By Amuji,
HO; Nwachi, CC; Tasie, NN; Mbachu, JC; Owolabi, WT (2023).
Correlation Analysis
of Enugu Electricity Distribution Company’s Electricity Bill
Harrison O. Amuji1*,
Christy C. Nwachi2, Nicholas
N. Tasie3, Justice C. Mbachu4 and Wale T. Owolabi5
1,5Department of Statistics, Federal
University of Technology, Owerri, Nigeria
2Department of Urban and Regional
Planning, Federal University of Technology, Owerri
Nigeria
3Department of Physics, Rivers State
University, Portharcourt Nigeria
4Department of Maritime Management
Technology, Federal University of Technology, Owerri
Nigeria
Emails:
1harrison.amuji @ futo.edu.ng, 2christynwachi @ gmail.com 3nickarta @ gmail.com 4justice.mbachu
@ futo.edu.ng 5taiwo.owolabi @ futo.edu.ng
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ARTICLE INFO
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ABSTRACT
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Article No.: 030123022
Type: Research
Full Text: PDF, HTML, PHP, EPUB
DOI:
10.5281/zenodo.7765101
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In this paper, we
carryout correlation analysis to analyze the
expenditure made by the users of electricity and the actual quantity of
electricity their given amount of money can buy for them. We observed from
the study that electricity users spent more money to get the same value
(quantity of electricity), and the relationship between these two variables
are inverse with correlation coefficient of  . That means that as one
is increasing, the other is decreasing.
The effect of this is so drastic and a reflection of what Nigerians face
generally in the other sectors of the economy. From the study, we also found
that tariff rate and value added tax is inversely related to quantity of
electricity. This means that both tax and VAT deplete the quantity of
electricity that is bought by the consumers. The only variables that have
direct relationship with each other are tariff rate and value added tax.
Both of them move in the same direction. The overall effect of these
relationship points to the fact that people spent more money in Nigeria now
to get the same value they used to get before. Hence, the cost of living is
high and increasing while the standard of living is falling and inflation is
at alarming rate.
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Accepted: 02/03/2023
Published: 23/03/2023
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*Corresponding
Author
Harrison O. Amuji
E-mail: harrison.amuji@ futo.edu.ng
Phone: +234 803 647 8180
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Keywords: Correlation,
Multivariate analysis, Energy sum, Quantity of electricity, Tariff rate,
Value added tax
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1. INTRODUCTION
Electricity all over the world is known for its importance in industrial
development, household supply of energy, economic growth and development; aid in
doing various businesses, help immensely in electronic dependent works and
businesses, and contributes to the GDP of a country. The importance of
electricity to human lives cannot be over stressed and for this reason, any
country that wants to be industrialized must take constant supply of electricity
as a priority. In Nigeria, electricity supply has been a problem from one
administration to another. The amount of public fund invested in the power
sector starting from 1999 when the country returned from military rule to
democracy and up to date was enormous and yet the problem of electricity
persisted.
Nigeria has severally changed her policies on electricity with corresponding
change in nomenclatures. Prior to 1999, the name was NEPA (National Electric
Power Authority) and it was changed to PHCN (Power Holding Company of Nigeria)
after the return of democracy with some innovations; huge investment to
stabilize the electricity sector and enhance electricity supply. In some few
years ago, the government of Nigeria succeeded in privatizing the power sector.
The privatization was based on the geopolitical zones of the country. Our
interest in this paper is on the South East geopolitical zone of Nigeria. In the
South East, the name of the electricity distribution company is called EEDC Plc
(Enugu Electricity Distribution Company). EEDC - one of the distribution
companies (DISCOs) - buys some quantity of electricity from electricity
generating companies (GENCOs). GENCOs are made up of public and private
electricity generating companies regulated by NERC (National Electricity
Regulatory Commission). The sole purpose of these DISCOs is to provide
electricity to companies, industries, businesses, households etc, and make
profit as business enterprise. Generally, EEDC operate at a loss because of her
inability to track non customers who use the electricity. For this reason, her
customers are made to pay for the electricity used by the noncustomers through
the charge of higher electricity bill. This higher bill is passed to those
customers whose bio-data are in the data base of EEDC.
EEDC Plc engages in
electricity distribution in the South Eastern part of Nigeria. The company is
based in Enugu capital city, Enugu State Nigeria. EEDC Plc
is a subsidiary of Power Holding Company of Nigeria (PHCN). On September 11,
2013, Enugu Electricity Distribution Plc was
commissioned to operate as a subsidiary of Interstate Electrics Limited. It was
fully owned and funded by the Nigerian Government until November 1st, 2013 when
it was acquired by Interstate Electricity Limited following the Privatization
of the power sector by the Federal Government of Nigeria. The company
distributes electricity across the five south eastern states, namely; Abia, Anambra, Imo, Enugu and Ebonyi States. The geographical area covered by EEDC is
about 30,000km2 and EEDC’s Business operations are managed by 18
Business Districts (BD) and 148 service centers spread across the five south
east states. The service centers are managed by a feeder manager while the
districts are managed by district managers who reports to the corporate
headquarters in Enugu. The census population of this geographical area is
estimated to be about twenty-one million (21,000,000) in 2018. However, EEDC’s
customer population is about 800,000 revealing a huge gap or variance between
census population and customer population for the distribution company. This
gives a ration of 1:26, meaning that every one customer of EEDC has twenty-six
dependents. Put differently, in every twenty-six persons using electricity in
the geographical area, there is only one customer of EEDC that pays for electricity
bill. This makes it practically impossible for the distribution company to
breakeven, and this has posed a lot of challenges to EEDC in particular and
other distribution companies (DISCOs) in Nigeria. The main problem facing
Electricity Distribution Companies in Nigeria is high Aggregate Technical,
Commercial and Collection (ATC&C) loses. The
ATC&C loss of EEDC stood at 63.38% of total revenue
received as at November, 2018 compared to all other Nigeria DISCOs average loss
of 49.15%. This loss is the difference between the amount of electricity
received by a distribution company from the transmission company and the amount
of electricity for which it issued invoices to her customers plus the adjusted
collection loss. The aggregation of the losses
is a technique for assessing the overall performance of a utility company
(EEDC). This
ATC&C loss is estimated to be about 24 billion naira yearly and has been
accumulating since the takeover of the electricity distribution company by EEDC
in 2013, Anyalewechi (2018).
It is
obvious, in order to survive in the business where the estimated majority of
electricity users are not paying the monthly electricity bills, EEDC introduces
a higher tariff rate compared to other DISCOs in Nigeria and this is affecting
the real customers. And since the same tariff
rate applies to different states under EEDC, the researchers restricted
themselves to Enugu districts for the study. The study concentrates on those
who use pre-paid meters to determine their electricity bills. Electricity bill
(a kind of printed receipt for electricity purchased by customers) comprise of
four variables stated in the bill namely; the energy sum measured in naira, the
energy measured in kwh, the tariff rate measured in naira and the value added
tax (VAT) measured in naira. These variables keep changing to reflect the
economic situation of the country. And we want to see how these variables (variates) correlate with one another and the economic lives
of Nigerians using EEDC Plc as a case study.
Hence, correlation is the measure of the
extent of relationship among variables, where both dependent and independent
variables are random. Since we have multiple variables of interest called variates, we applied an aspect of multivariate analysis to
determine the nature of relationship that exists among the variates.
This paper is aimed at applying correlation analysis to determine the degree and
nature of relationship among the variates (the energy
sum (N), quantity of electricity (kwh), tariff
rate (N) and value added tax (VAT) (N). The paper is divided into
five sections as follows: In section one; we give the general introduction of
the work. Section two was devoted to literature review. In section three, we
treated materials and methods. In section four, we implemented the developed
model and finally, in section five, we treated results and discussions.
2. LITERATURE REVIEW
We want to determine the relationship between the expenditure on electricity,
the quantity of energy (kwh), the tariff rate, value added tax (VAT) and their
impact on the customers. The cost of living would compare with the minimum
expenditure necessary to maintain the representative consumer at the same level
of well-being at different time periods or sets of prices, William (1999). But
this is slightly different because it is concerned with the extent of the
relationship and the direction of the relationship among the variates. This will
help to determine the cost; standard of living and inflation in the electricity
sector on one hand and the economy at large.
The analytical
framework for cost-of-living measurement is based on the assumption that a
household is trying to achieve the highest possible standard of living while
staying within its budget Dale and Daniel (1999). All common articles of consumption had fixed prices which often
did not change for a lifetime, and if any dealer had attempted to charge more
than custom demanded, it would have attracted the attention and aroused the
indignation of the whole community, Alan (2007). These conditions have been so
altered today that a merchant like EEDC has the monopoly of electricity supply
in the south eastern part of Nigeria and can charge their customers whatever
they like at any given time as electricity bills.
Properly measuring inflation is an essential
ingredient in economic policy making, setting optimal contracts, guiding
monetary policy, and determining the financing needs of all levels of
government. In trying to do this, some errors are incurred, but increasing
sample size not only will reduce bias, but also will eliminate the variance
effects of sampling error, Ralph (2007). Inflation plays a central role in economic policymaking, as well as
influencing decisions made by individuals. Consumers, economists, and
policymaker’s commonly use the consumer price index (CPI) as a measure of
inflation. However, critics have suggested that several sources of bias in the
CPI result in an overestimate of changes in the cost of living, Denise
and Hill (2003). What actually happened
was that biases were not initially considered before constructing various CPI’s
and hence, a heavy presence of bias that leads to over or under estimation of
inflation. In this study, inflation and cost of living are relative and not
pronounced. But the nature of the relationship among the variates
will indicate the economic status of the general consumers of electricity in
Nigeria.
3. MATERIALS AND
METHODS
The variables of
interest in this study are the Energy sum (N) (that is expenditure on
electricity), energy (kwh) (that is, the quantity of
electricity a specific money can buy), tariff
rate (N) and value added
tax (VAT) (N). Each of the variates are
represented by 
, i = 1, . . . , 4, and each of the variates dependent of the other, Arua et al (2000), Amuji et al (2022).
Assumption:
The
following are the assumption that must be satisfies before we apply correlation
analysis on the EEDC data:
1.
The data (variates) are dependent on one another
2. 
;
the correlation coefficient lies between minus one and plus one
3. 
;
implies that there is no relationship between the variables i and j.
4. 
;
perfect positive correlation
5. 
;
perfect negative correlation
The closer the correlation coefficient gets to one the stronger the relationship
and the more it gets closer to zero the weaker the relationship. A correlation
coefficient with positive value has a direct relationship between the variables
while a negative value indicate an inverse relationship. These relationships
among the variates correlate with the economic status of the customers, that use
the electricity. Correlation coefficient is a dimensionless quantity and
therefore has no unit of measurement.
Multivariate data are data collected on
several dimensions or characteristics of the same individual or item or
experimental trial, Onyeagu (2003). In this paper, we
are interested in four variates namely; Energy sum (N)
represented by the random variable (X1), energy (kwh)
represented by (X2), tariff
rate (N) represented by (X3) and value added tax (VAT) (N) represented by (X4).
These are multivariate data from the EEDC electricity bill considered in this
paper. The data was collected from customer’s electricity bills over a period
of six years, 2016 to 2021. We applied multivariate analysis since we are
considering many dependent variables at the same time and their effects
compared simultaneously, multivariate analysis provide the best model for such
a problem.
5.2 DISCUSSION
In this paper, we analyzed the energy sum; that is, the expenditure made by the
users of electricity, and the actual value (quantity of electricity) their money
can buy for them. We observed from the study that electricity users spent more
money to get the same value (quantity of electricity), and the relationship
between these two variables are inverse. That means that as one is increasing,
the other is decreasing. The effect of this is so drastic and a reflection of
what Nigerians face generally in the other sectors of the economy. From the
study, we also found that tariff rate and value added tax is inversely related
to quantity of electricity. This means that both tax and VAT deplete the
quantity of electricity that is bought by the customers. The only variables that
have direct relationship with each other are tariff rate and value added tax.
Both of them move in the same direction. The overall effect of these
relationship points to the fact that people spent more in Nigeria now to get the
same value they used to get before. Hence, the cost of living is high and
increasing while the standard of living is falling and inflation is at alarming
rate.
Competing Interests
There
is no competing interest
Authors Contributions
Each
author contributed in the preparation of the manuscript, Literature review
analysis and presentation of the work.
REFERENCES
Alan
K (2007). Yesterday's Bad Times Are Today's Good Old Times: Retail Price
Changes Are More Frequent Today than in the 1890s. Journal of Money, Credit and
Banking, 39: 1987-2020.
Amuji H O, Moneke U U, Igboanusi
C and Onukwube O G (2022). Modelling the
generation/transmission and distribution of electricity. Far East
Journal of Applied Mathematics, 114:49-64.
Arua A I, Chigbu P E, Chukwu
W I E, Ezekwem C C and Okafor F C (2000). Advanced Statistics
for Higher Education. Academic
Publishers, Nsukka Nigeria, 193-198.
Anyalewechi U N (2018). The relationship between GIS consumer
indexing and loss reduction in Enugu Electricity Distribution Company. A Dissertation Presented to the
Department of Administration, Faculty of Management Sciences, Enugu State
University of Science and Technology, Enugu Nigeria, 16-17.
Dale
W J and Daniel T S(1999). Indexing
Government Programs for Changes in the Cost of Living. Journal of
Business & Economic Statistics, 17:170-181.
Denise
H and Hill D C (2003). Calculating the Candy Price Index: A Classroom Inflation
Experiment, The Journal of Economic Education, 34:
214-223.
Ralph
B (2007). Analytical Bias Reduction for Small Samples in the U.S. Consumer
Price Index,. Journal of Business & Economic
Statistics, 25:337-346.
Onyeagu S I (2003). First
Course in Multivariate Statistical Analysis. Megaconcept Publishers. Awka Nigeria 1-18
William
D N (1999). Beyond the CPI: An Augmented Cost-of-Living Index. Journal of
Business & Economic Statistics, 17: 182-187.
