-off hypothesis predicts a negative relationship between probability of bankruptcy and
debt financing (Kayo & Kimura, 2011, p. 360). Justifying this hypothesis, Smith (2012, p. 160)
found a negative relationship using total debt to total assets as a measure of debt financing
level, while Gaud et al. (2005, p. 63) and Kouki and Said (2012, p. 221) found a positive
relationship in support of the pecking order theory of debt financing (Titman & Wessels, 1988,
p. 6).
Gross domestic product
Most studies on macroeconomic factors of debt financing have found statistically significant
results between the gross domestic products (GDP) of countries and the debt-financing levels
of corporations. Good examples are De Jong et al. (2008, p. 1966); Gungoraydinoglu and Öztekin
(2011, p. 1467) and Baltacı and Ayaydın (2014, p. 54) which found a statistically significant
positive relationship between the GDP and corporations’ debt financing levels. In contrast, Kayo
and Kimura (2011, p. 367); Drobetz et al. (2013, p. 67) and Jõeveer (2013, p. 306) also found
statistically significant results but with a negative relationship.
Inflation rate
The empirical results of the inflation rate have not been consistent (Mokhova & Zinecker, 2014,
p. 533). Literature reviewed by Gungoraydinoglu and Öztekin (2011, p. 1467); Drobetz et al.
(2013, p. 67); Jõeveer (2013, p. 306); Antonczyk and Salzmann (2014, p. 146) and Baltacı and
Ayaydın (2014, p. 54) found a negative relationship between inflation and debt financing. On
the other hand, Frank and Goyal (2009, p. 26) found a positive relationship, in contrast to the
above hypothesis.
Interest rates
Few studies have found any statistically significant relationships between interest rates and
debt financing. Antoniou et al. (2008, p. 32) and Mokhova and Zinecker (2014, p. 534) found a
negative relationship while studying the macroeconomic factors of debt financing levels of
corporations of European countries.
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9(9). 240-257.
URL: http://dx.doi.org/10.14738/abr.99.10094
Other factors
Other studies have attempted to find observations on other factors which have not been
frequently studied. For instance, Welch (2004, p. 120); Frank and Goyal (2009, p. 14) and
Baltacı and Ayaydın (2014, p. 53) found a positive relationship between the industry’s mean
debt financing level with the corporation’s debt-financing level. De Jong et al. (2008, p. 1965)
found a positive relationship between financial institutions’ development and corporations’
debt financing, while Kayo and Kimura (2011, p. 367)found a positive relationship between the
two. Smith (2012, p. 155) and Bassey et al. (2014, p. 44) also observed a negative relationship
between the corporation’s age and its debt financing level, which is consistent with the
theoretical expectation of the pecking order theory of debt financing. Jõeveer (2013, p. 306)
incorporated the corporation’s corruption perception index in his study and found that it was
positively related to the corporation’s debt financing level.
METHODOLOGY
The study applied a hybrid of cross sectional and longitudinal quantitative surveys. Rindfleisch,
Malter, Ganesan and Moorman (2008: 276), in their study of cross-sectional versus
longitudinal, argued that both the designs have limitations and a combination will give a strong
output. Therefore, the combination of the techniques allowed the researcher to analyse data
across state-owned corporations and also over a period of eight years from 2007 to 2014.
The population of this study was defined in terms of the number of state-owned corporations
established by the Acts of Parliament in South Africa. The population frame data was from the
official website of the Department of Government Communication and Information System of
Republic of South Africa. According to this data, there are 128 established state corporations in
South Africa, out of which 26 are income-generating corporations (State-owned corporations).
Hence, the target population for this study was made up of the 26 income-generating state
corporations in South Africa as at 31st December 2014.
The sample size for the study is made up of all the 26 income-generating corporations, selected
from the general population using the stratified non-probability sampling technique. The non- income generating corporations are excluded from the study, since their financial performance
is not profit based and may not be influenced by market-oriented decisions, such as debt
financing strategies. Struwig and Stead (2013, p. 116) argued that the non-probability sampling
technique should be used in special cases, usually when the population has much in common,
like the case of income-generating state corporations.
The study used the information from the financial statements to measure the study variables
across the state-owned corporations. In addition, ratio analysis was used to measure the
variables from the financial statements over the eight-year period. Most of the study variable
measures were extracted from the financial statements of the state-owned corporations for the
eight-year period 2007-2014 and the macroeconomic variables were collected from the World
Bank country data. The financial statements were collected from the official websites of the 26
targeted state-owned corporations.
In the identification of drivers of debt financing, the study used a multiple-linear panel-data
regression model 1, which has been applied by most studies such as Gungoraydinoglu and
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Öztekin (2011, p. 1461); Cortez and Susanto (2012, p. 128); Lim (2012, p. 196); Moosa and Li
(2012, p. 7); Smith (2012, p. 146); Chakraborty (2013, p. 113); Drobetz et al. (2013, p. 59);
Lemma and Negash (2013, p. 1092); (Alzomaia, 2014, p. 62) and (Bassey et al., 2014, p. 41). The
applied multiple regression panel data model is of the form:
��� = �� + ∑ ������
�
�'� + ��� + ���.....................................................................................1
Where ��� is a measure of debt financing (financial leverage) of firm � in year � and �
represents the measure of independent variables (firm specific drivers and macroeconomic
drivers). � represents unobserved factors (either firm-specific or macroeconomic) and �) is
the constant. � form � = 1 �� � are unknown parameters to be estimated. The measure of
independent variables � includes � factors which are the total number of all factors influencing
debt financing observed in this study. The independent variables and their respective measures
are given in table 3.1. The independent variables include both the firm-specific drivers and
macroeconomic drivers. In addition, to establish the significance of the variables in each of the
regression models, the t-test was applied at 90%, 95% and 99% levels of confidence.
The common regression model estimator, from the reviewed literature, appears to be the
pooled ordinary least squares (Guthrie & Olson) method and the generalized method of
moments (GMM). However, this study estimated the coefficients of multiple regression models
1 above, using the independent and dependent variables of the study, through the GMM system
panel regression model. According to Bond (2002, pp. 141-142), panel data models have an
advantage over pooled ordinary least squares (Guthrie & Olson) model since the former
incorporates the cross-sectional and longitudinal variables of the model. The panel data
advantages over pooled ordinary least squares (Guthrie & Olson), therefore, include the
possibility that underlying microeconomic dynamics (heterogeneity) may be concealed by
pooling biases, and the scope panel data offers to investigate heterogeneity in adjustment
dynamics between different types of individuals, household or corporations.
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Nyamita, M. O., & Dorasamy, N. (2021). The Drivers of Debt Financing Within State-Owned Corporations in South Africa. Archives of Business Research,
9(9). 240-257.
URL: http://dx.doi.org/10.14738/abr.99.10094
common practice amongst the state-owned corporations in South Africa, with some state- owned corporations having a total debt being eight times more than the total assets (insolvent).
On the other hand, table 4.1 also shows that the use of long-term debt, with a mean of 0.37,
makes more than half of the total debt. The minimum value (0.00) of long-term debt indicates
that there are some state-owned corporations in South Africa which use only short-term debt
as a form of debt financing.
Correlation analysis
Table 4.2 presents the Pearson correlation coefficients (�) for the panel data regression analysis
variables used in the study. Table 4.2 presents all variables used in the identification of the
drivers of debt financing within the state-owned corporations in South Africa. The table shows
that the total debt leverage (TDL), long-term debt leverage (LDL) and short-term debt leverage
(SDL), which are measures of debt-financing, have a significant strong positive correlation
(0.942, 0.973 and 0.514 respectively) with the tangibility of state-owned corporations in South
Africa. This indicates that state-owned corporations with more tangible assets tend to have
more of debt financing, both long-term and short-term debts, since tangible assets can be used
as collateral for the acquired debt.
On the other hand, table 4.2 shows a significant positive correlation between the measures of
debt financing (TDL, LDL and SDL) and state-owned corporation’s growth, i.e. -0.364, -0.369
and -0.226 respectively. This implies that as state-owned corporations grow, the level of their
debt financing tend to reduced, but at a low rate. Further, the correlation analysis results also
highlight a significant negative correlation between all the three debt financing measures (TDL,
LDL and SDL) and liquidity level of state-owned corporations, i.e. -0.256, -0.165 and -0.459
respectively. This also indicates that state-owned corporations which are liquid enough tend to
have slightly low levels of debt financing, both long-term and short-term.
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