QUALITY OF ELECTRICITY SUPPLY AND ITS IMPLICATIONS ON HOUSEHOLDS WELFARE IN NIGERIA CHAPTER ONE 1
QUALITY OF ELECTRICITY SUPPLY AND ITS IMPLICATIONS ON HOUSEHOLDS WELFARE IN NIGERIA
Electrical energy has always been and will always be one of the vital requirements of human societies, and presently its demand is far greater than ever in both developed and developing countries. The United State Energy Information Administration (EIA) noted in the International Energy Outlook report for 2013 that the global energy demand and generation are growing. World net electricity generation is projected to increase by 93% from 20.2 trillion kilowatt hours in 2010 to 39.0 trillion kilowatt hours in 2040 (EIA, 2013). This is buttressed by the fact that electricity is vital to human life, for his technological advancements. It is especially fundamental for emerging economies whose national developmental agenda require constant availability of power. Inadequate supply of energy restricts socio-political development, limits economic growth, and adversely affects the quality of life of citizens, both in urban and rural areas. Improved energy supply results in improved standards of living, which manifests in increased food production and storage, increased industrial output, provision of efficient transportation, adequate shelter, improved healthcare and enhancements in other human services.
Many households rely on electricity for performing domestic activities like cooking, washing, ironing, and lighting, among others. With technological advancement, people have become more and more dependent on electric power since most of these technological devices are powered by electricity. Electricity therefore is considered the fastest growing form of delivered energy in the world (EIA, 2013).
Nigerian total electricity net consumption has increased from 14,270 GWh in 2002 to 23,940 GWh in 2014 (IES, 2015). Recent data from World Bank also shows that the quantum of electricity consumed in Nigeria increased steadily from the 122.98 kWh per capita in 2004 to 143.65 kWh per capita in 2014 (WDI, 2016). This showed that demand for the supply of electricity has been trending upwards and it is a basic fact that reliable electricity supply is a critical factor and a catalyst for any industrial development. About half of the amount of electricity consumed domestically is estimated to be consumed by residential consumers for household uses such as lighting, ironing, refrigeration, air conditioning, television, etc. while commercial and industrial users account for the other half of domestic consumption.
Presently, majority of Nigerian population do engage in income earning activities from their homes using their computers and the internet while others engage in small scale economic activities such as tailoring, laundry services and hairdressing, among others that require electricity. Leisure, which is an important argument in a worker’s utility function, is also affected by electricity since some acts of leisure may require the use of electric energy. In fact it is becoming extremely difficult to live without electricity, especially in the cities where the benefits of electricity are more visible to residents. Electricity demand continues to grow because urbanization allows newly urbanized segments of the population to expand their electricity consumption. Iana Vassileva (2012) pointed out that increasing energy consumption is one of the relevant concern societies are facing in recent times. Incessant population growth, booming technology, society growth and increase comfort are some of the reasons noted.
Due to this heavy reliance on electricity, residents of both urban and rural communities always agitate whenever electricity supply is interrupted by the authorities involved.
Quality of electricity supply is more than just the availability of the power which an average layman is accustomed to. Quality of supply is normally split in three different dimensions: continuity of supply, voltage quality, and commercial quality.
Continuity of supply is related to availability of the service. This aspect of quality of service is the most relevant for customers since power supply is crucial for today’s way of living. The fewer the instances of interruptions and the shorter these interruptions are, the better the supply is from the customer’s point of view. For that reason, continuity of supply is determined by the number and duration of supply interruptions and it is extremely related to network investments and practices of operation and maintenance by distribution operators.
Voltage quality includes every technical aspect of the distributed electricity apart from outages. It is simply referred to as the usefulness of electricity when there are no interruptions. When the voltage quality (the usefulness) is very poor, several problems may arise in the use of electrical appliances and electrical processes. Naturally, voltage quality is more complex to regulate as it includes many quality issues and in turn each issue have several dimensions.
Regarding commercial quality, it is considered that is directly associated with transactions between electricity companies (either Distribution Companies or Generation Companies, or both) and customers, and covers not only the supply and sale of electricity, but also various forms of contacts between electricity companies and customers. The nature of the quality of electricity service or supply goes a long way in affecting the welfare of households. The Distribution Companies (Discos) should be responsible and accountable in guaranteeing these three dimensions of electricity service because they have the direct interaction with the end users.
The electricity generating and distributing companies, being human institutions and especially state owned institutions have their own fair share of internal challenges. Ineffective management practices and laxity on the part of workers are somehow responsible for the inefficient supply of electricity to consumers. Also, some members of the public do not pay electricity tariffs by making illegal connections to their homes and offices, sometimes even with the help of staff of the distribution companies. These factors among others have made it difficult for the producers, transmitters and the distributors of electricity to provide constant power supply free from interruptions.
1.1 Problem Statement
However, despite the importance of electricity to many households and industries in Nigeria, electricity supply has been epileptic and never reliable. There are indiscriminately power outages and worst of all is that there are no prior notification to consumers. The energy challenge is so recurrent that the acronym for the old state-owned electricity company, NEPA (National Electric Power Authority), was sarcastically rendered as ‘Never Expect Power Always’. When the name was changed to PHCN (Power Holding Company of Nigeria) it was twisted to mean the ‘Please Hold Candles Nigerian’ and ‘Problem Has Changed Name’. Nigeria’s growth potentials will remain unrealized if the power sector challenges are not addressed. Although Nigeria has 12.5 GW of installed generation capacity, less than 5,000 MW is typically available (USAID Power Africa Factsheet, 2017). The gross inadequacy of energy generation becomes glaring when compared with South Africa’s almost 4,229 kWh per capita (WDI, 2014). Indeed, 60 per cent of the time, there is no access to electricity in Nigeria (Aliyu et al. 2013). Most times, even when there is power supply, the service quality is so poor that customers prefer the use of their personal generators since they tend to be more reliable than services gotten from the Distribution Companies (Discos).
Nigerian electric power has been so epileptic that the Nigerian economy has been described as a generator economy (IseOlorunkanmi, 2014). The Manufacturers Association of Nigeria (MAN) and the National Association of Small Scale Industries (NASSI) estimated that their members spend an average of about N2billion (about $12 million) per week on self-power generation. A series of power sector polls conducted by NOI Polls Ltd for the second quarter of 2013 revealed that about 130 million, representing 81 per cent, out of the 160 million Nigerians generated their own electricity through alternative sources to make up for irregular power supply. IseOlorunkanmi (2014) pointed out that the study also showed a combined average of 69 per cent or 110 million of Nigerians experienced greater spending on alternative electricity supply. There are a lot of factors responsible for such unreliable electricity supply. These include the high demand for electricity which exceeds supply. The supply-demand gulf exist because of myriads of reasons: obsolete and dilapidated plants with 36% of installed capacity are over 20 years old; 48% are over 15 years old and 80% are over 10 years old (Adenikinju, 2003), lack of and poor maintenance of existing plants and poor managerial efficiency. There is also the problem of inconsistent supply of gas from the West Africa Gas Pipeline Company (WAGPCo) and other domestic gas producers to feed power plants in Nigeria– a situation which may be beyond the control of the generating companies. Also, there are transmission and distribution challenges faced by the Transmission Company of Nigeria (TCN) and the other distribution companies such as obsolete infrastructure, poor planning, among others. This, coupled with the low capacity to repair broken down power infrastructure on time and political selfish interests have contributed to power interruptions. Just about few months ago, for example, power generation crumbled completely to zero megawatt and remained like that for about three hours. Industry operators revealed that as a result of the complete collapse, no electricity distribution company received load allocation and the country was in total blackout that period. Sources in the power sector blamed the complete collapse in power generation on the extent of destruction of infrastructure and gas pipelines vandalism which had happened in the industry over the past years, as well as the poor upgrade of power installations across the country. This pathetic event even eliminated the option of load shedding which has become a constant phenomenon for years across the country.
Furthermore, the utilities report low cost recovery, resulting from consumers, particularly households paying lower tariffs than the average cost of production. This has been a concern for the service providers over the years. The power sector is characterized by substantive up-front fixed costs, and it takes many years for capacity to be fully utilized. Beyond that, costs vary across times of the day (peak/off-peak), seasons (dry/rainy), users (residential/commercial), and geographic areas (urban/rural), which should be taken into consideration when setting prices that promote efficient use (Briceño-Garmendia C. ; Shkaratan M., 2011). Electricity prices in Nigeria are currently below production costs. Therefore, the industry is barely able to generate enough revenue to cover its operating costs let alone meet its considerable capital expenditure needs (IseOlorunkanmi, 2014). Government regulation, mostly for equity reasons, has on many occasions allowed consumers of electricity to pay less than the cost of the electricity they consume. These tariffs were below cost recovery as reported by the utilities and made it difficult for the power producers to recapitalize. Since the establishment of The Nigerian Electricity Regulatory Commission (NERC) tremendous steps have been taken to address this issue with the tariff approach called the Multi Year Tariff Order (MYTO) which tries to ensure that prices charged by licensees are fair to the consumers and sufficient to allow the licensees to finance their activities and to allow for reasonable earning and profits for efficient operation. NERC has progressively been trying to increase tariffs to cost recovery levels but the real cost effective tariff level is yet to be achieved, especially for household consumers.
There have been constant concerns raised by Nigerians for the government and service providers to improve upon electricity service delivery. This is due to the fact that households and industries do suffer social and economic losses in the event of unannounced power outages to the point that many of them may be willing to pay higher tariffs if that will ensure an improved supply of electricity. After all, the cost of running other conventional backup power generators over time is very expensive.
There are a lot of economic losses that electricity customers are bound to experience in the face of erratic power supply; they include reduction in the total utility of the consumer since leisure activities which require the use of electricity cannot be undertaken in the event of power outages. Household electrical appliance such as televisions, refrigerators, deep freezers, washing machines, microwave ovens and others are not left without damages. Most times, some domestic activities that require electricity, such as washing clothes, ironing or vacuum cleaning, can be rescheduled after power is restored. Other activities like watching TV, listening to radio cannot be postponed and the loss associated with the disruption may vary. If the power goes off during your favorite television program, the loss can be troubling. Modern households cook on electric stoves that are not usable during an outage. Likewise, land line telephones may suddenly be disrupted by an outage. Today, widely used social media, such as Facebook, when not accessible, may cause great inconvenience to some people. Computers could shut down immediately leading to important data loss which is experienced by many researchers in Nigeria. With the increasing digitization of study materials and online courses, outages represent a major hurdle for students. Submitting homework online before a deadline is simply impossible when electricity fails. If the outage is of a larger extent, traffic lights or public transport, such as trams and trains will stop working complicating life on a much larger scale. Also, People connected to health appliances, such as respirators or infusions that require electricity for running, face a more serious problem. In many cases, outages lasting only a few hours can be devastating and deadly. Simple appliances such as fans or heaters, if not working, can cause health problems. For many, a room without air-condition during the hot dry season with high temperatures or a frigid room during cold seasons can cause strokes. This also applies to tropical house pets or vegetation which require specific temperatures to survive. Safety is mainly affected by non-functioning street lights leading to increased rates of robbery due to the failure of security systems and alarms.
Frequent and unannounced power outages may be accompanied by electrical shocks which the appliances may not be able to withstand causing them to break down. The same also goes for different industries that use different power equipment in their production or rendering of services. This becomes a loss to the owners who will have to incur extra costs to either repair or replace them. Most times food items being preserved in refrigerators go bad when there is no electricity to power their preservation and this is an example of losses which electricity customers do suffer under inconsistent power supply conditions. Also, the response time for the Discos in rectifying or attending to these power supply challenges faced by households is a great concern. Sometimes, households are left with erratic power or no power at all due to electrical faults for long periods after the customers have sent a complaint; this is part of the commercial quality dimension under quality of electricity supply that has been tremendously neglected.
A survey carried out on power distribution to the industrial sector in Nigeria showed that average power outage in the sector increased from 12.3 hours in January 2006 to 14.5 hours in March 2006. In a worsening experience, the outage increased to 16.48 hours per day in June, 2006. In other words, power distribution in the month of June, 2006 to the industrial sector, on the average, was 7.52 hours per day (Odiaka, 2006).
How much each household and industry will be willing to pay to improve electricity supply will differ across the electricity consumers depending on the extent to which these power outages cost the households and the industries therein. NERC have been cautious in granting tariff increases to the providers by using performance indicators to ensure that inefficiencies are not transmitted to consumers. As a result of these, the providers are confronted with the lack of investment and capitalization which makes it difficult for them to provide uninterrupted service to consumers.
However, accompanying the NERC’s efforts at increasing tariffs steadily are media reports that evidence the displeasure of some segments of the public whenever electricity tariffs are increased. This may be partly due to the fact that users of electricity do not think the service they enjoy merit increased tariffs.
In the midst of these arguments, some of the research questions that may arise are:
i. What are the social and economic cost of frequent and unanticipated power outages to households?
ii. What are the factors that influence consumers’ willingness to pay for uninterrupted electricity supply?
iii. How much are consumers willing to pay for improved quality electricity supply?
1.2 Objectives of the Study
The broad objective of this research is to investigate the importance of the quality of electricity supply for consumer welfare. Other specific objectives to be investigated and analyzed in this study include:
i. Analyze how the present state of quality electricity supply affects the welfare of households.
ii. Analyze the costs of frequent and unanticipated powers outages to consumers.
iii. Investigate the consumers’ willingness to pay for reliable and good quality electricity.
1.3 Justification for the Study
This research work is of great importance in a country crippled by persistent electricity power crisis evident in the industries incapable of providing a sustained adequate power supply. The demand and importance for an improved electricity supply, especially in urban areas cannot be over emphasized. The present study is justified for several reasons. First, there is little or no research on analysis of the elements of quality electricity supply in Africa as a whole. Most studies that pointed out this elements of quality electricity supply are in the European Countries (Solver T. 2005; Giannakis D et al, 2003). This research will assist in bringing to light this gap which have been ignored due to the misplaced priorities of the electricity service providers.
Secondly, concerning the subject area of willingness to pay, similar studies have been conducted in more advanced countries such as Belgium, Sweden among others (Pepermans, 2011; Carlsson & Martinson, 2004). These studies revealed that households are willing to pay significant amounts to avoid power outages and willing to accept significant amounts for at least one additional outage in a year. However, power outages are not the norm in these advanced countries unlike the case in Nigeria and most Africa countries, thus this study fills in the gap so far as literature for Nigeria and Africa is concerned.
Few studies have been conducted into estimating household’s willingness to pay for improved electricity in Kenya and Uganda amongst other African countries (Abdullah ; Mariel, 2010; Kateregga, 2009). However, the results are inconclusive. While the results of (Abdullah and Mariel, 2010) showed significant willingness to pay for improvement in electricity supply by a part of their sample, the same could not be deduced from the findings of (Kateregga, 2009). This necessitated the need for further empirical studies to clear the discrepancies and to know what exactly the Nigerian situation will be as far as consumers’ willingness to pay to avoid power outages is concerned. Oseni M. (2017) is the only known Nigerian that has done similar study in this area recently. The results of his study showed the extent to which the coping strategies especially self-generation, being the popular close substitute for public provision in the country might affect WTP for reliable electricity service (Oseni M., 2017).
This study will investigate significant factors that influence consumers’ willingness to pay for reliable and good electricity in households; this is what makes it different from other studies conducted on electricity supply. These factors, which are missing from recent studies, should enable the government and policymakers to know what policies to undertake and what areas of consumers’ lives to influence if willingness to pay for improved electricity supply is to be increased and sustained. Pepermans (2011) in his study failed to consider factors that influenced willingness to pay and also the study conducted by (Carlsson and Martinson, 2004) failed to infer any particular demographic factors which affect willingness to pay except whether the outage is planned or not.
It is noteworthy to point out that this study will be using some major cities in Nigeria as different case studies such as Abuja, Ibadan and Port Harcourt and Lagos.
Furthermore, outcomes of this PhD study is also significant for other reasons as follows: the study will bring to light how much power outages are costing households by eliciting their willingness to pay to avoid these unannounced power outages. This would help the government, the generation and distribution companies to have an insight of the social and economic cost of power outages and consequently put in measures to address the problem. Studies in Nigeria on this subject are limited and thus estimates from this study are expected to be invaluable to the utilities and lays a foundation for more research and innovations to be explored in this area.
Also, it will also inform the power sector regulatory body, NERC to know how much the average household and industries are willing to pay for improved electricity supply and thereby guide not only tariff adjustments but also the development of performance indicators for the electricity providers.
1.4 Scope of the Study
This research work is basically concerned with the quality of electricity supply and willingness of electricity consumers to pay for improved electricity in Port Harcourt, Lagos, Ibadan and Abuja, Nigeria.
The data that will be used in this study will be obtained from the use of survey. Well-structured questionnaires will be administered to households’ electricity consumers. Also, personal interviews will be carried out while administering the questionnaires.
This research will rely on primary and secondary data; data for this study will be sourced mainly from primary sources within the study area. Pieces of information will be obtained from secondary sources such as journals, annual reports, textbooks and the publications of the Nigerian Electricity Regulatory Commission, etc. to aid in the credibility of the study, the sampling of households for interviewing, and to aid in the analysis of the data.
The main instrument for the data collection will be a questionnaire. A well-structured questionnaire will be administered to a sample of households within the cities of Abuja, Ibadan, Port Harcourt and Lagos via face-to-face interviews. The questionnaire will be composed of two major sections; first, the nature of the quality electricity supply and how it affects households’ welfare. In the second section, a hypothetical scenario of an improved electricity supply system that conforms to all the dimensions of quality electricity supply will be created. In this scenario, power supply is assumed to be reliable and of good quality. Reliability means the power supply is available every time and good quality means the power supply comes with the appropriate level of voltage. The hypothetical case will rule out power outages to a large extent. Power outages may only occur when repair works need to be carried out and even in such cases, users of electricity who will be affected would be notified ahead of the outages and the outage will not last beyond three hours. Respondents will then be asked to state the maximum amount they are willing to pay for such an improved electricity supply system. The questionnaire will include questions about characteristics of the existing electricity supply system, consumers’ willingness to pay and the socioeconomic characteristics of the respondent and his/her household. Therefore, using a contingent valuation method (CVM), residential willingness to pay (WTP) for improved electricity service will be estimated. The Ordered Probit Model will be employed as the main estimation technique for the study. A descriptive data analysis will also be employed and the Statistical Package for Social Sciences (SPSS) will be used in analyzing the collected data.
1.6 Plan of the Study
This PhD research will be organized in six chapters. Chapter one will cover the background overview to the study, the research problem and the research questions that arise, the objectives of this study, the justification for this study, the scope and methodology.
Chapter two will give an overview of the electricity the sub sector in Nigeria.
Chapter three will be the literature review in this study area. Both theoretical and empirical literature in the areas of electricity demand and pricing, non-market valuation as well as willingness to pay or accept.
Chapter four will cover the theoretical framework and methodology adopted in this study.
The fifth chapter will present and discuss the results from the study.
The final chapter will be the conclusion of the study and will offer policy recommendations on the findings of this study. It will also highlight on the limitations encountered in the course of this study as well as recommendations for further research.
Background to the Study
Electricity is the hub of both economic and technological development. The electricity industry in the developing countries has gone through quite a lot of metamorphosis in recent years.
Electricity supply is a very sensitive issue with several political and economic sophistications in many countries which most of the time define the industry’s effectiveness. Thus, it has continuously drawn great attention from both the industrialists and the political class. As a matter of fact, it has become a veritable avenue to gaining more votes during elections. This is just because if a politician can easily tackle issue of unavailability of electricity supply, then, such is considered a national hero. More important is the fact that every other sector of the economy depends on adequate supply of electricity. This chapter gives an overview of the Nigerian economy, the structure of the electricity sector, electricity tariffs, quality of electricity service, as well as policy and institutional developments.
2.1 Nigerian Economy
Nigeria accounts for 47% of West Africa’s population with about 200 million inhabitants and has one of the largest populations of youth in the world. It is a political federation that consists of 36 autonomous states, and a multi-ethnic and culturally diverse society. With an abundance of natural resources, Nigeria-Africa’s biggest oil exporter- also has the largest natural gas reserves on the continent.
Nigeria’s economy grew by 2.7% in 2015, significantly below its growth of 6.3% in 2014. Since the fall in oil prices in mid-2014, growth has been on a downward spiral, and the economy is currently in recession. In 2016, it continued to deteriorate further after recording negative growth in the first two consecutive quarters; -0.4% and -2.1% year-on-year in real terms, respectively (NBS, 2016).
Much of the non-oil growth came from increased investment in and expansion of agriculture and reform of the communications sector leading to the rapid take-up of mobile telephony.
The improvement in telecommunication brought by mobile telecommunication has had significant benefits to the well-being of individuals and has improved the efficiency of businesses. Nigeria has also had notable success in restructuring the construction sector and sanitizing the banking and finance sectors.
It is an undeniable fact that economic growth, development and national security depends on crucially on the adequate provision of electricity supply to key and required industries. The importance of energy in the economic development process particularly for developing countries is well documented in the literature (Iwayemi, 1983, 1993, 1998, 2008; Okafor O., 2012; and Sambo, 2008). Altinay and Karagol (2004) discovered a rising energy need for most developing countries. Literatures available showed that, Electricity consumption has a positive effect on economic growth of a Country (Kraft ; Kraft, 1978; Wolde-Rufael 2004; Yoo 2005). This is achieved by directly improving the industrial performance thereby bringing growth in the industrial sector as noted by some authors. More essentially, the roles of energy in the industrial sector activities highlight its connection with economic development.
Electricity is a malleable form of energy and critical source for present life and a vibrant infrastructural input for economic development. In all economies, households and companies have extensive demand for electricity. This demand is motivated by such vital factors as industrialization, widespread urbanization, population growth, rising standard of living and even the modernization of the agricultural sector. Some literatures even concluded by suggesting that the adoption of energy conservation policies to conserve electricity may unwillingly decline economic growth (Shahbaz ; Lean, 2012).
Figure 2.1 below shows Nigerian annual GDP growth rate from 1970-2015:
Figure 2.1: Nigeria GDP annual growth rate
Source: World Bank Development Indicator 2016.
Nigeria is fortunate to have enormous energy resources, which potentially give the country ample opportunity to transform her economy and the lives of her citizens. Nigeria sits astride of over 35 billion barrels of oil, 187 trillion cubic feet of gas, 4 billion metric tons of coal and lignite, as well as huge reserves of tar sands, hydropower and solar radiation, among others. The provision of regular, affordable and efficient electricity is crucial for the growth, prosperity, national security as well as the rapid industrialization of any society. It is also an aphorism that any nation that desire to develop will ignore the power sector at its peril. One of the prominent infrastructure deficit gaps in Nigeria is in the area of power.
The power sector in Nigeria is marked by low generating capacity when compared to installed capacity and much of the citizens do not have access to uninterrupted supplies of electricity. Nigerians currently experience continuous power shortages and poor power quality. The gap between the electricity demand and supply continues to get wider year on year as industrialization and population increase which may be a very good sign for economic growth if the government is able to improve the electricity supply in the country.
Almost 50% of Nigerians have access to electricity, with only about 30% of their demands being met. Also, recurrent outages of power supply has forced about 90% of those in the industrial sector customers to provide their own power through different forms of generating sets at a huge cost to themselves and to the Nigerian economy. Aliyu et al. (2013) pointed out that 60 per cent of the time, there is no access to electricity in Nigeria. Blackouts are commonplace and Nigerians are forced to rely on biomass fuel and petrol or diesel generators to make up for the unreliable power supply from the national grid. The 2011/12 General Household Survey conducted by the National Bureau of Statistic (NBS) indicated that just 56% of dwellings have electricity. Moreover the national average for electricity supply is just 35 hours a week. Nigerian households spend almost four times as much on fuel/electricity as they do on healthcare and only half as much of their fuel/electricity expenditure on education. Figure 2.2 below shows the percentage of population in Nigerian that has access to electricity from 1990-2015 while Figure 2.3 shows the percentage of population in Nigerian that has access to electricity compared to other African countries in 2000 and 2014. Figure 2.4 shows percentage of Nigerians connected to the electricity grid.
Figure 2.2: Nigeria Access to electricity (% of population) 1990-2014
Source: World Bank Indicators 2016
Figure 2.3: Nigeria Access to electricity (% of population) 1990-2014
Source: World Bank Indicators 2016.
Figure 2.4: Percentage of Nigerians connected to the grid
Source: National Bureau of Statistics
2.2 Historical Trend on Electricity in Nigeria
The history of electricity development in Nigeria can be traced back to the end of the 19th and beginning of the 20th Century, when the first generating power plant was installed in Marina, Lagos, in 1898, fifteen years after its introduction in England. Its total capacity was 60kW. After the amalgamation of the Northern and Southern protectorates in 1914 to form modern Nigeria, other towns in the country started to develop electric power supply system on the individual scale.
The table below shows major cities that first had a dose of electricity supply with respect to year in the following order:
Table 2.1: First Cities to have Electricity in Nigeria
Port Harcourt 1928
Source: Author Compilation
2.2.1 The Establishment of Electricity Corporation of Nigeria (ECN) and Niger Dams Authority (NDA)
The Government and Native Authorities (NAs) owned systems remained separate operational entities for several years until 1946. The Public Works Department ceased to have control over the operation of the electricity generating plants and distribution system in the country that same year. In the same vein, the Nigerian Government Electricity Undertaking (NGEU) was immediately established (as an arm of the Public Works Department) to take over the assets and liabilities of electricity supply in Lagos. Four years later, in 1950, a central body was established to take over all the various electricity supply outlets within the country. This body is referred to and addressed as the Electricity Corporation of Nigeria (ECN). Meanwhile, the Native Authorities continued to manage their respective systems while Niger Dams Authority (NDA) was also inaugurated for the benefit of generating electricity through hydro power systems. As a result of this, the Colonial Government established the Electricity Corporation of Nigeria (ECN) under the ordinance no.15 of 1950.
The new body, i.e. ECN, officially took over all electricity supply activities in Nigeria in April 1951 by integrating all the Government owned as well as native-owned generating plants and systems. This creditably improved the electric power supply in the country through grid connection of generation, transmission and distribution of electricity. Meanwhile, the sale of electricity was also done in such a way that the return on its investment had a common purse. This was later referred to as the Vertically Integrated Utility (VIU). With the increase in demand for electricity, some projects were carried out in Ijora, Oji River, Kano and Ibadan power stations to improve availability and quality of power delivery. Thus, the Ijora power station was commissioned in February 1956 and it served satellite towns like Ikorodu, Shagamu, Ijebu-ode and other towns in the Ibadan-Ijebu provinces which provided the socio-economic transformation of these Western States ahead of other parts of the country.
In 1962, an Act of Parliament established Niger Dams Authority (NDA) which was responsible for dam construction after discovering the innumerable benefits that would accrue from the Dam. This led to the construction of Kainji Dam in 1962 and was completed in 1968.
The vast nature of the country grid power transmission system started operation in 1966 with the collaborative effort of the defunct ECN and NDA, which linked Lagos with Kainji. Kainji-Kaduna link was extended to Zaria and Kano. In the southern part, Oshogbo-Benin- Ughelli and Benin-Onitsha-Afam (Alaoji) links were constructed. Inspite of the great size of the country, the national grid now links the thirty-six state capitals and the Federal Capital Teritory Abuja.
On 1st of April 1972, ECN and NDA merged to form a unified body known as National Electric Power Authority (NEPA) with the actual merging taking place on the 6th of January 1973 when the first manager was appointed. The network continued to grow under NEPA and between 1978 and 1983, the Federal Government had sponsored two panels of enquiry to fashion out models for restructuring NEPA into an independent unit or toward privatizing it out of monolithic nature. This led to the establishment of the electrification boards whose work is to take power supply to the rural areas and new cities. Figure 2.5 below shows the Electricity industry structure under NEPA:
Figure 2.5: The Vertical Integration Model of the Electricity Industry
2.2.2 The Establishment and Unbundling of PHCN
The advent of democratic government (by 1999-2005), an act was enacted establishing Power Holding Company Nigeria (PHCN), an Initial Holding Company (IHC), as a result of Government effort to revitalize power sector. This was an intended name for privatization which was meant to transfer assets and liabilities of NEPA to PHCN. It was officially commissioned on the 5th of May 2005 and was to carry out business of NEPA which is still on.
In the same vein, the National Integrated Power Projects (NIPP) was inaugurated in 2004 to be able to catalyze and fast track the upgrading of adding more capacity to the current available electricity capacity in the country. This was basically a private iniative which is currently being supervised by the Niger Delta Power Holding Company (NDPHC).
The PHCN, as a Company, was unbundled into 18 companies as follows: six (6) generating companies, one (1) transmission company (i.e. Transmission Company of Nigeria-TCN), and eleven (11) distribution companies.
The generating companies are:
i. Egbin Electricity Generating Company (EEGC),
v. Shiroro and
There are also some new Independent Power Producers (IPP) under the auspices of the Niger-Delta Power Holding Company (NDPHC).
The 11 distribution companies are:
i. Abuja Electricity Distribution Company (AEDC),
ii. Benin Electricity Distribution Company (BEDC),
iii. Eko Electricity Distribution Company (EKDC),
iv. Enugu Electricity Distribution Company (EEDC),
v. Ibadan Electricity Distribution Company (IBEDC),
vi. Ikeja Electricity Distribution Company (IKEDC),
vii. Jos Electricity Distribution Company (JEDC),
viii. Kaduna Electricity Distribution Company (KAEDC),
ix. Kano Electricity Distribution Company (KEDC),
x. Port-Harcourt Electricity Distribution Company (PHEDC),
xi. Yola Electricity Distribution Company (YEDC).
Currently, the Federal Government owns 100% of the transmission company, while its hold on the generating companies is 20% (with 80% of equity sold to private investors) and in the case of the distribution companies, eleven of them that have been sold, government only sold 60% and is still holding 40%. In other words; the Transmission Company of Nigeria (TCN) is 100% owned, generating companies (GENCOs) 20% owned by government and 80% private sector ownership. For DISCOs, 60% owned by private sector, 40% owned by government. The TCN is controlled by the government (nonetheless, the management of TCN is handled by the Canadian company, Manitoba Hydro Company). On the 30th of September 2013, the Federal Government handed over certificates of ownership to prospective owners. Since then the generation and distribution of electricity have been transferred to the private investors.
2.2.3 Creation of the Nigerian Electricity Regulatory Commission (NERC)
In November 2005, the Nigerian Electricity Regulatory Commission (NERC) was inaugurated and charged with the responsibility of tariffs regulation and monitoring of the quality of services of the PHCN. Before the reform, tariffs in the Nigerian electricity industry were depressed by government order. The old NEPA was barred by decree from increasing tariffs, even when the cost of supply of electricity had increased. The result was underproduction of electricity and the absence of investment in the network. Ultimately, it led to inevitable collapse of the system. Cost reflective tariff is critical to any sustainable success we may have with the power sector reform. But, the idea of cost reflective tariff is controversial and politically explosive.
The EPSR Act 2005 isolated the NERC from the direct control of the government bureaucracy.
Nigeria now has a cost reflective tariff, with voluminous traffic in foreign and local investment in the electricity market. The NERC is an independent agency, and it fixes the tariff after due process and consultation with all stakeholders; and because the tariff is a product of scientific and technical analysis and modelling, NERC is insulated from the vagaries and anxieties of politics. The stability and credibility of the methodology for determining the Multi-Year Tariff Order, MYTO gives assurance to investors to continue to come to the Nigerian electricity market. As long as the regulatory landscape remains insulated from political manipulation, and as long as the regulation of the Nigerian electricity market remains legitimate and credible, foreign and local private sector investments will continue to flow into the Nigerian electricity market. Opportunities abound in the Nigerian electricity market, as the new owners of the distribution companies; DISCOs are committing themselves to better service delivery.
2.3 The Structure of the Nigeria Power Sector
The vertical integrated model initially adopted prior to the reform has the generation, transmission and distribution all in one entity called the National Electric Power Authority (NEPA) which was unbundled by the reform into successors companies called the Power Holding Company of Nigeria (PHCN) before it was finally privatized as discussed earlier. The sector has evolved since after privatisation. The following sub-sections provides a brief overview of each of the sectors presently.
2.3.1 Generation Sector
Prior to the enactment of the National Electric Power Policy of 2001, the Electricity Act of 1990 was in operation and was amended through the Electricity (Amendment) decree of 1998 which allows for private sector participation in power generation. This heralded the entrance into power generation of Independent Power Producers (IPPs), which have been responsible for the lion share of the increase in generating capacity since the law changed. This consist of generation companies that supply the national grid as well as embedded generation companies that are dedicated to (usually) manufacturing companies that rely on a constant and reliable supply of power and have opted to install more efficient gas-fired power plants rather than rely on diesel generators. There are currently three private IPPs supplying power to the national grid. They consist of those by set up by international oil companies (IOCs) Shell and AGIP and one run by AES Corporation. From a standing start in 2000, IPPs are now responsible for over 40% of the country’s generating capacity. They have also proved to be the most reliable supplier of electricity to the national grid. Three others are often also deemed IPPs as they are not funded by the Federal government however it is arguable that they are not independent in the true sense because they are funded by state governments
However, the additional generating capacity provided by the Independent Power Producers (IPPs) was still not enough to meet the ever increasing demand for power, and due to the fact that most of the government owned generating plants were not working to their full capacity, the government embarked on a programme of investment in new power generation, transmission and distribution called the National Integrated Power Project (NIPP). Pursuant to this a separate holding company, the Niger Delta Power Holding Company (NDPHC), was incorporated in 2005 to manage the US$8.4 billion investment in NIPP assets.
The NIPPs consist of ten power plants as well as the necessary gas supply, transmission and distribution infrastructure. About US$6 billion has been invested so far and they currently supply about 1,000 MW to the grid (TCN 2014). The NIPP generating companies were projected to increase the nation’s generation capacity by 5,153 MW over 3 years and to expand the transmission and gas networks.
There are currently 23 grid-connected generating plants in operation in the Nigerian Electricity Supply Industry (NESI), with a total installed capacity of 10,396.0 MW and available capacity of 6,056 MW. Most generation is thermal based, with an installed capacity of 8,457.6 MW and an available capacity of 4,996 MW. Hydropower from three major plants accounts for 1,938.4 MW of total installed capacity (and an available capacity of 1,324 MW).
The Successor generating companies from PHCN have a total combined generating capacity of more than 5000MW but they have never worked beyond half of their capacity.
At the beginning of 2014, the Federal government had projected that generation would peak at a minimum of 5,000 megawatts (MW) and possibly hit 6,000MW by the end of the year. However, the year ended with generation hovering between 3,800 and 4,000MW. This huge difference has been blamed on the incessant vandalism of gas pipelines across the country, these disruptions officials of the Ministry of Power said, prevented the sector from attaining the years’ projection.
In 2017, according to NBS, the power generation statistics for Q2 2017 reflected that a total average of 2,503 GWh of energy was generated by power stations consisting of 25 generating plants within the period under review (NBS, Q2 2017).
The major problem plugged to this sector of the market has been lack of generating capacity and deficiency of gas for the capacity available and from the look of the generation mix of the country, Figure 2.6 below gives a vivid description of why the country could meet up with its installed capacity. The following tables below shows the state of events in the generation aspect of the Nigerian Electricity Supply Industry:
Table 2.2: Successor Generation Companies
GENCO Type Installed Capacity (MW) Available Capacity (MW)
1. Afam Power Gas fired 987.2 178
2. Egbin Power Steam 1320 1030
3. Kanji Hydro Electric Hydro 760 199
4. Sapele Power Gas fired 1020 178
5. Shiroro Hydro Electric Hydro 600 565
6. Ughelli Power Gas fired 942 373
Total 5629 2523
Source: NERC and TCN 2014
Table 2.3: Other Generation Companies owned by PHCN (Legacy Plants)
GENCO Type Installed Capacity (MW) Available Capacity (MW)
1. Omotosho Power Gas fired 500 161
2. Geregu Power Gas fired 414 284
3. Jebba Hydro Electric Hydro 570 560
4. Olorunsogo Power Gas fired 304 161
Total 1788 1166
Source: Transmission Company of Nigeria 2014 (TCN)
Table 2.4: Independent Power Producers Projects
Ownership 95% AES, 5% Yinka Folawiyo Power
– Gas-fired Open Cycle Gas Turbine (OCGT) Barge
– Build Own Operate (BOO)
Fuel Natural gas provided by PHCN (contracted from Nigerian Gas Co.)
License 13.25 yrs, extended to 2025
Security against PHCN default, etc Sovereign guarantee
Commissioning Year/Online 2001
Installed Capacity 270 MW
Available Capacity 225 MW
Approximate Cost US$240 million
Ownership 20% Agip, 60% NNPC, 20% Phillips Oil Co.
Plant Type –
300MW OCGT upgraded with 150MW Combined Cycle Gas Turbine (CCGT).
– Build Own and Operate (BOO)
Fuel Natural gas provided by Agip
License 20 yrs, US$-based PPA
Security against PHCN default, etc.-
Backed by NNPC subsidiary, NPDC
– 80% min. capacity. Take-or-Pay.
– PPA based on Final Investment Cost (FIC) of US$312m + approx. Flat capacity charge.
– 5-yr amortization estimated.
– Final costs increased by US$150m due to vandalism and underestimation of cost to fix transmission infrastructure.
Commissioning Year/Online 2005
Installed Capacity 450 MW
Available Capacity 450 MW
Approx. Cost US$460 million
Ownership NNPC 55%, Shell 30%, Elf(Total) 10%, Agip 5%
– Brownfield 270MW Afam V (Acquire Operate Own, AOO) + Greenfield 624MW, Afam VI under BOO. Original project was Restore Own Transfer (ROT), of Afam I-IV and Lease Own Transfer (LOT) of Afam V.
Fuel Natural gas provided by Shell
License 20 yrs, US$-based PPA
Security against PHCN default, etc
– 80% min. capacity. Take-or-Pay.
– PPA based on FIC of US$540m
– L/C from Federal Ministry of Finance. (In June 2006 Nigeria received BB- credit rating thus it no longer needed to use oil or income from oil as security.)
Commissioning Year/Online 2008
Installed Capacity 650 MW
Available Capacity 650MW
Approx. Cost US$540 million
AKWA IBOM STATE/IBOM POWER
Ownership Private limited liability company owned by the Akwa Ibom State government.
– Greenfield BOO
Fuel Natural gas provided by Septa Energy, a wholly-owned subsidiary of Seven Energy.
License 10 yrs to 2018
Security against PHCN default, etc Sovereign guarantee
Commissioning Year/Online 2009
Installed Capacity 155 MW
Available Capacity 60 MW
Approx. Cost US$140 million
RIVERS STATE/TRANS AMADI
Ownership Private limited liability company owned by the Rivers State government.
Fuel Natural gas provided by Agip
License 10 yrs to 2023
Security against PHCN default, etc Sovereign guarantee
Commissioning Year/Online 2006
Installed Capacity 100 MW
Available Capacity 24 MW
Approx. Cost US$80 million
Ownership Private limited liability company owned by the Rivers State government.
– Greenfield, operation and maintenance by NG Power Ltd., an affiliate of KERL (Sahara Energy + KEPCO)
Fuel Natural gas provided by AGIP
License 10 yrs to 2023
Security against PHCN default, etc Sovereign guarantee
Commissioning Year/Online 2005
Installed Capacity 150 MW
Available Capacity 30 MW
Approx. Cost US$132 million
Source: NERC, TCN and Author Compilation
Table 2.5: National Integrated Power Projects
Plant Name Location (State) Type of Plant No of Turbines Gas Steam Installed Capacity (MW) Available Capacity (MW)
Alaoji Abia CCGT 4 2 831 497
Ihovbor Edo OCGT+ 4 0 508 360
Calabar Cross River OCGT+ 5 0 635 0
Egbema Imo OCGT+ 3 0 381 0
Gbarain Bayelsa OCGT+ 2 0 254 0
Geregu II Kogi OCGT+ 3 0 506 426
Sapele II Delta OCGT 4 0 508 249
Olorunsogo II Ogun CCGT 4 2 754 462
Omoku II Rivers OCGT+ 2 0 265 0
Omotosho II Ondo OCGT+ 4 0 513 249
Total 35 4 5,153 2243
Source: BPE, NDPHC 2013
*Designed capacity. Some NIPPs have not been completed. Totals rounded to nearest integer. CCGT: Combined Cycle Gas Turbine; OCGT: Open Cycle Gas Turbine. OCGT +: OCGT with possibility of conversion to CCGT.
Figure 2.6: Nigeria Installed Electricity generation mix
Source: World Development Indicator 2016
2.3.2 Transmission Sector
The Transmission Company of Nigeria (TCN) remains a Federal Government owned entity. However, it was handed over to a Canadian enterprise, Manitoba Hydro International as a management contract. The duty of the management company is to run it in an efficient manner. The TCN is split into three operational functions:
1. Transmission Service Provider (TSP)
2. System Operator (SO)
3. Market Operator (MO)
The current transmission network in the country is radial, meaning that the power is delivered from the main branch to sub-branches and then is split from the sub-branches again. It is the cheapest system but also the most unreliable and is often avoided for networks in densely populated areas due to the lack of alternate routes should a part of the system become faulty. The unreliable structure of the system is one of the issues that the TCN is currently dealing with. The figures below show the current transmission network and the plans to build a ‘super-grid’. The main barrier to achieving this goal has been access to funding.
Figure 2.7 shows the structure of TCN with their functions while Figure 2.8 shows TCN present network grid of the whole country and their proposed grid network.
Figure 2.7: Structure of TCN
Source: Presentation on future of TCN (by Bada A.S. 2016)
Figure 2.8: Nigeria Transmission Network with Proposed Super-Grid Network
Source: Transmission Company of Nigeria (TCN)
2.3.3 Distribution Sector
There are 11 Distribution Companies (DISCOS) in the country created after the unbundling of the electricity industry. DISCOS were created on a regional basis and have operational jurisdictions. Two separate DISCOS operate in Lagos State due to its high levels of commercial activity and the remaining nine DISCOS each supply multiple states simultaneous. Figure 2.9 shows each DISCO and the states they are responsible for servicing.
Each of the DISCOS face similar problems ranging from dilapidated distribution infrastructure, the reduction of aggregate technical, commercial and collection (ATC&C) losses, determining accurate customer number in their franchised jurisdiction, expansion and development of their network grids, proper metering of customers as well as settling imbalances in the market.
Figure 2.9: Geographical distribution of Nigeria’s DISCOs
Figure 2.10 below shows a comprehensive structure of the Nigerian electricity industry presently:
Figure 2.10: Nigerian Electricity Industry
2.4 Electricity Tariff
Power supply in Nigerian has been unstable, inadequate and unreliable. The problems have been attributed to the power sector’s inability to generate enough revenue to maintain the system due to under-pricing of electricity service. The industry has not been able to generate enough revenue to cover its operating costs let alone its considerable capital expenditure needs (NERC, 2013). Amadi (2012) maintains that the absence of a cost reflective tariff caused the inability of the power sector to render effective services. The Transmission Company of Nigeria (TCN, 2007), states that inappropriate pricing helped to compound the poor operational and financial performance of the industry. Part of the reform programme of the government is increase in tariffs. Power tariffs in Nigeria before the introduction of Multi-Year Tariff Order (MYTO), was said to be below the cost of supply. The pricing failed to consider commercial viability of the sector and the tariffs were not frequently reviewed. According to Kaitafi (2011), the average tariff in Nigeria was low for a very long time due to government control. The average tariff in Nigeria before 2002 was N4.50/kWh. In 2002, it was increased to an average of about N6.00/kWh (NERC, 2005). The first attempt to prepare an effective cost recovery policy/plan was made by NERC in 2008 when the agency introduced the Multi-Year Tariff Order (MYTO). It was believed that this new tariff order would ensure cost effectiveness (NERC, 2012). Consequently, the price was increased to an average of N11.20/kWh in 2008 under MYTO. This increase of about 50% was still considered as one of the lowest in the world (Kaitafi, 2011). It was also below the price paid in most West African countries (RPSR, 2010). As a result the MYTO was again reviewed in 2012 which raised the electricity tariff to an average of 23.89/kWh which is currently in use.
Efficient power pricing contributes immensely to proper functioning of the power sector because it ensures that tariff is cost reflective (Briceno-Garmendia et al, 2011). It is only full recovery of all costs associated with electricity service that can guaranty sustainability in the power sector under the Public-Private Partnership being arranged by the Federal Government of Nigeria. The question is whether this increase has made full operational cost recovery possible? Has it made any significant impact on the revenue generation of the power sector? Has the increase in tariffs in any way positively affected power generation and distribution especially to the end users?
Most Nigerians are highly displeasured with the consistent increasing tariff by the electricity providers because it doesn’t reflect on the quality of electricity supplied. Electricity supply is inconsistent, and epileptic and most at times, cause irreparable damages on household appliances. Also, the DISCOS do not respond speedily to electrical faults or technical issues even when several complaints has been sent by electricity customers. In fact, there is general poor quality of service regulations. Most Nigerians claim that there was better quality electricity supply in the early 90’s when electricity tariffs were moderate and low compared to the present situation. Table 2.6 shows the average price of electricity between the year 2010 and 2017 for all the subclass while Figure 2.11 gives a pictorial description of Nigerian Electricity Tariff from 1970-2017.
Table 2.6: Average Electricity Price in Nigeria (2010-2017)
AVERAGE ENERGY CHARGES, N / kWh
2010 2012 2013 2014 2015 2016 2017
Subclass Energy Charges, N / kWh
R1 1.8 4.00 4.00 4.00 4.00 4.00 4.00
R2 5.9 11.87 12.58 14.73 15.46 16.12 29.32
R3 8.9 33.41 33.73 34.49 35.29 36.13 42.41
R4 12.5 30.80 31.46 32.93 34.48 36.08 42.79
C1 9.4 16.77 17.35 18.12 18.94 19.71 35.22
C2 12.3 21.93 22.39 23.22 24.10 24.99 42.24
C3 12.3 35.87 36.03 37.17 38.36 39.61 39.94
D1 9.8 15.72 16.36 17.43 18.46 19.34 36.63
D2 12.9 24.74 25.47 26.55 27.68 28.85 42.97
D3 12.9 22.38 23.06 23.77 24.51 25.28 44.20
A1 8.6 11.69 12.07 12.65 13.18 13.68 34.51
A2 8.6 14.59 15.11 15.80 16.37 16.97 36.80
A3 8.6 19.77 20.65 21.76 22.81 23.90 40.30
L1 6.8 13.14 13.95 14.70 15.47 16.18 31.72
Source: NERC MYTO & Author Compilation
Figure 2.11: Electricity Tariff in Nigeria (1970-2017)
Source: Author Compilation
It is noteworthy to point out that one striking observation in Table 2.6 and Figure 2.11 is the constant increase in electricity tariff which has not convincingly reflected on the quality of electricity supplied and consumed. Figure 2.12 below shows Nigeria electric power consumption compared to other countries in Africa, Europe, Asia and America:
Figure 2.12: Electric Power Consumption (kWh per capita)
Source: World Development Indicator 2016.
2.5 Quality of Electricity Supply
Consumer satisfaction is a key issue for ensuring the continuity of liberalization and privatization reforms set up during the last decades in the electricity service sector.
Quality of electricity supply is more than just the availability of the power which an average layman is accustomed to. Quality of supply is normally split in three different dimensions: continuity of supply, voltage quality, and commercial quality.
2.5.1 Quality of Service Dimensions
1. Continuity of Supply: This is related to availability of the service (i.e. how often electricity is supplied to the end users). The fewer the instances of interruptions and the shorter these interruptions are, the better the supply is from the customer’s point of view. For that reason, continuity of supply is determined by the number and duration of supply interruptions and it is extremely related to network investments and practices of operation and maintenance by distribution operators. In many European countries (including Spain since their last regulatory reform) distribution companies are subjected to quality regulation and can be financially penalized if continuity supply standards are not met (Fernandes C. et al, 2012). This aspect of quality of electricity service is the most relevant for customers since power supply is crucial for today’s way of living. For that reason continuity of supply is the focus of most of research works related to electricity quality and is permanently in the agenda of energy regulators.
2. Voltage Quality: This refers to the usefulness of electricity when there are no interruptions. It includes every technical aspect of the distributed electricity apart from outages. When the voltage quality (the usefulness) is very poor, several problems may arise in the use of electrical appliances and electrical processes. In simple technical terms, voltage quality can be described by deviations from nominal values for voltage frequency and voltage magnitude and by distortions of the voltage wave shape. Naturally, voltage quality is more complex to regulate as it includes many quality issues and in turn each issue have several dimensions. The most common approach for regulating it is by means of setting mandatory values for compliance. These values are stated for only a few voltage disturbances under normal operating conditions and only for a given percentage of time and mean values over long time intervals. If these levels are ensured, consumer satisfaction will not be affected.
3. Commercial Quality: This is considered very important because it is directly associated with transactions between electricity companies (either Distribution Companies or Generation Companies, or both) and customers, and covers not only the supply and sale of electricity, but also various forms of contacts between electricity companies and customers. The most common approach for regulating this quality dimension is by the definition of timelines related to both pre-contract transactions, and transaction during the contract period. This dimension of quality electricity supply is very relevant because the end users are highly involved and it affects their level of utility derived. It is basically like the customer service the Distribution companies render to their customers.
This service measures relate to the timely provision of services, the timely repair of faults, call center performance and complaint handling, and may include the following: number of calls not answered, average waiting time before a call is answered, percentage of calls abandoned, appointment punctuality, number of complaints received and resolved by type, resolution time (average, minimum and maximum) by complaint type, billing and metering queries, time taken for new connections; and time taken to repair street lights, transformers or resolve any electrical fault.
The Nigerian electricity industry has weak or no rules regarding the implementation of these dimension of quality electricity service. This is an important part of electricity that NERC and Nigerian Electricity Management Services Agency (NEMSA) are meant to enforce especially on the Distribution companies for better service performance to the electricity customers. It is not a hidden knowledge that the poor, epileptic and unreliable power supply has led to the damage of many household appliances, hesitation from the customers to pay electricity bills and even electricity theft. The use of generators as alternative source of power supply in Nigeria is becoming a permanent solution to the power supply issue as there is little or no confidence placed on the electricity providers to deliver quality electricity supply to the end users.
2.6 Policy Development
2.6.1 Power Sector Reforms
A major challenge experienced by Nigerians is frequent power outages which has been attributed to the inadequate generating capacity and other flaws from the electricity providers. Even the available capacity is not enough to meet the available demand. Also is the issue of lack of adequate investment to upgrade and increase the existing plants with high level bureaucracy and corruption within the electricity industry.
Nigerian electric power has been so epileptic that the Nigerian economy has been described as a generator economy (IseOlorunkanmi, 2014). The Manufacturers Association of Nigeria (MAN) and the National Association of Small Scale Industries (NASSI) estimated that their members spend an average of about N2billion (about $12 million) per week on self-power generation. A series of power sector polls conducted by NOI Polls Ltd for the second quarter of 2013 revealed that about 130 million, representing 81 per cent, out of the 160 million Nigerians generated their own electricity through alternative sources to make up for irregular power supply. IseOlorunkanmi (2014) pointed out that the study also showed a combined average of 69 per cent or 110 million of Nigerians experienced greater spending on alternative electricity supply. The supply-demand gulf exist because of myriads of reasons: obsolete and dilapidated plants with 36% of installed capacity are over 20 years old; 48% are over 15 years old and 80% are over 10 years old (Adenikinju,2003), lack of and poor maintenance of existing plants and poor managerial efficiency. Currently according to NBS, the power generation statistics for Q2 2017 reflected that a total average of 2,503 GWh of energy was generated by power stations as Egbin Power Plant contributed about 11.22% share of the average energy generated which represents the highest generation among the twenty-five (25) power plants within the period under review (NBS, Q2 2017). This put our current electricity consumption on a per capita basis on about 144 kWh (WDI, 2016). The Federal Government in 2000 adopted a holistic approach of restructuring the power sector and privatising of business units unbundled from NEPA (Oyeneye O., 2014). The reasons for reform were:
i. Limited access to infrastructure and low connection rate.
ii. Inadequate power generation capacity.
iii. Inefficient usage of capacity.
iv. Lack of capital for investment.
v. Ineffective regulation;
vi. High technical losses and vandalism.
vii. Insufficient transmission and distribution facilities.
viii. Inefficient use of electricity by consumers.
ix. Inappropriate industry and market structure.
x. Unclear delineation of roles and responsibilities.
Thus, the objectives of the Power Sector Reforms are:
i. The overwhelming objective of the Electric Power Policy Statement (EPPS) is to ensure that Nigeria has an Electricity Supply Industry (ESI) that can meet the needs of its citizens in the 21st Century. This requires a fundamental reform at all levels of the industry.
ii. Nigeria ESI must be such that it is able to: meet all current and prospective economically justifiable demands for electricity throughout the country, modernize and expand its coverage, and support national economic and social development, including relations with neighboring countries.
iii. The priority is to create efficient market structures, within clear regulatory frameworks, that encourage more competitive markets for electricity generation and sales (marketing), which, at the same time, are able to attract private investors and ensure economically sound development of the system.
iv. To review and update electricity laws in conformity with the need to introduce private sector operation and competition into the sector.
The Reforms achieved the following:
i. Unbundled the Nigeria Electricity Power Authority (NEPA) through 18 separate successor companies incorporated in the Power Holding Company of Nigeria (PHCN).
ii. Privatised the unbundled entities.
iii. Established a regulatory agency – the Nigerian Electricity Regulating Commission (NERC).
iv. Established a rural electrification agency and fund.
v. Incorporation of Nigerian Bulk Electricity Trading (NBET) PLC.
vi. Established Electric Power Consumer Assistance Fund.
Other key components of the electric power sector reform bill include:
i. Powers of the NERC to regulate tariffs and quality service and powers to oversee the industry effectively.
ii. Powers of NERC in relation to anti-competitive behaviour, including mergers and acquisitions licensed electricity companies.
iii. Institutional and enforcement requirement of the regulatory regime.
iv. Requirement for licensing by the NERC of the generation companies system operator, transmission services, distribution companies and trading companies that will be created from the restructuring and unbundled of NEPA.
v. Legislative authority to include special conditions in licenses.
vi. Provision relating to public policy interest in relation to fuel supply environmental laws, energy conservation, management of scarce natural resources, promotion of efficient energy, promotion of renewable energy and publication of reports and statistics.
vii. Providing a legal basis with necessary enabling provisions for establishing, changing, enforcing, and regulating technical rules, market rules and standards.
Table 2.7 below shows major activities that has been carried out since the passage of the reform Act:
Table 2.7: Activities carried out since the passage of the reform Act
Date Events Timeline by ESPRA 2005
April 2001 National Electric Power Policy adopted
March 2005 Electric Power Sector Reform Act Passed
Unbundled NEPA to PHCN
Nigerian Electricity Regulatory Commission (NERC) established March 2005
October 2005 NERC Inaugurated 2005
November 2005 Successor PHCN companies incorporated November 2005
August 2006 Nigerian Electricity Liability Management Company (NELMCO) inaugurated. 2006
2009 Market Rules Approved
July 2010 Nigerian Bulk Electricity Trader (NBET) inaugurated 2006, initially carried out by NELMCO
August 2010 Roadmap for Power Sector Reform launched
December 2010 National Council for Privatisation (NCP) advertises for Expression of Interest (EOI) for PHCN successor Gencos and Discos As deemed fit by NCP
March 2011 Deadline for submission of EOIs for PHCN Companies
April 2012 Manitoba Hydro International wins Management Contract for Transmission Company of Nigeria (TCN)
July 2012 BPE receives technical and financial proposals for pre-qualified bidders
October 2012 14 Preferred and Reserved bidders approved
February 2013 BPE and Preferred bidders sign Industry Agreements
March 2013 Preferred bidders pay initial deposit, 25% of the bid price
July 2013 Deadline for submission of EOIs for NIPP Companies
August 2013 Pre-qualified bidders approved for NIPP companies announced
September 2013 Share certificates and Licenses handed over to purchasers of PHCN Gencos and Discos.
October 1, 2013 Original date planned for declaration of Transition Electricity Market (TEM)
Some stipulated conditions-precedent (CPs) to declaration of TEM still outstanding. After privatisation
November 1, 2013 Successor Gencos and Discos handed over to Purchasers June 30, 2011
November 1, 2013 Start of Interim Rule Period (IRP). The order was issued in December 2013 by NERC but to be retroactive to November 1, 2013
28 February 2014 IRP is now scheduled to end “on the first day of the calendar month following the declaration by the Minister of Power that TEM is operational”.
21 March 2014 Approval of Preferred and Reserved bidders of 7 of the 10 NIPPs
US$4.3 billion bid by the 7 preferred bidders. Alaoji, Omoku and Gbarain GenCos temporarily suspended pending ruling on Ethiope Energy’s case in the Federal High Court.
March 1, 2015 Start of Transition Electricity Market as declared by NERC
Source: Author Compilation
2.6.2 The Roadmap to Power Sector Reform
In 2010 the President of Nigeria, established the Presidential Action Committee on Power (PACP). This committee is chaired by the President and is charged with driving forward the electric power sector reform programme. The Presidential Task Force on Power (PTFP) is the implementation and monitoring arm of the PACP. In 2010 it published the Roadmap to Power Sector Reform which set out to emulate the successful approach taken in reforming the telecommunications sector.
There was notable progress in implementing the 2010 Roadmap to start with, however government bureaucracy resulted in delays and missed targets. It also became evident that some of the assumptions in the 2010 plan had been too optimistic. The PTFP-initiated Roadmap Revision 1 review process was principally undertaken to address cases of slipped projections in the 2010 Roadmap. In 2013 the PTFP published a revised plan with a new set of assumptions. The 2020 generation target was changed to 20 GW from 40 GW. The Roadmap for Power Sector Reform – Revision I (The Roadmap) is the current operating manual for the sector.
There are currently 23 grid-connected generating plants, with a total installed capacity of 10,396 MW and available capacity of 6,056 MW. The table below shows the PTFP installed generation capacity projections (MW) for Nigeria.
Table 2.7: PTFP Installed Generation Capacity Projections (MW) for Nigeria
GENCOS 2013 2014 2015 2016 2017 2018 2019 2020
Successor Thermal 2525 2815 3591 3591 3591 3591 3591 3591
Successor Hydro 1270 1300 1520 1610 1610 1960 3610 4910
NIPP 2909 4259 4771 4771 4771 4771 4771 4771
IPP – A 429 529 529 529 529 529 529 529
IPP – B 361 361 455 2870 7246 8970 8970 8970
IOC 1130 1130 1130 2155 3380 3380 3380 3380
Others 40 60 110 110 110 110 110 2110
Annual Addition 1790 1652 3530 5601 2074 1650 3300
Total Annual Capacity 8664 10454 12106 15636 21237 23311 24961 28261
Source: The Roadmap to Power Sector Reform – Revision I, August 2013, Presidential Task Force on Power (PTFP).
NIPP – National Integrated Power Project;
IPP-A – Existing (non-IOC) Independent Power Producers;
IPP-B – Identified IPP generation projects coming on stream;
IOC – International Oil Company power plants;
Other – small hydro, renewables and coal. 2019/2020 increase in generating capacity by 2,000 MW is from Coal (1 GW) and Renewables (1 GW).
2.7 Institutional Developments
2.7.1 The Federal Ministry of Power:
This is the Government administrative arm that deals with policy formulation and provides general direction to other agencies involved in the power sector.
The key function of the Ministry is to develop and facilitate the implementation of policies for the provision of adequate and reliable power supply in the country. In carrying out its functions, it is guided by the provisions of the National Electric Power Policy, 2001, the Electric Power Sector Reforms (EPSR) Act, 2005, the Roadmap for Power Sector Reform, 2010 as well as the Transformation Agenda on Power of the Federal Government.
2.7.2 Nigerian Electricity Regulatory Commission:
The Nigerian Electricity Regulatory Commission (NERC) was established by the EPSR Act, 2005. It is an independent regulatory agency mandated to regulate and monitor the Nigerian power sector. The industry regulator was formed by the section 31 of the Electric Sector Power Reform Act of 2005 and is responsible for creating an efficient structure for the market. As the regulator it also manages the relationship between the different parties in the sector. The major objectives of the commission as specified by the Act are:
i. To create, promote and preserve efficient industry and market structures and to ensure the optimal utilisation of resources for the provision of electricity services.
ii. To maximize access to electricity services, by promoting and facilitating consumer connections to distribution systems in both rural and urban areas.
iii. To ensure that an adequate supply of electricity is available to the consumers.
iv. To ensure that the prices charged by licensees are fair to consumers and are sufficient to allow the licensees to finance their activities and to allow for reasonable earnings for efficient operation.
v. To ensure the safety, security, reliability and quality of service in the production and delivery of electricity to consumers.
vi. To ensure that regulation is fair and balanced for licensees, consumers, investors and other stakeholders; and
vii. To present quarterly reports to the President and National Assembly on its activities.
Also, the Act empowers the commission to carry out some functions as specified in section 32, which include licensing of persons engaged in generation, transmission, system operation, distribution and trading of electricity as specified by sub-section 2d. The construction, ownership or operation of generating facilities requires a license from NERC, issued according to the ESPR Act, this is only exempted by captive generation. The Act defines captive generation as production of no more than 1MW with a distributive capacity of no more than 100kW for exclusive use of the generator. NERC has the power to issue licenses as prescribed by the Act, and the term for the license is clearly specified for a maximum of ten years and renewable for a further term of five years. In applying a feasibility study of the generator is recommended with an environmental impact assessment report required from the Federal Environmental Protection Agency. A breakdown of licenses provided by NERC in Table 2.8 below shows that they have issued 99 licenses. 82 for generation, 15 for distribution, 1 for bulk purchaser and 1 for Transmission.
Table 2.9: List of Licenses Issued by NERC
No Name License Type Location Capacity/Coverage Status
1. Aba Power Distribution Aba Aba Not Operational
2. Abuja Electricity Distribution Co Plc Distribution Abuja FCT, Niger, Kogi and Nassarawa Operational
3. AES Nigeria Barge Ltd Generation on-grid Lagos 270MW Operational
4. Afam Power Plc Generation on-grid Afam, Rivers State 987.2MW Operational
5. African Oxygen ; Industrial Gases Ltd Generation off-grid Ikorodu, Lagos State 19MW Operational
6. Agbara Shoreline Power Ltd Generation on-grid Agbara, Ogun State 100MW Not Operational
7. Akute Power Ltd Generation off-grid Lagos Water Corporation 13MW Operational
8. Alaoji Generation Co. Ltd (NIPP) Generation on-grid Alaoji, Abia State 1074MW Operational
9. Anita Energy Ltd Generation on-grid Agbara, Lagos State 90MW Not Operational
10. Azura Power West Africa Ltd Generation on-grid Ihovbor Benin, Edo 450MW Not Operational
11. Benin Electricity Distribution Co. Plc Distribution Benin City, Edo State Edo, Delta, Ondo and Ekiti Operational
12. Benin Generation Company Ltd Generation On-grid Ihonvbor, Edo State 450MW Operational
13. Calabar Generation Company Ltd Generation On-grid Calabar, Cross River State 561MW Not Operational
14. Century Power Generation Ltd Generation On-grid Okija, Anambra State 495MW Not Operational
15. CET Power Projects (Ewekoro) Generation Off-grid Wapco Ewekoro, Ogun State 6MW Unknown
16. CET Power Projects Ltd Generation Off-grid Tinapa, Cross River 20MW Operational
17. CET Power Projects Ltd Generation Off-grid Nigerian Breweries Ltd, Iganmu Lagos 5MW Operational
18. CET Power Projects Ltd (Sagamu) Generation Off-grid WAPCO Sagamu, Ogun State 7MW Unknown
19. Contour Global Solutions Generation Off-grid NBC Bottling Plant, Ikeja 10MW Unknown
20. Contour Global Solutions Generation Off-grid NBC Bottling Plant, Apapa 4MW Unknown
21. Contour Global Solutions Generation Off-grid NBC Bottling Plant, Benin 7MW Unknown
22. Coronation Power and Gas Ltd Generation Off-grid Sango-Otta 20MW Unknown
23. Delta Electric Power Ltd Generation On-grid Oghareki, Etiope West, Delta State 116MW Not Operational
24. DIL Power Ltd Generation Off-grid Cement Factory, Ogun State 114MW Unknown
25. Egbema Generation Company Ltd Generation On-grid Egbema Imo State 338MW Not Operational
26. Egbin Power Plc Generation On-grid Egbin, Lagos State 1320MW Operational
27. Eko Electricity Distribution Co Plc Distribution Marina, Lagos Lagos South Operational
28. Eleme Petrochemical Company Ltd Generation On-grid Eleme, Port-Harcourt, Rivers 135MW Not Operational
29. Energy Company of Nigeria (NEGRIS) Generation On-grid Ikorodu, Lagos State 140MW Not Operational
30. Energy Company of Nigeria Ltd Generation Off-grid Nestle, Agbara, Ogun State 3MW Operational
31. Energy Company of Nigeria Plc Distribution Ikeja, Lagos State Marina, Lagos Operational
32. Enersys Nigeria Ltd Generation On-grid Ado Ekiti, Ekiti State 10MW Not Operational
33. Enugu Electricity Distribution Co Plc Distribution Enugu, Enugu State Enugu, Abia, Imo, Anambra and Ebonyi Operational
34. Ethiope Energy Ltd Generation On-grid Ogorode, Sapele, Delta State 2800MW Not Operational
35. Ewekoro Power Ltd Generation off-grid Ewekoro, Ogun State 12.5MW Unknown
36. Farm Electric Supply Ltd Generation On-grid Ota, Ogun State 150MW Unknown
37. First Independent Power Co. Ltd Generation On-grid Omoku, Rivers State 150MW Operational
38. First Independent Power Co. Ltd Generation On-grid Trans-Amadi, Rivers State 136MW Operational
39. First Independent Power Co. Ltd Generation On-grid Eleme, Rivers State 95MW Unknown
40. Fortune Electric Power Co. Ltd Generation On-grid Odukpani, Cross River State 500MW Unknown
41. Gateway Electric Limited Distribution off-grid VI, Lagos Certain Locations not covered by PHCN in Ogun State Unknown
42. Gbarain Generation Co. Ltd Generation On-grid Gbarain, Bayelsa state 225MW Not Operational
43. Geometric Power Ltd Generation On-grid Aba, Abia State 140MW Not Operational
44. Geregu Generation Co. Ltd Generation On-grid Geregu II, Kogi State 434MW Operational
45. Geregu Power Plc (BPE) Generation On-grid Geregu, Kogi State 414MW Operational
46. Hudson Power Ltd Generation On-grid Warawa, Ogun State 150MW Not Operational
47. Ibadan Electricity Distribution Co Plc Distribution Ibadan, Oyo State Oyo, Ogun, Osun, and Kwara Operational
48. Ibafo Power Station Ltd Generation On-grid Ibafo, Ogun State 200MW Not Operational
49. Ibom Power Ltd Generation On-grid Ikot Abasi, Akwa Ibom State 190MW Operational
50. ICS Power Ltd Generation On-grid Alaoji, Abia State 624MW Not Operational
51. Ikeja Electricity Distribution Co. Distribution Ikeja, Lagos State Lagos North Operational
52. Ikorodu Industrial Power Ltd Distribution for Ewekoro Cement Ikorodu, Lagos State Operational
53. Ikorodu Industrial Power Ltd Embedded Generation Ikorodu, Lagos State 39MW Unknown
54. Ilupeju Power Ltd Generation off-grid Academy Press, Ilupeju 2MW Unknown
55. Income Electrix Ltd Generation off-grid NPA, PH, Rivers State 6MW Unknown
56. Island Power Ltd Embedded Generation Marina, Lagos State 10MW Operational
57 Isolo Power Generation Ltd Generation On-grid Isolo, Lagos State 20MW Unknown
58. JBS Wind Power Ltd Generation On-grid Maranban Pushit, Mangu Plateau State 100MW Unknown
59. Jos Electricity Distribution Co. Distribution Jos, Plateau State Plateau, Bauchi, Benue and Gombe Operational
60. Kaduna Electricity Distribution Co. Plc Distribution Kaduna, Kaduna State Kaduna, Kebbi, Sokoto, Zamfara Operational
61. Kaduna Power Supply Co. Ltd Embedded Generation Kudenda Industrial Area, Kaduna 84MW Operational
62. Kainji Hydro Electric Plc (Jebba Station) Generation On-grid Jebba, Niger State 570MW Operational
63. Kainji Hydro Electric Plc (Kainji Station) Generation On-grid Kainji, Niger State 760MW Operational
64. Kano Electricity Distribution Co. Plc Distribution Kano, Kano State Kano, Jigawa and Katsina Operational
65. Knox J;L Energy Solutions Ltd Generation On-grid Ajaokuta, Kogi State 1000MW Unknown
66. Lotus ; Bresson Nigeria Ltd Generation On-grid Magboro, Ogun State 60MW Unknown
67. Mabon Ltd Generation Dadinkowa, Gombe State 39MW Unknown
68. MBH Power Ltd Generation On-grid Ikorodu, Lagos State 300MW Unknown
69. Minaj Holdings Ltd Generation On-grid Agu-Amoriji Nike, Enugu State 115MW Unknown
70. Nigerian Agip Oil Co. Ltd Generation On-grid Okpai, Delta State 480MW Operational
71. Nigerian Bulk Electricity Plc Bulk Procurement and Resale of Electricity Operational
72. NESCO Ltd Generation On-grid Bukuru, Plateau State 30MW Unknown
73. Notore Power Ltd Generation On-grid Onne, Rivers State 50MW Unknown
74. Ogorode Generation Co. Ltd (NIPP) Generation On-grid Ogorode, Delta State 450MW Operational
75. Olorunshogo Generation Co. Ltd(NIPP) Generation On-grid Olorunshogo, Ogun State 750MW Operational
76. Olorunsogo Power Plc (BPE) Generation On-grid Olorunsogo, Ogun State 335MW Operational
77. Omoku Generation Co. Ltd Generation On-grid Omoku, Rivers State 250MW Unknown
78. Omotosho Generation Co. Ltd Generation On-grid Omotosho II, Ondo State 500MW Operational
79. Omotosho Power Plc (BPE) Generation On-grid Omotosho, Ondo State 335MW Operational
80. Paras Energy ; Natural Resources Dev. Ltd Generation On-grid Ogijo, Ogun State 96MW Unknown
81. Port-Harcourt Distribution Co. Plc Distribution Port-Harcourt, Rivers State Rivers, Cross River, Bayelsa and Akwa Ibom Operational
82. PZ Power Company Ltd Generation Off-grid PZ Cussons Aba Factory, Abia State 4MW Unknown
83. Sapele Power Plc Generation On-grid Sapele, Delta State 1020MW Operational
84. Shell Petroleum Dev. Co. Ltd Generation On-grid Afam VI 642MW Operational
85. Shiroro Hydroelectric Plc Generation On-grid Shiroro, Niger State 600MW Operational
86. Shoreline Power Co. Ltd Generation Off-grid Lafarge Wapco, Sagamu, Ogun State 9MW Unknown
87. Supertek Electric Ltd Generation On-grid Ajaokuta, Kogi State 500MW Unknown
88. Supertek Nig. Ltd Generation On-grid Akwete, Abia State 1000MW Unknown
89. Tower Power Abeokuta Ltd Generation Off-grid Abeokuta, Ogun State 20MW Unknown
90. Tower Power Utility Ltd Generation off-grid Ota Industrial Estate, Ota, Ogun State 20MW Unknown
91. Transmission Company of Nigeria Transmission Maitama, Abuja 36 States of the federation Operational
92. Ughelli Powet Plc Generation On-grid Ughelli, Delta state 942MW Operational
93. Unipower Agbara Ltd Generation off-grid Unilever, Agbara Ogun State 6MW Unknown
94. Wedotebary Nigeria Ltd Generation off-grid Kuru, Jos 5MW Unknown
95. Westcom Technologies ; Energy services Ltd Generation on-grid Sagamu, Ogun State 1000MW Unknown
96. Yola Electricity Distribution Co. Distribution Yola, Adamawa State Adamawa, Borno, Taraba and Yobe Operational
97. Zuma Energy Nigeria Ltd (Gas Plant) Generation On-grid Egbema, Owerri, Imo State 400MW Unknown
98. Zuma Energy Nigeria Ltd (Coal Plant) Generation On-grid Itobe, Kogi State 1200MW Unknown
Source: NERC List of Licenses 2015 (www.nercng.org)
As part of the functions of the commission as specified by the Electric Power Sector Reform Act of 2005, section 76(1) of the ESPRA of 2005 empowers the commission to regulate tariff for generation, transmission, distribution and system operation while sub section 2 of 76, empowers the commission to regulate this tariff according to a set methodology.
Other functions carried out by the commission since its inception include:
i. Issuing of appropriate regulations and codes for the efficient running of the Nigerian Electricity Supply Industry as specified in section 96 of the ESPR Act 2005.
ii. Ensure the effective and efficient operation of the Nigerian Electricity market.
2.7.3 Nigerian Bulk Electricity Trader (NBET):
NBET was incorporated in 2010 with a mandate to operate as the trading licensee holding a bulk purchase and resale license. It is responsible for buying and reselling electrical power and ancillary services from IPPs and from the Successor generation companies. It is not intended to exist in perpetuity in its current incarnation. Rather its role is to act as a broker between power producers and the distribution companies until the market is mature enough to support commercial bi-lateral trading. In other words, once the distribution companies become creditworthy NBET will be phased out and cease to exist as it currently stands.
The role of the NBET is seen as the middleman in the Nigerian Electricity Supply Industry (NESI). Its role is to enter into, or continue existing Power Purchase Agreements (PPAs) with the GENCOS and IPPs in order to buy electricity. The NBET will also enter into vesting contracts with the DISCOS to whom they would sell the electricity. These contracts are long-term contracts with approximately twenty-year life spans. However, in the long run, it is expected that the NBET will be phased out, as the market becomes fully competitive and the distribution companies commercially and financially viable to enter into direct PPAs with generation companies. It also act as the Federal Government of Nigeria’s implementing institution for guarantees provided by the World Bank Partial Risk Guarantee in support of Gas Supply Agreements and Power Purchase Agreements. In other words, NBET assumes sovereign risks when guaranteeing payments to generation companies. Figure 2.13 below gives a pictorial description of the role of NBET in the current Electricity market.
Figure 2.13: Role of NBET
2.7.4 Nigerian Electricity Management Services Agency (NEMSA):
The Nigerian Electricity Management Services Agency (NEMSA) Formerly the Electricity Management Services Limited (EMSL), is one of the successor companies established by the Federal Government in line with the provision of part 1Section 8 of the Electric Power Sector Reform (EPSR) 2005, the Supplementary Regulation number 46/47 (B499 452) of the Federal Government Official Gazette No. 374 0f 2010 and the NEMSA Act No.6 of 2015.
Nigerian Electricity Management Services Agency (NEMSA) was set up by NEMSA Act No.6 of 2015 to carry out the Functions of Enforcement of Technical Standards and Regulations, Technical Inspection, Testing and Certification of All Categories of Electrical Installations, Electricity Meters and Instruments to ensure the Efficient Production and Delivery of Safe, Reliable and Sustainable Electricity Power Supply and Guarantee safety of Lives and Property in the Nigerian Electricity Supply Industry; and for Related Matters.
2.8 Pricing and Operational Development
2.8.1 The Multi-Year Tariff Order (MYTO)
Section 76(1) of the ESPRA of 2005 empowers NERC to regulate tariff for generation, transmission, distribution and system operation while sub section 2 of 76, empowers the commission to regulate this tariff according to a set methodology. Following from this, the commission in 2008 came out with a methodology which was said to be a cost-reflective methodology called the Multi Year Tariff Order (MYTO).
The MYTO provides a 15 year tariff path for the electricity industry, with limited minor reviews each year in the light of changes in a limited number of parameters such as inflation, foreign exchange rates, actual daily generation capacity and gas prices and major reviews every 5 years, when all inputs are reviewed with stakeholders.
The Multi-Year Tariff Order (MYTO) was intended to set electricity tariffs for consumers over a 15-year period, from 2008 to 2023. There were to be minor reviews of the industry’s pricing structure twice a year (announced on 1 December and 1 June) and major reviews every five years.
The methodology used to arrive at the MYTO tariff path is known as the building block approach. This approach combines the positive attributes of rate of regulation and price caps. It is a regulation that is known as the incentive-based regulation. The incentives are based on performance thereby encouraging investors to continuously improve their services.
To determine the approach, 3 standard building blocks were used:
i. Allowed return on capital used to achieve a fair rate of return on assets invested
ii. Allowed return on capital used for recouping the capital over the useful life of assets (depreciation)
iii. Efficient operating costs and overheads.
Inputs to the methodology are initial capital valuation and future capital expenditure, operating costs, quantity sold, costs and efficiency improvements.
Prices in MYTO are to be regulated at the beginning but will be expected to reduce over time as competition increases in the market and electricity supply increases to meet requirement. The regulation of the prices will be as follows:
i. Generation will be subject to vesting contracts, with set prices to be received by the generators who do not hold a PPA. When the industry matures, generation prices will not be regulated.
ii. Transmission will remain a monopoly and will be subject to tariff regulation.
iii. Distribution also will be treated as a monopoly and its price regulated.
Figure 2.14 below shows a block diagram of how the end users tariff are set using the MYTO:
INPUTS TO THE TARIFF
? Load Forecasts
? Invested Capital
? Aggregated Technical, Commercial ; Collection Losses
? Fuel Costs
? Return on Capital
? Operating and Maintenance Costs
? Generating Capacity ? Inflation
? Exchange Rate
? Other Technical Data
? Customers Number
Figure 2.14: Multi-Year Order Tariff Methodology
From Figure 2.14 above, the total wholesale contract price is calculated for each year as a capacity and an energy charge. The capacity charge comprises fixed operation and maintenance cost, capital cost and two-third of tax (2/3) cost. While the energy charge comprises fuel cost, variable operation and maintenance cost, the transmission loss cost and a third (1/3) of tax cost. The capacity and energy charge will be included in the wholesale contract and will be the basis for payments to the eligible generators.
This wholesale contract price added with the transmission and distribution prices with other charges are used in deriving the end-user tariff that is paid by the customers. The tariff is made up of all the cost incurred by the all the segments of the electricity supply industry which is divided by the total energy supplied to the consumers.
The average tariff of electricity over the years has always been a subject of debate as investors see them as unacceptable and cannot attract investment. When checked across all classes of customers, the average tariff of electricity has remained constant over the years at N6.31/KWh or $4.3 US cents/KWh till 2008. This tariff has been said to be insufficient to meet operating cost talk less of encouraging investment and plant upgrade. Where cost recovery is not achievable through tariffs, there must be an arrangement to determine the subsidies that may lead to complete cost recovery (ADB, 2013).
The Multi Year Tariff Order became effective on July 2008, the NERC determined tariff for supply was ?6.00 per kWh, with the idea that the Federal government will provide subsidy. This basic assumption was that the tariff will gradually reach a cost reflective level by 2011 and this was based on the customer distribution and also the MYTO 1 assumption was based on the fact that generating capacity will increase over the years which will necessitate a decrease in estimated average tariff over the years.
To increase the capacity available in the sector, new investments in generation and loss reduction are envisaged. NERC has also proposed a gradual introduction of cost reflective tariffs such that tariffs gradually increase to cost reflectivity over 3 years, with no tariff increases in the first year (12 months) of the period, till July 2009. The tariff levels are expected to in¬crease to N10/KWh by 2012.
The proposed tariff re-alignment re¬quires Government support to meet the shortfalls between the required revenue and the collected revenue, with the subsidy being sunset over 3 years; 1st Year N64.84 billion, 2nd Year N77.31 billion, 3rd Year N35.80 billion through a tariff equalization fund. The Government of Nigeria approved the implementation of MYTO and agreed to provide N177.95 billion over a three-year period to finance the Electricity Equalization Fund. The subsidy levels and tariffs are based upon a cost plus analysis.
A new tariff structure was introduced in June 2012, the main effect of which was to increase tariffs. This was due to the fact that a number of key assumptions that underlay the 2008 MYTO had not been met and others did not reflect the actual operating environment. Thus the tariff schedule was not cost-reflective, which is a prohibitive condition to new investors.
NERC concluded that the tariffs in MYTO I covered about 50% of the revenue required to achieve a viable and growing electricity industry. It surmised that the tariffs could barely cover basic operating expenditure much less the capital investment required for growth. The MYTO I assumptions that subsequently went under major review included:
i. MYTO I projected that by 2011 Nigeria would be generating 16,000MW of electricity. At this time it was expected that the Revenue Requirement of the industry would be met.
ii. It was also assumed that the PHCN distribution and generation companies would have been privatized by 2009.
On 26 May 2014 NERC announced that following a minor review of tariffs, tariffs would increase from 1 June. The reason cited for the review was a greater than 5% change in some of the four variables assessed in minor reviews i.e. rate of inflation, gas prices, foreign exchange rates and actual daily generation capacity. This review gave birth to the MYTO 2.1 which is currently used to determine the tariff for each customer class. The current prices are based on the generating capacity of between 3000 – 5000MW, and this form the basis for determining the tariff pending any minor review.
The current average tariff as provided by MYTO 2.1 is N19/kWh while the proposed revised average price for 2015 is N30/kWh, this represents 50% increase in average prices from the 2012 prices and a 63% increase from the current prices to the new proposed price. The proposed average price for 2015 is actually the average electricity tariff currently in 2017.
This chapter reviews the relevant literature in the study area. The review incorporates the theoretical and empirical literature. The theoretical literature focuses on issues such as electricity demand and pricing models as well as the various types of methods that are used for economic valuation whereas the empirical literature focuses on studies carried out in this study area by earlier researchers. The relevance of the review is to bring to light what has been done and said about the costs of power outages and how much people are willing to pay for improved reliable electricity supply as well as identify which areas are yet to be explored in this study area.
3.1 Theoretical Review
3.1.1 Electricity Demand and Pricing Models
More often than not, electricity demand has been modeled after conventional demand theory which proposes that the demand for a commodity depends essentially on the price of the commodity, prices of related goods and the income of the consumer. From the literature on electricity demand, these basic factors – price of electricity, price of other sources of energy and real income of consumers have cut across as affecting electricity demand. However, other factors are reported to influence electricity demand alongside these ones by various studies. Some of these other factors that are likely to affect electricity demand include household appliances stock of capital (Narayan and Smyth, 2005); prices of household appliances (Diabi, 1998); temperature (Diabi, 1998; De Vita et al. 2006); real GDP per capita (Adom et al. 2012; Babatunde ; Shuaibu, undated ); industry efficiency (Adom et al. 2012); demographic features (Filippini ; Pachauri, 2002; Adom et al. 2012); population (Babatunde ; Shuaibu, undated); weather conditions and consumer usage patterns (Foley et al. 2010) and factors likely to influence consumers’ tastes such as technology. Interestingly, Babatunde and Shuaibu (undated) study finds that own price elasticity of demand of electricity, which has been observed to run through many studies as a determinant of electricity demand, was not significant in the demand for electricity because the own price component of electricity demand has been a difficult component to measure in several electricity demand models.
Another major issue of concern in modeling electricity demand is the stock of appliances and how that influences electricity demand. The nature and stock of electrical appliances was likely to affect a household’s demand for electricity. To deal with this problem, researchers have advocated that applying discrete choice modes, sample selection corrections as well as discrete – continuous combinations would allow for estimating electricity consumption per each appliance owned (Adom, 2011).
3.2 Non-Market Valuation
3.2.1 Economic Valuation of Non Market Goods
In Economics, non-market goods and services may refer to goods and services that are not captured in the market place or for which no or limited market exists and for which people do not pay money to receive them. Usually, most environmental goods are non-market goods because they exhibit the characteristics above. Not many of such environmental goods have markets and hence prices. The prices that exist for those few indicate that minimum amount at which suppliers and consumers have agreed to enter into a market transaction. At these prices therefore, surpluses are bound to exist either on the producer side or the consumer side. The economic value of such goods thus goes beyond the price to include all the surpluses unaccounted for in the price.
Given that most environmental goods do not have markets and those that do, have prices that do not reflect the full value of the goods, economic valuation is most important to the sustainability of non-market goods.
The theory of economic valuation is based on individual preferences and choices (Perman et al. 2003). Hence, the economic value of a good, service or a resource is based primarily on what people want. It is generally assumed in Economics that individuals are rational agents and are the best judges of what they want. Individual preferences are observed by the choices and the tradeoffs they make. Economic value is measured by the maximum that someone is willing to forego in terms of other goods or services to obtain a good or service. This may be different from the market price since the market price may not accurately measure the economic value. In fact, from conventional demand analysis, most people are usually willing to pay more for a good especially the first units of the good than the price of the good resulting in their WTP going beyond the market price.
The economic value of a resource such as improved quality electricity supply can be classified into use value and non-use value. These together, make up the total economic value (TEV) of the resource, a concept which emerged in the mid-1980s.
Use value refers to the benefits that is being derived from society’s gains from using the resource. For example, society may use a clean river for drinking purposes, swimming, boating, among others without paying for it. This is use value. Use value is further divided into two; direct use value and indirect use value. Direct use value of a resource is the contribution of the resource to current production or consumption or the value derived from directly consuming services provided by the resource. Cutting down of trees in a forest to obtain wood for fuel could be an example of direct use value. Indirect use value of a resource refers to the functional services the resource provides to support current consumption and production (Perman et al. 2003). In the case of the forest, water shed protection and checking erosion are examples of an indirect use value derived from the resource.
In the case of electricity, having light to be able to study at night may be considered an example of direct use value whiles having your compound well lighted at night (even though the consumer may be indoors and therefore may not be using outside lights at that moment) for security measures may be an example of indirect use value.
Non-use value of a resource is the value that individuals attach to a resource in appreciation of the resource and not because they are using the resource. Non-use value is the demonstration of people’s WTP for a resource regardless of their ability to make any use from it either now or in the future (Perman et al. 2003). Under non-use value, we have option value, existence value and bequest value.
Option value is the value an individual attaches to a resource for the sake of future benefits that may be derived from the resource. In other words, the resource may not be producing or giving them any benefits at the moment but its capacity to do so in the future is uncertain hence individuals prefer to preserve it rather than do away with the resource (Perman et al. 2003).
Existence value is the satisfaction derived by simply knowing that the resource exists although one may not have any intention of using it. It is the value non users may be willing to pay to keep the resource knowing fully well that they have no aim of using the resource either presently or in the future. In Nigeria for instance, a citizen may value the Cross River National Park just for the mere fact that there is one in his home country and it has a canopy walkway even though the individual may have phobia to use the walkway. Such an individual may be willing to pay something significant to preserve the resource. This individual is said to have an existence value for the Cross River National Park.
Bequest value is sometimes referred to as sustainable development. This value is associated with passing on the resource to future generations. In other words, this value arises from selflessness on the part of current generations and wishing to leave the resource behind for the future generation (Perman et al. 2003).
3.2.2 Methods for Non Market Valuation
Methods for valuing non market resources may be generally classified into two; pecuniary and non-pecuniary methods. Pecuniary methods are those methods that use money as the standard for currency exchange. Non pecuniary methods on the other hand do not look to assign a money value. They are more general in nature and any value or standard may be used as the means of currency exchange.
The pecuniary methods may be grouped into three main categories; Revealed Willingness to Pay, Imputed Willingness to Pay/Circumstantial Evidence and Expressed Willingness to Pay.
220.127.116.11 Revealed Willingness to Pay
In this category- Revealed Willingness to Pay, the methods therein are based on the market price or on consumers’ revealed willingness to pay. The main idea here is that if the good, service or resource being valued has a market, then it will have a market price and buyers will reveal their preference for that particular resource by paying for it at the market price. They reveal their willingness to pay by paying what the market price is. Thus the existence of a market price is exploited to assess the value of the resource. Based on this principle, several valuation methods have been developed, they include: Travel Cost Method (TCM), Averting Behaviour Method (ABM), Market Price Method (MPM), Hedonic Pricing Method (HPM), and Production Function Method (PFM).
The revealed willingness to pay only measures the use value of a resource and since use value only form a component of the total economic value of a resource, estimates obtained from valuation methods in this class fall short of what the total value of the resource may be.
18.104.22.168.1 The Travel Cost Method (TCM)
This method is often used to value tourist centres like recreational sites and parks. The basic assumption that underpins this method is that if people are willing to incur the costs of travelling to a recreational site and the price of being admitted to the site, then they must value the site that much. It can be noted from how this method works that the value of the resource is drawn from the prices people are willing to pay to access it; that is the cost of transporting oneself to the site and the cost of admission to the site. This way, it is only the use value of the resource that is observed. This is because the inherent values that the users of the site have for the resource is not measured. It is just the cost they pay to use the resource that is measured. Hence, TCM cannot measure the total economic value of a resource.
A major criticism against the TCM is that an individual’s decision to visit a site does not only depend on the cost of visiting but also to a large extent, dependent on the time available at the disposal of the individual. Therefore, sampling only visitors to a site to ask about their travel costs and use that as a measure of the value of the resource may be flawed since other people may equally have value for the resource but may have other engagements such as a tight work schedule or academic engagement that do not afford them the time to visit the site for recreation. The values of such individuals may not be regarded or counted and this is likely to bias the value given to the resource at the end of the valuation exercise.
Also, it is argued that potential visitors to a recreational site may not be fully informed about the total costs involved and the total benefits they may derive from the site before deciding to visit. Thus for such people, it is difficult to assume that they embarked on the visit because the costs involved indicates their valuation of the resource.
The issue of multipurpose visit is also essential in assessing the validity of value estimates derived from the TCM. A multipurpose trip is the situation whereby an individual embarks on a visit to a particular area for several reasons. Perhaps work related or family related visits may be combined with a visit to a recreational site; a situation which adversely affects the value attributed to the resource by such a visitor based on his travel costs since he did not incur all those costs solely for the purpose of the recreational site.
Since the TCM values only use values and especially because the method has been used to value recreational sites and parks, it may not be suitable for valuing improved quality electricity supply as is the focus of this study. Rationally, people do not travel to go and use electricity and return back to their homes thus making this method less preferred for a study such as this one.
22.214.171.124.2 The Averting Behaviour Method (ABM)
The Averting Behaviour Method (ABM) values a particular resource by looking at the costs of the actions people take to avoid or as the name goes to avert the risks they face should that resource deteriorate in quality. ABM has been basically used to value environmental quality.
The underlying assumption here is that individuals are aware of the adverse effects of deterioration in environmental quality such as air pollution, water pollution, and depletion of the ozone layer among others. Knowing the adverse effects that comes with the deterioration, individuals do take certain measures that seek to avert or reduce the risks they face in such environments. The cost of the measures they take is used as a measure of the value of the resource. For example the willingness of people to pay for clean water from a river will be derived from the purchases people make to purify the water to avoid the risks they face because of the polluted water. Another example is when people purchase such goods as sun glasses to avoid the risks of blurred or aching vision they face by walking under the sun due to ozone layer depletion. The costs of these actions are used as a measure of how much they value environmental quality. In the specific case of this study on electricity, an example could be the costs households incur in purchasing items that reduce the adverse effects of poor electricity supply on them such as purchasing a generator or a stabilizer due to the quality of the electricity supply.
ABM faces a number of criticisms. A common one is that individuals may value a resource much more than it costs to avert the adverse effects that come with the deterioration of the resource. For example, buying sun glasses may cost far less than the value society places on an undepleted ozone layer. Further, people may purchase a good not because they seek to avert any risk. In the example of the sun glasses, if it becomes fashionable to wear sun glasses, people will make expenditures on it for the sake of fashion and not for the sake of mitigating the effects to the eye of walking under the sun due to ozone layer depletion.
It is further argued that, just because people do not make any expenses to avert the effects of deterioration in environmental quality does not imply they have no value for it. In the case of electricity, the fact that people do not purchase generators to shield them from the adverse effects of frequent power outages does not imply that they do not value continuous supply of power. Also, households not using power surge protectors or stabilizers to regulate an unstable voltage does not infer they do not value quality electricity supply with a stable or useable voltage. They may be constrained by other factors for which reason they are unable to make those ‘needed’ purchases. Hence, valuing a resource based on information only from those who take certain actions is likely to bias the value given to the resource at the end of the valuation exercise.
The ABM can only be used to determine the value of resources of nature based on certain qualities. Since it does not help in giving the total value of nature because it loses out on non-use value, it is not the preferred method for this study.
126.96.36.199.3 The Market Price Method (MPM)
This method calculates the total net economic benefit or the total economic surplus of a good and uses that as a measure of value of the good. The higher the economic surplus, the greater is the value of the good or service and vice versa. Total economic surplus is the sum of the consumer and producer surpluses. Consumer surplus measures the benefits a good or service gives a consumer over and above the cost of acquiring the good. Producer surplus is a measure of the benefits that accrue to a producer over and above the cost of making the good or service available to the consumer.
This MPM is largely dependent on the market price of the commodity being valued since surpluses are calculated using the market price. However, only a few of environmental goods have markets and hence prices. Therefore, this method cuts off quite a number of non-market goods needing valuation. For those goods that have market prices, information asymmetry and other imperfect market conditions do not yield an efficient price and thus arriving at the true economic surplus from these prices is highly questionable.
Also, in many developing economies, the government takes care of many resources while many inputs are not accounted for in the price of the final commodity probably due to inefficient systems leading to prices that do not fully reflect the worth of the commodity. For instance, the increasing high electricity tariff that households have to pay for the epileptic power supply in Nigeria. Again, prices paid by consumers are the going market prices and does not capture their intrinsic value for a resource hence the MPM is not very appropriate for this study.
188.8.131.52.4 The Hedonic Pricing Method (HPM)
The Hedonic Pricing Method (HPM) is often used to value the properties’ market and the labour market. In the properties market, it is known as Property Value Approach while in the labour market, it is known as the Wage Differential Approach. The HPM is used to measure non market components or attributes of a marketed good. The HPM relies on the assumption that the price of a good is dependent on the attributes of the good in question and that individuals do value the attributes that make up a good more than the good by itself. A good may however, have as part of its attributes or characteristics an environmental component which may be difficult to value and the HPM comes in handy to value such non market components of goods.
The HPM measures the value of the separate attributes of a good by looking at how the price of the good changes when the attribute changes. The HPM regresses the price of the good on its attributes yielding a certain function V = f (Ais).
Where V is the value or price of the marketed good and Ais are the attributes of the good.
From this function, one can calculate the how the value of the good changes when there is a marginal change in the explanatory variables (the attributes, A).
HPM assumes weak complementarity and this is a weakness of this method. Weak complementarity in this case means that for a person who does not use the good or pay for the good, his value of its attributes is zero which includes the environmental qualities of the good. For a property, this means that HPM will only value the environmental quality of the neighbourhood within which the property is located and not for other places. This method also assesses use values only since it measures environmental changes’ effects on price that an individual is willing to pay of the good. It does not measure non-use values and hence cannot be used in this study.
184.108.40.206.5 The Production Function Method (PFM)
The Production Function Method investigates how environmental qualities affects output levels of an economic activity and from that, gives value to the environment. PFM depends on the fact that some natural resources and environmental quality are inputs in the production process. Thus changes in these resources or environmental qualities will have some effects on production and the value of the impacts observed through changing market prices. The method essentially measures changes in qualities of nature on production costs and output.
Critics have argued that losses arising from costs of production due to changes in environmental quality may not be very representative of society’s value for that environmental quality. In other words, it is one sided because only the producer side is considered without due consideration given to consumer side issues such as consumer surpluses. Furthermore, some producers in the course of production may resort to averting behaviour to reduce the impact of changing environmental quality on their output. This makes it difficult to accurately measure losses in production output as a result of changing environmental quality. For example, a farmer whose land suffers from soil erosion may resort to fertilizers to booster the nutritional needs of the soil in order to avert the soil’s inability to sustain high crop yields. The PFM does not capture the total economic value of nature; it captures only a part of total value and thus cannot be used in this study.
220.127.116.11 Imputed Willingness to Pay/ Circumstantial Evidence
The second category is known as the Imputed Willingness to Pay or Circumstantial Evidence.
Circumstantial Evidence Approach is sometimes known as Surrogate Market Valuation Approach. This is because it involves measuring the value of a non-market good, service or resource by looking at the market price or shadow price of related goods and services. These related goods and services in this case act as surrogates from which the value of a particular non market good can be inferred.
Here, the value of a resource is arrived at by finding out people’s willingness to pay or the cost of the actions people take to avoid the losses they will incur should the services rendered by the resource be ceased. In the case that the losses do actually occur, the cost of people’s actions to replace the losses could also be used as a measure. The idea here is that if people incur costs to avoid damages that arise as a result of lost services provided by non-market resources, or to replace them in the event they are totally lost, then the resource must be worth at least the costs incurred to keep or replace them. This is because typically, a rational individual will not pay more money to replace a good or service if the existence of the good or service in question does not yield benefits to him worth the amount he is willing to spend on it. Based on this principle, the following valuation methods have been developed: Damage Cost Avoided Method (DCAM), Replacement Cost Method (RCM), and Substitute Cost Method (SCM).
18.104.22.168.1 The Substitute Cost Method (SCM)
The Substitute Cost Method (SCM) hinges its estimations of the value of a natural resource on the cost of providing a substitute to the resource or the services provided by the resource.
22.214.171.124.2 The Replacement Cost Method (RCM)
The Replacement Cost Method (RCM) bases its value of a resource by observing the costs incurred in replacing the resource or the services provided by the resource. Replacement cost is often in terms of the market prices of the resource used as a replacement. For example, if fertilizer is purchased to replace nutrients lost in the soil due to soil erosion, then the costs of the fertilizer in terms of its market price is used to value the soil.
These related goods or surrogates may either be substitutes to the non-market good in question or complements to the good or service a resource may provide or any good from which indirect information about the non-market good’s changing economic impact may be obtained. It is argued that the surrogate market valuation technique is limited by the fact that it is potentially able to provide dependable estimates only if the value of the non-market good under consideration is revealed by the prices and behavior of consumers in related markets. Since market prices typically reflect use values of a commodity, what it implies then is that the surrogate market valuation technique is not appropriate if a resource exhibits non-use values rather than benefits from use.
126.96.36.199.3 The Damage Cost Avoided Method (DCAM)
The Damage Cost Avoided Method (DCAM) bases its value estimates of a resource on the costs of actions that society takes to avoid damages or loses that may occur should the resource cease.
It is argued that the methods in this class circumstantial evidence are risky and inaccurate to use. This is because human beings though rational, make some replacement and damage avoidance decisions not entirely out of economic reasons. Sometimes, emotions and feelings guide their decisions. Due to these considerations, damage avoidance or replacement methods of valuation are most appropriate to situations where those damage avoidance or replacement decisions have actually been made or will definitely be made (Mishra, undated ).
As earlier stated, these methods are not appropriate for valuing the improved electricity system for this study because among their other flaws, they are unable to intrinsically measure the non-use value of nature.
188.8.131.52 Expressed Willingness to Pay
The third class of valuation methods is known as the Expressed Willingness to Pay. As earlier stated, non-market goods are not traded in the market place and some if not most of them may not have close semblance with any good or service traded in the market place. Thus ‘revealing’ ones preference to pay for them is not an option. It is also not always possible to impute people’s willingness to pay for a good by observing the costs of their actions taken to avert suffering damages as a result of the loss in the resource. In such cases, people are asked in a survey to state their willingness to pay for a resource after they have been presented with a hypothetical scenario. In other cases, they may be asked to make tradeoffs among different alternatives. Data generated from these surveys are used to estimate people’s willingness to pay for the good, service or resource in question.
This class of valuation techniques, also known as stated preference approach involves directly asking individuals what value they attach to unmarketable environmental services, and to express their preferences towards changes in service flows (Lareau and Rae, 1987).
Methods under this category measure both use and non-use values of a resource thus giving the total economic value of the good, service and resource being valued. Botchway (2011) pointed out in his work that because these methods are not tied to behaviour, they can be used to value some goods and services that the revealed preference methods may not be able to value. Valuation methods in this class are the Contingent Valuation Method (CVM) and Contingent Choice Method or the Choice Experiment Method (CEM).
184.108.40.206.1 The Choice Experiment Method (CEM)
Under this valuation technique, WTP is deduced from hypothetical choices or tradeoffs that respondents make. Respondents are given a set of alternative representations of a good and are asked to choose their preference. This is similar to real market situations where consumers face two or more goods which possess similar characteristics but at different levels of these characteristics. The respondents are asked to choose whether to buy one of the goods or none of them. In other words, Choice Experiments are a contingent valuation method based on random utility theory and Lancaster’s characteristic theory of value which states that, the value of a good is determined by the attributes that make up the whole (Garrod and Willis, 1999). Choice experiment therefore seeks to find the values for each of these attributes of a particular resource by presenting respondents alternative choices each made of different degrees of the various attributes. Respondents are required to either choose an option or maintain the status quo. The analysis of the tradeoffs helps to arrive at the WTP for each attribute.
Choice experiment provides more information about the resource being valued on the whole and the decisions here mirror the decisions faced by consumers in real life where they have options of varying attributes from which to choose.
220.127.116.11.2 The Contingent Valuation Method (CVM)
Ciriacy Wantrup first came out with the Contingent Valuation Method in 1947 as a means of eliciting the market value of a non-market good. However, it was first used in a study by Davis (1963). Although this method is tagged as the most controversial of all environmental valuation techniques, it has become the most widely used technique (Hanley et al. 2002).
The CVM measures the value of a resource by calculating the WTP of local residents to keep the resource or the amount required to compensate them for deterioration or a total loss of the resource. In effect, this method asks people to directly state their WTP for a particular good or to improve a particular service or their Willingness -to -Accept (WTA) to give up a good or for deterioration in a service. In other words, this approach involves asking individuals directly the value they attach to a particular resource and/or its characteristics. Thus, the method is able to estimate the respondent’s consumer surplus for the resource and therefore the maximum amount the resource is worth to the respondent. In this technique, a hypothetical scenario which details out the attributes of a certain resource and its effects is created and respondents are asked in a survey how much they (or their household) will be able to pay for that resource or how much compensation they will accept should the resource deteriorate or be lost completely. This technique is called Contingent Valuation because people are asked to state their WTP based or contingent upon a specific hypothetical scenario and description of the resource. The total value of the resource is determined by averaging respondents’ values and extrapolating it across the population. This is an open ended contingent valuation format. It has been argued, however, that respondents often find it a difficult task to assign an appropriate value to the resource on their own. This often leads to a wide range of responses in a survey. In contrast to the open ended format is the close ended format of contingent valuation. This is a discrete or dichotomous choice question where respondents are presented with a value and are asked to either respond ‘yes’ if they would pay that amount or ‘no’ if otherwise. This typically mirrors the choice of consumers face in an actual market for a commodity where the good has a price and they either buy the commodity at the going price (yes) or they don’t (no).
Other elicitation techniques exist. The choice of an elicitation technique however, depends on the type of resource being valued and the nature of the sample. Among the common elicitation techniques are:
i. The Bidding Game Technique: The bidding game was first used by Davis in 1963. This elicitation technique involves taking the respondent through a series of bids until a negative response is generated and a threshold established. There is a starting bid given by the interviewer to which the respondent either agrees to pay (or accept) or disagrees. The interviewer keeps increasing the bid till the respondent answers ‘no’ to it or keeps decreasing the bid till the respondent answers ‘yes’ to it. The latest bid to be accepted represents the respondent’s maximum WTP (or minimum WTA). There is a starting point bias in this technique. The situation whereby the starting bid suggested by the interviewer has the potential to ultimately influence the respondent’s final bid is what is termed as a starting point bias.
ii. The Payment Card Technique: This technique was developed by Carson and Mitchell (1981 and 1984 respectively) as an alternative to the bidding game. This format asks respondents to choose from a range of values which best suits their maximum WTP. This approach doesn’t provide a single starting point and thus eliminates the starting point bias as found in the bidding game. However, biases may arise as a result of the ranges used on the cards.
iii. The Discrete Choice Technique: Bishop and Heberlein in 1979 developed the discrete or dichotomous choice technique which is also referred to as the take-it-or-leave-it format or the referendum format (Bishop ; Heberlein, 1979). This approach asks the respondent to either agree or disagree to an amount stated by the interviewer. The amounts given are varied across the sample. This is what most consumers face in actual markets and hence, are familiar with this system. This is also called the single bounded dichotomous choice. This method makes the respondents’ task easier similar to the bidding game but this excludes the iterative process component of the bidding game. As noted by Botchway (2011), the disadvantage with this method is that more observations are required for the same level of statistical exactness in a sample estimate.
iv. Single and Double Bounded Voting Game: This approach is also referred to as the Discrete Choice with a Follow up approach. It requires respondents to answer ‘yes’ or ‘no’ to an amount regarding their willingness to pay for a particular resource. A ‘yes’ response draws out a follow up question with a higher amount while a ‘no’ response attracts a follow up question with a lower amount this time round. This approach though gives the survey process significant gain in efficiency, still has the limitations observed under the discrete choice technique. After all, this is just the same as the discrete choice; only with follow up questions. Additionally, the follow up questions gives this format some semblance with the bidding game and thus suffers from the limitations of the bidding game especially the starting point bias.
Some of the biases that are likely to confront the use of CVM as a valuation technique include:
i. Starting Point Bias: The starting point bias arises when the starting bid given by the interviewer goes to ultimately influence the final response given by the respondent. This bias is best minimized by varying the starting bid among the sample. This way, the interviewer is able to investigate the influence of the starting bids on the final WTP.
ii. Strategic Bias: This bias arises when respondents intentionally understate their WTP or overstate their WTA. Sometimes also, WTP may be overstated especially if the respondents are aware that they will not be asked to pay for the resource but their responses are merely being used to get a value for the resource after which the government will provide the good. Respondents are likely to overstate their WTP if they want the good provided or may understate it if they do not want the resource provided. A discrete choice format where ‘yes’ or ‘no’ responses are required for differing amounts within the sample may minimize this bias.
iii. Hypothetical Bias: Hypothetical bias results from a poor understanding of the hypothetical scenario created from which WTP questions are asked. If respondents misunderstand the scenario or the scenario is misrepresented by the interviewer, it will lead to responses that do not match the hypothetical scenario hence biases. This can be minimized by well explaining the hypothetical scenario and avoiding any ambiguity whatsoever. Hypothetical bias may also arise because people may respond differently to hypothetical decisions compared to how they make actual decisions.
iv. Interview and Compliance Bias: Interview bias arises from the conduct of interviewers that tend to influence the responses given by the respondents in a survey. Compliance bias arises when respondents attempt to give answers that they think may please the interviewer. These biases can be minimized by training interviewers well to adhere to the principles of conducting an effective survey.
v. Non response Bias: Non response bias results from the fact that some sample members do not respond and yet they have values for the resource which may be different from those given by respondents. This has the tendency to bias the overall value placed on the resource.
vi. Information Bias: Information bias arises because respondents may be asked to value attributes for which they have little or no knowledge of. This means that the information that they are given to the respondents will have substantial influence on their responses.
However, despite the likely biases that may arise when the CVM is employed, there are effective ways by which to reduce or eliminate them in some cases as have been discussed. This makes it less costly to use the CVM since the potential biases may be dealt with as opposed to the earlier valuation methods discussed whose biases may be difficult to overcome.
One major merit of the CVM over other valuation methods is its ability to measure both use and non-use values. It is able to measure the total economic value of a resource because respondents will consider both the use values as well as non-use values of the resource to them before arriving at the maximum amount they are willing to pay for the resource or willing to accept for deterioration in the resource. CVM is also the most widely used because it is widely applicable as Hanley et al. (2002) posited. According to Pearce and Turner (1990), the CVM is the only known technique for finding the value of many non-market benefits especially their non-use values.
Compared to other methods especially revealed preference methods, the CVM has an advantage. It is flexible enough to allow for the creation of hypothetical market scenario. These hypothetical scenarios may go beyond observed market behaviour and thus helps to measure existence values that are not related to the consumption of other goods.
These are the reasons for which the CVM is the valuation method employed in this research.
3.2.3 Willingness to Pay (WTP) and Willingness to Accept (WTA)
There are two Hicksian measures of utility change developed by Hicks (1941) which can be used to study the value attributed to a good or service in a contingent valuation survey; compensating variation and equivalent variation. Compensating Variation is the change in income that would ‘compensate’ for a price change. It is the maximum amount that an individual would give up for a good or service to keep his utility constant. Equivalent Variation is the change in income that will be ‘equivalent’ to a proposed price change. It is the minimum amount an individual would accept to forego a good or service or lose some part of the good. Table 3.1 below gives a detailed summary of Hicksian measures of utility change:
Table 3.1 Hicksian Monetary Measures for the Effects of a Price Change
Willingness to accept compensation for the change occurring
Willingness to pay for the change not occurring
Willingness to pay for the change occurring
Willingness to accept compensation for the change not occurring
Source: Perman et al. 2003
Willingness to pay and willingness to accept may provide different values for the same commodity change. WTP for a good is usually lower than WTA compensation to forego the same good (Bishop and Heberlein, 1979) and most studies have also suggested that people tend to value losses more highly than corresponding gains.
It is often difficult to measure WTA accurately in contingent valuation. Bishop and Heberlein (1979) and Bishop et al (1983) substantiate this by reporting in their studies that WTA compensation in contingent valuation surveys exceed actual WTA compensation for the same goods. Due to this, researchers have almost always focused on WTP in assessing the value of a resource.
3.3 Empirical Literature Review
Literature on the use of valuation techniques are quite numerous. A variety of public programs and other environmental issues have been valued making use of these techniques. The Contingency Valuation Method has been widely used as a technique for valuation in both developed countries and developing countries more recently. Studies to assess willingness to pay for infrastructures in areas such as water supply, health insurance, and environmental quality are numerous. However, those that concentrate on assessing the cost of power outages are limited especially in Africa.
This section will review works on willingness to pay for reliable quality electricity supply or to avoid outages.
3.3.1 Willingness to Pay: Improved Electricity and Avoiding Power Outage Costs
Carlsson and Martinson (2004) carried out a study on households in Sweden to investigate their WTP to avoid power outages. The results observed was that households are willing to pay more to avoid a power outage the longer the duration of the outage. Another significant determinant identified in the study was whether outages were planned or unplanned. By planned outages, households are notified in advance about an impending power outage; unplanned outages referring to the opposite. Specifically the authors reported that households were willing to pay 6.30 SEK (Swedish Krona) for a one hour outage as compared to 189.25 SEK for a 24 hour outage for planned outages. For unplanned outages, the figures were 9.39 SEK and 223.01 SEK for an hour and 24 hours outage respectively.
Adenikinju (2005) conducted a study into the costs of infrastructure failures in a developing economy with focus on the electricity sector in Nigeria. Using both a survey and the revealed preference approach, the cost of power outages to the business sector of the Nigerian economy was analyzed. The study infers that the poor supply of electricity in Nigeria has come at great costs to the business sector; these costs include costs of acquiring very expensive back up capacity to cushion firms against the losses arising from power fluctuations. In other cases, some firms had to shut down production at one time or another as a result of power outages. Factors that underlie power outage costs in this study were the frequency and duration of outages as well as the presence of a backup power facility in a firm.
Serra and Fierro (1997) carried out a study on power outage costs to Chile’s industrial sector. Three components of net outage costs were identified, they include: surplus losses cost, rationing cost, and disruptive cost. Their focus was on surplus losses. A sample of 200 firms under different classifications giving respondents nine different outage scenarios were interviewed, the study concluded that for a 10% restriction of electricity in a month, outage costs were between US$ 0.5 and US$ 83.5 with the lower costs applying to firms with back up facilities. Different costs were recorded for the different outage scenarios. It was inferred that the outage costs are highly dependent on the rationing strategy used.
Oseni M. (2017) conducted a study to investigate the extent to which the coping strategies especially self-generation, being the popular close substitute for public provision in the country might affect WTP for reliable electricity service in Osun State and Lagos State, Nigeria. He observed that having a generator tended to increase (rather than decrease) households’ WTP. This is despite the fact that having and using a generator could potentially reduce the welfare impact of power unreliability. Further exploration in his research of the link between the marginal (outage) cost of self-generation and backup households’ WTP decisions, however, revealed that the significantly high cost of self-generation (outage cost) might be responsible for the observed WTP behaviour of the backup households. The decision by backup households to pay more appears to be driven by rational behaviour, because paying more to enjoy reliability would mean having extra benefits—i.e., enjoying extra reliability at a lower cost than that of self-generation. For this study, the author inferred that backup households’ decisions to pay a higher amount than non-backup households are influenced by the costs of self-generation: an increase of N1 (US$0.006) in self-generation’s fuel cost per-hour is associated with WTP about N5.22 (US$0.032) more in the monthly bill. However, households’ WTP US$0.15–0.16/kWh of improved reliability is smaller than the marginal costs of reliability from self-generation—US$0.27–0.41/kWh. Further analysis, shows the estimated mean WTP that Nigerian households, regardless of their income, would be willing to pay an extra amount (up to 86 per cent) above the current tariff for improved service quality. This implies that households would value the reliability of a more expensive supply above the current highly subsidised tariffs that come with low quality. The estimation of outage (self-generation) cost in this study provides insights into the cost imposed on households of poor electricity services and the households’ preferences for improved electricity service performance, which, in turn, can help policymakers in terms of reliability investment planning.
Also, Babawale, G. and Awosanya, A. (2014) carried out a study to investigate the Willingness-to-pay for improved electricity supply in Lagos Metropolis, Nigeria using two medium-income public residential estates as a starting point in a series of similar studies intended to cover different types and composition of residential estates/neighborhoods in the Metropolis. The results showed that Willingness-to-pay for improved electricity services in Millennium Estate is affected by household income, household size, number of days households use their generators within a week, and the cost of running generator. Cost and revenue projections showed that the residents of the two estates need to be willing to pay substantially more in order to make electricity generation from wind turbines a viable option. One obvious inference from the study is that sustainable electricity supply to the housing estates under reference through private sector participation is presently not feasible. It implies that electricity supply to the estates and other estates of similar (or lower standards) socio-economic characteristics in the metropolis would continue to be provided by the state-owned Power Holding Company of Nigeria (PHCN) at the existing subsidized rates. The study throws light on cost recovery in electricity supply. The results therefore provide useful inputs into government policy formulation when choosing and designing alternative source of power supply for residential areas of different socio-economic characteristics in the metropolis particularly in the light of the ongoing private-public partnership arrangements for provision of infrastructure.
The research work of Serra and Fierro (1997) in Chile as well as that of Adenikinju (2005) in Nigeria, though focusing on the business sectors of their respective economies as opposed to the focus of this study – households, make the logical conclusion that poor electricity supply is a cost whether viewed from the perspective of the household of from that of the firm. When both households and firms suffer from poor electricity supply, losses that will accrue to society will be greater because there would be non-production and under production of goods and services due to insufficient or poor supply of electricity (Munasinghe, 1980) thereby affecting the national income of the country due to unreliable and unstable power supply.
Damigos et al. (2009) carried out a study to determine the willingness of households to pay for securing natural gas used in electricity generation in Greece. The CVM was employed in this study. Their study was based on the fact that most of Europe’s energy especially fossil fuel sources were imported and about 70% of the European Union’s gas imports went into power generation. This situation, according to them, called for a need to undertake measures that will secure the supply of natural gas so as to ensure a steady supply of electricity. This would come at an extra cost to society for which the authors sought to investigate how much more households were ready pay to secure natural gas supply. The study inferred that households were willing to pay a premium of between €4.5 and €12.7 per MWh on their electricity bills. The WTP amounts in total represented a surcharge of 7.1% on electricity bills. It was concluded that security of natural gas for electricity generation was of great value and households were ready to support measures geared towards it.
It is noteworthy to point out that the study focused on the input used in the generation of electricity and not the final product itself. This deviates from other studies on this subject matter that dwelt on the final product – electricity. This may suggest that transmission and distributional problems and inefficiencies must have been reduced to their barest minimum in Greece hence once the input which is natural gas is secured, the supply of electricity would be steady. For other studies however, households were asked their WTP for the final product which includes all processes in the electricity value chain.
Twerefou, D.K. (2014) conducted a study in Ghana and employed a CVM to assess households’ WTP for improved electricity supply as well as the factors that influence WTP. Results from his analysis indicated that, households in Ghana are prepared to pay on the average about ?0.2734 for a kilowatt-hour which is about one and a half times more than what they are paying currently. An econometric analysis of the factors that influence households WTP for uninterrupted electricity supply inferred that household income, sex, secondary as well as tertiary level of education of the household head and household size are significant factors that affect households’ WTP for improved electricity. It was recommended that government invests in infrastructure in the power sector and increases tariffs since Ghanaian are prepared to pay about one and a half times more than what they are paying now if they will be provided with improved electricity supply.
Also, Kateregga (2009) employed the CVM to elicit power outage costs of consumers in three Ugandan suburbs interviewing a sample of 200 households in these 3 suburbs. Payment cards and open ended questions were asked and the Tobit model was used to explore the effects of socioeconomic factors on responses. The study revealed that estimated WTP means were greater than the medians. This means that although households incurred costs during outages, few of the sampled homes were willing to pay significant amounts to avert the inconveniences that come with power interruptions. The factors that were found significant determinants of the WTP were income, electric energy as the main source of cooking fuel in the household, and substitution costs.
Abdullah and Mariel (2010) conducted a choice experiment valuation study among electrified rural households in Kisumu District, Kenya to estimate the WTP to avoid power outages or blackouts. A mixed logit estimation was applied to identify various socioeconomic and demographic factors that influenced WTP. The study reported that some households in the surveyed district are willing to pay a certain amount above their monthly bills to improve electricity supply while others are not prepared to pay any more money above the monthly bills they paid at the time.
It was further revealed that the decision of a household to belong to either of the categories depends on factors such as employment status, age, number of years a household has been living in the district under consideration, family size, ownership of a bank account or otherwise among others. It was further asserted in their study that those who are unemployed, older in age or have been living in the area for a longer period will not be ready to pay more than their monthly bills for electricity improvement. However, individuals who own bank accounts, engage in farming activities or have larger family sizes will be willing to pay more to avoid outages.
The findings of Kateregga (2009) that few of the sampled homes were willing to pay significantly to avoid losses from power interruptions partly agrees with the findings of Abdullah and Mariel (2010) that only a part of the sample was ready to pay significant amounts (in this case, amounts above their monthly bills) to avoid costs of power interruptions. In terms of the determining factors, income or employment status as used in the work by Abdullah and Mariel (2010) was seen to be significant in both cases signifying a strong reliance of WTP on a respondent’s ability to pay measured by his income level or his employment status.
McNair et al. (2011) carried out a study on households WTP for the conversion of electricity distribution networks from overhead to underground in Australia. It was noted in their work that underground low voltage electricity networks are advantageous compared to overhead ones. The benefits of the underground networks include reliability of supply, safety as well as improved visual amenity. However, the value that households place on these benefits will determine whether or not it is economically rational to convert overhead networks to underground ones. The study therefore sought to establish how much households were willing to pay for this conversion (which will stem from how much they value the associated benefits) via a choice survey in residential areas in Canberra, Australia. The study reported that the value that households place on undergrounding electricity networks (and for that matter, the benefits that come with it such as reliability of supply, safety and visual amenity) was a conservative average of at least A$6,838 per property. The conclusion drawn out from the study was that households have some value for the overhead to underground conversion exercise because of the benefits that it will bring them and thus are willing to pay for it.
The research actually admits that electricity supply is largely reliable in Australia with few power cuts occasionally and does not necessarily calculate outage costs or focus on improving electricity. However, households chose to pay for undergrounding of electricity networks in order to enjoy its benefits which include more reliable supply (even though supply is quite reliable already). This goes to show that for reliable and quality electricity supply, households can never have enough of improvement. Once there is room for further improvement, rational economic agents will go for it. Also, another benefit that underground electrification would offer to Australian nationals is the relaxation of tree trimming responsibilities because in Australia it is the responsibility of residents to ensure that overhead networks, which are reticulated right along the boundaries of their houses, are not interfered by trees. Tree trimming is therefore constantly required of residents in order to keep them from coming close to the electricity networks.
Pepermans (2011) conducted a study on Flemish households in Belgium to determine the value of continuous power supply. The study noted that electricity supply is largely reliable in Belgium and as such power outages are quite unlikely. Using the choice experiment approach, it was established that on average most household types will be willing to accept as much as €30.00 – €50.00 to have just one additional power outage per year. Additionally, he estimates the average Willingness to accept (WTA) for just a one minute increase in the duration of an outage to be in the region of €0.30 – €0.60 per minute.
Regarding placing monetary values on the costs of erratic power supply, both Carlsson and Martinson (2004) and Pepermans (2011) have the same conclusion. Both studies agree that their respondents were willing to give up significant amounts to avoid power outages or willing to accept significant amounts for the occurrence of power outages. Both studies have as a strong determining factor, the duration of the outage. The findings of these two studies conducted in Sweden and Belgium interestingly deviate slightly from those conducted in African countries (Uganda and Kenya). In terms of WTP in the context of the developed countries, it is neither lost nor even doubtful that households have high WTP to avoid the costs they face when electricity supply is cut. There is no compromise on the value placed on constant flow of electricity by residents of the more developed economies. However, in the African context, the same cannot be said. Not many of the respondents would readily be willing to pay huge amounts of money to avoid losses from power outages because they are already used to the historic blackout trends.
In terms of significant determining factors, income was a key factor in influencing WTP within the African context whereas within the context of the more advanced economies, the major issue was on the duration of the outage rather than income. This may be due to the fact that in the more developed economies, having continuous supply of electricity is deemed an absolute necessity; not at all an option irrespective of the income or social status of a person. However, in the African setting, having continuous supply of power in every home for most of the African economies would be considered a ‘miracle’ or an unusual phenomena. This is because having electricity continuously and continually is deemed by most commoners as a luxury; mostly affordable to high income earners or of the highly respected persons in society. Therefore, WTP for improved electricity in these countries is most likely to be highly dependent on the income levels of the people as Kateregga (2009) and Abdullah and Mariel (2010) rightly inferred.
Theoretical Framework and Methodology
This chapter explains the methodology adopted in this study. It discusses the theoretical framework structuring this study, gives an overview of how the survey will be conducted and the means by which the responses obtained will be analyzed.
4.1 Theoretical Framework
The underlying economic theory adopted in this study is the random utility theory pioneered in the 1920s and later modified to incorporate the manner of specifying utilities developed by Lancaster (1966) and McFadden (1974). This study assumes a utility function after the Random Utility Model (RUM) in which utility provided to individual i by good j (Uij) is a function of observed characteristics of the individual and of the good being consumed as well as a function of an unobserved stochastic error term eij. The indirect utility function associated with this kind of utility function may be written as:
Uij = Ui (Yj, Vj, eij) ………… (4.1)
Where Yj is disposable income for household j, Vj is the vector of observed characteristics of the household and of the given choice of the household, and eij is the unobserved error term of the indirect utility function.
A payment bid Yi* is introduced which changes the characteristics of the good in a contingent valuation survey such as the quality of the good. The consumer will agree to the payment proposed if and only if the utility derived from the improved state is greater than the utility derived from the status quo. Symbolically,
Uij (Yj – Yi*, Vj, eij) > Uij (Yj, Vj, eij) ………… (4.2)
Where Yi * is the amount the household is willing to pay for the proposed improvement in the resource. The probability that a respondent will answer yes is an indication that he prefers the proposed improvement. Thus for the jth respondent, the probability that he answers ‘yes’ is given by:
Pr (yes) = U1j (Yj – Yi*, Vj, eij) > U0j (Yj, Vj, eij) ……… (4.3)
A common formulation of the Random Utility Model (RUM) is the Additive Random Utility Model (ARUM) (Cameron & Trivedi, 2005). The ARUM assumes that the utility function is additively separable into deterministic and stochastic preferences. Thus equation 4.1 may be written as:
Uij= Ui (Yj, Vj) + eij ………….. ….. (4.4)
The probability statement that a respondent answers ‘yes’ to a proposed bid therefore becomes:
Pr (yes) = U1j (Yj – Yi*, Vj) + e1j > U0j (Yj, Vj) + e0j ….. (4.5)
Now let WTPi be the maximum amount a household is willing to pay for improvement in quality electricity supply. From consumer demand theory, WTPi is hypothesized to be a function of the household’s socioeconomic attributes and the characteristics of the electricity supply (Greene, 2008). Also, since utility in the RUM depends on deterministic and random components, the change in utility associated with an improvement in quality electricity supply will equal the change in the deterministic and random components. In other words, WTP can be written without loss of generality as:
WTPi= ?iV’i + ei ………………. (4.6)
Where, ?i = vector of estimated parameters,
Vi = vector of the household’s socioeconomic attributes and the characteristics of electricity supply and
ei = the error term which captures all other factors that affect households’ WTP which have not been included in the model.
The error term is assumed to follow a standard normal distribution with a mean of zero and variance of one. On the basis of this framework, this study estimates the following equation:
WTPi = ?1ETi + ?2FBi + ?3GENDi + ?4HSZi + ?5HYi + ?6 PEDi + ?7SEDi + ?8TED + ?9 RELi + ?10PNTFi + ?i ……… (4.7)
WTP = Maximum Willingness to Pay
ET = Electricity Tariff
FB = First Bid
GEND = Gender of Respondent
HSZ = Household Size
HY= Household Monthly Income
EDU= Highest Educational Level Attained by Respondent
(PED= Primary Education; SED= Secondary Education; TED= Tertiary Education)
REL= Reliability of Current Supply
PNTF= Prior Notification Given Before Current Outages.
4.2 Data Types and Sources
This research will rely on primary and secondary data; data for this study will be sourced mainly from primary sources within the study area; Port Harcourt, Ibadan, Lagos and Abuja. Pieces of information will be obtained from secondary sources such as journals, annual reports, textbooks and the publications of the Nigerian Electricity Regulatory Commission, etc. to aid in the credibility of the study, the sampling of households for interviewing, and to aid in the analysis of the data.
The main instrument for the data collection will be a questionnaire. A well-structured questionnaire will be administered to a sample of households within the cities of Abuja, Ibadan, Port Harcourt and Lagos via face-to-face interviews. The questionnaire will be composed of two major sections; first, the nature of the quality electricity supply and how it affects households’ welfare. In the second section, a hypothetical scenario of an improved electricity supply system that conforms to all the dimensions of quality electricity supply will be created. In this scenario, power supply is assumed to be reliable and of good quality. Reliability means the power supply is available every time and good quality means the power supply comes with the appropriate level of voltage. The hypothetical case will rule out power outages to a large extent. Power outages may only occur when repair works need to be carried out and even in such cases, users of electricity who will be affected would be notified ahead of the outages and the outage will not last beyond three hours. Respondents will then be asked to state the maximum amount they are willing to pay for such an improved electricity supply system. The questionnaire will include questions about characteristics of the existing electricity supply system, consumers’ willingness to pay and the socioeconomic characteristics of the respondent and his/her household.
The elicitation format that will be employed in this study is the discrete choice with a follow-up approach. A first bid will be given to each respondent. If the respondent agrees to pay that amount, a higher amount will be proposed. If he agrees to that, a third amount, higher than the second will be further proposed. If he declined to pay the first bid, the follow up bid proposed to the respondent will be lower. After going through the follow up process, all respondents will be asked to state after careful thoughts what their maximum WTP for the improved quality electricity supply would be. The amounts each respondent states here will be compared to the responses from the follow up process to check for consistency. This format was chosen due to the advantages it has over other applicable formats as previously discussed in Chapter 3 of this research work.
A likely bias associated with this format is the starting bid bias. To help correct for this bias, the initial bids given will be varied among the sample.
4.3 Data Analysis and Estimation Techniques
In this study, the Contingent Valuation Method (CVM) will be used to obtain the willingness of households to pay for improved quality electricity supply. This technique is appropriate for this study because how much a consumer is willing to pay to avoid power outages invariably depict the cost to households of these outages. Also, this method allows us to assess both use and non-use value compared to other methods like Travel Cost which assess only use values.
A survey in the study areas will be conducted and household heads or their representatives will be asked questions about their existing electricity supply and other socioeconomic characteristics of the respondents and their households. A hypothetical scenario of an improved quality electricity supply system will be created. Based on this scenario, respondents will be asked to state the maximum amount they will be willing to pay per kilowatt hour of electricity for the proposed improvement.
The Ordered Probit Model will be employed as the main estimation technique for the study. The ordered probit is preferred in this study because although households may give an amount as their WTP, it may not be their maximum WTP. Their true WTP may lie within a certain interval of the maximum value the respondent is willing to pay and the next highest value. Hence, this implies that although the outcome of the event is discrete, the multinomial logit or probit model would fail to account for the ordinal nature of the response variable. The ordered probit model has merits over the unordered multinomial conditional or nested logit or probit model in that while accounting for the nature of the dependent variable, the unordered multinomial probit and logit models fail to account for the ordinal attribute of the dependent variable (Botchway, 2011). Also, Linear regression model is not an appropriate procedure for dealing with such an ordinal dependent variable because the assumptions regarding the specification of the error term in the linear model will be violated (Maddala, 1983). The ordered probit model is also preferred to linear regression model because it accounts for unequal differences between the ordinal categories in the dependent variable (Greene, 2008). The ordered probit model is specified as follows:
WTPi= ?iV’i + ei …… (4.8)
The respondents WTPi is unobserved, however, we would know the ranges within which WTPi falls from the responses. Let P1, P2, ……, PJ be the j prices which divide the range of WTP space into J+1 categories and WTPi be a categorical variable such that:
1 if WTPi* ? P1
2 if P1 ? WTPi*? P2
WTPi = 3 if P2 ? WTPi*? P3 ……. (4.9)
J+1 if PJ ? WTPi*
If j=1, 2,…, J+1, then the WTPi = j.
Furthermore, descriptive data analysis will also be employed and the Statistical Package for Social Sciences (SPSS) will be used in analyzing some of the collected data.
Abdullah, S. and Mariel, P. (2010) ‘Choice Experiment Study on the Willingness to Pay to Improve Electricity Services’. Energy Policy, 38, 4570-4581. http://dx.doi.org/10.1016/j.enpol.2010.04.012
Adenikinju, A. (2003) ‘Electric Infrastructure failures in Nigeria: A survey based analysis of the costs and adjustment responses’. www.sciencedirect.com/science
Adenikinju, A. and Center for Economics and Allied Research (2005) ‘Analysis of the Cost of Infrastructure Failures in a Developing Economy: The Case of the Electricity Sector in Nigeria. AERC Research Paper 148.
Adom, P.K. Bekoe W. and Akoena S. K. K. (2012) ‘Modelling aggregate domestic electricity demand in Ghana: An autoregressive distributed lag bounds cointegration approach’. Energy Policy, vol 42 pp. 530-537.
African Development Bank Group (2013), The High Cost of Electricity Generation in Africa,www.afdb.org/en/blogs/afdb-cham;ioning-inclusive-growth, retrieved 30/08/13 and Porter, D. V. (2004). 87 – 100.
Ajumogobia & Okeke (2015). ‘Nigerian Energy Sector: Legal and Regulatory Overview 2015’, Nigerian Energy sector Review, 2015, pp. 18-19.
Aliyu, A., A. Ramli, and M. Saleh (2013). ‘Nigeria Electricity Crisis: Power Generation Capacity Expansion and Environmental Ramifications’. Energy, 61(8): 354–67.
Altmay, G, and Karagol E, (2005). “Electricity Consumption and Economic Growth: Evidence for Turkey.” Energy Economies 27(6), 859-856.
Amadi, S. (2012), “Absence of Cost Effective Tariff Led to the Failure of Power Sector NERC”. www.royaltimes.net/absence-of-cost-effective-tariff-led-to-the-failure-of-po Retrieved on 4th July, 2017
Babawale, G. and Awosanya, A. (2014) ‘Estimating Household Willingness to Pay for Improved Electricity Supply in Lagos Metropolis’. British Journal of Economics, Management & Trade 4(5): 672-693, 2014. SCIENCEDOMAIN international www.sciencedomain.org
Bada A.S. (2016). ‘The Future of TCN: Ensuring Professional Management of and Investment in the Transmission Network’, 2016.
Bishop, R. C. and Heberlein, T. A. (1979) ‘Measuring values of extra-market goods: Are indirect measures biased?’ American Journal of Agricultural Economics, vol. 61, no. 5, pp. 926- 930.
Botchway, E. (2011) ‘Willingness to pay for improved water supply in the Accra Tema Metropolis’. An unpublished MPhil thesis, University of Ghana.
Briceño-Garmendia, C. & Shkaratan, M. (2011) ‘Power Tariffs: Caught between Cost Recovery and Affordability’. Africa Region Sustainable Development Unit. The World Bank WPS5904
Cameron, A. C. and Trivedi, P. K. (2005) ‘Microeconometrics-Methods and Applications’. New York: Cambridge University Press.
Carlsson, F. and Martinsson, P. (2004) Willingness to Pay among Swedish Households to Avoid Power Outages. Working Papers in Economics No. 154.
Carson, R. T. and Mitchell, R. C. (1981) ‘An experiment in determining willingness to pay for national water quality improvements’. A draft report to the US Environmental Protection Agency, Washington DC.
Carson, R. T. and Mitchell, R. C. (1984) ‘A contingent valuation estimate of national freshwater benefits: Technical report to the US Environmental Protection Agency’. Resources for the Future, Washington, D.C.
Damigos, D., Tourkolias, C. and Diakoulaki, D. (2009) ‘Households’ Willingness to Pay for Safeguarding Security of Natural Gas Supply in Electricity Generation’. Energy Policy, 37, 2008-2017. http://dx.doi.org/10.1016/j.enpol.2009.01.042
Davis, R. (1963) ‘Recreation planning as an economic problem’. Natural Resources Journal vol. 3, no. 2, pp. 239-249.
De Vita G. Endresen K. and Hunt L. C. (2006) ‘An empirical analysis of energy demand in Namibia’. Energy Policy 34, pp. 3447–3463.
Diabi, A. (1998) ‘The demand for electricity in Saudi Arabia: an empirical investigation’. OPEC Review. Energy Economics and Related Issues 22(1), pp. 12–17.
EIA (2013) ‘The United State Energy Information Administration (EIA) noted in the International Energy Outlook report for 2013’.
Electric Power Sector Reform Act 2005 www.nercng.org
Federal Government of Nigeria (2005), Electric Power Sector Reform Act, Lagos Nigeria, The Federal Government Press.
Fernandes C, Candela A, ; Gómez T (2012). “An approach to calibrate incentives for continuity of supply in the Spanish electricity distribution system”. Electric Power Systems Research, Volume 82, Issue 1, January 2012, Pages 81-87, ISSN 0378-7796, 10.1016/j.epsr.2011.08.020.
Filippini, M. and Pauchauri, S. (2002) ‘Elasticities of electricity demand in urban Indian households’. CEPE Working paper No.16.
Foley, A. M. Ó Gallachóir, B. P. Hur, J. Baldick, R. and McKeogh, E.J. (2010) ‘A strategic review of electricity systems models’. Energy Policy, vol. 35 pp. 4522-4530.
Garrod, G. D. and Willis, K. G. (1999) ‘Economic Valuation of the Environment’. Cheltenham, UK. Edward Elgar Publishing Ltd.
Giannakis D., Jamasb T, and Pollitt M. (2003). ‘Benchmarking and Incentive Regulation of Quality of Service: an application to the UK Electricity Distribution Utilities’. Massachusetts Institute of Technology Center for Energy and Environmental Policy Research.
Greene, W. H. (2008) ‘Econometrics Analysis’. Sixth Edition, New Jersey: Prentice Hall.
Hanley, N. Shogren, J. F. and White, B. (2002) ‘Environmental Economics in Theory and Practice’. New York: Palgrave MacMillan.
Hicks, J. R. (1941) ‘The rehabilitation of consumers’ surplus’. Review of Economic Studies, vol. 8, no. 2, pp. 108-116.
Iana Vassilena (2012). ‘Characteristic of Household Energy Consumption in Sweden: Energy Savings Potential and Feedback Approaches’. Mälardalen University Press Dissertations No. 129, School of Sustainable Development of Society and Technology.
IES (2015) ‘International Energy Statistics, February 2015: Nigeria Electricity Consumption, Export ; Import 1980-2013’.
http://nso.nigeria.opendataforafrica.org/vpzjzkg/nigeria-electricity-consumption-export- import- 1980-2013
IseOlorunkanmi O. J. (2014) ‘Issues and challenges in the Privatized Power Sector in Nigeria’. Journal of Sustainable Development Studies ISSN 2201-4268 Volume 6, Number 1, 2014, 161-174
Iwayemi, A. (1983). “Energy in West Africa Issues and Policy Approaches”. Energy policy, 1983, vol. 11, issue 3, 235-249
Iwayemi, A. (1993). “Energy development and sub-Saharan African economies in a global perspective”. OPEC Energy Review, 1993, Volume 17, Issue 1 March 1993 Pages 29–45.
Iwayemi, A. (1998). “Energy sector development in Africa” Background paper for the 1998 African Development Bank report.
Iwayemi, A. (2008). “Nigeria’s Dual Energy Problems: Policy Issues and Challenges”; IAEE Energy Forum, 4th Quarter, 2008
Kaitafi, A. I. (2011). ”Imperatives of Tariff/Tariff Setting and Subsidy in Nigerian Electricity Industry (NESI)”, Authoritative Journal of Power Holding Corporation of Nigeria, 15(4) 6 -14 Left review. 74(4)16-32.
Kateregga, E. (2009) ‘The Welfare Costs of Electricity Outages: A Contingent Valuation Analysis of Households in the Suburbs of Kampala, Jinja and Entebbe’. Journal of Development and Agricultural Economics, 1, pp. 1-11.
Kraft, J and Kraft A. (1978). “On the Relationship between Energy and GDP”. Journal of Energy and Development 3, 401-403
Lancaster, K. (1966) ‘A new approach to consumer theory’. Journal of Political Economy 74, 132– 157.
Lareau, T. and Rae, D. (1987) ‘Valuing willingness to pay for diesel reduction odours’. Southern Economics Journal, pp. 728-7742.
Lean, H. H. and M. Shahbaz (2012). “The dynamics of electricity consumption and economic growth: A revisit study of their causality in Pakistan”, Energy. 39, 146- 153.
Maddala, G. S. (1983) ‘Limited-Dependent and Qualitative Variables in Econometrics’. New York: Cambridge University Press.
McFadden, D. (1974) ‘Conditional logit analysis of qualitative choice behavior’. In: Zarembka, P. (Ed.), Frontiers of Econometrics. Academic Press.
McNair, B. J. Bennett, J. Hensher, D. A. and Rose, J. M. (2011) ‘Households’ willingness to pay for overhead-to-underground conversion of electricity distribution networks’. Energy Policy, vol. 39 pp. 2560-2567. http://dx.doi.org/10.1016/j.enpol.2011.02.023
NBS Q2 (2017). ‘Quarter 2, 2017’, National Bureau of Statistics Annual Bulletin 2017.
Niger Delta Power Holding Company (NDPHC) 2013 report
Nigerian Bulk Electricity Trader (NBET)
Nigerian Electricity Management Services Agency (NEMSA) Act, 2015. http://www.nemsa.gov.ng
Nigerian Electricity Regulatory Commission (2012), ”Multi-Year Tariff Order (MYTO) II (2012 – 2017), Abuja, Nigerian Electricity Regulatory Commission” Authoritative Journal of Power Holding Corporation of Nigeria
Nigerian Electricity Regulatory Commission (2012). Multi Year Tariff Order Financial Model, Abuja.
Nigerian Electricity Regulatory Commission Orders and Reports (2008, 2010, 2013 and 2014) www.nercng.org
Odiaka, P. (2006) ‘Power sector reforms, still a reign of blackout’. Journal of Social Sciences, Vol.4. University of Uyo, Nigeria.
Okafor O. (2012), “Testing the Relationship between Energy Consumption and Economic Growth: Evidence from Nigeria and South Africa”. Journal of Economics and Sustainable Development, ISSN 2222-1700 (Paper) ISSN 2222-2855 (Online) Vol.3, No.11, 2012.
Oseni, M. (2017) ‘Self-Generation and Households’ Willingness to Pay for Reliable Electricity Service in Nigeria’. The Energy Journal, Vol. 38, No. 4. Pp. 165-194.
Oyeneye O. (2014). ‘Socio-economic Influences on Policies of Power Deregulation’, Proc. 20th National Conference of the Nigerian Society of Engineers (Electrical Division), October 6-7, 2004, pp. 1-15.
Pearce, D. W. and Turner, R. K. (1990) ‘Economics of Natural Resources and the Environment’. Harvester: Hemel Hempsted.
Pepermans, G. (2011) ‘The value of continuous power supply for Flemish households’. Energy Policy, vol. 39 pp. 7853-7864.
Perman, R. Ma, Y. McGilvary, J. and Common, M. (2003) ‘Natural Resources and Environmental Economics’. Third Edition, London: Pearson Addison Wesley.
Roadmap for Power Sector Reform (RPSR) 2010.
Roadmap for Power Sector Reform Revision 1 (2013)
Sambo, A.S. (2008), “Matching Electricity Supply with Demand in Nigeria”. IAEE, 4th quarter, pages 32-36.
Serra, P. and Fierro, G. (1997) ‘Outage costs in Chilean industry’. Energy Economics, vol. 19 pp. 417-434.
Solver, T. (2005). ‘Comparison of Incentives for Distribution System Reliability in Performance-Based Regulation’. Thesis in Electrical power systems Department of electrical systems Royal Institute of Technology Sweden, 2005.
Transmission Company of Nigeria (TCN) (2007) “Appropriate Electricity Pricing Through Multi- Year Tariff Order”, Nigeria Transmission Company of Nigeria.
Twerefou, D.K. (2014) ‘Willingness to Pay for Improved Electricity Supply in Ghana’. Modern Economy, 5, 489-498. http://dx.doi.org/10.4236/me.2014.55046
USAID Power Africa Factsheet (2017) https://www.usaid.gov/powerafrica/nigeria
Wolde-Rufael Y. (2009). “Energy Consumption and Economic Growth: the Experience of African Countries revisited”. Energy policy 34(10), 1106-1114.
World Bank (2013). ‘World Bank Indicator: Electric Power Consumption (kWh per capita) 2014’.
World Bank (2016). ‘World Bank Indicator: Electric Power Consumption (kWh per capita) 2014’.
Yoo, S. (2005). “Electricity Consumption and Economic growth: Evidence from Korea”. Energy policy 33(12), 1627-1632.