assessment of access to electricity and the socio-economic impacts in
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Energy Policy 36 (2008) 2016–2029
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Assessment of access to electricity and the socio-economic impacts inrural areas of developing countries
Makoto Kanagawa, Toshihiko Nakata�
Department of Management Science and Technology, Graduate School of Engineering, Tohoku University, Aoba-Yama 6-6-11-815, Sendai 980-8579, Japan
Received 10 April 2007; accepted 30 January 2008
Available online 18 April 2008
Abstract
The purpose of this study is to reveal relations between access to electricity and advancement in a socio-economic condition in rural
areas of developing countries. Recently, multi-dimensional aspects of poverty, for example, economy, education, and health, has been
increasingly focused on, and access to modern energy such as electricity is one possible solution. As a case study, we have analyzed
unelectrified rural areas in Assam state, India. We have developed an energy-economic model in order to analyze the possibility of
electrification through dissemination of electric lighting appliances as well as applied multiple regression analysis to estimate the socio-
economic condition, a literacy rate above 6 years old, in the areas. As a result of the case study, the household electrification rate, the
1000 km2 road density, and sex ratio have been chosen as the explanatory variables of the literacy rate. Moreover, the model analysis
shows that complete household electrification will be achieved by the year 2012. In combination with the multiple regression and model
analysis, the literacy rate in Assam may increase to 74.4% from 63.3%.
r 2008 Elsevier Ltd. All rights reserved.
Keywords: Energy access; Energy poverty; Rural electrification
1. Introduction
Poverty is a major obstacle for sustainable developmentof not only developing countries but also the entire world.It has been the main objective of the bilateral and multi-lateral donors, together with economic growth. Nowadays,poverty is defined as low attainment of social condition, forexample, education, health, and nutrition in addition toeconomic deprivation. One way to cope with this multi-dimensional aspects of poverty is to promote opportunity(World Bank, 2001), and one of the opportunities is accessto modern energy such as electricity. In many literaturesrelated to condition of energy consumption in rural areasof developing countries, the term ‘‘energy access’’ is used torefer to the situation where people can secure the modernenergy, which is commonly consumed in developedcountries, at affordable prices (Bhattacharyya, 2006, inpress; Spalding-Fecher et al., 2005). The definition of theterm ‘‘energy poverty’’ is, then, the situation in which
e front matter r 2008 Elsevier Ltd. All rights reserved.
pol.2008.01.041
ing author. Tel./fax: +81 22 795 7004.
ess: [email protected] (T. Nakata).
energy access is not established yet (Pachauri et al., 2004;Sagar, 2005).Works dealing with developmental issues from the
field of energy can be mainly divided into three cate-gories, and their characteristics and references are thefollowing:
�
Descriptive study (Aggarwal and Chandel, 2004; Basta-koti, 2003; Dung et al., 2003; Gangopadhyay et al.,2005; Rehman et al., 2005)—It describes currentsituations of energy demand or consumption as well aspolicy and program in developing countries. It alsoinvestigates critical components of the policy andprograms, and evaluates the outcomes. Although itincludes various aspects of the policy and programssuch as legal, social, and fiscal, most of the study isqualitative evaluation, which is highly case-oriented,and it is difficult to obtain ideas applicable to otherareas. � Experimental study (Bhattacharya et al., 2002; Chakra-barti and Chakrabarti, 2002; Masera et al., 2000;Wijayatunga and Attalage, 2002)—It tests technological
ARTICLE IN PRESSM. Kanagawa, T. Nakata / Energy Policy 36 (2008) 2016–2029 2017
or economic efficiency of devices or appliances in orderto compare technologies adopted by rural households. Itmeasures not only the data of energy demand,consumption, and expenditure but also emissions ofhazardous pollutants, which cause indoor pollution.Although it contains highly disaggregated or highlyprecise data, policy implication to promote thesetechnologies is not sufficiently discussed based on theresults.
� Analytical study (Bailis et al., 2005; Biswas et al., 2001;Howells et al., 2005; Mathur et al., 2003; Pachauri et al.,2004; Parikh and Ramanathan, 1999)—It analyzesenergy demand or consumption structure of a develop-ing country, and applies an analytical tool to energydemand and supply structure at village, regional, andnational level, taking into account economic andtechnological parameters. It contains model analysis,which is divided into top-down and bottom-up modelingapproaches. Moreover, it can incorporate emissionsassociated with energy consumption such as greenhousegas emissions and government policies, for example,environmental tax.
There are a large number of literatures for the descriptiveand experimental studies. In contrast, there are a limitednumber of researches categorized as the analytical study.In particular, few researches estimate socio-economiceffects of results of analyses. Given that nowadays povertyis regarded as a lack of socio-economic welfare, it isunavoidable to consider socio-economic impacts of transi-tion or improvement of energy sources consumed indeveloping countries. With respect to this point, the modelanalysis with a bottom-up modeling approach, in combi-nation with the estimation of socio-economic aspects, has a
Income- Enterprise development throughelectrification creates job.- Mechanization in industry achieves higherproductivity.- Small-scale energy system in rural areasgenerates local industry.
Health- Using modern energy reduces exposure tohazardous pollutants.- Avoiding drudgery such as collecting fuelwoodimproves health condition of, in particular,women and children.- Access to electricity enables vaccination andmedicine storage by a refrigerator.
Energy
Fig. 1. Links between energy and
potential to reveal the links between energy accessimprovement and poverty eradication as shown in theprevious work of the authors (Kanagawa and Nakata,2007). Therefore, we have developed an energy-economicmodel with bottom-up modeling approach and applied itto rural areas of developing countries in order to clarify thepossibility of energy access improvement. Furthermore,socio-economic impacts are incorporated into the analysis.
2. Energy and poverty
2.1. Energy and Human Development Index (HDI)
Energy influences socio-economic condition of develop-ing countries as shown in Fig. 1. In particular, access tomodern energy like electricity will drastically improve thequality of life of those who do not have yet. There has alsobeen increasing attention on poverty reduction throughenergy access improvement among international organiza-tions in the energy field. For example, recently theInternational Energy Agency (IEA) has been focusing onthe topic through the improvement of energy demand andsupply situations in developing countries, devoting achapter to explain the roles of energy for the developmentin its World Energy Outlook 2002 (IEA, 2002). It mentionsthat some 2.4 billion people depend on traditional biomasssuch as wood, agricultural residues, and dung for theircooking and heating demand and that there is one fourthof the world’s population, about 1.6 billion people, whodoes not have access to electricity. Furthermore, most ofthem are in rural areas. It is estimated that 2.6 billionpeople will not improve their energy situation for cookingand heating and 1.4 billion people will not have electricityaccess by 2030. The lack of energy access also causes
Environment- Reduction in use of fuelwood pretendsdeforestation.- Use of efficient electric appliances saves energyconsumption.- Application of renewable energy promotesclimate protection.
Education- Lighting appliances enables to study at night.- Utilization of modern energy results in freeingup from drudgery and creating time for study.- Electricity helps narrow the digital dividethrough Information CommunicationTechnologies (ICTs).
other components of poverty.
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1
10
Electricity consumption per capita [kWh]
GD
P pe
r ca
pita
[U
S$]
Log(y) = 0.6452 Log(x) + 1.7655
R2 = 0.8081
1 10 102 103 104 105
103
102
104
105
Fig. 2. Relation between electricity consumption per capita and GDP per
capita in 2002 (based on IEA, 2005; UNDP, 2004).
y = 0.2139Log(x) + 0.0688R2 = 0.8288
1 10 102 103 104 1050
0.2
0.4
0.6
0.8
1
Electricity consumption per capita [kWh]H
DI
[-]
Fig. 3. Relation between electricity consumption per capita and HDI in
2002 (based on IEA, 2005; UNDP, 2004).
M. Kanagawa, T. Nakata / Energy Policy 36 (2008) 2016–20292018
serious adverse effects on the socio-economic condition ofrural population. Therefore, achieving energy accessimprovement has huge impacts on people’s lives in ruralareas of the developing countries.
Nowadays, development strategy has been increasinglyfocusing on microlevel, or software of the developmentalissues, in other words, human development. Access tomodern energy enables people to not only have economicopportunities for income generation but also save theirtime from time-consuming drudgery and allocate to moreenjoyable or educational activities. Considering electricityas a representative of modern energy, electricity consump-tion has significant correlation with GDP as well as HDIfor 120 countries, and the countries which mark highconsumption level of per capita electricity, attain upperrank of both economic activities (GDP per capita) andHDI as shown Figs. 2 and 3, respectively.
2.2. Energy and the Millennium Development Goals
(MDGs)
The MDGs are the numerical target that should be metby the year 2015 and were adopted at the UN GeneralAssembly in 2000. The MDGs consist of eight goals asshown below (UN, 2006): Eradicate extreme poverty andhunger; achieve universal primary education; promotegender equality and empower women; reduce childmortality; improve maternal health; combat HIV/AIDS,malaria and other diseases; ensure environmental sustain-ability; and develop a global partnership for development.
The Department for International Development (DFID)of the United Kingdom mentions links between energy
and the MDGs, classifying into direct and indirectcontributions (DfID, 2002). For one of the MDGs,gender equality and women’s empowerment, energy accessimprovement directly contributes to freeing up women andgirls from time-consuming housework such as laundry,cleaning, etc. by utilization of electricity. In addition,through reduction of time-consuming chores and attain-ment of energy services, it has indirect contributions forwomen to have opportunity to attend schools or educa-tional activities as well as take into a part in the labormarket or establish small enterprises. As a result, genderequality and empowerment of women are promoted. Of thevarious socio-economic conditions, education is one of themost indispensable components to be considered in orderfor developing countries to achieve poverty alleviation.
2.3. Energy and education
Education is also widely recognized as one of the mostessential components for poverty reduction according tocurrent discourses of developmental studies, which con-clude that inequality of income affects opportunities ofeducation. Moreover, primary education generally showsthe highest return to investment. Poor households attainless enrollment and completion of schools because directand indirect educational expenditures are considerableburdens. This results in a perceptibly lower literacy rate ofthese households than that of middle or high incomehouseholds. Such low-level attainment of education causesa lack of employment opportunity for poor households,and, even though there is the opportunity, these poorhouseholds cannot earn sufficiently for their basic needs.
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duca
tion
inde
x [-
]
y = 0.1896Log(x) + 0.2173R2 = 0.6625
1 10 102 103 104 1050
0.2
0.4
0.6
0.8
1
Electricity consumption per capita [kWh]
Fig. 4. Relation between electricity consumption per capita and the
education index in 2002 (based on IEA, 2005; UNDP, 2004).
M. Kanagawa, T. Nakata / Energy Policy 36 (2008) 2016–2029 2019
Along with the effects on economic condition, througheducational achievement poor people are able to attainconfidence, sociality, concern for society, participation forsocial activity, resistance for oppression, and involvementin the political processes. Furthermore, education has notonly direct effects on those who are educated but alsoexternal and indirect effects on their household/family,community, and society toward poverty reduction (Okada,2004).
Energy access improvement, in particular access toelectricity, has huge impacts on education. For example,it reduces such drudgery and allows children to expandtheir opportunity for school attendance and other educa-tional activities. Also, due to electrification, rural house-holds obtain sufficient luminescence for study in ahousehold at night and are able to utilize TV, radio, andInformation and Communication Technologies for educa-tional purposes. Thus, access to electricity and othermodern energy creates child-friendly educational environ-ment, and, in fact, electricity consumption per capita isrelated to the education index, a component of HDI, asshown in Fig. 4 (IEA, 2005; UNDP, 2004).
3. Method of the analysis
3.1. Definition of energy access improvement
In the study, energy access improvement is defined as‘‘electrification in analyzed areas through dissemination ofelectric lighting appliances such as incandescent bulbs,fluorescent tubes, and Compact Fluorescent Lamps (CFL)instead of using kerosene lamps.’’
3.2. Procedure of the analysis
The procedure of the analysis of lighting demand is thefollowing:
1.
Select a socio-economics factor related to energyconsumption for lighting by multiple regression analy-sis; a literacy rate above 6 years old.2.
Design an energy-economic model of analyzed areasin order to reveal the possibility of energy accessimprovement, that is, dissemination of electric lightingappliances.3.
Estimate the impacts of the energy access improvementon the literacy rate in the areas.3.3. Analyzed areas
As a case study, we have chosen rural areas of Assam,India and referred to the data of Sarmah et al. in 2002, suchas population, size of households, and so on for the modelanalysis explained in Section 3.5. There are 1.24 billionpeople in India, and about 75% of the total population isin rural areas. According to prospects of the UN agency, inspite of rapid urbanization, 818 million people of the totalpopulation still live in the rural areas (Population Divisionof the Department of Economic and Social Affairs of theUnited Nations Secretariat, 2006). With respect to theeconomy, India is one of the most successful developingcountries, and, in fact, its GDP has rapidly risen at anannual growth rate of 4.6% from the year 2001 to 2002.Energy use and electric power consumption in the countryas a whole have also increased steadily to 22,540.4 (PJ) and576.5 billion (kWh) in 2001 at annual growth rates of 3.6%and 6.5% from 1990 to 2001, respectively. However,population living on less than $1 a day and $2 a day are34.7% and 79.9%, respectively, and thus there is seriousinequality in the country (World Bank, 2004). From theviewpoint of energy, is is estimated that there are 585million people who depend on traditional biomass and thepopulation will increase to 632 million in 2030 (IEA, 2002).For the electricity sector, the Government of India has
launched several projects. For power sector development,the Ministry of Power of the Government of India has set‘‘Mission 2012: Power for All,’’ which includes completehousehold electrification as well as power supply to achievecontinuous economic development of the country (Minis-try of Power of the Government of India, 2002).Furthermore, the Rural Electrification Supply TechnologyMission was also adopted in 2002, and its purpose is tocomplete electrification of all villages and households bythe year 2012 with renewable energy sources, decentralizedtechnologies, and grid expansion.Fig. 5 shows the relation between electricity consump-
tion per capita and Gross Domestic State Products(GDSP) per capita for 25 states and Union Territories(UTs) in India. The more electricity is consumed in a state,
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1
10
1 10 102
Electricity consumption per capita [kWh]
GD
SP p
er c
apita
[U
S$]
Log(y) = 0.3633 Log(x) + 1.5453R2 = 0.4036
103
103
102
Assam
Fig. 5. Relation between electricity consumption per capita and GDSP
per capita in India in 2001 (based on Central Electricity Authority, 2005;
Ministry of Statistics and Programme Implementation, 2006).
0
20
40
60
80
100
1 10 102
Domestic electricity consumption per capita [kWh]
Lite
racy
rat
e ab
ove
6 ye
ars
old
[%]
y = 0.0246Log(x) + 0.2685R2 = 0.4328
103
Assam
Fig. 6. Relation between domestic electricity consumption per capita and
a literacy rate above 6 years old in India in 2001 (based on Central
Electricity Authority, 2005; Office of the Registrar General, 2006).
y = 0.2764x + 0.511R2 = 0.3881
0%
20%
40%
60%
80%
100%
0% 20% 40% 60% 80% 100%
Electrification rate [%]
Lite
racy
rat
e ab
ove
6 ye
ars
old
[%]
Assam
Fig. 7. Relation between a household electrification rate and a literacy
rate above 6 years old in India in 2001 (based on Banthia, 2003; Office of
the Registrar General, 2006).
Table 1
Description of the analyzed areas
Population [�] 5958
Male (54%)
Female (46%)
Population growth 1.4%
Energy consumption (GJ) 67,267
Cooking and water heating (fuelwood) (85%)
Space heating in winter (fuelwood) (14%)
Space lighting (kerosene) (1%)
Source: CIA (2005), Sarmah et al. (2002).
M. Kanagawa, T. Nakata / Energy Policy 36 (2008) 2016–20292020
the higher per capita economic production, which can be aproxy to the level of a household’s prosperity, is achieved.Also, domestic electricity consumption per capita hascorrelation with educational attainment, the literacy rateabove 6 years old as shown in Fig. 6. Moreover, sincedomestic electricity consumption per capita is in logarithmin the figure, those households which consume less electricitybenefit more due to an additional consumption of electricity.Thus, as shown in Fig. 7, it is rational to consider thatelectrification for households without electricity access hashuge impacts on the literacy rate in a state.
For the analysis, we have targeted villages of the Jorhatdistrict of Assam in India, where fuelwood consists ofapproximately 85% of total energy consumption andaccess to electricity is not established (Sarmah et al.,2002). Table 1 summarizes the size and energy consump-tion patterns of the areas. Although the analyzed areas arestrictly specified, the framework of the analysis includingconcepts of estimation of the educational attainment isapplicable to other rural areas in developing countries.
3.4. Literacy rate
Educational attainment such as a literacy rate andenrollment in schools is one of the most fundamentalelements of economic and social development. Highilliterate rates have been the major obstacle of furtherprogress in developing countries, preventing poor popula-tion from income-generating activities and attainingempowerment. It is presumed that advancement in the
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Table 2
Possible factors influencing on the literacy rate
Factor Year
Economic
GDSPa per capita in logarithm 2000–01
Expenditure on education etc. per capita in logarithm 2001–02
Educational
Number of teachers in primary schools per 1000 persons 2002–03
Number of primary schools per 1000 persons 2002–03
Geographical
Railway density per 1000 km2 2000–01
Road density per 1000 km2 1998–99
Social/cultural
Household size 2001
Sex ratiob 2001
Ratio of Scheduled Caste 2001
Ratio of Scheduled Tribe 2001
Ratio of Hindus 2001
Ratio of Christian 2001
Electricity
Electricity consumption per capita in logarithm 2000–01
Domestic electricity consumption per capita in logarithm 2000–01
Household electrification rate 2001
Source: Banthia (2003), CMIE (2004), Ministry of Human Resource
Development of the Government of India (2005), Ministry of Statistics
and Programme Implementation (2006), Office of the Registrar General
(2006), RBI (2002).aGDSP: gross domestic state products.bSex ratio ¼ number of female/number of male.
M. Kanagawa, T. Nakata / Energy Policy 36 (2008) 2016–2029 2021
literacy rate is affected by five aspects: economic, educa-tional, geographical, and social/cultural aspects as well asan aspect of electricity.
In order to specify factors quantitatively, which influencethe literacy rate, multiple regression analysis has beenapplied. First, based on literature surveys, possible factorsof 19 states and UTs in India have been listed up as shownin Table 2. Second, applying a stepwise method, we haveselected explanatory variables, which explain a literacy rateabove 6 years old in India with statistical significance at 0.5in p-value. Utilizing this method, we have been able todetermine a regression equation, which explains therelation between explained and explanatory variablesamong possible factors.
The possible factors considered in the regression analysisare justified by the following explanation: GDSP percapita, Expenditure on education, etc. per capita, Numberof primary schools per 1000 persons, Number of teachersin primary schools per 1000 persons, Road density per1000 km2, Rail density per 1000 km2, Household size, Sexratio, Ratio of Scheduled Caste, Ratio of Scheduled Tribe,Ratio of Hindus, Ratio of Christian, Electricity consump-tion per capita, Domestic electricity consumption percapita and Household electrification rate. These factorsare explained in more detailed in the Appendix of thisstudy.
3.5. Energy-economic model
3.5.1. Method of the analysis
For the analysis, we have developed an energy-economicmodel of rural areas in India, the energy access model, basedon both economic and technological parameters of energyconversion processes, and adopted a nonlinear optimizationtool. The energy access model is shown in Fig. 8. The modelconsists of 40 nodes: 5 end-use nodes (cooking demand,lighting demand, etc.), 28 technological conversion nodes(traditional wood stove, improved wood stove, gas stove,etc.) including seven market nodes (heat market for cooking,electricity market, etc.), and seven resource nodes (fuelwood,LPG, etc.). We have applied the META �Net economicmodeling system being developed at Tohoku University andthe Lawrence Livermore National Laboratory, as an analysistool (Lamont, 1994). META �Net is a partial equilibriummodeling system that allows for explicit price competitionbetween technologies (in this study, lighting devices andgenerating technologies) at the market nodes, in a network ofmainly four types of node explained above. It finds the multi-period equilibrium prices and quantities of the network andthe solution includes the prices and quantities of eachresource, technology and device along with the capacityadditions for each conversion process (in this study, selectionof a lighting device, for example). This analysis tool has beenalready used to analyze energy systems of national andregional levels, and is also compatible with a local levelwithout any particular modification. Further explanation ofthe details is available in the previous studies (Kanagawa andNakata, 2006; Nakata, 2004). The periods of the analysis arefrom the year 2004 to 2012.In this type of analyses, there are several key assump-
tions for simplification. It is assumed that total energydemand in the areas increases linearly during the analysisperiods according to population growth of the areasreferred to the annual growth rate of India, 1.4% (CIA,2005). There is another assumption that other demographicconditions, for example, average number of people in ahousehold and outflow of the population to urban cities,are constant. Cost parameters for lighting devices,generating technologies and resources are provided inTables 3–5, respectively. As for the generating technology,only community based electrification and grid electricityhave been considered, in terms of sustainable utilization ofelectricity, although Solar Home System is one of theuseful options for electrification in rural areas. It isassumed that the costs of the devices, technologies andprice escalations of the resources are constant during theperiod of the analysis. For kerosene and LPG, currentlythe Government of India subsidizes the prices and willreduce the subsidy, and there is the assumption that theirprices will be at the international level. According to theinitial size and growth rate of the market, we have hadassumption about market of electric lighting appliances,that is, an incandescent bulb, fluorescent tube, and CFL(Kumar et al., 2003; Ramaswamy, 2004).
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Dsl.Rsc
SH.Dmd
Accum.Elect
Mkt.Elect
Solar.Rsc
PV.Elect
Wind.Elect
Dsl.Elect
Trad.Wood.Stv
Imprv.Wood.
Stv
Wind.Rsc
Grid.Rsc
CFLFlr.Tub
Wood.Rsc
Wood.Mkt
Inc.Blb
Gas.Stv
LPG.Rsc
TV.Dmd
Light.Mkt
Light.Dmd
Cook.Dmd
Cook.Mkt
Gas.Mkt
Electricity
Lighting TV&RadioCooking
PV.Btr
Wind.Btr
Wind.Ivr
PV.Ivr
Gas.Ht
Trad.Wood
.Ht
SH.Mkt
Space heating
Radio.Dmd
Abbreviation:SH: Space heating Cook: Cooking Light: Lighting Dmd: Demand Mkt: Market Trad: TraditionalImprv: Improved Stv: Stove Lmp: Lamp Inc: Incandescent Blb: Bulb Flr: FluorescentTub: Tube CFL: Compact Fluorescent Lamp Ivr: Inverter Btr: Battery Elect: ElectricityKrs: Kerosene Dsl: Diesel Clct: Collection Cnct: Connection Rsc: Resource
Krs.Lmp
TV Radio
Grid.Cnct
Krs.Rsc
Wood.Clct
Imprv.Wood.
Ht
Fig. 8. Energy access model.
Table 3
Costs of lighting devices
Equipment
costa (US$)
Unit
costa
(US$)
Life (h) Energy
consumption
per unit-hour
(kWh)
Kerosene lamp 0.602 0 5b 0.400
Incandescent
bulb
0.736 0.241 1000 0.060
Fluorescent
tube
6.024 1.205 10,000 0.040
CFLc 0.736 4.819 10,000 0.011
Source: Jana and Chattopadhyay (2004), Kumar et al. (2003).aUS$1 ¼ 41.5Rs. (World Bank, 2004).bLife for kerosene lamp is in years.cCFL: compact fluorescent lamp.
M. Kanagawa, T. Nakata / Energy Policy 36 (2008) 2016–20292022
3.5.2. META �Net Economic Modeling System
The META �Net Economic Modeling System has beendeveloped jointly by Nakata laboratory at TohokuUniversity and Lawrence Livermore National Laboratory,USA. In this sub-section, the analysis tool used in thisstudy is explained according to the user’s guide (Lamont,
1994). It is categorized as a bottom-up model, which dealswith disaggregate process of energy production andconversion process by network of nodes. In addition, it isa partial equilibrium model, based on technological andeconomic characteristics of technologies, for example,electric power generation in an electricity sector or heatingand electric equipments in an industry sector. Themodeling approach is characterized as the networkmodeling approach. It represents the economy as anetwork of nodes, and each node models actual actors inthe economy, for example, end-users, conversion technol-ogies, and resources. Among these entities, signals of priceand quantity are sent and received.Furthermore, it is mentioned that the META �Net can
take into account constraints on prices and quantities aswell as various taxes and constraints on environmentalemissions affected by government policies.
4. Results of the analysis
4.1. Multiple regression analysis
As a result of the multiple regression analysis, thefollowing three explanatory variables are selected to
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Table 4
Cost of power-generating technologies
Capital costa (US$/kW) Fixed O&Mb (US$/kW) Variable O&M (mills/kWh) Life (year) Efficiency (–)
Diesel generator 289 7.229 6.024 10 0.278
PV 7229 180.72 0 25 1
Wind 1479 36.97 0 20 1
Grid electricityc 919 29.87 1.246 30 0.234
Batteryd 1318 0 0 3 1.250
Inverterd 591 0 0 6 1.111
Source: Banerjee (2006), Central Electricity Authority (2005), Chakrabarti and Chakrabarti (2002), Gullberg et al. (2005), TERI et al. (1999), Tongia and
Banerjee (1998).aUS$1 ¼ 41.5Rs. (World Bank, 2004).bFixed O&M is 2.5% of capital cost except grid electricity.cGas steam power plant.dBattery and inverter are considered for PV and wind.
Table 5
Price and price escalation of resources
Price (US$/kWh) Price escalation
Kerosene 0.022 0.079
LPG 0.031 0.087
Diesel 0.030 0.039
Natural gas 0.011 0.112
*US$1 ¼ 41.5Rs. (World Bank, 2004).
Source: Banerjee (2006), Chakrabarti and Chakrabarti (2002), IEA (2005),
UNDP/ESMAP (2003), US DOE, EIA (2002).
Table 6
Result of the multiple regression analysis
Literacy rate above 6 years old
Partial regression
coefficient
Standardized partial regression
coefficient
Constant �0.489 (0.040)a
Electrification
rate
0.166 (0.004)b 0.421
Sex ratio 0.683 (0.003)b 0.425
Log (road
density)
0.142 (o0.001)b 0.684
Adjusted R2 0.743
Observation 19
Note: Value in the parenthesis is p-value.a5% significant.b1% significant.
M. Kanagawa, T. Nakata / Energy Policy 36 (2008) 2016–2029 2023
estimate a literacy rate above 6 years old in India:household electrification rate, road density per 1000 km2
in logarithm, and sex ratio. This result is shown in Table 6.From 19 observations including 18 states and one UT,
the regression equation attains the adjusted coefficient ofdetermination of 0.743. All of the explanatory variablesaffect the literacy rate positively, and it is compatible withtheir simple correlation coefficients. All variables, theelectrification rate, road density in logarithm, and sexratio, indicate 1% level of statistical significance. Of thethree variables, the household electrification rate is thethird significant variable, according to standardized partialregression coefficient; the road density is the first and thesex ratio the second. The partial regression coefficient ofthe electrification rate means that a percentage pointincrease in households electrified might increase the literacyrate by 0.17 percentage point. Combined with the result ofthe model analysis described in the next sub-section, thecoefficient is used to estimate the literacy rate achieved byenergy access improvement.
4.2. Model analysis
Fig. 9 shows changes in lighting demand supplied bylighting devices from the year 2004 to 2012. As the result ofthe model analysis, it is revealed that complete householdelectrification, which the Government of India has beentargeting, will be achieved by 2012. Thus, the electriclighting appliances are widely adopted by the rural
households in the analyzed areas. On the contrary, akerosene lamp is replaced although it shows relativelylower cost for initial installation. It is explained that,although the cost and lifetime are competitive to electriclighting appliances, the total lifetime cost of a kerosenelamp for an hour of use is much higher than that of theelectric appliances, partly due to its low efficiency. Inaddition, as the Government of India has decided to phaseout subsidies on fossil fuels, the cost of kerosene isanticipated to increase.Of the three electric lighting appliances, a fluorescent
tube acquires the largest share in the analyzed areas in2012, reaching to more than 70% of the number of thehouseholds. Although the equipment for fitting the tube ina house is high, the long life and high efficiency result in thewide dissemination. On the other hand, the incandescentbulb obtain approximately 25% of the share because of thelow unit cost, and CFL is hardly used by the ruralhouseholds due to the high unit cost even though it lasts for10,000 on average and is highly efficient in terms of energyconsumption.As for the supply side, the result of the analysis is shown
in Fig. 10. Of all technologies, the diesel generator will
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0.E+00
1.E+05
2.E+05
3.E+05
4.E+05
2004 2006 2008 2010 2012
Year
Lig
htin
g en
ergy
con
sum
ptio
n by
dev
ices
[uni
t-hr
]
CFLFluorescent tubeIncandescent bulb
Kerosene lamp
Fig. 9. Changes in energy demand supplied by lighting devices.
PV0%
Grid30%
Wind0%
Yr.2012
Diesel engine70%
Fig. 10. Electricity supply structure by generating technologies in 2012.
M. Kanagawa, T. Nakata / Energy Policy 36 (2008) 2016–20292024
share the highest percentage of the electricity supply in thearea. It is because the diesel generator is the cheapestoption though the price of diesel will increase considerablyduring the analysis period and, as a decentralized energysupply technology, it needs neither battery nor inverter onthe contrary of PV system and wind turbines. PV and windturbines are recognized as possible electrification options inrural areas and, in the case of wind, its capital cost has beenmore competitive recently. However, as it needs ancillarysuch as a battery and inverter, PV and wind turbine systemas a whole becomes uncompetitive to other generatingtechnologies.
4.3. Estimation of literacy rate increase
Stated as a whole, there are only 24.9% of householdselectrified in Assam and also 83.5% of rural householdswho do not have electric lighting appliance according to
the Census of India, 2001 (Banthia, 2003). Combining theresult of the model analysis with that of the multipleregression analysis in Section 4.1, we have also estimatedthe potential of increase in literacy rate above 6 years old inthe state of Assam. Assuming that the same results mightbe achieved in the rest of unelectrified rural areas of Assam,96.3% of households in the entire state attain electricityaccess through the dissemination of the electric lightingappliances. When the value of the partial regressioncoefficient of the household electrification rate is appliedto the consequent electrification rate, it is expected that theliteracy rate above 6 years old in Assam will reach to74.4% from 63.3%, increase by 11.9% compared to theliteracy rate before energy access improvement, accordingto the following equation.
Literacy rate above 6 years old ¼
� 0:489þ 0:166�Household electrification rate
þ 0:143� Log ðRoad densityÞ þ 0:683� Sex ration:
¼ �0:489þ 0:166� 0:963þ 0:143� 3:039þ 0:683� 0:935
(4.1)
Thus, the impact of electrification on the educationaloutcome is huge even when only the direct link isconsidered. It also has large ripple effects on othercomponents. For example, electrification will stimulatesmall industries in the areas, improve productivity, and,consequently, generate income. Therefore, energy accessimprovement will alleviate poverty in combination with theincrease in the educational level and ripple effects.
5. Discussion
The model analysis we have conducted is based onreliable electricity supply and secured availability oflighting devices on the supply side as well as decisionmaking by the rural household, which takes present valueof the devices into account, on the demand side. However,in reality, lack of infrastructure and capacity of supplyprevents rural areas from achieving energy access improve-ment. Moreover, electric lighting appliances are notadopted because of their higher initial investment in spiteof lower life-time cost than a kerosene lamp.In this section, first, we discuss issues for the supply side,
infrastructure and capacity of supply. Then, for thedemand side, international assistance such as OfficialDevelopment Assistance (ODA) and government policiesare illustrated for activating private investment. Finally,ripple effects on other socio-economic aspects are argued inorder to provide implication to the results of the analysis.
5.1. Supply side—infrastructure and capacity of supply
The result of the model analysis shows that householdsin the rural areas of India will select the electric lightingappliances. Infrastructures such as road, transmission line,and distribution line, are one of the fundamental components
ARTICLE IN PRESS
Table 7
Cumulative and annual investment needed to provide access to modern
energy services to 1 billion people
Low (US$
billion)
High (US$
billion)
Cumulative investment
(2002–2015)
Electricity supply 128 208
Grid connections 50 150
LPG 19 37
Total 197 395
Annual investment (2002–2015) 14 28
Source: Spalding-Fecher et al. (2005).
M. Kanagawa, T. Nakata / Energy Policy 36 (2008) 2016–2029 2025
to ensure accessibility to market for not only electricappliances but also distributed generators or grid electri-city, which are necessary to acquire reliable electricity.
In terms of road infrastructures, Assam is a relativelyadvanced state compared to the other states, reaching to1000 km2 road density of 1093.58 km, one tenth of 25Indian states. In particular, there are 90.92% of villages,which have the connection to so-called pucca roads inJorhat district, to which the analyzed areas belong(National Commission on Population of the Governmentof India, 2001). Assam is also ranked at 21st of 29 statesand UT, for transmission and distribution line per area,indicating 1.00 (circuit km/km2), given that the average ofthe states and UTs is 1.88 (Central Electricity Authority,2005).
In addition to the infrastructures, it is also indispensableto discuss the supply side of electricity. For ruralelectrification, the Government of India has launched‘‘Mission 2012: Power for All’’ to achieve completehousehold electrification in the country, focusing onsocially weaker groups (Ministry of Power of the Govern-ment of India, 2002). Moreover, due to the high rate, morethan 30%, of the transmission loss, rural electrification ispromoted with renewables such as solar PV, small hydro,biomass, and wind in disconnected, remote regions sincethe year 2001 (Ministry of Non-Conventional EnergySources of the Government of India, 2004). On the otherhand, the country as a whole, India has been increasing itsinstalled capacity of captive electricity generation from587.85 (MW) in 1950 to 18,740.31 (MW) in 2004. In theprocess of the electricity sector reform, the government hasopened the electricity market for the generation sector toprivate companies in 1991 as well as for the transmissionsector in 1998. Since then, although no entity has enteredinto the transmission sector, participation of privatecompanies into the generation sector has been steadilyexpanding and it gains 10% share of the total generation in2004 (Central Electricity Authority, 2005). Thus, it ispromoted to utilize private investment in the electricitysector, and it is also necessary to attract the investment toelectrify rural areas, considering the government’s limitedfinancial source.
5.2 Demand side—initial investment
As a result of the model analysis, it is revealed thatelectric lighting appliances such as an incandescent bulb,fluorescent tube, and CFL are widely adopted by the ruralhouseholds of Assam, India. This means that, evenincluding costs of electricity-generating technologies andfuels, the cost of the lighting appliances attains cost-effectiveness in the rural areas, where presently thehouseholds are completely dependent on kerosene forlighting and there is no facility or equipment to generateelectricity. In fact, it is reported that the real cost of energy,which poor rural households expend, is higher than that ofelectricity (ESMAP, 2000; IEA, 2003). However, in reality,
large initial investment on the electric lighting appliancesand generating technologies prevents the households fromimproving the energy access.
5.3. Implication to the study
As a result of the analysis, it is revealed that rural areasof developing countries, rural Assam in India in this study,have potential to attain access to electricity. In addition,the results imply how and where government policies orinternational aids can contribute to the promotion ofelectricity access and consequent advancement in socio-economic condition.For the supply side, private sectors must be fully
incorporated into the countries’ development strategies.Financial sources of governments of developing countriesare limited and huge investment, US$ 197–395 billion, isneeded to provide energy access as shown in Table 7,according to the estimation by Spalding-Fecher et al.(2005). Public expenditure of the government is to be spenton constitution of a market performing efficiently andestablishment of institutions. Here, the institution is one ofthe basic concepts to succeed in assistant programs, andfundamental and indispensable structure of society towarddevelopment (Akiyama et al., 2003). Therefore, govern-ment expenditure promotes the private investment, work-ing as a catalyst.ODA has so-called ‘‘catalytic effects’’ to activate
penetration of private entities, which are expected tobecome the main driving force of economic growth ofdeveloping countries. The idea of the catalytic effects isthat ODA should be expended on encouraging the privatesector to invest their funds as well as demonstrate theinitiatives, through establishment of soft infrastructures.Soft infrastructures mean institutional condition, and it isimportant to establish the institutions in order for a marketmechanism to function effectively (Watanabe and Miura,2003).For energy access issues, as a key instrument for
financing the access, a new Global Energy Access Fund isproposed (South Africa, 2002). This new financingmechanism uses public and private financial resources to
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catalyze private-sector investment flows. It includes dis-tribution investment, and related capacity building; grantfunding for feasibility studies and capacity building; seedfunding for innovative delivery models; and microfinancingfor entrepreneurs, particularly for women (Spalding-Fecher et al., 2005). It is also argued that the fund andestablishment of the institutions are primarily supported byredirecting current financial flows through internationaldonors and export credit agencies (ECA). Here, an ECAprovides exporters of capital goods and services withfinance and insurance to assist them in wining overseasorders as well as to insure businesses, which invest abroadagainst the risk of loss on their investment arising frompolitical risks (ECGD, 2006). It plays, in particular, animportant role because each dollar of support from ECAscatalyses another dollar and a half of private-sectorinvestment, and, therefore, only by shifting ECA fundingpriorities can a significant change in private-sector invest-ment patterns be attained.
For the demand side, as for government policies,financial support systems play a critical role to createfavorable situations for rural areas in developing countriesto adopt advanced technologies. It is a well-known myththat the poor cannot pay for energy services even thoughmany of poor households pay more now because ofinefficiency of traditional energy and devices (Energy andMining Sector Board, 2005). However, comparativelyhigher initial costs of advanced technologies prevent ruralhouseholds from participating in a market mechanism.Therefore, for the households, financial support aiming toreduce initial costs of the technologies is needed. Theseinclude subsidies and loans with a considerably low interestrate for rural households. Microcredit is programs extend-ing small loans, and other financial services such as savings,to very poor people for self-employment projects thatgenerate income, allowing them to care for themselves andtheir families (Microcredit Summit Campaign, 2006). Incombination with government policies and microcredit,poor rural households, which hardly obtain financialsources, are able to pay for initial costs of advancedtechnologies. There is an example of an electrification
Access toelectricity
- Infrastructure- Capacity of supply- Governmental policy- International cooperation
Energy accessimprovement
Fig. 11. Summarized fi
project with solar panels in Nepal; approximately one halfof the installation cost is covered by a government subsidyand the rest of the payment is supported by the microcreditscheme, in which households repay with sales of hand-made bags sold via internet (The GEF Small GrantsProgramme, 2006).Finally, in terms of the environmental issue, developing
countries will be major actors in post-Kyoto phase, and,given India’s population, high birth rate without any birthcontrol policy and strong economic growth, India will playan influential role in this challenge face by the internationalsociety. Thus, for India it is sought the compatible strategyfor economic development against environmental dete-rioration. Although in the process of energy accessimprovement, it might be inevitable to consume morefossil fuels, proper policy implementation or internationalassistance, as discussed in this section, will lead the countryto approach energy access issues with environmentallyfriendly manner. In this sense, the results of the studyillustrate the way to improve the quality of life as well asminimizing harmful effects on the environment.As described above, with the supports by governments of
developing countries or international donor communityincluding Japan, rural households are able to selecttechnologies based on cost-effectiveness for a unit ofenergy demanded. Then, as the results of the study haveillustrated, energy access improvement will be achievedthrough self-help efforts by rural households in developingcountries, which is the major objective of Japan’s ODACharter (Ministry of Foreign Affair of Japan, 2004). It willimprove socio-economic condition there and, moreover,developing countries will take the first step toward self-independent and sustainable development.In conclusion, the results of the entire study conducted
are summarized in Fig. 11.
6. Conclusion
In the study, it is aimed to reveal relations quantitativelybetween access to electricity and advancements in socio-economic condition in rural areas of developing countries.
Ripple effect onother factors
Increase ineducational level
- Infrastructure- Gender equality
Advancement insocio-economic factors
gure of the study.
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As reported in previous works, energy access improvementincluding electrification has huge impacts on such factorsas health, education, economy, etc. Rural households indeveloping countries adopt kerosene lamps in order tomeet their lighting demand. They do not obtain sufficientluminance for studying in a house at night, and this is oneof the obstacles to achieve higher educational attainment.Therefore, it is largely expected that energy accessimprovement for lighting demand through electrification,which is achieved by the dissemination of electric lightingappliances, creates desirable educational environment forchildren.
Energy access improvement influences significantlysocio-economic factors such as health and education asmentioned above. Furthermore, it has substantial rippleeffects on other factors, for example, economy, genderequality, environment, etc., in rural areas of developingcountries. Together with such socio-economic factors as awhole, it might contribute to poverty eradication and leaddeveloping countries toward sustainable development.
Based on the analysis, we can draw the followingconclusions:
�
The multiple regression analysis shows that the literacyrate above 6 years old, a socio-economic factor, isexplained by Household electrification rate, Sex ratio,and road density per 1,000 km2. The household elec-trification rate shows 1% of statistical significance, and1 point of increase in electrification rate will result in0.17 point improvement of the literacy rate. Applyingpanel data to the regression analysis might reveal preciseinsights of relation between the literacy rate and theelectricity consumption. � As for the model analysis, it is revealed that householdelectrification will be completed by the year 2012 due torelatively lower costs of electric lighting appliances interms of a unit of lighting demand. Electrification willboost the demand of electricity for appliances, whichalso affect educational level in the rural areas. There-fore, interactive relation between electrification andconsequent electricity demand, incorporating incremen-tal demand for these appliances and their influence,should be analyzed as the next study.
� Assuming that all rural areas in Assam state, India,would be electrified and other factors would be un-changed, it is estimated that the literacy rate could riseto 74.4% from 63.3%. Electrification also has influenceon other socio-economic factors with large impacts.Therefore, along with the level of educational attain-ment, socio-economic condition in rural areas ofdeveloping countries might be advanced through elec-trification.
In terms of technological and economic aspects, thepossibility of energy access improvement might be high inrural areas of developing countries. A market economy,infrastructures, and capacity of electricity supply are the
essential components. Although, in the analyzed areas,road infrastructures are highly established, there arevarious assumptions for simplification of calculationprocess, for example, stable supply of electricity anddevices and rural households evaluating devices by theirpresent values, in the model analysis. Uncertainties fortechnological parameters and lives of devices and appli-ances are also included. Nevertheless, taking into con-sideration the roles of government policies andinternational assistance, the results of the study offerinsights about links between poverty reduction and energyaccess improvement in rural areas of developing countries.The roles of a government and a market are complemen-tary and a market economy will function due to theutilization of government policies and ODA as well asfinancing mechanism by international donor communityand ECA. These work as a catalyst in order to promoteprivate investment, and, as a consequence, sustainabledevelopment by self-help efforts of developing countriesmight be achieved through establishment of institutions,which are essential for a market economy. As illustrated inthe example of an electrification project utilizing both agovernmental subsidy and a microcredit scheme, initialcosts of advanced technologies are reduced due to acombination of government policies and a market econo-my. As a result, poverty reduction through advancement insocio-economic condition might be achieved by energyaccess improvement.Further research is needed for the following points in
order to conduct more practical analysis: acquisition ofmore field-oriented data, inclusion of other socio-economicimpacts of energy access improvement, interactive influ-ence between socio-economic condition and energy accessimprovement.
Appendix
Possible factors for the regression analysis:
�
GDSP per capita—GDSP per capita is regarded as aproxy of economic affluence of a state. Due to higherGDSP per capita, better economic condition, infra-structures, and educational environment are providedby the state. It is rational to presume that inhabitants ofthe state have more opportunity for education. � Expenditure on education, etc. per capita—This repre-sents educational environment in a state more directlythan GDSP per capita. Higher amount of the expendi-ture on education results in providing people in the stateto have more opportunity for education.
� Number of primary schools per 1000 persons—Thisfactor is regarded as a quantitative aspect of educationalenvironment. The more schools are built, the morecapacity a state can obtain in order for children toattend a school. However, it should be noted that, withlimited educational expenditure, quality of school is notsecured.
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�
Number of teachers in primary schools per 1000persons—This is also considered as a quantitative aspectof educational environment. Hiring more teachersavailable in a state allows expanding capacity ofschooling. We have considered the number of teachersin primary schools per 1,000 persons as a determiningfactor of the literacy rate. � Road density per 1000 km2—It represents the accessi-bility of education in terms of infrastructures. Becauseof a lack of the infrastructures, children in remoteregions or geographically disadvantaged areas cannotattend schools.
� Rail density per 1000 km2—It is a proxy of theaccessibility of education in terms of infrastructuresalong with the road density. Poorer infrastructures in astate hinder children in schooling opportunity.
� Household size—It explains a situation that a householdhaving more children is unlikely to afford the educationunder the constraint of low income. It results in lowachievement of educational level.
� Sex ratio—It represents gender equality of a state. Thehigher the rate is, the more equally male and female aretreated. Thus, it is rational to postulate that opportunityof girls for education is equal to that of boys, whichresults in improvement of the literacy rate.
� Ratio of Scheduled Caste—It is regarded as a possibleexplanatory variable, which shows a social equity in astate. Higher percentage of the Scheduled Caste meanslower educational attainment of the state as they live insocially and economically disadvantaged condition.
� Ratio of Scheduled Tribe—It also indicates a socialequity as in the case of the ratio of scheduled caste. SinceScheduled Tribes are socially and economically under-privileged, it is likely that lower educational level isattained in the state with the higher ratio.
� Ratio of Hindus—It is taken into consideration as afactor of religious condition in a state. Hinduism is themost fundamental principle in the Indian society, and itis the basis of the caste system. High percentage ofHindus may represent the conservative aspect of India.
� Ratio of Christian As well as the ratio of Hindus—Itshows religious condition in a state. It is reported thatmissionaries of Christianity give basic education as apart of the propagandist activities, and it explains thepart of the reason the Northeastern region of Indiaattains higher educational achievement despite lowereconomic condition compared to the other regions(Inoue, 2002).
� Electricity consumption per capita—Utilization ofelectricity results in higher productivity in industry andreduction of time-consuming activities in a household,creating preferable educational environment for womenand children.
� Domestic electricity consumption per capita—It indi-cates the impacts of electricity utilization on educationalenvironment in a household more directly than theelectricity consumption per capita. Electricity enables
children to study at night with sufficient luminescence.
� Household electrification rate—It shows the number ofhouseholds with electricity for their lighting demand in astate. In contrast to the factors of electricity consump-tion, it measures the access to electricity explicitly.
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