JGED Volume 1 Issue 1 · 2015. 10. 20. · 4 Journal of Green Economy and Development, Volume 1,...

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Executive Committee

Tidings Ndhlovu – Chair

Ahmed C. Bawa

Pantaleo DM Rwelamila

Pumela Msweli

Editorial Team

Pumela Msweli: Editor-in-Chief

Tidings Ndhlovu: Associate Editor Pantaleo DM Rwelamila: Associate Editor

Tracey Greyvenstein: Conference Administrator

Editorial Review Board

Prof Aziakpono, M., University of Stellen-bosch, SA

Prof Balkaran, K., Durban University of Technology, SA

Prof Bbenkele, E.K., University of Johan-nesburg

Dr Cameron, J., Erasmus University Rotter-dam, Netherland

Prof Chipunza, C., Central University of Technology, SA

Prof Dzansi, D., Central University of Tech-nology, SA

Dr B Dzwairo, Durban University of Tech-nology

Prof El-Said, H., MMU Business School, UK

Prof Gqaleni, N., Durban University of Technology

Prof Dima Jamali, University of Beirut

Prof Jolayemi, J., Tennessee State Universi-ty, US

Prof Kaehler, J., Institute of Economics, Er-langen University, Germany

Prof Khomo, T.M., University of Limpopo, SA

Dr Lazarus, I. Durban University of Technol-ogy

Mr Marwa, N., Stellenbosch University, SA

Prof Mbatha, C.N., University of South Africa Prof Moyo, S., Durban University of Tech-nology, SA

Dr Moyo, T., University of Limpopo, SA

Prof Mtapuri, O., University of KwaZulu-Natal, SA

Prof Mollel, N., University of Limpopo, SA

Prof Musvoto, W., North West University, SA

Prof Ndlovu-Gatsheni, S., University of South Africa

Prof Netswera, F., University of Limpopo, SA

Prof Ngcobo, S., Mangosuthu University of Technology, SA

Prof Ngwakwe, C., University of Limpopo, SA

Mr Nyandeni, R. HABI, South Africa

Ms Ntuli, N., Department of Trade & Industry

Prof Odeku, K., University of Limpopo

Dr Singh S. Unique Consulting, SA

Prof Steyn, R., University of South Africa

Artwork and Design

Enock Zungu

Web Design

Njinu Kimani

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Mission

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Journal of Green Economy and Development, Volume 1, Issue 1, 2015

From 2015 MDGs to 2030 Sustainble Development Goals: Is

South Africa ready for the challenge? An Editorial Note

Pumela Msweli

Reflections on Thomas Piketty’s Capital in the Twenty-First Cen-

tury: Inequality, Sustainable Development and Power Relations

Tidings P. Ndhlovu

The Impact of Capital Structure of Electricity Generation Projects

on Electricity Tariffs in Uganda

Vianney Mutyaba and Nyankomo Marwa

Non-Revenue Water Assessment Strategy for the Umzinto Water

Supply Schem: Towards Green Economy

James Magombo, Bloodless Dzwairo, Sibusiso Moyo, Mendon Dawa

Author Guidelines

Content

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This issue is published a few days after a

historical launch of the United Nations

2030 Agenda on Sustainable Develop-

ment. World leaders who attended the

Global Sustainability Summit on 25-27

September 2015 made a commitment to

implement a universal policy programme

to achieve 17 sustainable development

goals and 169 targets by 2030 (United Na-

tions, 2015). For developing countries

such as South Africa, the new agenda will

build on the policy infrastructure and work

put in place to achieve the United Nations’

2015 MDGs.

There are 53 globally designed MDG indi-

cators that South Africa adapted from the

UN official (UN 2015). Out of these indica-

tors targets related to nine indicators were

reported as unlikely to be achieved by

2015 (South Africa, 2015). This was at-

tributed to socio-economic backlogs, slow

economic growth, and high levels of ine-

quality (South Africa, 2013). Data deficien-

cy, as I have shown in Table 1, was rec-

orded in relation to primary education

(MDG 2), maternal health (MDG 5),

HIV/AIDS, malaria and other disease

(MDG 6), environmental sustainability

(MDG 7) and global partnerships (MDG 8).

Insufficient data further reduced South Africa’s

From 2015 MDGs to 2030 Sustainable Development Goals: Is South Africa ready for the challenge? An Editorial Note

Pumela Msweli Durban University of Technology E-mail: [email protected]

Abstract This paper describes the salient features of the United Nations 2030 Agenda on Sustainable Devel-opment; how these features compare to the 2015 millennium development goals (MDGs); and the implications thereof for South Africa. There are 53 globally designed MDG indicators that South Africa adapted from the UN official list of MDG indicators. The key difference between the eight MDGs and the newly established 17 sustainable development goals (SDGs) lie in the scope and applicability of these two goals. While the 2015 MDGs focused mainly on the social agenda, SDGs integrate social, economic and environmental goals, and recognise the interlinkages between these dimensions. Moreover, SDGs are applicable to both rich and poor countries, irrespective of the development sta-tus. Out of 53 MDG indicators, targets related to nine indicators were reported as unlikely to be achieved by 2015. This was attributed to socio-economic backlogs, slow economic growth, and high levels of inequality in South Africa. Data deficiency was recorded in relation to primary education (MDG 2), maternal health (MDG 5), HIV and Aids, malaria and other diseases (MDG 6), environmen-tal sustainability (MDG 7) and global partnerships (MDG 8). Insufficient data, further reduced South Africa’s capacity to achieve the MDGs. Pro-poor policies that saw the country halving the amount of people living below $1 a day (ppp) have neither dented the levels of inequality, nor increased growth. The new agenda for 2030 challenges South Africa first, to accelerate research processes to develop baseline data to capture, monitor and evaluate the newly launched sustainable development agenda; and to closely interrogate the relationship between development, growth and inequality.

© Pumela Msweli, 2015

mailto:[email protected]

6


capacity to achieve the MDGs. If eight

MDGs could not all be achieved after a fif-

teen-year period, what is the likelihood of

achieving double the amount of goals and

more than quadruple the amount of tar-

gets, as envisaged in the 2030 sustainable

development agenda?

A pessimistic view would hold that given

the country’s underperformance with a few

MDG dimensions, notably, inequality in its

various forms, economic growth, unem-

ployment and environmental sustainability

targets, the 169 targets would be out of

reach. In this paper I present the pessimis-

tic and an optimistic view going forward.

I present my argument in two sections.

First, I describe the salient features of the

2030 Sustainable Development global

agenda and how it compares to the 2015

MDGs and implications for South Africa. In

the second section I present evidence that

highlights a number of reasons to support

an optimistic outlook going forward.

I conclude by pointing out peculiar risks

that the country faces and offer a re-

search agenda going forward.

From 2015 MDGs to 2030 SDGs:

Implications for South Africa

Figure 1 depicts the new sustainable

development goals. The key difference

between the goals lies in the scope and

applicability of the two sets of goals.

While the 2015 MDGs focused mainly

on the social agenda, SDGs integrate

social, economic and environmental

goals, and recognise the inter-linkages

between these dimensions.

There are six key points to take away

from the comparison above. First, some

of the targets and indicators from the

2015 MDGs have been broadened and

reclassified as goals. For example, clean

water and sanitation, slum dwellers, and

issues related to life in water, were sus-

tainability indicators (MDG7).

Millennium Development Goals

MDG Indicators

Total Indi-cators re-lated to each MDG

Achievability by 2015 Data defi-ciency

Achieved Likely Unlikely

MDG1: Eradicate poverty 14 5 5 4 0

MDG2: Primary education 2 0 1 0 1

MDG3: Gender equality 6 3 2 1 0

MDG4: Reduce child mortality 3 0 3 0 0

MDG 5: Maternal health 6 1 0 0 5

MDG6: HIV/AIDS, Malaria 11 5 2 2 2

MDG7: Environmental sus-tainability

9 1 2 1 5

MDG 8: Global partnerships 2 0 0 0 2

Total 53 15 15 9 15 Source: Generated by author using data from Republic of South Africa MDG 2013 Country Report

Table 1: South Africa’s MDG indicators and achievability

7

These indicators have been broadened

and reclassified as sustainable develop-

ment goals (SDG6, SDG11 and SDG14).

Another case in point is poverty eradication

(MDG1). Here we have a goal that had a

combination of social and economic indica-

tors. However, post the MDG era, we see

specific sustainable goals that have a

bearing on the economy. These include

SDG8 (decent work and economic growth),

SDG9 (Industry innovation and infrastruc-

ture), reduced inequality (SDG10), and af-

fordable and sustainable modern energy

(SDG7).

Secondly, the environmental sustainability

dimension of the 2015 MDGs has been

expanded substantially to include access

to clean, affordable and modern sources of

energy (SDG7), responsible consumption

and production (SDG12), and climate

change (SDG13).

Thirdly, the only time the words “urgent

action” have been used is in relation to

climate change (SDG13).Fourthly, dis-

ease and health related Issues (MDG 4,

MDG5, and MDG6) have been reshaped

to include well-being “for all, at all ages”.

Fifthly, infrastructure development has

been made more prominent in SDG16.

The manner in which this goal is stated

proposes an agenda to accelerated indus-

trialisation, innovation and a need to de-

velop skilled human capital to operate in a

modern economy. Lastly, the 2030 agen-

da introduces a new dimension that cap-

tures issues around peace and govern-

ance and (MDG 16). The 2015 MDG

agenda did not address peace, justice,

governance and accountability. The ques-

tion is how ready is South Africa to take

on this new global agenda? What are the

implications of post MDG agenda for

South Africa?

Figure 1: An illustration of the United Nations 2030 Agenda for Sustainable Develop-

ment

1 No poverty

2 Zero Hunger

3 Good Health and Wellbe-

ing

4 Quality Edu-

cation

5 Gender

Equality

6 Clean Water and Sanita-

tion

7 Affordable and Clean

Energy

8 Decent Work & Economic

Growth

9 Industry, Innovation and Infra-

structure

10 Reduced

Inequality

11 Sustainable Cities and Communi-

ties

12 Responsible Consump-tion and

Production

13 Urgent Cli-

mate Action

14 Life below

Water

15 Life on Land

16 Peace, Jus-tice and Strong Insti-

tutions

17 Partnerships

for the Goals

Sustainable Develop-

ment Goals

Source: United Nations 2015: http://www.un.org/apps/news/story.asp?NewsID=51968#.VguP0enZfdk


8


Going forward – an optimistic view Let us first look at environmental sustain-

ability, socio-economic infrastructure and

capacity to implement the 2030 agenda.

The Constitution of the Republic of South

Africa (Act 108, of 1996) sets the tone for

sustainable development in Chapter 2,

Section 24 (a) and (b). These sections

clearly state that the environment has to

be protected “for the benefit of present

and future generations, through reasona-

ble legislative and other measures that

prevent pollution and ecological degrada-

tion; promote conservation; and secure

ecologically sustainable development and

use of natural resources while promoting

justifiable economic or social develop-

ment”.

A battery of policies to give expression to

sustainability sentiments have been de-

veloped. These include the 2008 National

Energy Act, the Industrial Policy Plan of

2010, the 2013 Carbon Tax Policy, and

the 2014 Waste Management Act. The

socio-economic legislative framework is

even much more robust than is the case

with environmental sustainability. The in-

auguration of the new government in

1994 prompted development of a series

of policies to address the inequities of the

past.

The Reconstruction and Development

Programme (RDP) was among the first

set of policies to be introduced. Funda-

mentally, RDP was founded on the tenets

of the developmentalist vision of having

the state playing the leading role in the

reconstruction and development project.

However, two years down the line the

government changed its macro-economic

stance and implemented the Growth

stance and implemented the Growth,

Employment, and Redistribution (GEAR)

programme. In 2006, ten years after

GEAR was implemented the South Afri-

can government introduced the Acceler-

ated and Shared Growth Initiative for

South Africa (ASGISA). The wording

used in the ASGISA policy suggest that

the policy was inspired by the 2015

MDGs because it uses similar terminolo-

gy used in MDG1: “to halve the level of

poverty and unemployment by 2014 and

enable South Africa to achieve and sus-

tain high average economic growth…”

(ASGISA, 2006).

A year after ASGISA was implemented

the government adopted the National In-

dustrial Policy Framework (NIPF) with the

purpose of setting out an approach to in-

dustrialisation, almost pre-empting the

SDG 16 of the 2030 agenda. Implemen-

tation of the National Industrial Policy

Framework was set out in the Industrial

Policy Action Plan (IPAP1), which was

later revised to (IPAP2).

Shortly after the introduction of ASGISA

and the National Industrial Policy

Framework, the government launched

the New Growth Path (NGP) which lays

out a vision for a “more developed, dem-

ocratic, cohesive and equitable economy

and society… in the context of sustained

growth” (New Growth Path, 2009). The

NGP aims at using macro and micro

economic policies to support labour ab-

sorbing activities that result in the crea-

tion of millions of quality jobs, economic

growth and poverty eradication. In 2011

the National Development Plan was

adopted. The National plan sets out a vi-

sion and strategies to create 11 million

jobs by 2030, to eliminate poverty and

9


to reduce inequality by reducing the Gini co-

efficient from 0.69 to 0.6 by 2030 (NDP,

2011).

A pessimistic view

My observation is that South Africa is not

short of economic policies. It is quite clear

from the country MDG report that with all the

policies developed in the past twenty years

South Africa remains trapped in a low growth

trajectory with widening inequalities, low

country savings, limited supply of skilled hu-

man capital, lack of innovation and high un-

employment rate to count but a few factors

attributed to MDG under achievement (South

Africa, 2013).

As I have illustrated in Figure 2, South Africa

has the highest level of inequality in South-

ern Africa. The figures mask the gender, re-

gional and non-income disparities. The MDG

country report (2013) shows that while the

female to male literacy ratio is one, gender

disparity is more prominent in wage em-

ployment income. The source of the dispari-

ties are more visible in Figure 3 where I

show GDP per capita grouped by Province.

Eastern Cape is the poorest province in

South Africa in terms of GDP per capita, fol-

lowed by Limpopo. While Gauteng is the

smallest province in terms of geographical

space, it generates the largest amount of

GDP and has the highest GDP per capita

closely followed by the Western Cape.

The foregoing discussion points to in-

come inequality and economic growth as

the key issues to tackle in South Africa

going forward. Pro-poor policies that saw

the country halving the amount of people

living below $1 a day (ppp) have neither

dented the levels of inequality, nor in-

creased growth. The new agenda for

2030 calls for modernisation and accel-

erated industrialisation of the economy.

Going forward the country needs to close

the knowledge gaps that were prominent

in an attempt to capture, monitor and

evaluate MDG goals.

This can be done by making the 2030

sustainability development agenda a

broader, interdisciplinary priority that in-

cludes civil society, trade unions, private

sector, public sector, primary and higher

education sector. South Africa needs to

also meticulously unpack the relationship

between economic development, eco-

nomic growth and inequality. The rela-

tionship between growth and inequality is

complex because while inequality has

been found to have a negative impact on

growth it is also an essential component

of a functioning market economy as it

provides the incentives needed for eco-

nomic growth and investment.

Figure 2: Gini Coefficient of South Africa in comparison to selected Southern Afri-

can Countries

Source: World Bank 2013 Gini Index World Bank, http://data.worldbank.org/indicator/sl.POV.GINI.

http://data.worldbank.org/indicator/sl.POV.GINI

10


This complexity is manifested in a myriad

theoretical strands that depict different nu-

ances of the relationships between inequality

and growth. For example there are theoreti-

cal strands that show that inequality can

cause political and economic instability, con-

sequently reducing the pace of growth (Berg

and Ostry, 2011; Ostry, Berg, and Tsan-

garides, 2014). Another theoretical strand

emerging from literature is that, when wage

income lags behind GDP per capita, income

inequality widens (Van Zanden, Baten,

Foldvari and Van Leeuwen (2011). Following

the same line of thought, if wage income

grows faster than GDP per capita, income

inequality is likely to decline.

Milanovic (1995) on the other hand argues

that initial inequality can have a permanent

effect on a country’s growth. . Does this

mean that there are other avenues to tackle

inequality other than to look at economic

growth? Future research should explore this

question. Is it possible that in going through

the motions with the intricacies of economic

policy formulation South Africa is focusing

narrowly on solutions that will solve country’s

unique problems?

The reality is that South Africa is the only

country in World that has a Gini coefficient

in the 60s (see World Bank 2015).To move

forward the country might need to find solu-

tions from sources unexplored previously.

South Africa does not have sufficient hu-

man capacity to tackle the SDG goals nor

does it have sufficient resources to imple-

ment the goals. All the 17 goals are urgent.

South Africa might have to walk the mini-

malist approach called for in the sustaina-

bility discourse by replacing ‘urgent’ with

‘vital’. On the balance of evidence, eco-

nomic development appears to be urgent.

A focus on development rather than on

growth is likely to help the country achieve

the 17 sustainable development goals.

To introduce this new journal by reviewing

South Africa’s development successes and

challenges sets the context for the mission

and purpose of the Journal of Green Econ-

omy and Development. Theoretical contri-

bution and application of knowledge to

achieve sustainable livelihoods, and to pro-

tect ‘mother earth’ together with Her vari-

ous ecosystems will make us relevant in

the journey to sustainable development.

Figure 3: GDP per capita (2010, R million) by Province

Source: Statistics South Africa(2014)

http://www.statssa.gov.za/publications/P0441/P04413rdQuarter2014.pdf

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Acknowledgements

The founding of a journal and its subse-

quent progress depends on associate edi-

tors and reviewers who volunteer their

precious time to advance scholarship. I

take this opportunity to thank our Associ-

ate Editors and all our reviewers, as well

as our authors for their contribution to this

issue.

References

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Berg A.G. and Ostry J.D. (2011) ‘Inequality and Unsustainable Growth: Two Sides of the Same Coin?’ (online) Available: https://www.imf.org/external/pubs/ft/sdn/2011/sdn1108.pdf Retrieved: 4 November 2013

Milanovic B. (2005) ‘Worlds Apart’. Princeton University Press (online). Available: press.princeton.edu/Chapters/s7946.pdf. Retrieved: 13 September 2014

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http://data.worldbank.org/indicator/sl.POV.GINI

13

Whereas racist ideology was1 unquestiona-

bly present in the thinking of many classical

political economists of the time (Ndhlovu

and Khalema, 2015), this was not necessari-

ly the basic reasoning behind Carlyle’s

thinking. The best way to describe the posi-

tion adopted by Carlyle and other analysts

of a radical Tory persuasion by the mid-19th

century, is that it was not slavery per se they

advocated as their abhorrence of the direc-

tion that modern free market capitalism was

taking. For example, Carlyle went so far as

to advocate a return to serfdom as an alter-

native to the system prevailing. His key point

was to highlight that even something as gro-

tesque as serfdom or slavery was preferable

to free market capitalism based on princi-

ples of political economy. However, he had,

among many others, a real crisis of con-

science when the American Civil War erupt-

ed and the whole question of slavery be-

came a central issue.

1 © Tidings P Ndhlovu, 2015

Notwithstanding this, Carlyle’s epithet and

“world weariness” (Groenewegen, 2001: 74)

highlighted questions of inequality - whether

conceptualised in terms of choice and op-

portunity, technology and distribution, or

ownership and control of the means of pro-

duction and power relations between capi-

talist and worker. One reason why Karl

Marx, coming from the study of jurispru-

dence, became fixated with the study of po-

litical economy was the tendency to sepa-

rate economics from the role played by insti-

tutional structures in valuation, and he felt

that this field of study was devoid of any in-

stitutional compass. Latterly, one economist

who also did not subscribe to the view that

institutions had little place in economics was

the eminent British academic, John Maynard

Keynes (Ndhlovu and Cameron, 2013). Dur-

ing negotiations of the Bretton Woods

Agreement in 1943-44, his radical views

concerning “state regulation of capitalism”

(as the solution to a structural tendency to


Reflections on Thomas Piketty’s Capital in the Twenty-First

Century: Inequality, Sustainable Development and Power Rela-

tions

Tidings P. Ndhlovu1

Manchester Metropolitan University Business School

Visiting Research Fellow, Graduate School of Business Leadership, University of South Africa

E-mail: [email protected]

Abstract Professor Thomas Piketty’s impressive historical work, “Capital in the Twenty-First Century”, has raised many issues concerning inequality, the role of rentiers and “supermanagers”, while identifying “patrimonial capitalism” as the main cause of inequality. Increased marginal rates of taxation, amongst others, are seen as a way of ensuring redistributive social justice. This paper critically ex-amines Piketty’s enquiry on inequality from a political economy perspective, suggesting that the for-mer’s analysis is reformist rather than revolutionary. We point out to some problems concerning economic growth (industrialisation) and environmental protection, as well as Piketty’s inability to in-corporate structurally institutionalised power relations and class struggle into his analysis.

Key words: Inequality, Sustainable Development, Power Relations


14

economic depression) were listened to po-

litely but ultimately rejected in favour of Har-

ry Dexter White’s (a non-academic and

“practical economist” who was Assistant

Secretary to the US Treasury) plan that vir-

tually sealed the dominance of the more free

market institutional “American capitalism”

over emerging welfare state institutions of

“British capitalism”. It is also noteworthy

that, for Marx, inequality is a necessary pre-

condition of capitalism. In fact, the very na-

ture of the institutional control of the means

of production necessitates that the work-

force must be kept ‘elastic’ and subservient;

hence his famous dictum in The German

Ideology (Marx and Engels, 1989): “Philoso-

phers have only hitherto interpreted the

world in various ways: the point is to change

it”.

Greeted with media fanfare, the recent pub-

lication of Thomas Piketty’s Capital in the

Twenty-First Century sets out to interpret

the history of inequality by "draw[ing] from

the past a few modest keys to the future [re-

garding ‘changes’ in social organisation]”

(Piketty, 2014a: 35). Feted by the White

House and Nobel Laureates such as Pro-

fessor Robert Solow, Piketty has also been

described as having “entered rock stardom

– economist style” (Professor George Aker-

lof, another Nobel Prize Winner in Econom-

ics). Being routinely referred to as the “rock

star economist” (London Evening Standard)

or the “rock star of economics” (right-leaning

The Telegraph) is no mean feat, especially

for one hailing from the Left of “the dismal

science”; more so, one whose huge tome

runs to 685 pages! However, such praise

has been tinged with a stinging rebuke for

Piketty having the temerity to propose a

(Tobin) wealth tax (Heath, 2014). Presuma-

bly, this frightening spectre for the Right of

the political spectrum evokes former UK La-

bour Party Chancellor of the Exchequer

Denis Healey’s alleged nightmarish promise

to “squeeze the rich until the pips squeak”.

Ironically, Piketty’s first steps on his “Road

to Damascus” started with an article on

mathematical modelling in 1993 that was

steeped in Pareto Optimality, game theory

and Bayesian models of sustainable risk

taking. His transformation from mainstream

econometrician was complete when he be-

came economic advisor to then (in 2007)

French Socialist Party presidential candidate

Segolene Royal and later supported the

French (Socialist Party) President, Francois

Hollande. Indeed, Piketty now dismisses

mathematical models as often “no more

than an excuse for occupying the terrain and

masking the vacuity of the content”. It is to

this “content” that I will now turn my atten-

tion. What follows is an examination of the

implications of Piketty’s analysis for sustain-

able development and power relations.

The Content

Piketty’s (2014a) central concern is to pre-

vent a slide back to patrimonial (inheritance)

capitalism that occurred between the 18th

century and La Belle Epoque Europe in the

19th century. According to him, a few ren-

tiers who had inherited wealth and never did

a stroke of work dominated society. By the

time the First World War broke, 10 per cent

of the population in the USA owned 80 per

cent of capital, while the figure for Europe

stood at 90 per cent. Like Keynes, preserv-

ing capitalism and saving it from its worst

excesses is paramount in his mind. He is

also concerned that economic growth lags

behind returns on capital. In his quest to ex

plain the reasons behind this, he sets clear

blue water between what he actually means

by “capital” and the ideas of mainstream

economists, whilst seeking to distance him-

self from Marx’s analysis, especially since

the title of his book seems to mimic Karl

Marx’s (1977a: 1977b; 1977c) three vol-


15

umes of Capital: A Critique of Political

Economy. Let me refresh your memory, par-

ticularly on Marx who argued that the con-

cept of capital as an institutional relationship

was needed to understand the very founda-

tions of bourgeois society. It was the

wherewithal (relation to means of produc-

tion) by which the dominant class uneasily

imposed their power and authority to extract

surplus value from the working class. In this

sense, capital took many varied forms, start-

ing with money (moneyed wealth) which, in

turn, is used to purchase machines etc. and

to hire labour power (and thus could either

be constant or variable capital), through the

production of commodities. Thus for Marx,

capital can take several forms while the

ownership and power derived from it re-

mains in the same hands. The neoclassical

or free market conception, on the other

hand, stripped capital of its social and politi-

cal content to merely becoming a (physical)

factor of production that is combined with

labour to produce final products.

Piketty rejects Marx’s conception and is also

wary of the neoclassical one, although he

faces the same problem as the latter on how

to add up and value the capital stock. He

devotes a great deal of the book (Parts One

and Two, Piketty, 2014a: 39-234) in mar-

shalling an impressive array of data to cor-

roborate what he means by “capital”. Wealth

is defined as physical capital equipment plus

land (and housing), and wealth is often used

interchangeably with capital. According to

Erik Olin Wright, such a combination of

homeownership and capitalist property into

one category “capital” does not make much

“sense if we want to identify the social

mechanism through which this return [on

capital] is generated” (Wright, 2014; also

see Fremeaux, 2014). Piketty also disre-

gards the neoclassical “human capital” in

the estimation of the total value of wealth.

In his book and subsequent TED (Technol-

ogy, Entertainment and Design) conference

address, Piketty (2014b) argues that as long

as r > g (i.e. the rate of return on capital is

greater than the rate of economic growth),

then the capital/income ratio (i.e. 𝛽 or the

ratio of capital to national income) will rise,

thus resulting in increased inequality. He

contends that the 18th and 19th centuries

had global economic growth rates per capita

that were close to zero while the rate of re-

turn (primarily on land) stood at around 5

per cent. He goes on to argue that through-

out history r has mostly been around 4 or 5

per cent, while g has oscillated around the 1

or 2 per cent mark. To use Myrdal’s (1957)

“circular cumulative causation” language

where “backwash effects” (divergence)

squeeze out “spread effects” (convergence),

whenever growth slows down, some sec-

tions of the rich get richer while the workers

get poorer as they struggle to keep roofs

over their heads (also see Cameron and

Ndhlovu, 2001).

In his TED conference address, Piketty

merely asserts that r and g depend on tech-

nology (capital-intensive sectors, real estate,

energy, robots), saving behaviour (s) and

scale effects (e.g. de/regulation). He does

not address the capital controversy which

showed the futility of measuring and ac-

counting for Solow’s (1956; 1997; 2000)

physical capital vis a vis changes in prices

and rates of profit. Although Piketty ignores

the problem, the outcome of the capital de-

bate, accepted by Samuelson (1966; 1987),

was that there can be no measure of aggre-

gate capital that is independent of changes

in distribution (also see Cohen and Har-

court, 2003).

In his book, Piketty adds that we can link the

capital/income ratio (𝛽) to the social savings

rate (s) and the growth rate (g) so that we

end up with the equation 𝛽 = s/g (or g = s/v


16

as in the textbooks). Venturing into the ter-

rain of the Harrod-Domar growth model

(which in fairness is a short-run model as

compared to Piketty’s long-run model),

Piketty (2014a: 166) argues that an annual

savings rate (s) of 12 per cent that is ac-

companied by a growth rate (g) of 2 per cent

will result in a capital/income ratio (𝛽) of 600

per cent. The country would have accumu-

lated capital that is equivalent to 6 years of

national income. It stands to reason that the

lower the growth rate (g), the higher the cap-

ital/income ratio (𝛽).

While everyone can potentially benefit from

increased capital, so Piketty notes, “what

this [also] means is that the owners of capi-

tal – for a given distribution of wealth – po-

tentially control a larger share of total eco-

nomic resources” (Piketty, 2014a: 167).

However, the equation 𝛽 = s/g is an ac-

counting identity and not a theory (“The

Second Fundamental Law of Capitalism”),

unless further assumptions about casualties

are added.

For Harrod, if g is fixed at the rate of popula-

tion growth (n), then equilibrium is only pos-

sible if saving and investment (whose caus-

es are independent) both happen to grow at

a rate of n – a very Keynesian argument.

Solow also assumes g = n, but allows 𝛽 to

vary (variable K/L ratios) to allow for multiple

equilibria. Is Piketty (2014a: 166-167) also

assuming that his 2 per cent economic

growth rate is fixed by the rate of population

growth; if not, where does it come from?

Apart from some notable exceptions, Piket-

ty’s enduring contention is that r > g has

held throughout most of the history of man-

kind. Left to its own devices, (free-market)

capitalism will continue to drive a wedge be-

tween the rich and poor. Thus, there is no

natural tendency towards convergence as

Solow argues; instead, divergence is often

the order of the day.

The fall in the capital/income ratio in Europe

during World War 1 is to some extent expli-

cable from the relatively little or no physical

destruction of capital that was accompanied

by a rise in incomes as people were em-

ployed in military service. In addition, the

low rate of return and rapid reductions in in-

equality in the period 1914-1945 is best ex-

plained by high levels of government inter-

vention, particularly regarding some more

progressive taxation (taxation of

wealth/capital) and the destruction of some

inherited wealth through bankruptcies. In

fact, the most notable exception to r > g was

the “long boom” (1945-1970) where there

was unusually high economic growth, with

reconstruction after World War 2 and

investment in global post-colonial “develop-

ment”, resulting in a fall in inequality in the

USA and Europe. In his view, this created

an illusion that a solution had been found to

the problem of inequality.

The imposition of swinging tax rates on the

rich only postponed the day of reckoning.

However, long run reality would reassert

itself with a tendency towards rising ine-

quality. Piketty’s findings are in contrast to

Kuznets’ (1955) Inverted-U Hypothesis that

posits a tendency of income inequality to

rise in the early stages of development (as

measured by GNP per capita), reaching a

peak and then declining in the latter stages.

Instead, his historical data shows an initial

rise in inequality, particularly in Europe and

the USA, but one which fell and stabilised in

the 1910-1970 period, before rising again

and is continuing to rise in the contemporary

period.It is noteworthy that the physical de-

struction of capital that Piketty alludes to is

not necessarily the same as the oscillation

of market values (prices), although Piketty

does not seem to make this distinction. This

is perhaps why he arrives at the conclusion

that financial crises from the 1970s and ris-

ing inequality have both been due to unsus-


17

tainable rises in r relative to g in the USA

and Europe (his magical r > g formula).

However, this conclusion needs to be

couched in a more global context by bring-

ing in the massive movement of physical

manufacturing capital to Asia. In this regard,

Piketty could take a leaf out of Arthur Lewis’

(1954) work in seeking more encompassing

explanations rather than ones that are fo-

cused on Europe and the USA at the exclu-

sion of the rest of the world.

Apparently, the situation has been exacer-

bated by the rise of the “supermanager” in

the USA and the reappearance of patrimo-

nial capitalism in Europe (Piketty, 2014a:

315: 377). “Supermanagers” are corporate

or financial executives that do not necessari-

ly inherit wealth but still command astronom-

ical incomes, or what Hutton (2014) de-

scribes as “super-salaries”. The fall in mar-

ginal rates of taxation on the rich has argua-

bly strengthened their bargaining power for

high salaries and bonuses and thus rein-

forced their perceived importance in society.

Like Hutton, Piketty is perturbed by the ten-

dency of “supermanagers” to take reckless

risks.

Chang (2011: 14) also notes that: “Marx had

foresight to call the joint stock company

‘capitalist production in its highest develop-

ment’. Marx was aware of, and criticized,

the tendency for limited liability to encourage

excessive risk-taking by managers”. But

Marx would also have argued that “super-

managers” or CEOs, as Piketty himself

seems to acknowledge, are no ordinary

“workers” - they set their own astronomical

salaries, hire and fire workers, and give

commands and instructions to workers. As

Wright (2014) notes, “their [the “superman-

agers”] capitalist-derived power” sets them

apart and enables them to appropriate part

of the profits for their own purposes. In the

circumstances, these top managers’ earn-

ings can be categorised within the context of

“a return on capital”, even if this takes “a dif-

ferent form from dividends derived from

ownership of a stock” (ibid; also see Folbre,

2014). Notwithstanding this, Piketty is less

concerned about the role played by “super-

managers” in explaining the ever-widening

gulf particularly in the USA. Instead, he sees

patrimonial capitalism as the primary cause

for inequality. In his TED conference ad-

dress, he asserts that new data on tax re-

ceipts shows that inequality in the USA is

even higher than the results of his findings

in his book.

Piketty (2014a: 377) also identifies a new

phenomenon of a patrimonial middle class

that owns up to a third of the total wealth

which consists of property, including hous-

es, and financial largess that have been

passed on to them by previous generations

who generally constitute a pro-capital politi-

cal vote bank. As indicated before, capital in

Piketty’s hands has thus metamorphosed

from primarily land to encompassing “indus-

trial, financial and real estate” (ibid.). But

what fundamentally worries Piketty is the

disproportionate share of wealth in the

hands of a few increasingly dynastic fami-

lies. Indeed, the share of income of the top 1

per cent in Europe and the USA (the so-

called “fat cats”) has rapidly increased par-

ticularly from 1980.

According to Piketty, the period 1987-2013

saw wealth rising by around 7 per cent per

annum, while average incomes rose by ap-

proximately 2 per cent. In his view, while

wealth inequality is not as extreme today as

it was a century ago, it still has “not recov-

ered” (in a social justice/stability evaluative

sense?) to pre-World War (WW) 1 levels,

although he also points out that “total quanti-

ty of wealth is now close to the pre-WW 1

level”. He reiterates that one of the main

reasons why wealth inequality is more than


18

income inequality is because of the trans-

mission of wealth from generation to gen-

eration and the prospects of high returns, as

well as the societal prestige that accumulat-

ed wealth accords the families that are in-

volved.

What is to be done? Having started with

such a bang, this is perhaps the weakest

part of Piketty’s (2014a: 471-570) book

where he seems to end with a whimper.

Clearly, interventionist policies are required

to reduce inequality, although what he offers

is a shopping list and even he admits that

some of the items are probably politically

unattainable. He advocates for financial

transparency, the international transmission

of bank information and a global registry of

financial assets. Chang (2011) goes even

further in advocating the banning of “com-

plex financial instruments [such as deriva-

tives], unless they can be unambiguously

shown to benefit society in the long run”.

However, Chang also faces the same prob-

lems that confronted Piketty on how realistic

such a proposition is in the face of institu-

tionally-secure vested interests.

Given his stance on redistributive social jus-

tice, Piketty places particular emphasis on

increased marginal rates of taxation on the

rich (as much as 80 per cent income tax

rates for those with incomes of more than

US$500,000 per annum). This involves a

global coordinated strategy on wealth taxa-

tion, starting with those whose assets are

worth around US$200,000, and progressive-

ly increasing until the tax rate peaks at

around 10 per cent for the assets of wealthy

billionaires (the controversial proposed

“mansion tax” in Britain may have relevance

here), a tax on private capital, and generally

tackling patrimonial capitalism (through in-

heritance tax) head-on.

While Piketty recognises the problems con-

cerning tax havens and tax evasion, he ap-

peals to common sense, reason and histori-

cal precedent to come to the rescue. In his

TED conference address, he says that histo-

ry shows that initial scepticism did not pre-

vent the implementation of progressive taxa-

tion. Moreover, while increasing overall ine-

quality may arguably fuel growth as “decent

shares” go to the consuming middle classes,

Piketty feels that in the long-run this is “bad

for our democratic institutions” (also see

Piketty, 2014a: 10). Indeed, Keynes would

have come to the same conclusion. The re-

formist agenda has also gone down well

with the advisers of the former Labour Party

Leader in Britain, Ed Miliband.

Implications of Piketty’s analysis for

sustainable development and power

relations

In his book and subsequent TED conference

address, Piketty is more or less silent on

what constitutes destabilisation in society

and, more importantly, why there is an in-

creased risk of instability in the era of re-

emerging and rejuvenated patrimonial capi-

talism. We can surmise that he means that

widening disparities create social resent-

ment and tensions that threaten the very

fabric of capitalist society. In a separate

wide-ranging polemic against bankers, lais-

sez faire advocates and such-like vis a vis

the financial crisis, and a call for more regu-

lation, John Kenneth Galbraith best captures

the mood in Piketty’s book:

Perhaps as a slight, not wholly inconse-quential service, it can be said that we have here had the chance to see and in some small measure to understand the present discontent and dissonance and the not inconsiderable likelihood of an eventual shock to the contentment (Gal-braith, 1993: 183).


19

Piketty himself states that social democratic

policies will not only ensure the survival of

democratic institutions, but these policies

have also the added merit of being “less vio-

lent and more efficient” in curbing the ex-

cesses of private capital and its incessant

thirst for a return on capital. However, we

already know that Piketty’s r (the rate of re-

turn on capital/profit) has stayed more or

less the same throughout the history of

mankind, and at a level that has been higher

than the growth rate (r > g). Little wonder

that he calls for redistribution to rectify the

situation.

Piketty reiterates that he is not interested in

revolutionary struggles, rather, he is only

concerned with “the best way to organise

society and the most appropriate institutions

and policies to achieve a just social order”.

This is a far cry from the opening statements

in chapter one, where Piketty posited antag-

onistic class relations, and even went so far

as citing the case of the eighteenth century

peasantry as well as the struggle between

owners of the Marikana platinum mine in

South Africa and the mineworkers which

ended in 34 miners being shot dead by the

police in August 2012. Wright (2014) ob-

serves that class or the exploitation of “the

labour of workers” either “disappears” after

these opening proclamations or “is treated

as simply a convenient way of talking about

regions of the distribution of incomes and

wealth”.

Having hinted on his concern with functional

distribution of income (i.e. shares that go to

land, capital and labour), one would have

thought that Piketty would follow through Ri-

cardo’s analysis of “the laws which regulate

this distribution” (Ricardo, 1817), that is,

rent, profit and wages. In Ricardo’s eyes,

these distributional struggles lead to the

squeezing out of capitalists’ profits. The lat-

ter virtually loose the will to live as their pri-

mary motive for expanding business is ex-

tinguished, and thus economic growth ceas-

es (for reflections on Ricardo’s theories and

their later interpretations, see Gibbard,

1994). Unlike Ricardo, Piketty (2014: 10)

has no explanation as to why destabilisa-

tion, and associated observable crises, have

occurred in the first place. Instead, attention

is concentrated on how far wealth is bol-

stered by inheritance.

It was left to Marx to pick up the baton from

Ricardo. To be fair, Piketty disassociates

himself from Marx’s analysis of institutional-

ised capitalist structural crises in capitalist

societies. For Marx, tensions relating to “un-

limited expansion of production” are endem-

ic or an ever-present in capitalist societies.

Whenever the rate of return on invested

capital is considered to be insufficient, the

reaction is often to cease investment as well

as the purchase of goods (Kliman, 2014;

Ndhlovu, 2012; Ndhlovu and Cameron,

2013). This leads to periodic crises and we

can refer to this process as the tendency of

the rate of profit to fall (TRPF).

Indeed, Kliman (2014) shows that only when

there is the devaluation and destruction of

capital value can the tendency towards a

low rate of profit be temporarily arrested. In

fact, Kliman’s calculations confirm Marx’s

TRPF. He also shows that Piketty’s reform-

ist policy of downward redistribution of in-

come is no panacea for recurring crises.

Because such a policy cuts into profit that

drives the capitalist system, it may paradox-

ically result in further destabilising the sys-

tem. He asks a rhetorical question that, if

downward redistribution was the answer to

the problem of both economic growth and

inequality, how come the US economy has

taken years to dig itself out of the 2007-2009

recession hole in which it found itself?


20

Earlier we also indicated that Piketty sees

capital as no different from wealth, while

Marx saw it is the enabler (means of produc-

tion) to the subjugation of the worker by the

capitalist. Wright (2014) reiterates that, the

combination of homeownership and owner-

ship of capitalist capital in Piketty’s definition

of “capital” means that Piketty is unable to

distinguish the differential impact of public

policies (such as progressive taxation and

the proposed global tax) on “different kinds

of ‘return to capital’”, and the social strug-

gles that may accompany the resulting ine-

qualities. In addition, Piketty does not pay

much attention to inequalities that are

“based on ethnicity, citizenship and gender”

(Folbre, 2014). Moreover, as Kliman (2014)

rightly points out, Piketty’s calculation of in-

come excludes “the social wage”, that is,

social security such as unemployment bene-

fits, healthcare, pensions, child benefits that,

if received “for free at the point of use”,

would necessarily come out of wag-

es/salaries “up front”.

According to Kliman, when Piketty is talking

about the top 1 per cent to whom a greater

share of income goes (vis a vis the remain-

ing 99 per cent), he is actually referring to

tax receipts and “not people, not families,

not households”. Tax receipts will change

over time, particularly for poor people. This

can only highlight the problems regarding

the measurement of “income trends” – how

long is a piece of string? As Jerven’s (2013)

Poor Numbers illustrates regarding GDP da-

ta, there are collection data problems (relia-

bility and accuracy), problems of compre-

hensiveness, consistency across time and

comparison, as well as conceptual prob-

lems. For example, if one takes account of

“the social wage”, there is reason to believe

that the total income of the 99 per cent may

actually have risen rather than stagnated.

These gains could only have been won by

people engaging in social struggles for bet-

ter facilities, for “family planning and gov-

ernment-provided benefits” which, as Kliman

(2014) correctly states, “are anathema to

much of the right”. In other words, we need

to go beyond poor numbers, to use Jervens

(2013) characterisation, and beyond profit

into understanding social processes and the

implications for fundamental social change.

People’s social struggles should ideally mat-

ter more than profit.

Marx’s examination of periodic and worsen-

ing crises consequent upon overproduction,

that is, the tendency of the rate of profit to

fall, is thus inapplicable to Piketty’s notion of

a constant r at around 5 per cent, while g

remains at the 1-2 percentage mark (r > g).

How do we explain a high g and increasing

inequality in emerging economies such as

China and India? Piketty gazes into the fu-

ture and sees that, because of an anticipat-

ed fall in population growth as well as the

slowing down of technological progress, g

will eventually go back to the 1-2 percentage

mark, while r will rise markedly. Like Keynes

(1936) and Chang (2011), his acceptance of

the general institutional robustness of capi-

talism logically leads him to the conclusion

that no fundamental social change is re-

quired, that greater redistributive justice will

be sufficient to iron out the problems of

growing inequality in the system.

It is against this background that debates on

sustainable development and/or “Green

Economy” (Newton and Cantarello, 2014)

have taken place. Piketty’s contention has

echoes of the “End of Growth” debates

which suggest that growth has either slowed

down or stagnated as wealth-generating

technologies are arguably no longer being

rapidly developed as in the Second Industri-

al Revolution (the Age of High Economic

Growth, 1867-1914), or technological pro-

gress appears to have already come to an

end (Gordon, 2012; Jackson, 2011; Wolf,


21

2012). Like Piketty, analysts of this ilk con-

tend that an aging population has been ac-

companied by the retirement of “baby

boomers” in the USA and Europe, while the

problem of distributing income to the bottom

99 per cent is beginning to rear its ugly head

again.

As Wolf (2012) puts it, Solow’s proposition

of “unlimited growth is a heroic assumption”.

In the circumstances, emphasis is put on

reconciling industrialisation (high carbon en-

ergy inputs) and environmental concerns

(less carbon energy inputs) (Brundtland,

1987), especially since the world is now fac-

ing problems of climate change and food

security. Whereas Piketty presents his con-

stant g and links inequality (r > g) with tech-

nology (including the energy sector and

possible introduction of robots in the future),

Jackson (2012), on the other hand, goes fur-

ther in questioning the very need for growth

and suggests that prosperity can actually

take place without growth (also see Storm,

2009). Just like Keynes (1936), Piketty

(2014a; 2014b) and Chang (2011), Porritt

(2005) accepts the logic of capitalism, and is

only concerned about the levels of dissatis-

faction resulting from “grotesque disparities

of wealth” or “inequality of income distribu-

tion”. Indeed, he calls for a “reform agenda”

that is apparently “radical” rather than “revo-

lutionary”.

For Porritt (2005; 2013), sustainability

should not be just an add-on issue such as

increased corporate social responsibility

(CSR), nor should we be forced to choose

between economic growth and securing the

environment for the purposes of achieving

social justice. For Porritt, there is no differ-

ence between sustainability and social jus-

tice. Similarly to the “resource curse” debate

and the phenomenon of the “Dutch Disease”

that faced the Netherlands State once large

quantities of fossil gas supplies were dis-

covered in the 1970s (Ndhlovu and Camer-

on, 2013), the South African government is

now having to grapple with the prospect of

large oil deposits off the coast of Durban.

How can the South African government, in

its Operation Phakisa (hurry up or innovative

delivery programme), manage these poten-

tially large reserves in a way that does not

intensify the use of carbon emissions (pollu-

tion), while perpetuating inequalities and so-

cial conflict? A strong regulatory system in

the Netherlands, that utilised rising gas rev-

enues for institutional support for education

and skills development, helped to maintain

social cohesion in the short run (ibid).

However, in the face of vested interests, so-

cial democratic policies have often been

shown to be unable to translate populist

declarations into concrete action (ibid). In

addition, Burkett (2003: 111) and Lohmann

(2011: 650) note that some fractions of capi-

tal tend to profit from climate disasters, in

terms of producing and selling air condition-

ers, oxygen masks etc., that is, new busi-

ness avenues that are opened for construc-

tion and real estate at the expense of finan-

cial capital (such as the insurance busi-

ness). In other words, the incessant push for

accumulation (“Accumulate, Accumulate,

that is Moses and the Prophets!” – Marx,

1977a: 558) leads to recurring crises and

conflict within capitalist societies, which

tends to deflect political discourse away

from environmental concerns towards reso-

lution of crises in the institutional interests of

capital (Ndhlovu, 2012; Ndhlovu and Cam-

eron, 2013).

Nevertheless, Piketty must be commended

for shaking the pro-capital “institutionalist”

economic fairy-tale (Chang, 2011) to its

roots, and seeking to demystify “the dismal

science” (Carlyle, 1888). However, his re-

examination of the return on capital vis a vis

economic growth - i.e. opulence, inequality

and poverty - and/or social justice does not

take into account overproduction that is at

22

the root of periodic crises in (patrimonial)

capitalism. Small wonder that his Capital in

the Twenty-First Century gives prominence

to reform, and income distribution is regard-

ed as the panacea for inequality. Given his

distributional stance, it is in any case not

surprising that Piketty is unable to include

structurally institutionalised power relations

and class struggle (including people’s anti-

capitalist global struggles for social justice)

as key elements in understanding instability

in 21st capitalism.

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25

Introduction2

Unreliable and inadequate electricity supply

is one of the major challenges affecting

Uganda’s economic growth and develop-

ment. “Frequent power outages cause sig-

nificant losses, equivalent to 6 percent of

turnover on average for firms in the formal

sector, and as much as 16 percent of turno-

ver for informal sector enterprises” (Eber-

hard & Shkaratan, 2011). Electricity in

Uganda is highly unreliable because of the

dilapidated distribution and transmission

network infrastructure. Eberhard & Shkara-

tan (2011), about 15 cent

2 V Mutyaba, N Marwa, 2015

Africa is not operational because of inade-

quate maintenance of the existing facilities.

According to the World Bank (2000:224)

Ugandan firms lose an average of 91 days a

year because of power outages. The impli-

cation is that Uganda and Africa must not

only address the challenge of electricity reli-

ability but also ensure that the price of elec-

tricity is affordable to attract investment into

the country. According to Mawejje (2013),

business executives perceive the cost of

electricity as the biggest hindrance to doing

business in Uganda. In order to address the

challenges of unreliable electricity supply

and high tariffs, in 2003, the Government of

Uganda made a strategic decision to liberal-

The Impact of Capital Structure of Electricity Generation Pro-

jects on Electricity Tariffs in Uganda

Vianney Mutyaba

University of Stellenbosch Business School

[email protected]

Nyankomo Marwa

University of Stellenbosch Business School

[email protected]

Abstract The recent transformation in the Ugandan energy sector has led to a significant surge in private electricity generation companies in the country. These companies have a heterogeneous capital structure and they tend to charge different tariff rates for the electricity generated. While the capital structure might have an important role to play in differential tariff setting, it is not clear to what ex-tent it influences the tariff structure of electricity generation projects. Thus, the objective of this study was to examine the effect of capital structure on the tariff of electricity generation projects in Uganda after controlling for other factors such as operation and maintenance costs, technology used for generation, project development costs, and installed capacity of generation plants on the generation tariffs. Using cross-sectional data from 29 electricity generation companies as at Sep-tember 2014, a bootstrap linear regression analysis was used for estimation. The results of the study indicated that the higher the debt portion in the capital structure, the lower the generation tar-iff. However, the impact of debt in the capital structure was not statistically significant. What stood out is that renewable technologies have a much lower generating tariff than non-renewable tech-nologies.

Key words: Capital Structure, Uganda, Electricity Generation Tariffs




26

ise and unbundle the Electricity Supply In-

dustry (ESI). Before 2003 electricity genera-

tion was the sole responsibility of govern-

ment but liberalisation encouraged private

sector participation, increased investment,

reduced inefficiency and reduced depend-

ence on government financing. In addition,

liberalisation also changed the operation of

the electricity sector in Uganda.

Since the liberalisation of the electricity sup-

ply Industry, there are more operators with

diverse financing structures for generation

projects (Electricity Regulatory Authority

(ERA), 2013) and use of debt financing by

utility firms has been an increasing trend.

According to the Uganda Electricity Trans-

mission Company Limited (UETCL) (2013),

in 2012 about 55 percent of the energy was

generated by Independent Power Producers

(IPPs) compared to five percent in 2005.

The UETCL report further indicates that

since 2003, the number of private electricity

generation facilities selling power to the Na-

tional Grid increased from four to twelve in

2012. This inflow of private sector capital in

electricity generation created competition,

diverse capital structures and therefore dif-

ferent generation electricity tariffs for the

generation plants (ERA, 2013). The pro-

spective developers submitted proposals to

ERA under a competitive framework with

optimal cost structures in order to be issued

a license.

The World Bank (2000) stated that electricity

tariffs in Africa are high compared to other

regions of the world, mainly because of cost

and policy differences. According to Umeme

Limited (2011), the Uganda Electricity gen-

eration segment has the largest contribution

to the retail tariff, contributing 68 percent of

the total electricity sector costs. Cornille and

Dossche (2006) stated that the major de-

terminants of prices are quantity demanded,

quality supplied and cost of production.

Since investment in generation companies

requires significant upfront cost, we hypoth-

esise that the capital structure, for electricity

generation companies may be one the ma-

jor drivers of the generation tariff. It is ex-

pected that if the cost of capital directly in-

fluences the costs of production, it will be

transmitted to the prices of commodities.

This study will look at the generation tariff

and how capital structures of generation

plants influence the generation tariff in

Uganda.

Overview of the Ugandan Electrici-

ty Supply Industry and the Capital

Structure of Operators

Uganda’s electricity supply industry started

with the commissioning of the Owen Falls

dam in 1954 and establishment of the

Uganda Electricity Board (UEB). At the time

of Uganda’s independence in 1962, it was

clear that the energy future of the country

was very bright. The national demand was

low and generation was high. Uganda was

generating adequate electricity to meet the

national demand, and the rate of industriali-

sation and economic growth was stimulated

by the existence of a generation facility that

supplied adequate electricity.

The Uganda Electricity Board was a vertical-

ly integrated fully state-owned enterprise

that was responsible for generation, trans-

mission and distribution of electricity in

Uganda. Like in other countries in Sub-

Saharan Africa (SSA) at the time, Uganda

Electricity Supply Industries experienced

challenges of inadequate investment amidst

competing government priorities, poor

maintenance, unreliable and expensive

electricity. According to Eberhard & Shkara-

tan (2011), SSA is experiencing a power cri-

sis with unreliable, inadequate, expensive


27

electricity infrastructure and limited access

to electricity with less than three in every ten

people living in SSA having access. Eber-

hard & Shkaratan (2011) further stated that

power supply in SSA is unreliable, with 15

percent of the installed capacity not opera-

tional mainly as a result of aging plant and

inadequate/irregular maintenance with aver-

age electricity tariffs in SSA twice the tariffs

in other parts of the developing world. Addi-

tionally, the World Bank (2011) states that

SSA is experiencing an infrastructure financ-

ing gap of US$ 31 billion per year resulting

from the required additional investment for

new infrastructure and addressing ineffi-

ciencies in the existing infrastructure. SSA

governments do not have the ability to fi-

nance the required investment amidst a

constrained resource envelope, thus there is

a need to encourage partnership with the

private investors to bridge the financing gap.

In 2004, the Government of Uganda decided

to encourage participation of the private sec-

tor in the ESI. The purpose of encouraging

private sector participation was to increase

investment in the sector, increase genera-

tion capacity, reduce power losses, and im-

prove collection rates and efficiency. Since

liberalisation of the ESI in 2004, there has

been increased generation capacity installed

in Uganda. The electricity generation ca-

pacity has increased from 425MW in 2004

to 868 MW in 2013 (ERA, 2013). The num-

ber of companies generating electricity and

selling to the national grid increased from

four in 2003 to twelve in 2012 (UETCL,

2013). According to UECTL (2013), electrici-

ty generation increased from 1,887GWh in

2005, when the Government of the Uganda

was the main generator of electricity, to

2,857GWh in 2012 after encouragement of

private sector participation. As private sector

participation increased, there was a need to

ensure a cost recovery mechanism (includ-

ing capital costs, financing costs and operat-

ing costs), accordingly the weighted average

generation tariff increased from US$

0.02/KWh in 2005 to US$ 0.13/KWh in

2011. The participation of the private sector

led to the existence of a diversity of capital

structures for investors in the ESI, especially

in the Generation segment where there is

more private sector participation (ERA,

2013). The capital structures of companies

operating in the ESI include debt composi-

tion ranging from 100 percent: 0 percent, 80

percent: 20 percent, 70 percent : 30 percent,

65 percent : 35 percent, to mention but a

few (ERA, 2013).

Review of Relevant Literature and

Theoretical Framework

From the theoretical framework it should be

noted that apart from the capital structure,

there are other factors affecting the genera-

tion tariff including;- the operations &

maintenance costs, the technology used,

the installed capacity of the generation facili-

ty among others. The theoretical framework

can be conceptually summarised as in Fig-

ure 1. Accordingly, Figure 1 can be ex-

plained by moving from the right-hand to

left. That is, at macro-level, the generation

tariff is affected by two major factors: the

volume of electricity generated and the cost

of generation.


28

The volume of electricity generated depends

largely on the type of technology employed

or fuel used such as hydropower or thermal-

power deployed; the installed capacity of the

plant; and other factors (for example climatic

factors such as hydrology, solar intensity).

In this study, the full cost pricing theory is

considered appropriate in describing the

generation tariff determination process. Ac-

cording to the microeconomic theory, the

typical approach of determining the price (P)

under this method is to estimate the average

variable cost (AVC) and to add a fair margin

of profit (Dwivedi, 2003). That is:

𝑃 = 𝐴𝑉𝐶 + 𝐴𝑉𝐶(𝑚) (1) …(1)

Where P is the price (which in our case is

the generation tariff), AVC is average varia-

ble cost, and m is mark-up percentage of

profit that is fixed to cover average fixed

cost (AFC) and a net profit margin (NPM).

Thus:

𝑃 = 𝐴𝑉𝐶 + 𝐴𝐹𝐶 + 𝑁 (2)

From the theory of costs (Koutsoyiannis,

1978), the average cost (AC) is an aggrega-

tion of AVC and AFC; and AC is the ratio of

total costs (TC) to total output (Q). That is:

𝐴𝐶 = 𝐴𝑉𝐶 + 𝐴𝐹𝐶 (3) …(3)

𝐴𝐶 =𝑇𝐶

𝑄 (4) …(4)

Figure 1: Conceptual framework of effect of debt-equity structure on electricity tariffs

of generation project

Generation

tariff

Volume of

eletricity

Generation

technology

Installed

capacity

Other factors

e.g climate

Total cost of

production

Debt-equity

structure abd Finance costs

O&M costs

Return on owner equity

Other factors


31

Substituting Equation 4 into Equation 3 im-

plies that the electricity generation tariff (PE)

is a function of total cost of production, out-

put produced and the net profit margin for

owners or equity providers for generation

plants. This is presented in Equation 3.5 as:

𝑃𝐸 =𝑇𝐶

𝑄+ 𝑁𝑃𝑀 (5) …(5)

In the electricity industry literature, the right-

hand side of Equation 3.5 is referred to as

the revenue requirement, which is com-

posed of the operating and maintenance

costs, invested capital and profit margin.

According to Bauer (2004:4), the capital

structure is determined by the size of the

firm, profitability of the firm, growth pro-

spects / opportunities, existing tax shield

and the industry in which the firm operates.

From a project finance perspective, Gatti

(2013:138) stated that project sponsors pre-

fer to commit as limited equity as possible.

Gatti (2013: 138) further stated that the ba-

sis for the debt to equity ratio is: economic

soundness of the project, the acceptance

level of risk for the lenders, and precedent in

the financial markets.

Harris and Raviv (1991:334) stated that

many studies have been conducted to pro-

vide guidance on how specific characteris-

tics of firms and industries determine their

capital structure. Hatfield, Cheng & Da-

vidson (1994:2) noted that firms operating in

the same industry will have generally similar

financing structures. However, other re-

searchers such as Boquist and Moore

(1984) found weak evidence to support this

theory. Electricity generation firms in Ugan-

da have diversified financing structures de-

spite operating in the same industry (ERA,

2013).

Bauer (2004:4) agreed with other research-

ers that determinants of capital structure in

clude the size of the firm, profitability of the

firm, growth prospects / opportunities of the

firm, existing tax shield, tangibility of the firm

and the industry of operation. Bauer (2004)

stated that more profitable firms are ex-

pected to have higher debt in their capital

structure because they have income to

shield from taxes. Bauer (2004) further ar-

gued that companies with more tangibility

have more access to credit/debt because of

their ability to use their assets as collateral

to obtain debt financing. Mark and Clifford

(1992), however, found no evidence to sup-

port the finding of Bauer (2004) in respect of

factors that influence the capital structure of

firms.

Some researchers, such as Huang and

Song (2006), Rajan and Zingales (1995)

and Friend and Lang (1988) concluded that

there is a positive relationship between size

and capital structure. Song (2005) agreed

with Bauer (2004) that the determinants of

the capital structure include tangibility (asset

structure), non-debt tax shield, profitability,

size, expected growth, uniqueness and in-

come variability. Titman and Wessels

(1988), argue that firm’s choice of the capital

structure is influenced by the costs and

benefits of using debt or equity.

Researchers such as Kester (1986), Kim

and Sorensen (1986) and Titman and Wes-

sels (1988) however disagree and conclude

that there is a negative relationship between

size and the capital structure. According to

Oolderink (2013), the pecking order theory

of capital structure states that in circum-

stances where external financing is needed,

firms prefer debt financing to equity financ-

ing. Johnson (1998) stated that there is no

predetermined rule for determination of capi-

tal structure as every company experiences

unique risks, threats and opportunities. He


32

further noted that although the traditional

view is that any company has an optimal

capital structure the determination of this

optimal structure is subjective and complex.

Scannella (2012: 85), like Johnson (1998),

noted that there is no universally acceptable

rule for choosing the capital structure of a

firm. Scannella (2012: 85) noted that typical

projects have 70–75 percent debt and 25–

30 percent equity. The National Renewable

Energy Laboratory (2008: 4-1) stated that

between 35 and 45 percent equity is stand-

ard for commercial projects. Berger (2011:6)

stated that electric power projects in Europe

have typical debt to total capital range of

60–70 percent.

Clarke, Wilson, Daines and Nadauld

(1988:167) noted that a study by Scott and

Johnson concluded that there is a target

capital structure for very large American

companies that guides decisions regarding

financing. He further noted that while this

target capital structure varies between 26

and 40 percent there is no consensus on the

exact percentage and every company uses

its own.

The capital structure is key as it determines

the cost of capital. Johnson (1998) noted

that the value of the firm/company increased

as the weighted average cost of capital re-

duced. Firms’ costs reduce as the weighted

average cost of capital reduces up to the

optimal capital structure. As the portion of

debt in the capital structure increases, the

weighted average cost of capital reduces,

increasing the value of the firm. As the por-

tion of debt further increases, the cost of

both debt and equity increase to cater for

increased financial risk. When the debt por-

tion increases beyond the optimal capital

structure, the increase in cost of equity off-

sets the benefit of lower cost of debt. Leland

and Toft (1996) noted that there is a need to

balance the tax advantages of debt with the

risks of bankruptcy and high agency costs in

the determination of the optimal capital

structure. Puwanenthiren (2011:1) stated

that the capital structure is the most signifi-

cant discipline in the operations of any com-

pany, and concluded that there is a negative

relationship between the capital structure

and the financial performance of any com-

pany. Like Puwanenthiren (2011:1), Dhan-

kar and Boora (1996: 29) stated that the

capital structure is the most important deci-

sion for a firm. The capital structure affects

the profitability of the company, the cost of

capital, earnings per share, dividends and

liquidity position of the company. Duca

(2010:523) concurs with Chowdhury and

Chowdhury (2010), and Mark & Clifford

(1992) that the capital structure decision is

one of the most fundamental premises of

the financial framework of a corporate entity.

According to Chowdhury (2010:112), the

decision in respect of how much debt and

equity to employ is aimed at ensuring an op-

timal financing structure that maximises

shareholder returns.

Many other researchers agree that the fi-

nancing structure has an impact on firm’s

costs and profitability. Mohammed Omran

(2001) studied 69 Egyptian firms privatised

between 1994 and 1998 that started using

debt financing. The study concluded that

firms that were privatised and used debt fi-

nancing increased in profitability, operating

efficiency, capital expenditure and divi-

dends.

Pirashanthini and Nimalathasan (2013)

studied the capital structure of manufactur-

ing companies in Sri Lanka and concluded

that the debt to equity ratio is positively and

strongly linked to the profitability ratios of

gross profit margin and net profit margin.

According to Russo, Weatherspoon, Peter-


33

son and Sabbatini (2000: 27), excessive

leverage leads to financial distress, increas-

es the firm’s costs in terms of high transac-

tion costs and forgone profit opportunities

and therefore influences prices. Russo et al.

(2001:34) stated that there is a positive cor

relation between the cost of financing and

the portion of equity in the capital structure.

When interest rates increase, the cost of

debt financing increases and makes equity

financing more attractive than debt. Financ-

ing more assets using equity reduces the

risk brought about by operating leverage

and increases profitability. The National Re

newable Energy Laboratory (NREL) (2012)

states that firms whose financial structure is

fully debt-financed generally yield a lower

levelised cost of energy (LCOE) than those

that rely purely on equity capital.

Empirical results from a study by Dhankar

and Boora (1996) on the capital structure of

companies in India showed that there is no

definite relationship between change in the

capital structure and the value of a firm but

81 percent of the companies showed a neg-

ative relationship between the capital struc-

ture and the cost of capital. Cost of capital

reduces as debt levels in the capital struc-

ture increase because cost of debt is

cheaper than cost of equity as interest rate

payments are allowable deductions for tax

purposes. Chowdhury and Chowdhury

(2010:112) argued that increasing debt fi-

nancing within the capital structure would

increase the firm’s value up to a point where

any further increase in debt financing in-

creases the overall cost of capital.

The Brattle Group (2005: 5) stated that the

amount of debt in the capital structure influ-

ences the cost of equity. Debt financing re-

sults in financial risk which equity share-

holders incorporate when pricing the cost of

equity. Scannella (2012:85), and Chowdhury

and Chowdhury (2010:111) agreed that

firms dedicate operating cash flows to debt

service before paying returns / dividends to

shareholders. Debt financing ensures that

the company benefits from interest expens-

es, which is an allowable expense for tax

purposes, but too much debt makes debt

issuers become nervous regarding the com-

pany’s ability to pay. On the other hand,

Modigliani and Miller’s findings in 1958 con-

cluded that the decision in respect of the

company’s capital structure is not important

because of the existence of frictionless mar-

kets and homogeneous expectations. Modi-

gliani and Miller (1958) argued that all firms

experience the same risk, their expectations

are similar, there is absence of growth,

agency costs and bankruptcy costs and the

risk-free rate can be applied for lending and

borrowing by individuals.

Puwanenthiren (2011:2) explained that Mo-

digliani and Miller’s (1958) relevance theory

reveals that no capital structure is better

than another, the benefits of increasing debt

financing is offset by the higher risk in-

curred. Some researchers agree with Modi-

gliani and Miller’s (1958) findings that the

decision in respect of the company’s capital

structure is not important. Brigham and

Gapenski (1990) in their study of the effects

of capital structure on utilities’ cost of capital

and revenue requirement concluded that

decisions regarding capital structure have a

negligible effect on firms’ revenue require-

ments.

Data and Methodology

Data type and sources

The data used in this study is secondary da-

ta, obtained from ERA, Uganda’s ESI regu-

lator. The data was obtained for companies


34

that have obtained or are about to obtain

licenses and permits from ERA to develop,

own and operate electricity-generating facili-

ties in Uganda.

Econometric model

Based on the theoretical framework pre-

sented in section three, the empirical model

to estimate the relationship between the

capital structure and the tariff of electricity

generation projects in Uganda can be stated

in a general functional notation as:

TG = β0 + β1DE + β2FC + β3ROE + β4OM +

β5GT + β6PC + ε (6) …(6)

According to Gujarati (2003), Equation 6 can

be written as an econometric equation as

follows:

TG = β0 + β1DE + β2FC + β3OM + β4ROE +

β5GT + β6PC + εWhere 𝛽0 … … 𝛽7 ( 7)

Where are β0 … . β7 𝑎𝑟𝑒 unknown parame-

ters to be estimated and ε is the error term

representing other unknown variables that

may affect the generation tariff.

Estimation Procedures and Model Diag-

nostics

Data used in this study is from various com-

panies and therefore cross-sectional in na-

ture. According to Gujarati (2003), in order

to get efficient estimates from cross-

sectional data, the data of the dependent

variable should be normally distributed and

the explanatory variables should not be

highly linearly correlated (multicollinear). In

case the dependent variable is not normally

distributed, Gujarati (2003) suggested that

such data can be transformed such as into

natural logarithms, squared, squared root,

etc., so as to make the data normally dis-

tributed. Ordinary least squares (OLS) was

used to estimate regression parameters.

Since our sample was limited we used ro-

bust standard error with bootstrap option in

order to get reliable test statistics.

To improve the skewness and relationship

patterns among the variables, the following

variables were log transformed: DE (portion

of debt in the capital structure), OM (opera-

tion and maintenance costs), PC (installed

capacity), DC (Development costs). In the

analysis, the transformed explanatory varia-

bles were used in the econometric analysis.

Bivariate linear regression models were es-

timated with each dependent variable. Then,

a forward and backward selection approach

was used manually to estimate the final full

model. Cook’s Distance was used to detect

the influential outliers using a cut-off point of

4/n which is 0.134 in our case (n=29). Three

observations were identified as influential

and were left out during the analysis.

Based on the correlation matrix there was

significant association between develop-

ment cost and installed capacity (r=0.98). To

avoid multicollinearity only one of the varia-

ble installed capacities was included in the

model.

After the selection of the final model, we

used robust standard error bootstrap option

with 1000 iterations and seed of 1. Boot-

strap was used in order to achieve correct

inferences given a small sample size (Guan,

2003). Only the results from the final model

with bootstrap option will be used for inter-

pretation and discussion purpose. The

analsis was done using STATA SE 12 Sta-

tistical Program.

Estimation of the Model and Reliability of

the Estimates

To identify the relationship between the cap-

ital structure of electricity generation pro-

jects and electricity tariffs in Uganda, Equa-

tion 5 was estimated using econometric mul-

tiple linear regression analysis. Similar stud-

ies that have used OLS include ECME Con-

sortium (2010) to estimate the functioning of

retail electricity. The econometric analysis

35

involves running one OLS regression; in

which the projects will be the observations,

the Generation Tariff will be the dependent

variable, and debt to equity ratio, return on

equity, debt financing costs, operation and

maintenance costs, technology employed,

development costs and installed capacity

will be the explanatory variables.

As mentioned earlier, given that the sample

for this study was relatively small and there

are more than five variables, the analysis

can lead to inefficient estimates (Deaton,

2003). To enhance efficiency and reliability

of the estimates involving a relatively small

sample, Efron (1979) introduced the boot-

strapping technique. The bootstrap is a sta-

tistical technique that artificially increases

the sample size through replication (produc-

ing a large number of “copies”) of a sample

statistic, computed from bootstrap samples

at five percent confidence interval (Boos &

Munahan, 1986). In this study, the bootstrap

technique is used to improve the efficiency

of the estimates.

Results and Discussions

Descriptive Statistics

Table 1 describes the data used in the anal-

ysis. In Table 1, Tg is the generation tariff

which is the dependent variable measured

in US$ per KWh. The figures in the table in-

dicate that the average generation tariff is

US$ 0.105/KWh and ranges from US$

0.053/KWh to US$ 0.243/KWh. The type of

technology was coded 1 if the technology

was renewable and 0 if it was non-

renewable.

From Table 1, it can be observed that 89.7

percent of the generation technology is re-

newable energy that includes hydro, bio-

mass and bagasse co-generation. Operation

and maintenance costs average

US$ 0.031/KWh. On average, debt contrib-

utes 70.7 percent to the capital structure of

electricity generation projects, and the aver-

age cost of debt is 7.9 percent per annum.

The average return on equity is 16.8 per-

cent. Project development costs range from

US$ 4 million to US$ 755 million and aver-

age US$ 67.7 million, and the average in-

stalled capacity is 25.7MW with a maximum

installed capacity of 250MW.

Table 1: Description of the data

Variable Description of the variable Mean Std. Dev. Min Max

Tg1 Generation Tariff with only re-

newable technology (without

outliers)

0.905 0.135 0.053 0.107

Tg Generation Tariff with both re-

newable and non-renewable

technology (outliers included)

0.105 0.046 0.053 0.243

GT Type of Technology 0.897 0.310 0.000 1.000

Om Operation & maintenance costs 0.031 0.029 0.003 0.100

De

Debt portion in the capital struc-

ture 0.707 0.128 0.263 1.000

Fc Debt financing costs 0.079 0.026 0.012 0.120

Roe Return on equity 0.168 0.054 0.000 0.250

dc_100 Development costs 0.677 1.403 0.040 7.550

pc_100 Installed Capacity 0.257 0.473 0.010 2.500


2

Testing for reliability of the data

Testing for reliability of the data was under-

taken using the approaches below.

Testing for multicollinearity

Table 2 below shows the pairwise correla-

tion of the variables to check for any possi-

ble multicollinearity. When there is a perfect

collinearity, the result is 1, when there is no

relationship between the variable the result

is zero. According to Gugarati (2003), if the

variables are perfectly collinear, then one of

these should be dropped out of the analysis.

Table 2 shows that there is almost perfect

collinearity between installed capacity and

development cost. Development cost was

omitted from the regression analysis to

avoid the problem of multi-collinearity.

Table 2: Pairwise correlation of the variables

TG GT Om de Fc roe dc_100 pc_100

TG 1

GT -0.9596 1

Om 0.7388 -0.7187 1

De 0.2443 -0.2523 -0.075 1

Fc -0.2221 0.2618 -0.1169 -0.2459 1

Roe -0.3582 0.3057 -0.243 -0.1923 0.2707 1

dc_100

0.0062 -0.0166 -0.1883 0.3681 -0.2675 -0.0483 1

pc_100 0.1527 -0.1774 -0.0722 0.4325 -0.2815 -0.0723 0.9789 1

Regression Results

Table 3 below shows the results of the re-

gression using the OLS method with the

bootstrapped standard error technique to

improve efficiency and robustness. The

bootstrap included 948 replications. The re-

sults of the regression are robust given that

the Wald chi2 statistic (70.18) is statistically

significant at less than 1 percent level. The

adjusted R_Square is 79.2 percent, implying

that the model describes up to 80 percent of

the relationship between the generation tariff

and explanatory variables.

From Table 3, two variables, that is GT

(Generation Technology) and installed ca-

pacity (log_pc_100), are found to have a

significant effect on the generation tariff (gt),

while the portion of debt in the capital

structure (log_de) is found to have a positive

but not statistically significant effect on the

generation tariff (gt). Details of the analysis

are provided below.

Capital structures of generation projects

Debt-equity (DE): Table 5.4 illustrates that

there is a positive relationship between the

debt portion of the capital structure and the

generation tariff of electricity generation pro-

jects. The results in Table 5.4 indicate that a

one percent increase in the portion of debt

in the capital structure results in a 15.4 per-

cent increase in the electricity generation

tariff. When the outliers are excluded, a one

percent increases in the portion of debt in

the capital structure results in a 24.7 percent

increase in the electricity generation tariff.

The result is however not statistically signifi-

cant. Studies such as Russo et al. (2001)

also concluded that there is a positive

Source: Author, 2014


36

relationship between the portion of debt in

capital structure and prices, explaining that

a high proportion of debt in the capital

structure leads to financial distress and high

costs therefore increasing prices/tariffs.

Table 3: Multiple Regression Results

Results when both renewable and non-

renewable technology are included

(outliers included)

Results for renewable technolo-

gy only

(outliers excluded)

Variable

Observed

Coefficient

Boot-

strap

Std.

Err. Z P>z

Ob-

served

Coeffi-

cient

Z P>z

GT -1.024*** 0.167 -6.150 0 - - -

log_om 0.034 0.051 0.660 0.509 0.223 2.550 0.011

log_de 0.154 0.342 0.450 0.653 0.247 0.540 0.592

Fc 0.701 2.021 0.350 0.729 0.108 0.040 0.968

Roe -0.657 0.893 -0.740 0.462 -1.346 0.900 0.369

log_dc_100 0.122 0.104 1.170 0.240 -0.066 -0.380 0.702

log_pc_100 -0.168* 0.091 -1.850 0.064 0.117 0.690 0.487

_cons -1.369 0.224 -6.120 0 -0.968 -1.930 0.054

N 29 29.000

R_Square 0.844 0.538

Adj R-squared 0.792 0.4115

Wald chi2(7) 70.180*** 9.580

Root MSE 0.155 0.260

Replications 948 1000

In order to further understand further why the relationship between the portion of debt in the

capital structure and the generation tariffs was positive but not statistically significant, a polyno-

mial graph of the relationship is plotted in Figure 1.

Figure 1: Illustration of relationship between debt portion in the capital structure and genera-

tion tariffs

Source: Author, 2014


2

Figure 1 shows a slight inverse relationship

when the portion of debt in the capital struc-

ture is low and later a positive relationship

as the portion of debt in the capital structure

increases. Because of this mixed relation-

ship, it is indeed clear that it cannot be sta-

tistically significant. However other studies,

such as that of Pirashanthini and Nimala-

thasan (2013), found that high debt compo-

sition in the capital structure leads to a lower

tariff but nonetheless not significant.

Technology of generation projects

Technology (GT): Table 3 shows that there

is a negative and statistically significant

(p<0.01) relationship between the genera-

tion technology and the electricity genera-

tion tariff. To further understand why this

may be the case, a comparison was done in

respect of the average generation tariff for

renewable and non-renewable generation

technologies in Uganda. The generation

tariff for renewable generation technology is

about US cents 10.7 per KWh compared to

about US cents 23 per KWh for the genera-

tion tariff for non-renewable technology. The

likely reason why the generation tariff for

non-renewable generation is high in Uganda

is due to the high costs of fuel utilised in

non-renewable electricity generation.

Installed Capacity

Installed Capacity (PC): Table 3 shows

that installed capacity is a statistically signif-

icant variable in the determination of gen-

eration tariffs at 6.4 percent. The table fur-

ther shows that there is a negative relation-

ship between the installed capacity of the

generation plant and the generation tariff of

the respective plant. A 16.8 percent in-

crease in installed capacity results in a 1

percent reduction in the generation tariff.

The results are consistent with Dwivedi

(2003) who concluded that a large installed

capacity implies that costs are recovered

over more units therefore reducing the gen-

eration tariff. When the installed capacity is

small, the generation tariffs are high and in-

crease as the installed capacity increases

up to a certain level, beyond which an in-

crease in the installed capacity leads to re-

duction in the generation tariff.

Development costs of generation projects

Development costs (DC): Table 3 shows

that there is a positive relationship between

the development costs and the generation

tariff and that the development costs varia-

ble is significant. Table 5.4 shows that for a

one percent increase in development costs,

the tariff increases by 12.2 percent. This

finding is supported by Ragwitz et al. (2012)

who concluded that there is a positive rela-

tionship between development costs and the

tariff (i.e. an increase in development costs

leads to increase in the generation tariff).

Operation and Maintenance costs (OM

Table 3 shows that there is a positive rela-

tionship between the operation and mainte-

nance costs and the generation tariff. For a

3.4 percent increase in the operation and

maintenance costs, the generation tariff in-

creases by one percent. The variable is sig-

nificant because it is dependent on the units

generated as it is measured in US$/KWh.

Literature on the relationship between the

operation and maintenance costs and tar-

iffs/prices indicates that the effect of the op-

eration and maintenance costs on prices of

commodities depends on the proportion of

operation costs to the total costs. A high

portion of operation and maintenance costs

in the total cost structure will have a higher

effect on the tariff / prices.


38

Costs of debt

Debt financing costs (FC): The results in

Table 3 indicate that there is a positive rela-

tionship between the costs of debt and the

generation tariffs, although the table further

shows that debt financing costs are not sta-

tistically significant in the determination of

the generation tariff. An increase in the debt

financing costs by one percent results in a

70 percent increase in the generation tariff.

The results are in line with findings by Rus-

so et al. (2001) that a high interest rate in-

creases the generation tariff.

Return on equity

Return on equity (ROE): The results in Ta-

ble 5.4 indicate that there is a negative rela-

tionship between return on equity and

generation tariffs. When the return on equity

reduces, the generation tariff increases. An

increase in return on equity by one percent

leads to a reduction in generation tariff by

65.7 percent. This result is not consistent

with findings of the Brattle Group (2005),

which concluded that a high return on equity

has a positive effect on the generation tariff.

Conclusion and Recommendations

The objective of this study was to examine

the relationship between the debt-equity

capital structure and the electricity genera-

tion tariffs in Uganda. The study found a

positive but not significant relationship be-

tween the debt portion in the capital struc-

ture and the generation tariff of electricity

generation projects.

There is a negative and statistically signifi-

cant relationship between the generation

technology and the electricity generation tar-

iff. The generation tariff is high for non-

renewable technology and low for renewa-

ble technology. Installed capacity is a statis-

tically significant variable in the determina-

tion of generation tariffs and there is a nega-

tive relationship between the installed ca-

pacity of the generation plant and the gen-

eration tariff of the respective plant. The

study has identified that generation tariffs

are low for electricity generation plants using

renewable technology and high for electricity

generation plants using non-renewable

technology. Government of Uganda and

Electricity Regulatory Authority should priori-

tise licensing and development of renewable

technology generation projects in order to

keep the generation tariffs low.

It is instructive to note that generation pro-

jects with small /low installed capacity tend

to have higher generation tariffs. The Gov-

ernment of Uganda and Electricity Regulato-

ry Authority should prioritise development of

bigger projects and ensure fully optimisation

of the project capacities in order to ensure

lower generation tariffs. Also the level of de-

velopment costs is a major determinant of

electricity generation tariffs in Uganda.

Measures should therefore be implemented

to minimise development costs in order to

ensure lower electricity generation tariffs.

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42

a3

3James Magombo, Bloodless Dzwairo, Sibusiso Moyo, Mendon Dawa, 2015


NON-REVENUE WATER ASSESSMENT STRATEGY FOR THE UMZINTO WATER SUPPLY SCHEME: TOWARDS GREEN ECONOMY James Magombo Durban University of Technology [email protected]

Bloodless Dzwairo Durban University of Technology [email protected]

Sibusiso Moyo Durban University of Technology [email protected]

Mendon Dawa Durban University of Technology [email protected]

Abstract Huge infrastructure investment is imperative for the collection, treatment and distribution of potable water. Prior to further investment into the production of potable water, more emphasis should be placed on utilizing the available resources. One of the major drawbacks in achieving a green econo-my in the water sector is the significant losses in potable water which are incurred after having invest-ed substantially in its production. If the current global trends continue, water demand is estimated to exceed supply by 40% within the next 20 years. This is an alarming situation when compared to the estimated 25-40% loss of this resource in developed countries and is worse in developing countries. In this study, a strategy for assessing and reducing Non-Revenue Water (NRW) in the Umzinto Water Supply Scheme (UWSS) was developed. The water supply scheme consisted of Pennington, Umzin-to, Umzinto Flats, Ghandinagar, Shayamoya, Park Rynie, Scottburg South, Scottburg Central, Amandawe, Malangeni, Amahlongwa and Imfume. The first eight areas are urban supply zones while the last four are rural zones.The method employed in the assessment was a combination of the top-down and component-based approach. A few modifications were allowed for, to enable the calcula-tion of NRW component as advised in the Standard South African Water Balance. Results of the NRW assessment for UWSS showed that Real Losses were a dominant component. As percentages of NRW, the components consisted of 65% Real Losses, 32% Apparent Losses and 3% Unbilled Au-thorised consumption. The NRW itself was 28% of the System’s Input Volume. From the assessment, a strategy that would help reduce the NRW was developed and coupled with this, is a discussion of how the strategy could contribute towards developing the green economy.

Keywords: Green Economy, Water Loss, Non-Revenue Water, Water Balance, Investment in Water.


43

Introduction

The primary goal of most drinking water

treatment plants is to provide potable water

to consumers. This is a complex process as

it should not only be governed by the water

quality and quantity. Consideration should

also be given to the great investment re-

quired for the infrastructure to collect, treat

and distribute water. Instead of just increas-

ing investment in the production of potable

water, greater focus needs to be put into uti-

lising the available resources. This is where

the concept of green economy comes in the

water sector where emphasis is that every

drop of potable water should be accounted

for. According to the current global trends,

water demand is estimated to exceed supply

by 40% within the next 20 years (Hoekstra,

2013, Olsson, 2015). This is an alarming

situation when compared to the estimated

25-40% loss of this resource in developed

countries and is worse in developing coun-

tries.

In this study, instead of just looking at water

loss, Non-Revenue Water (NRW) is also

considered. NRW is a better component of

measure as it considers the financial as-

pects of the water distribution system.

Mutikanga et al. (2011), defined NRW as the

difference between system input volume

and billed authorized consumption. Work by

Wyatt and Romeo (2011) described NRW

as comprising of physical losses and com-

mercial losses. Physical losses are made up

of pipe bursting and leakages while com-

mercial losses are a result of illegal connec-

tions, unmetered public stand pipes, meter

error and data recording errors.

The global NRW level is estimated to be at

35%. (Farley et al., 2008, Bhagwan et al.,

2014). Further, the global volume of NRW is

48.6 Billion Cubic Meter (BCM) per year of

which 32.7 BCM is real (physical) losses

(Kingdom et al., 2006, Aalto, 2014). In addi-

tion to this amount of water wastage, water

utilities incur costs as high as US$14 billion

a year in producing the water that is lost as

NRW. If half of this amount was saved, it

would be enough to provide water service

to an additional 100 million people with-

out further investments (Kingdom et al.,

2006, Farley et al., 2008).

It should be noted that there has been great

achievements in the development of both

technical strategies (pressure management,

flow monitoring) and operational manage-

ment to reduce physical losses by devel-

oped countries. However, developing coun-

tries have faced great difficulties in imple-

menting these strategies. Poor infrastruc-

ture, equipment that have been unmain-

tained for long periods, high unbilled water

through fraud and illegal connection have be

cited as the major contributors to their chal-

lenge (Liemberger et al., 2007, Frauendorfer

and Liemberger, 2010).

Langa and Quessouji (2007) raised the is-

sue of poor equipment and technologies in

developing countries with the example of

Maputo. The lack of flow meters or their

non-accuracy prevent a good knowledge of

the networks and make difficult the estab-

lishment of a precise water balance and

therefore action plans. The authors empha-

sized the fact that in their attempt to assess

the water losses in Maputo, most of the val-

ues were uncertain or based on estimated

data that prevented them to make any relia-

ble conclusions on volumes lost or any rec-

ommendations to tackle the losses. Fur-

thermore, they also missed data on the net-

work by itself due to poor installation condi-

tions, and illegal connections. Their recom


44

mendation under such circumstances was

installation of monitoring equipment and the

conduct of surveys on physical and com-

mercial data (Langa and Quessouji, 2007).

Gumbo and Van der Zaag (2002) experi-

enced the same difficulties in evaluating the

water balance of the Mutare water supply

system in Zimbabwe due to non-working

bulk meters or the absence of meters, espe-

cially for big consumers such as industries.

They also brought to the fore the role of po-

litical constraints that influence the prioritisa-

tion of objectives, choice of projects and al-

location of budgets. They noted the need to

assess water losses and ways of reducing

such losses before embarking on expensive

engineering projects to increase the volume

of water supplied (Gumbo and Van der

Zaag, 2002). This case illustrates the role

played by external pressure from politicians

and funders and underlines the complexity

of water projects and the need for strong

leadership.

In contrast, Mahmoudi (2007) revealed the

positive role played by the Iranian govern-

ment in addressing NRW by putting pres-

sure on the water and wastewater compa-

nies to allocate part of their budget to this

task. This led to improved water loss man-

agement through better operational practic-

es (leakage detection and quicker respons-

es to detection, replacements and the im-

plementation of new monitoring equipment)

in line with national standards whilst in-

stalling new branches and conducting pilot

projects (Mahmoudi, 2007).

Ndokosho et al. (2007) examined the rela-

tionship between a public utility and the

government in Namibia. The government

sets overall objectives, such as full recovery

cost, but the “Board of Directors” defines

specific targets and formulates policies to

achieve these objectives. While the water

utilities are generally not totally free to im-

plement new policies as they generally do

not have sole authority to set tariffs, this

governance system aims to reduce political

influence (Ndokosho et al., 2007). In this

study NRW assessment in the Umzinto Wa-

ter Supply Scheme (UWSS) was conducted

and discussion on a strategy reduction is

given.

Study Area

The UWSS is located in the Umdoni Local

Municipality and it falls in the Ugu District

Municipality. The supply scheme consists of

Pennington, Umzinto, Umzinto Flats, Ghan-

dinagar, Shayamoya, Park Rynie,

Scottburgh South, Scottburgh Central,

Amandawe, Malangeni, Amahlongwa and

Imfume. The first eight areas are urban sup-

ply zones while the last four are rural supply

zones.

The components of NRW in the UWSS will

generally include those in the South African

Water Balance. The components are:

Unpaid Water Bills (non-recovered

revenue);

Unbilled metered consumption

(authorised consumption);

Unbilled unmetered consumption

(authorised consumption);

Unauthorised consumption (apparent

losses);

Customer meter inaccuracies (apparent

losses);

Leakage on transmission and distribution

mains (real losses);

Leakage on overflows at storage tanks

(real losses); and


45

Leakage on service connections up to

the point of customer meter (real losses).

Unpaid Water Bills

This is usually a result of bad debts in the

water sector. The consumer would have

been billed but eventually they fail to pay

their bills. This water will exclude the

6Kl/month free basic water that is given to

every household in South Africa. The data

can only be obtained from the financial de-

partment at the Ugu District Municipality.

Unbilled Metered Consumption

These include the water being used in mu-

nicipal buildings, parks and swimming pools.

Another component here will be unreadable

consumer meters.

Unbilled Unmetered Consumption

This authorised component of unbilled water

comes from consumers that are billed on a

flat rate. The component adds to NRW when

the actual consumption is far much more

than the flat rate amount. In some cases

consumers who are billed actually take ad-

vantage of this arrangement.

In low income areas, stand pipes are enact-

ed. Users of the standpipes do not pay for

the water and hence it is a major contributor

to the unbilled metered consumption. With

most stand pipes being unmetered, the vol-

ume of water is often estimated and includ-

ed in the water balance. Major losses

through the stand pipes occur due to van-

dalism and lack of maintenance. The most

common criteria is a spindle that has been

removed from a tap and the water just runs.

Adding to the unbilled unmetered consump-

tion is the use of fire hydrants. Most fire hy-

drants are unmetered and are subsequently

subject to abuse from consumers through

illegal connection. In some cases, taxi driv-

ers can use the hydrants to wash their vehi-

cles. Beside these illegal activities, the vol-

ume of this portion of unmetered consump-

tion will also include the water lost when the

hydrants are opened to reduce pressure in

the distribution system before maintenance.

Unauthorised Connection

Like any other municipality, Ugu District Mu-

nicipality also has to deal with problems of

illegal connections. In South Africa, water

connections are deemed illegal when the

consumer connects directly to the water

source without the consent of the municipali-

ties. The most common forms of unauthor-

ised connections involve the by-passing of

meters and connecting on to air valves.

Customer Meter Inaccuracies

With time, customer meters lose their accu-

racies. The accuracy of the meter is also

dependent on the water quality. In the

UWSS, age is the main determinant of me-

ter accuracy. This is a very difficult compo-

nent to estimate volume of water that has

been lost through an inaccurate meter.

Leakage on Transmission and Distri-

bution Mains

When there is excessive pressure, mains

can burst and this can be a significant con-

tributor to real losses in the UWSS. Another

component from the mains is the back-

ground leaks. To control these two sources

of loss, the municipality has a pressure

management programme and invests into

the maintenance of the distribution system.

Community awareness programmes are run

to help the consumers understand their


46

role in reducing water loss. This is very es-

sential for the municipality to reduce or elim-

inate unreported leaks. When consumers

are not educated about the importance of

reporting water leaks they will not do so un-

less their household taps run dry.

Leakage and Overflows at Storage

Tanks

The municipality has a good reservoir bal-

ance system to avoid these leakages. The

system will contain meters, valves and con-

trol systems at the reservoirs. Although wa-

ter losses cannot be reduced to zero, this

type of water loss is very minor in the

UWSS.

Leakage on Service Connections up

to the Point of Customer Meter

In most systems, leakage from connections

is by far the greatest source of physical

leakage; often 80% or more of the total

physical losses. A portion of the service

connection leakage also contributes to the

unavoidable annual real losses. The total

volume of water lost as a result of this leak-

age is therefore dependant mainly on the

number of service connections within a sys-

tem and the average operating pressure.

Methods

The method employed in the assessment

was a combination of the top down and

component based approach. A few modifi-

cations were allowed to enable the calcula

tion of NRW components as advised in the

Standard South African Water Balance. This

is because the top-down, bottom-up or the

component based approach were seen to

be inappropriate for the UWSS unless they

were modified or combined. The top-down

approach makes an assumption on the input

volume that lead to underestimation of ap-

parent losses.

The approach assumes that the unauthor-

ised consumption will be at least 0.25% to

1% of the input volume. Liemberger et al.

(2007) show that the bottom approach can

be applied to distribution systems that meet

particular hydraulic conditions. This makes it

difficult to apply it on the UWSS.

The limitation for the third method is its well-

known uncertainty. The component based

analysis is data driven hence its accuracy

will be depended on the accuracy and com-

pleteness of the data. For the UWSS, some

values are estimated hence it affects the ac-

curacy. To mitigate this, it is usually not en-

couraged to use this approach on its own.

Evaluation Steps

The first step was to determine the NRW by

subtracting the volume of billed water for the

UWSS from the volume of the water pro-

duced by the Umzinto water treatment plant.

The next step involved the calculation of the

NRW components. The evaluation steps are

illustrated in Figure 1.

Figure 1 Steps involved in the calculation of NRW of the UWSS


47

.

Figure 2 General Framework to be taken in Determining the NRW

Determining volume of NRW

It should be noted that the time period of the

billing month does not coincide with that of

the production month. The meters also will

have some inaccuracies. This means before

the NRW is determined, adjustments should

be done to account for these. The produced

water volume was obtained from the SIV da-

ta reading and adjustments were made to

account for the inaccuracies. The volume of

the billed consumption is obtained for both

the metered and unmetered connections.

After correcting the time, the adjusted NRW

volume is obtained.

Adjusted NRW = Adjusted Produced Water – Adusted

Billed Water

Figure 2 shows the general framework to be

taken in determining the NRW. AWWA

(2009) recommends a period of at least one

year for assessing the NRW levels. This

makes it possible to take into consideration

the seasonal variations. In this study the da-

ta used was for the year period ending De-

cember 2013. The system input volume

(produced water) was adjusted for produc-

tion meter inaccuracies. Since it is not pos-

sible for the time frame of this study to con-

duct accuracy analysis and experiments for

the production meters, the production meter

inaccuracy was assumed at 7% under-

registration based on the estimation of the

production unit in Umzinto water utility. This

estimation is justified by the following:

There is no maintenance programmed

for production meters. The production

meters are examined or maintained only

once they have stopped working or when

readings being obtained from them are

too low.

Some meters are not installed according

to their manuals that require minimum

straight distance before water meter or

specified sizes of pipe diameters.

Setting Time Period

Measure SIVCalculating Billed Metered

Consumption

Adjusting For Input Meter

Accuracies

Computing Billed

Unmetered Consumption

Adjusting Time Lag of

Supply and Billing

Determining the NRW


48

Billed Metered and Unmetered Consumption

Metered consumption and the estimated unmetered consumption of customers with flat rate pol-

icy were obtained from the billing records of Umzinto water utility. Then the billed water (me-

tered and unmetered) was summed.

Lag Time Adjustment

For the reason that water produced in Umzinto water utility is billed after a month,

the production data were taken for all the months of the in 2013 except January 2013. Instead,

the billed consumption for January 2014 was counted to represent the consumption of Decem-

ber 2013. Other time lag adjustments were neglected. After all adjustments, NRW volume was

determined by subtracting the adjusted volume of billed water from the adjusted volume of pro-

duced water.

Estimating Unbilled Authorized Consumption

Unbilled authorized consumption has two types; metered and unmetered. The unbilled metered

consumption in the UWSS consists of the consumption of the staff in buildings belonging to the

utility as they are metered. The unbilled unmetered consumption in Umzinto water utility con-

sists of water used for pipes washing, fire-fighting, special institutions, and consumption of

some notable people. All these types are supplied by means of water tankers, and thus esti-

mated by the number of the tankers per year for each type in every administrative zone. The

unbilled authorized consumption (metered and unmetered) was estimated by obtaining relevant

data from the internal reports of the utility.

Calculating Real and Apparent Losses

As the apparent losses are defined and the unbilled authorized consumption is estimated, then real

losses could be calculated straight forward from the following formula:

𝑅𝑒𝑎𝑙 𝐿𝑜𝑠𝑠𝑒𝑠 = 𝑁𝑅𝑊 − 𝐴𝑝𝑝𝑎𝑟𝑒𝑛𝑡 𝐿𝑜𝑠𝑠𝑒𝑠 − 𝑈𝑛𝑏𝑖𝑙𝑙𝑒𝑑 𝑎𝑢𝑡ℎ𝑜𝑟𝑖𝑧𝑒𝑑 𝑐𝑜𝑛𝑠𝑢𝑚𝑝𝑡𝑖𝑜𝑛

Results Results of the NRW assessment for UWSS showed that Real Losses were a dominant component. The

NRW components consisted of 65% Real Losses, 32% Apparent Losses and 3% Unbilled Authorised

consumption. The NRW itself was 28% of the System’s Input Volume.

Percentage of NRW in the System input Volume

NRW in the UWSS makes up 28.1% of system input volume and these amounts to 5017 Kl/day.

Table 1 shows the volume of NRW, the volume of billed water, and the adjusted volume of pro-

duced water with consideration to time lag adjustment in the period starting July 2013 to June

2014. Figure 3 illustrates the percentage of NRW in the System Input Volume.


49

Table 1: Volume of NRW in the UWSS for the year ending in June 2014

Table 2: Volumes of metered and unmetered unbilled authorized consumption for the year end-

ing June 2014

Figure 3 Percentage of NRW in the System Input Volume.

72%

28%

Billed Water

Non-Revenue Water

Produced Water (Kl/year) Total Billed Water

(Kl/year)

NRW

Measured 6193651 Metered 4285185 Kl/year 1831060

Adjusted for Me-

ter Accuracies

325981 Unmetered 403387 Kl/day 5017

Total 6519632 Total 4688572 % of system

input volume

28.1

System Input Volume (Kl/day) 5017

Billed Water (%) 72

Non-Revenue Water (%) 28

Apparent Loss (%) 9

Real Losses (%) 18

Unbilled Authorised Consumption (%) 1


50

Components of Authorised consumption

Authorised consumption consisted of metered and unmetered, billed and unbilled consumption.

Table 2 shows that for the year 2014, the total volume of unbilled authorized consumption was

68364 Kl/year which made up 1% of the system input volume. Figure 4 shows the components

of consumption in the UWSS.

Figure 4: Components of Authorised consumption for the UWSS

Table 3: Volume of Apparent and Real Losses in the UWSS

Apparent Losses Real Losses

Kl/year 580598 1182098

Kl/day 1591 3238

% of System input Volume 9 18

Table 4: Components of NRW in the UWSS

Metered (Kl/Year) Unmetered (Kl/Year) Total

Billing Database

Shortfall

65292 Municipal use,

Fire water, and

Flushing of Pipes

and Reservoirs

3072 Kl/year 68364

Kl/day 187

% of System

Input Volume

1

1%< 1%

99%

Unbilled Metered Consumption

Unbilled Unmetered Consumption

Billed Authorised consumption


51

Components of NRW Breakdown

Table 5 shows the System Input Volume, its components are Billed Water and NRW. It also

shows three components of NRW as percentages of System Input Volume. Figure 5 shows that

Real Losses are the dominant component of NRW making up 65% of NRW and 18% of the

System Input Volume. Apparent Losses make up 9% of System Input Volume and stand for

32% of NRW volume as shown in Figure 5. Unbilled authorized consumption make up 1% of the

System Input Volume

Figure 5: Components of NRW in the UWSS

Water Balance for UWSS

Table 5 illustrates the final results of NRW assessment for the UWSS in Kl/year. The water bal-

ance is different from the Standard South African Water Balance in the sense that the free basic

water is taken as a component of the billed authorised consumption.

Table 5 Water Balance for the UWSS in kl/year

System Input Volume 6 519 632 kl/year

Authorised Consump-tion4 756 936 kl/year

Billed Authorised Consumption

4 688 572 kl/year

Exported Water

71 547 kl/year

Potential Reve-nue Water

4 688 572 kl/month Billed Metered Consumption

4 285 185 kl/year

Free Basic Water (Stand-pipes) 331 840 kl/year

Unbilled Authorised

Consumption

68 364 kl/year

Unbilled Unmetered Con-sumption 3 072 kl/year

Non-Revenue Water 1 831 060 kl/year

Unbilled Metered Consump-tion

65 292 kl/year

Water Losses 1 762 696 kl/year

Apparent Losses 580 598 kl/year

Unauthorised Consumption 430 616 kl/year

Metering Inaccuracies

149 981 kl/year

Real Losses

1 182 098 kl/year

Mains and Distribution Leaks

969 321 kl/year

Reservoir Overflows

5 910 kl/year

Service Connection Leaks

206 867 kl/year

65%

32%

4%

Real Losses

Apparent Losses

Unbilled Authorised Consumption


52

Discussion

When developing a NRW strategy for any

water network it is crucial to put focus in its

design and introduction. A review should be

conducted to gain a full understanding of the

network’s behaviour and operation. From

water audits such as NRW assessment, the

levels of water losses should be quantified.

For example the NRW assessment for

Umzinto showed that Real Losses were

high. This is what should inform the setting

targets and dividing them between short and

long term. A good strategy would consist of

an appropriate mix of NRW reduction activi-

ties combatting the different causes of water

loss.

In the planning and design stage, a NRW

strategy should stipulate ways of dealing

with the inadequate background data in the

supply schemes/systems. This is a major

challenge for small water supply schemes

and was a major contributor in the selection

of a method to assess NRW for the UWSS.

Baseline field measurements such as flow

(System Input Volume and Minimum Night

Flows) and pressure should be reliably set.

In addition there should be a centralised

(and electronic) information database to fa-

cilitate research and data analysis. The

most important aspect of a NRW strategy is

to clearly stipulate its purpose. For example,

a strategy can be developed to reduce water

losses to an acceptable or economic level

and to improve performance. In some case

it can include or just involve the mainte-

nance improvements gained.

NRW strategies should be developed with

the aim of improving sustainability in water

supply schemes. This can only be achieved

if the financial components involved are fully

considered. In a supply, an economic level

of leakage should be set. This defines the

relationship between cost of saving water

and its value (Lim et al., 2015). It is evident

that more support would be given to a strat-

egy in which the cost of saving water is low-

er than its value. A plan to sustain the cash

flow during the strategy implementation

should be in place as some of the activities

such as customer meter replacement can

have long payback periods of at least one

year. It will be very important for any water

utility to make sure that all the advances and

improvements that are made in introducing

the water loss strategy are sustained. This

involves the following activities:

• Ensuring appropriate staffing levels

• Staff education and training

• Operation and Maintenance

• Assessing and monitoring

performance

Conclusion

Evaluation of NRW is an integral phase of

designing a management strategy to reduce

and control water losses in a distribution

system. This is important to ensure that the

greatest possible percentage of water

treated by a treatment plant reaches the

consumer and is turned into revenue. The

process can be demanding and data con-

suming. To make it efficient there is need to

prioritise components of NRW in a water

distribution system. This study assessed

NRW components for UWSS and suggest

an approach which water utilities could use

to breakdown NRW and efficiently draw up

water balances.

NRW consisted of 65% Real losses, 32%

apparent losses and 3% Unbilled Authorised

consumption and it was concluded that Real

losses are a dominant component of NRW

for UWSS.


53

Acknowledgments

Durban University of Technology (DUT) is

sincerely acknowledged for the financial

support during the Masters research.

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Author Guidelines

In order for the manuscript to be published in JGED it should at the minimum meet the following criteria:

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55

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