erty in Indian Households

. KEMMLER and D. SPRENG *

chnology, Zurich, Switzerland

d poverty is obvious and goes both ways. Recog-oeanharvao

p

The relationship between energy and poverty isapparent and goes both ways. On the one hand,high levsumption patterns at the household levellowlevels ocial fuea highwhich iing stovis nowimportenergypoorsmake an important dierence to their welfare

burg Summit also explicitly acknowledged that

To implement the goal accepted by the internationalcommunity to halve the proportion of people living

as a reection of the general level of humanwell-being.

moretheoretical. We introduce a two-dimensional

trix),ent tobaseduse.

mpor-nsionsre. In

the Government of India, for making available to us the

for providing partial funding for this work. Finally, we

thank two anonymous reviewers for their insightful re-

marks and suggestions. Final revision accepted: 5 Aug-

World DevelopmentVol. 32, No. 12, pp. 20832104, 2004 2004 Elsevier Ltd. All rights reserved

Printed in Great Britain0305-750X/$ - see front matter

lddev.2004.08.005on less than US$1 per day by 2015, access to aord-access to energy services is an essential elementof sustainable development, stating that:

unit level household consumer expenditure survey data.

We would also like to acknowledge the Alliance for

Global Sustainability (http://globalsustainability.org/),and can be a catalyst for human development(World Bank, 2000). The Millennium Develop-ment Goals formulated at the 2002 Johannes-

* The authors would like to acknowledge the National

Sample Survey Organisation, Department of Statistics ofablels, ecient equipment and electricity anddependence on traditional biomass,

s mostly burned in inecient and pollut-es (IEA, 2002). On the other hand, therealso an increasing recognition of the

ance of the provision of clean and reliablefor poverty alleviation. Improving theaccess to modern energy sources can

(the energy accessconsumption mawhich we believe is a good complemthe conventional income/expendituremeasures of poverty commonly inEnergy consumption and access have itant social and environmental dimethat are reected in such a measuf use, a lack of access to cleaner commer- indicator of energy poverty and distributionels of poverty are reected in energy con- The second purpose of the paper isOn Measuring Energy Pov

S. PACHAURI, A. MUELLER, ASwiss Federal Institutes of Te

Summary. The relationship between energy annizing this, this paper provides a short overviewerty. It then presents a novel two-dimensional mthat combines the elements of access to dierent eassessment of the extent of energy poverty and cby applying this measure to Indian household sunicant reduction in the level of energy povertymeasure is a good complement to conventional mplied to other developing countries. 2004 Elsevier Ltd. All rights reserved.

Key words household poverty, energy consum

1. INTRODUCTION

Recent analysis of poverty in India suggeststhat 2030% of its population still live in povertyand that the problem is more acute in rural areasof the country. 1 For many of those who fall inthis category, they have neither the access northe means to meet their basic energy needs.

doi:10.1016/j.worwww.elsevier.com/locate/worlddevenergy services is a prerequisite (CSD9, 2002).

208f dierent approaches to measuring energy pov-sure of energy poverty and energy distributionergy types and quantity of energy consumed. Annges in energy distribution pattern are analyzedey data for 19832000. The analysis shows a sig-nd a rapidly developing subcontinent. The newnetary measures and is general enough to be ap-

tion, energy access, India, Asia

Recognizing that there are important linksbetween energy and poverty, this paper servesthree purposes:

First, to provide a short overview andsummary of dierent approaches to measur-ing energy poverty and how indicatorsrelated to energy access and consumptioncan be used for poverty measurement andust 2004.

3

energy poverty and distribution in India, wepresent a novel way of describing develop-

2084 WORLD DEVELOPMENTment in terms of the net movements over timeof households grouped by the type of energythey have access to and by the quantity con-sumed. We also examine the characteristicsof the energy poor and nonpoor in India interms of their access to other assets and serv-ices, such as education, and study the dynam-ics of changes in the nature and extent ofenergy poverty and energy distribution pat-terns across all households in India during19832000.The analysismakes useof individ-ual household-level data from the householdconsumer expenditure surveys conducted bythe National Sample Survey Organisation(NSSO) of the Government of India.The rest of the paper is organized as follows:

Section 2 discusses some important issues relat-ing to poverty, basic needs and minimum en-ergy needs. Section 3 then goes on to reviewthe dierent approaches applied to measuringenergy poverty in the existing literature. Section4 describes the data sources used for illustratingthe application of our measure of energy pov-erty, based on the access to and consumptionof energy, for the case of India. Section 5 pre-sents some key issues and the methods weadopt for constructing an energy poverty anddistribution measure. The subsequent sectiondescribes the shifting numbers and some ofthe main characteristics of the energy poorand nonpoor that emerge from the applicationof this measure over the period from 1983 to2000 in the context of Indian households. Thelast section concludes with a summary of majorndings and a discussion and reection onsome of the advantages of this measure, its suit-ability for application in the case of other devel-oping countries, and some general lessons thatemerge from this work.

2. POVERTY, BASIC NEEDS ANDMINIMUM ENERGY NEEDS

Traditionally, poverty has been assessed inmonetary terms based on the standard incomeor expenditure based indices. Over the years,addition, given that energy has such a perva-sive role in modern life, its measurement inits various dimensions can reect importantaspects of the reality of the poor in adynamic and accurate way.Third, to assess the evolution and nature ofhowever, poverty has evolved into a multidi-mensional concept in order to overcome someof the deciencies of purely money based indi-cators and to enrich the information set so thata plurality of well-being dimensions are consid-ered. It is now generally agreed that poverty isassociated with deprivation. Deprivation canbe thought of in terms of constraints on peo-ples choices to access certain material goods,assets, capabilities, freedoms and opportunities.The elimination of poverty is associated with

fullling the fundamental or basic needs ofindividuals at some minimum level. The wordneed is, however, controversial 2 In some in-stances it has been used synonymously withwants and desires, as by Maslow who illus-trated his famous hierarchy of needs in theshape of a pyramid (Maslow, 1954). He be-lieved that needs could be divided and priori-tized into ve levels. Individuals do notseek the satisfaction of a need at one level untilthe previous level of need is met. At the lowerlevel, the needs relate to safety, food and shelter,but at the higher levels human needs change tosocial interaction and self-esteem. Sens viewsare to some extent contrary to Maslows. Heuses the concept of capabilities and functi-onings to reect the various things a personmay value as being necessary for achieving agood life and these can range from the simple,such as being adequately nourished or free fromavoidable disease, to the complex such as beingable to take part in the life of a community andhaving self-respect (Sen, 1993).While energy itself is not generally recognized

as being one of the basic needs, 3 it is clearly nec-essary for the delivery and provision of basicssuch as food, clean water, shelter, health andeducational services, etc. (WEC, 1999). Yet,while the centrality of energy for the provisionof basic needs is recognized, there is no consen-sus on the amount of energy needed to meetbasic human needs. The issue is complex asthere is no universally accepted set of minimumbasic needs and because needs vary signicantlybetween countries and regions depending onweather, social customs, and a number of otherregion and society specic factors. 4

(a) Dening energy consumption at thehousehold level and the appropriateness ofuseful energy for poverty measurement

Energy consumption 5 can be measured atvarious levels of the energy supply chain:

Primary energy is the energy embodied in

natural resources (e.g., coal, crude oil, sun-

ENERGY POVERTY IN INDIAN HOUSEHOLDS 2085light, uranium) that have been mined, col-lected or extracted but have not undergoneany anthropogenic conversion or trans-formation.End-use energy is the energy content ofenergy supplied to the consumer at the pointof end-use (e.g., electricity at the electricitymeter).Useful energy is the energy that has beentransformed in the form required for actualuse, e.g., the heat generated from a hot plateor the mechanical energy applied to air forair circulation.But nally, the direct demand by house-holds is on energy services: a cooked meal,a well-lit room, being transported from Ato B, a hot shower, etc.In energy analysis all levels are of impor-

tance, but they have dierent explanatorypower and the choice of the level therefore de-pends on the purpose of the analysis. For pov-erty assessment the level of energy servicesappears to be the most appropriate. The prob-lem for the analyst is that these so-called energyservices can often not be measured in energyunits, and they require many other things fortheir delivery in addition to the energy carriersthemselves. Thus, there is no way of distin-guishing energy services from other servicesand products. In absence of the possibility ofdirectly measuring energy services, a promisingapproximation is to measure consumption atthe level of useful energy.We have to add a note of caution here. Ana-

lyzing useful energy makes a lot of sense, whenone compares various ways of providing onekind of useful energy for one specic energyservice. But, adding up useful energy employedfor dierent energy services is more problematic.For instance, adding up heat supplied to acooking pot and the energy of light comingfrom a light bulb are two energy ows of verydierent physical quality, form and utility,which are produced at dierent costs (techni-cally, resource wise and economically). Compar-ing or adding them up often produces irrelevantresults. We note, however, that in the case ofmeasuring energy poverty, cooking is such adominant energy service that we are not over-stretching the applicability of useful energy,and we will therefore add it up in what follows.

(b) The importance of noncommercial energy

The importance of traditional noncommercial

sources of energy for meeting household energyneeds is still very signicant in India. In fact,about 80% of the energy consumed in villagescomes from noncommercial sources, whichcomprises more than 30% of the total energyconsumed in the country (Pachauri, 2002).Including noncommercial energy in our analysisis also consistent with our analytic approach sit-uated, in terms of disciplines, between engineer-ing and economics. It has the welcome eect ofincluding the consumption of nonmonetizedgoods. In some cases, households following atraditional agricultural lifestyle might be con-sidered fairly well-o if they are self-sucientin meeting their basic food and energy needs,even if all energy used is noncommercial bio-mass. When such households experience achange in lifestyles as a result of a massive shiftat the macro-level away from a barter economyand self suciency, but with a small increase inthe market economy, it often implies for them adecline in the availability of noncommercial en-ergy and little or no improvement in their accessto commercial energy. In such cases, it is impor-tant to include noncommercial energy in anyanalysis of household energy use patterns inorder to reect more accurately whether ornot the change in lifestyle is really accompaniedby an improvement in overall well-being.There are, however, two problems with the

inclusion of noncommercial energy in the anal-ysis:

The available data for nonmonetaryexchanges of goods are not recorded withthe same accuracy as monetary exchanges.The latter are recorded by vendors and buy-ers, often are then registered in formalizedbalance sheets of traders and banks as wellas on tax forms. For wood and other bio-mass collected in nature, nobody is obligedor much interested in recording theamounts. The data we have are estimatesor records of surveys. The survey estimatesdepend on the good will and memory ofthe respondents, who do not have the possi-bility of looking up any bills or bankstatements.We actually would have liked to alsoinclude data on animal traction, an impor-tant source of mechanical drive. But wedid not nd data of sucient quality anddetail to make it worth including them (adistinction of traction for agricultural pur-poses, such as tilling and pumping, for trans-port in the productive sectors, and fortransport in the household sector, would

have been the minimum requirement).

2086 WORLD DEVELOPMENTThe NSSO household expenditure database,which is employed in the second half of thepaper, provides information regarding boththe expenditure and quantity of fuelwood con-sumption at the household level. Data are col-lected both regarding cash purchases of thesefuels and consumption out of home-grownsources or from that collected from commonlands, forests, etc. and this provides a richsource of information for analysis. Unfortu-nately though, no information is collected onthe time taken to gather fuelwood and otherbiomass by the household or the nearness ofsources of supply. The time required in manycases can be quite signicant and has an oppor-tunity cost associated with it, in most cases forthe women and children of the household, interms of time that could have been spent moreproductively by women in income-earningactivities and by children in education. Aswitch from biomass fuels to modern commer-cial fuels also involves a further saving in time,as the ease of using these modern fuels is muchgreater and there is less time needed to igniteand tend the stove, resulting in greater conven-ience and speed of cooking.The inclusion of noncommercial energy has

important implications for the nature of therelationship between energy consumption andexpenditure levels. In general, in the absenceof any noncommercial use, there is a strongpositive correlation between energy consump-tion and expenditure levels. But, since noncom-mercial energy is often collected freely innature, constraints in terms of resource availa-bility, labor availability, land and livestockholdings have a larger impact on the amountof total energy used rather than the per capitaexpenditure levels or budget constraints of thehousehold. Moreover, there is an upper con-sumption limit for noncommercial energy, be-cause its use is restricted to cooking andheating purposes. This is in contrast to electric-ity, where no such limit exists. Additionalconsumption of electricity provides additionalservices; additional use of fuelwood only pro-vides extra benet as long as there is food tocook. Contrary to expectation, an analysis ofthe household survey data from India showthat average consumption of biomass doesnot decline with increasing expenditure (Figure1). The literature on fuel switching suggests thatin general people switch to commercial fuelswith an increase in income, if they are able to(Smith, 1987; UNDP/WB, 2003a). Yet, house-

holds with no access to markets are unable to3. APPROACHES TO MEASURINGENERGY POVERTY

Although there is a fairly substantial litera-ture on the existence of energy-poverty link-ages, there is relatively little direct, empiricalevidence concerning the nature of these link-ages in developing countries. There have beensome attempts to calculate the amount of en-ergy needed to meet basic needs, based on somesubjective assessment of what constitute basicneeds. In this section, we try to summarizeand provide a brief, yet nonexhaustive, over-view of dierent approaches that have beenused in the literature to measure energy pov-erty. The rst two classes of approaches pre-sented below make use of informationpertaining to the expenditure on and quantityof energy consumption, the third to the accessto dierent energy sources.

(a) Economics-based approaches

Among the most common economic ap-proaches to measuring energy poverty are thosethat involve dening an energy poverty linepurchase and therefore switch to commercialfuels. These households continue to use non-commercial biomass, even when they have highper capita expenditure levels. In addition, somehouseholds actually do not switch, but ratherstack their fuels (Masera, Saatkamp, & Kam-men, 2000). In such cases, with increasing in-come additional superior fuels are bought, butat the same time the use of the inferior fuel(biomass) is not abandoned. These householdstherefore continue to use biomass along withcommercial fuels.As a result, there is little evidence of correla-

tion between noncommercial energy use andincome (Figure 1). In this case, measuring pov-erty in monetary terms alone by assessing theper capita expenditure levels of individualscould be misleading. A household with lowexpenditure levels that has access to sucientnoncommercial energy can be considered ri-cher in energy terms than a household withhigher per capita expenditure but poor accessto noncommercial energy and no access to othercommercial energy forms. Thus, by the inclu-sion of noncommercial energy use we take intoaccount an important nonmonetary dimensionof poverty.or fuel poverty line analogous to the conven-

ENERGY POVERTY IN INDIAN HOUSEHOLDS 2087tional monetary poverty line. In order to do so,calculations are often made as to the averagelevel of energy consumption of persons havinga level of income or expenditure ocially spec-ied by the poverty line or minimum moneyamount needed to meet basic needs. A recentexample of such an approach can be found inFoster, Tre, and Wodon (2000). They usehousehold survey data from Guatemala to cal-culate a fuel poverty line. In this work, theydene the fuel poverty line as the average en-

Figure 1. Per capita useful energy plotted against the per c

against the mean per capita expenditergy consumption of all households whoseoverall per capita consumption expenditurelevel falls within a plus or minus 10% rangeof the ocial expenditure poverty line. As op-posed to dening household fuel or energy pov-erty in relation to the monetary poverty line,authors such as (Goldemberg & Johansson,1995) or (Krugman & Goldemberg, 1983) havedened energy poverty by assessing energy con-sumption at the aggregate national level in rela-tion to other broader measures of poverty such

apita expenditure (bold lines depict useful energy plotted

ure for expenditure demi-centiles).

2088 WORLD DEVELOPMENTas the human development index (HDI) orphysical quality of life index (PQLI). Whilesuch approaches are computationally fairlysimple, they only provide a single energy or fuelpoverty line, i.e. a single number that is basi-cally a transformation of the monetary povertyline or some other poverty index, and do not,by themselves, add any new insight.Often energy poverty has been dened in

terms of energy budget shares i.e. the share ofhousehold expenditure or income spent on fuelsand electricity. Thus for instance, studies suchas those by Leach (1987) state Their (the poor-est groups) share of income spent on energy isnormally much greater than that of middleand upper income groups. The trend of declin-ing energy budget share with rising income isone observed in developed countries as well.The government of the United Kingdom, forinstance, denes a fuel poor household asone which needs to spend more than ten percent of its income on all fuel use and to heatits home to an adequate standard of warmth(DTI, 2002). The problem with such a measureis that the energy budget share of a householdis often dependent not only on the type of fuelor energy used and its market price, but alsothe eciencies and the costs of appliancesneeded for burning/using the specic energytypes. In addition, a large budget share couldalso be a result of high consumption, eitherdue to high prices or large household size,and this further complicates the interpretationof this indicator (Foster, 2000).In order to take into account the dierent

eciencies of the wide range of fuels used byhouseholds, another approach for comparingpoor and non-poor households adopted bysome authors such as Leach (1987) and Fosteret al. (2000) is to estimate the eective price,or net price dened as the price per unit ofuseful energy consumed. It is often the case thatpoorer households use the most expensive fuelsin terms of the price per unit useful energy. Thisis because poorer households commonly usethe most inecient fuels and devices. Someauthors have even suggested comparing theaverage total cost of energy, inclusive of theamortized capital costs of the equipment andappliances used to avail energy services, for dif-ferent groups of households (Hosier & Kipon-dya, 1993; Reddy, 2003). Results of suchstudies also indicate that poorer households,that are dependent on more inecient fuels,are often at a disadvantage compared to better

o ones.Poorer households are at a further disadvan-tage as compared to richer ones when a com-parison of the eective cost of energy per unituseful energy consumed also includes the timecosts and transaction costs of gathering oracquiring fuels. Thus, while there may not beany monetary value or price associated withcertain non-commercial fuels, such as wood ordung, there is still a signicant opportunity costin terms of the value of the time spent in col-lecting the fuel wood. Dutt and Ravindranath(1993) report that it is often the case that poorhouseholds spend more money buying, or moretime collecting, each unit of energy they con-sume compared to wealthier households. Theyestimate that the time involved in fuel woodgathering is very signicant and varies from lessthan one hour to more than ve hours per dayin dierent regions of India.

(b) Engineering-based approaches

In addition to these economic based ap-proaches at comparing the energy poor andnonpoor, another approach to measuring en-ergy poverty uses engineering type estimatesfor determining the direct energy required tosatisfy basic needs. The use of engineering typecalculations for estimating basic energy needs isreported in early studies by Revelle (1976),Bravo cited in Krugman and Goldemberg(1983), Goldemberg (1990) and Goldemberg,Johansson, Reddy, and Williams (1985, 1987).Goldemberg et al. estimated that the require-ment of direct primary energy per time unit tosatisfy basic needs is about 500W 6 per person.This kind of a calculation rests on a number ofassumptions regarding the type of energy con-suming equipment (stove, light bulbs, etc.),their sizes, eciencies and intensity of use. Inaddition, the approach requires as a rst nor-mative step the denition of a set of basicneeds. This is a problematic endeavor sincebasic needs vary with subjective wants, as wellas with climate, region, period in time, ageand sex.A similar engineering approach for estimat-

ing the basic energy needs for cooking, lightingand heating was adopted by planning agenciesin India in xing norms that where then usedwhile forecasting and evaluating energy de-mand, especially in rural areas. The AdvisoryBoard on Energy in its 1984 report on energydemand modeling for India (ABE, 1984) as-sumed that about 30W of useful energy is

needed per capita to meet cooking energy

Analyses presented in this paper depended

ENERGY POVERTY IN INDIAN HOUSEHOLDS 2089needs. Similarly, about 1.5W of useful energyper capita is required to meet space heatingneeds and the same amount again, 1.5W of use-ful energy per capita, to meet lighting needs.These values are normative in the sense thatthey are calculated on the basis of variousassumptions regarding what is considered asthe basic minimum required to meet humanneeds. Thus a total of some 33W of useful en-ergy per capita was assumed by ABE to be re-quired at the household level to meet thethree basic direct energy services, cooking,lighting and space heating. This converts to al-most 250W of primary energy, which is abouthalf of Goldembergs estimate, which is basedon his own stipulations of basic needs. A simi-lar engineering type estimate of the end-use en-ergy per capita required to meet basic needs forthe average Indian, assuming that LPG is usedfor cooking and electricity for lighting isapproximately 100W per capita (Reddy, 1999).In this paper, such engineering type calcula-

tions are made to determine the energy require-ments for a normatively dened set of basicneeds, based on assumptions regarding thetypes of energy used, and the sizes, ecienciesand intensities of use for end-use energyequipment. In this way, the energy needs corre-sponding to a vector of energy services aredetermined, rather than just a single averagevalue. In this sense, this is a more robust meas-ure, as it is able to better capture the multidi-mensionality and diversity of the poor. Inaddition, the approach has the added advan-tage that in theory it allows for distinguishingbetween the basic energy needs of rural andurban households and those residing in dier-ent climatic regions or dierent socio-culturalgroups.

(c) Poverty and access to energy

A number of authors have dened energypoverty in terms of access to energy services(see for, e.g., Alam, Bala, Huq, & Matin,1991; Mark, 1998; or Barnett, 2000 for a discus-sion on how access to more ecient energysources is related to an improvement in peopleslevel of well-being). This is an important com-plement to a consumption based measure ofpoverty. For instance, whether a householdchooses to use a number of dierent electricalequipments or not is a matter of choice, whatis important however, is that the householdhas that choice to make and for that the house-

holds must have access, i.e. physical access tocritically on the availability of unit level budgetsurvey data from the National Sample SurveyOrganisation (NSSO) of India from several dif-ferent rounds of its household consumerexpenditure survey. 7 The wealth of informa-tion provided by these large representativesurveys, has so far been used largely for con-ventional monetary poverty measurement atthe all-India or regional level (for dierentstates, rural and urban). However, informationcollected via the survey provides a rich basis forstudying other dimensions of well-being of In-dian households, particularly those relating totheir energy proles. Data from the surveys in-clude information on monetary expendituresand physical quantities of consumption of anumber of household items, including fuelsand electricity, as well as information on a hostof other socioeconomic, demographic andinfrastructural characteristics of households.Each round of the survey collects informationfrom a cross-section of households coveringthe entire area of the country over a period ofone year. Details regarding the survey method-ology and sample are provided in the Sar-electricity (the electrical grid and a home con-nection), physical access to markets where itcan buy electrical equipment, and the purchas-ing power to buy the equipment and the elec-tricity at a competitive price. Thus, whatdistinguishes a poor household from a bettero one is also the wider range of choice in termsof which fuels to use (more ecient, more con-venient, less polluting), and which equipmentand appliances to buy.Finding data, however, on access to energy

services can be quite dicult. One needs datanot only on the physical access to dierent en-ergy types, but also data on whether the house-hold has access to markets that sell dierentenergy using equipments and information onthe purchasing power of the household, as wellas the market prices of the fuels and equip-ments. Using data on coverage to indicate ac-cess can therefore be problematic as coveragesays little about whether households in facthave the ability to access the particular fuel orelectricity. In addition, there is often little infor-mation available on the quality and security ofsupply of dierent fuels and electricity.

4. DATA SOURCESvekshana publications (NSSO, 1986, 1990,

It has to be kept in mind that the householdsurveys were not designed specically to collect

2090 WORLD DEVELOPMENTinformation on energy consumption and henceestimates are not based on direct measurementsbut instead on the recall of the respondents. Inaddition, the survey does not provide a breakdown by purpose of purchase or end-use.Hence, there might be some measurement er-rors and inaccuracies in the estimates of con-sumption inferred from the survey. Given thevery large sample size of the surveys, however,in the average one might expect that the dataare fairly accurate. In particular, the level ofreliability for estimation of energy poverty atthe national level is high. A comparison of datafrom the surveys, pertaining to the percentageof users of dierent fuels and electricity, withcensus data (Census of India, 2001) also indi-cates that, at the aggregate state and nationallevel, the survey data are representative. A re-cent World Bank study on the access of thepoor to modern household fuels in India alsocompares data from the National Sample Sur-veys on energy consumption with data on o-cial supplies of household fuels and nds theconsumption data match fairly well at theaggregate level (UNDP/WB, 2003b).

5. CONSTRUCTING A NOVELTWO-DIMENSIONAL MEASURE OF

ENERGY POVERTY ANDDISTRIBUTION

This section discusses the construction of anew measure of energy poverty and distributionthat combines information on access to dierentenergy carriers, based on data pertaining to ac-tual purchases or utilization, and quantity of en-ergy consumed per capita and compares thiswith engineering type calculations for a list ofbasic energy services consumed by households,1996, 2002). Information is not collected fromthe same set of households across dierentrounds of the survey and therefore it does notconstitute a panel. But, the sample for each ofthe quinquennial rounds that we employ inour analysis is very large and representative ofthe nation as a whole. The data on householdexpenditures and physical consumption fromdierent rounds of the survey form the basisfor dening access and calculating end-use anduseful energy associated with the use of dierentfuels and electricity by households. The meth-odology used to do so is described in Section 5.to assess whether the individual has sucientenergy to meet basic needs. One main advantageof such an approach is that it measures not onlyconsumption, but also, in some sense, capabil-ity. This approach also takes into account thenonmonetized part of household transactions(by the inclusion of noncommercial energy), itcaptures to a greater extent the diversity of thepoor and nonpoor by looking at dierent com-binations of fuels/equipments and consumptionlevels that might provide the same energy serv-ices, and it allows for dening any number ofdierent normative energy poverty lines ratherthan a single static one.As a rst step to the construction of this

measure, in the following section, the basic en-ergy needs of an average sized household areestimated and then combined with correctionsfor the scale eects for diering household size.

(a) Estimating basic energy needs for theaverage household

Table 1 lists the main energy services that arein demand in households and some engineeringestimates for their direct energy requirement.Depending on what one considers as the basicminimum in terms of energy services that ahousehold needs, one can then use Table 1 tocalculate the minimum energy requirements tomeet these basic needs in terms of either usefulor end-use energy.It should be noted that the power requirements

in Table 1 do not refer to the installed power ofthe equipment, but to the averaged power re-quired to deliver the specic energy services. Fol-lowing in the tradition of Goldemberg, we usethe unit of power (energy per unit time) in watt(watt = Joules per second), to measure energyneeds per person in this paper. By using the unitwatt, we measure the average power consumedby a person during any given time interval.In order to estimate basic energy needs, we

start by calculating the end-use energy require-ments for specic energy services. For instance,we assume an electric light bulb with an in-stalled power of 40W is used on average for5h per day. Therefore, this light bulb consumes200Wh per day (5h 40W). We then calculatethe averaged power requirements for lightingwith an electric light bulb by dividing the en-ergy requirement by the time span in whichthe energy is consumed: 200Wh/24h = 8W.Another example, for the case of preparationof a daily meal for a ve-member householdusing fuelwood we assume an energy require-

ment of about 34MJ. That refers to an aver-

es

ENERGY POVERTY IN INDIAN HOUSEHOLDS 2091Table 1. Power requirements of energy servic

Energy services

Scooter per 5km/day)a

Car (per 10km/day)a

Lighting, one electric bulb (5h/day, 40W)a

Lighting, 12 kerosene lampsb,c,d,e,f,g

Space cooling 1 roomb

Cooking traditional biomass 1 meal dailyb,d,e,f,h,i,j

Cooking kerosene stove 1 meal dailyb,d,e,f,h,i,k

Cooking LPG stove 1 meal dailyb,d,e,f,h,i,k

Warm water (fuelwood; 5 l/day)b,d,e,f,h,i,k

Warm water (kerosene; 5 l/day)b,d,e,f,h,i,k

Warm water (electric geyser, 5 l/day)d,e,h,i

Refrigerator smalll,m

Refrigerator largel,m

Washing machinel,maged power per day of 34MJ/(24h*3,600s/h) = 393W. Accordingly, the preparation oftwo meals per day requires 68MJ per day or786W. These estimates of end-use energyrequirements for specic energy services arethen converted into useful energy by assumingcertain eciencies of the end-use equipments. 8

The estimates are averages and underlie specicassumptions. Real requirements vary fromhousehold to household, depending on severalfactors like device type, intensity and mode ofuse, household size, etc.

(b) Correcting for household size economiesof scale

The energy requirements listed in Table 1refer to those needed per capita for someone

Various household devicesn

Radion

TV (Black&White/Color)n

Computern

Sources:a Bockhorst (2001).b Leach and Gowen (1989).c Plas and de Graa (1988).d Reddy (1996).e Reddy (2003).f US Congress (1991).g Natarajan (1998).h Ravindranath and Hall (1995).i Ravindranath and Ramakrishna (1997).j Gupta and Rao (1979).k Ramachandra et al. (2000).l Huser and Spalinger (1992).m Bayrisches Staatsministerium fur Wirtschaft (1995).n Cremer et al. (2003).(for an average sized 5 member household)

Average power per household (in W)

Useful energy End-use energy

13 73

66 365

6 8

9 19

110 145

55 393

55 123

55 93

7 52

7 16

7 10

15 20

28 37

11 14residing in an average ve-person household.It has to be pointed out that the eciencies ofsome equipment are strongly dependent onthe household size. The problem therefore isto compare energy consumption of individualsresiding in households of diering sizes. Sincecooking energy plays such a dominant roleand accounts for about 90% of the total resi-dential energy consumption in India (Natara-jan, 1985), we focus on the scale eect forcooking. One way to estimate the cooking scaleeect is to divide the monthly-consumed usefulenergy for cooking by the total number ofmeals served at home as reported in the NSSOdata. Figure 2 shows the average per capita en-ergy consumption per person-meal grouped byhousehold size. Following this estimation, asingle member household requires about three

2 2.5

4 6

11 14

13 17

77.

9

si

ne

-si

2092 WORLD DEVELOPMENT86.192.6

100.0111.2

127.7

149.3

193.8

83.2

0

50

100

150

200

250

300

1 2 3 4 5 6 7 8

household

rela

tive

ener

gy c

onsu

mpt

ion

in %

Figure 2. Estimations of household-scale economics in e

persons living in an averagedtimes more energy for a single person-mealthan a household with about six members.Using regression analysis is another way to esti-mate the scale eect. This approach has theadvantage that it enables one to control forthe household income eect. This is important,as the per capita income or expenditure also hasa signicant eect on the per capita energy con-sumption, apart from household size. Based onNSSO data 9 a simple loglog regression wascarried out, where the variable useful energyfor cooking was the dependent variable andper capita expenditure and household sizedummy variables were the independent varia-bles.The regressions, a separate one for each NSS

round, show rather low R-squares (0.20.35),but signicant scale eects, and the average tswell with the results estimated from the calcula-tions based on useful energy per person meal.In addition, to verify the scale eects obtainedwith the NSSO data, they were crosscheckedwith household size scale eects reported inother publications (Bayrisches Staatsministe-rium fur Wirtschaft, 1995; Bensel & Remedios,1995; Hughes-Cromewick, 1985; Huser & Spa-linger, 1992; Ironmonger, Aitken, & Erbas,1995; Song & Bradbrook, et al., 2002; Wang,1 77.1 73.2 70.5 67.5 69.567.8

10 11 12 13 14 >=15

ze

regressionenergy/mealreports

rgy consumption for cooking (scale is relative to that of

zed ve-member household).Feng, Gao, & Jiang, 1999). The comparisonillustrates that for household sizes equal or big-ger than four the curves overlap fairly well. Forhousehold sizes 1, 2 and 3 the regression analy-sis and the average of the reports show a smal-ler scale eect to those estimated from thecalculations based on useful energy per personmeal. We made adjustments based on theequivalence scales estimated from the averageof the regression results for dierent years, inorder that the data used are consistent withthese used for the rest of the analysis presentedin this paper.In addition to the household size, other fac-

tors also inuence the per capita energyrequirement. The per capita expenditure wasmentioned previously. Another important fac-tor is the household composition. Since youngchildren and elderly people eat less than hard-working adults, less energy is required forcooking for these members. The compositioneect has not been studied in depth here, butwe found that the average family compositionfor the dierent household sizes is more or lessalike. 10 A more sophisticated method to ana-lyze the eects of household size and householdcomposition for dierent regions in India is de-scribed in Meenakashi and Ray (2002). They

ENERGY POVERTY IN INDIAN HOUSEHOLDS 2093perform a simultaneous estimation of a systemof share equations to determine the scale andcomposition eects on expenditure shares.Their results indicate considerable diversity inthe composition and scale eects in consump-tion expenditure for the dierent Indian States.It would be interesting to carry out a similarestimation of a system of equations for dierenttypes of energy consumption. This is left for fu-ture research.

(c) Grouping households by the amount of energythey consume

To assess the relationship between povertyand energy we dene four segments or classesof physical energy consumption per capita, de-ned by the amount of useful energy consumed.Based on the engineering type data from Table1, we create the following four segments of use-ful energy consumption: 60W per capita useful energy consumption inan average ve member household. Combiningthese values with the household size scale eectsas calculated previously (see 5b) allows us to as-sign individuals residing in households of dier-ing size in the data set to one of these segments.These segments correspond to the kind of en-ergy services that reect the range typically con-sumed in Indian households (see Table 2). Inwhat follows, we refer to the segments as Bot-tom (B), Lower (L), Upper (U) and Top (T).These segments of useful energy consump-

tion, while somewhat normative, have beenconstructed and chosen to reect a progressiveimprovement in the kinds of energy servicesthat they can aord. 11 Thus, for instance, inthe Bottom energy consumption segment, onlya level of energy services that might be associ-ated with abject poverty is aordable, whilethe Top segment consumes energy services thatwould be associated with a comfortable level ofwell-being. The typical range of energy servicesthat might be available to those in the dierentenergy consumption segments is shown inTable 2. The implicit assumption we make hereis that an improvement in the level of well-being of a person or household is related toan increased demand for more diversied en-ergy services. The cut-o values for useful en-ergy intervals constructed on the basis ofengineering calculations can in principle bexed dierently and rened in order to takeinto account a more detailed account of availa-ble energy services, or dierences in amounts of

useful energy needs arising from climatic or re-gional dierences or varying tastes and cus-toms.

(d) Grouping households with respect to theiraccess to dierent energy carriers

Since dierent energy carriers vary greatly inquality, convenience and utility, not only theamount or quantity, but also the type of energyused is of importance when assessing energy usein relation to poverty. For instance, only house-holds that have access to electricity can enjoybenets of energy services associated with theuse of electrical equipment and appliances.And traditional wood stoves cause much higherlevels of indoor air pollution than kerosene orLPG stoves. In the absence of more detaileddata on access, for the purpose of this paper,we dene and measure access by using dataon utilization and distinguish between house-holds that incur positive expenditures or havepositive consumption of a particular fuel orelectricity as those having access and the othersas not. Of course, we realize that though a lackof access implies nonutilization, the latter maynot be due to lack of access in every case. Therationale behind dening access in this way isthat only those households that have the energysource available to them, and the purchasingpower (either monetary or in labor time) tobuy it, are capable of using it and thereforecan be thought to have real access to it. 12

In Figure 3 we present the distribution ofhouseholds in India according to the type of en-ergy used based on the data from the NSSrounds spanning the period between 1983 and199900. The majority of the households (stillmore than 60% for the most recent year) usea combination of biomass and kerosene or bio-mass, kerosene and electricity to meet theirdirect energy needs. The proportion of electric-ity users grew considerably over this period.About a third of all households use three ormore fuels (increasing from less than 20% overthe last 20 years). In contrast, the number ofhouseholds dependent on a single energy typefor meeting their direct energy needs is verylow for all years. The 1520% of inconsistenthouseholds have been termed thus as the datareported by these households appear inconsist-ent. There are two questions in the survey thatpertain to the type of energy carriers used bythe household. If in the rst question, whichasks for the major source of energy for cookingand lighting, respectively, they report the use

of a certain energy type, but in a subsequent

Table 2. Examples of energy services, which may be available for an average sized ve-person household in the given intervals of useful energy

Energy use segments Less than 15W/cap Bottom (B) 1530W/cap Lower (L) 3060W/cap Upper (U) More than 60W/cap Top (T)

Examples of

energy services

Up to one warm meal

per day, a kerosene lamp,

possibly a little hot water

12 warm meals per day,

a few kerosene lamps

or one electric bulb,

some hot water

Two warm meals per day,

hot water and lighting.

Some small electric appliances

(radio, TV, telephone) for

groups with electricity.

Possibly a scooter

2 or more warm meals per day,

hot water, lighting, some space

heating andin case of groups

with electricity, possibly some

space cooling, as well as other

electric appliances. Possibly a

scooter or a car

2094

WORLD

DEVELOPMENT

6. CHANGES IN ENERGY POVERTY

s

ENERGY POVERTY IN INDIAN HOUSEHOLDS 2095question relating to the quantity and expendi-ture on that energy type they report no con-sumption, then data for that household havebeen excluded.For our analysis, we classify households into

three levels of access. To allow for the fact thathouseholds use multiple fuels and that theremight be fuel stacking (Masera et al.,2000), the levels are dened to reect improvedaccess to more ecient energy sources, but donot preclude the use of less ecient sources inconjunction. Dened in this way, householdsthat use biomass and kerosene, but no electric-

0%

20%

40%

60%

80%

100%

83 87-88 93-94

Figure 3. The distribution of householdity and no LPG are classied as being at theBIO level; households using electricity but noLPG and who may use other fuels are classiedas being at the ELEC level; and householdsusing both electricity and LPG and who mayuse other fuels are classied as being at theLPG level. Only very few households fall intonone of these levels and are excluded.

(e) The energy accessconsumption matrix

Combining the results from the previous sec-tions, a matrix we call the energy accesscon-sumption matrix can be constructed. It hasbeen referred to as the energy accessuse matrixin Pachauri and Spreng (2004). This matrix di-vides the population according to their accessto dierent energy types (Section d) and thequantities of per capita useful energy they con-sume (Section c). The three levels of access toenergy combined with the four energy con-sumption segments produce 12 groups thatAND THE ENERGY DISTRIBUTIONPATTERN BETWEEN 1983 AND 2000

The accessconsumption matrix does notportray exclusively energy poor households,comprise this matrix (see Figure 4). In what fol-lows, we discuss how this matrix can trace thedevelopment of society with respect to a num-ber of poverty-related variables measured atthe household level.

99-00

wood-electricity

electricity-LPG

kerosene-electricity-LPG

kerosene-electricity

wood-kerosene-electricity

kerosene

wood-kerosene

inconsistent

with access to dierent energy carriers.but in fact, represents all households in India.For illustrative purposes, an energy povertyline is depicted in Figure 4. Clearly, otherchoices of poverty lines are possible and thereader is invited to draw hers/his own povertyline. This line has been chosen so as to separatepeople having less than sucient energy forcooking one to two meals a day and very lim-ited lighting from the ones having morethan that. This division is able to capture pov-erty on the level of both functionings and capa-bilities (Sen, 1999), as reected by the energyservices obtainable. It also takes account ofthe fact that useful energy from dierent energysources provides diering qualities of energyservices (see Section c). For this reason, theenergy poverty line does not coincide with asingle useful energy consumption segment.Energy poverty measured by means of thisline decreased from more than 75% to less than40% in India during the period 1983 to 19992000.

Figure 4. The accessconsumption matrix: the development of the size of the 12 groups over 19832000 (number of people, rural and urban, within each group).

2096

WORLD

DEVELOPMENT

ENERGY POVERTY IN INDIAN HOUSEHOLDS 2097Deaton (1996) discusses the relative merits ofpoverty lines versus welfare measures that takeinto account both the mean of distributions andits dispersion. The accessconsumption matrixmeasures not only energy poverty in twodimensions, but also combines the advantagesof a poverty line-measure with the advantagesof a distribution measure. Dening an energypoverty line allows us to count the number ofenergy poor. At the same time, however, thematrix allows one to see the distribution of en-ergy access and consumption for the entire pop-ulation, at a glance.Unlike relative divisions such as deciles or

quartiles, the divisions in our matrix are xedand do not change with shifts in mean valuesover time. On the access axis the divisions aredened, quite naturally, by the important ac-cesssituations encountered in the countrybeing analyzed. On the consumption axis, thedivision boundaries are set normatively, inour analyses at 15, 30 and 60W per capita forthe useful energy supplied to meet specic en-ergy needs of households.Besides analyzing the shift, or the net move-

ment of households across the matrix, we ana-lyze in this section how much the groups dierin terms of other welfare measures, both acrossthe matrix and across time. We will see that thegroups dier very much in terms of meanexpenditures, and level of literacy across thematrix, but interestingly, the characteristics ofhouseholds within individual groups hardlychange over time. In other words, the groups,solely dened in terms of energy access andconsumption, represent xed levels of well-being.

(a) Shifting shares of people across theaccessconsumption matrix over time

Figure 4 contains information on the changeof the size of the groups over the years. 13 Thedarker shade indicates urban population, thelighter shade the rural. Development is seenhere as net movements from one group to an-other. We investigate the horizontal and verti-cal movements of members of representativehouseholds between groups. We emphasize,that this description of the dynamics capturesthe situation at an aggregate level only. Onlynet changes of the groups or members ofrepresentative households, respectively, aredescribed, and not real movements or migra-tions of people between the groups. Thus, this

description captures well the situation formembers of representative households ineach group, but not that at the level of individ-uals (in contrast, for example, to the shifts ofindividual households in Bangladesh describedin Sen (2003), where an average decrease ofpoverty goes along with some groups of house-holds ascending out of and others descendinginto poverty).The general trend is clearly from groups con-

suming little and having limited access togroups consuming more and having less re-stricted access to energy, especially a net shiftfrom the group of extreme energy poverty, theupper left group, to the central ones. This over-all development aects at the same time boththe types of energy carriers employed and theamount consumed.There are also big dierences between the net

movement of members of rural and urbanhouseholds over this period. In general, thereare few urban households at the BIO level,and relatively large numbers at the ELEC andLPG level. The number of rural householdsis very large at the BIO and ELEC level andsmall at the LPG level. More than half of theurban households and more than a third ofthe rural households that were extremely en-ergy poor (B consumption segment at the BIOlevel) in 1983 managed to improve their lot bythe year 1999. The number of urban house-holds that achieved a reasonably comfortableenergy situation (U and T consumption levelat the ELEC and BIO level) by 1999 wasby far larger than the number of rural house-holds, many of which only barely managed tomove out of energy poverty. The largestshift in the number of rural households isthe increase in the two central groups of thematrix.

(b) Changes in per capita expenditure (PCE)across the matrix and across time

The mean PCE, measured in constant 199394 Rupees, diers widely across the dierentgroups. Having better access to more ecientenergy types (especially to LPG) or being inhigher energy consumption segments is posi-tively correlated to mean PCE values. Althoughthe mean PCE value has increased at the all-India level, during 19832000, there is hardlyany change, both within the access levels or theconsumption segments (see Figure 5). A slightdecrease in the mean PCE for those at the ELEClevel can be noted. 14 The absence of change

within the access levels and consumption

0.0

100.0

200.0

300.0

400.0

500.0

600.0

700.0

800.0

1980 1985 1990 1995 2000

biomasselectricityLPGall India

0.0

100.0

200.0

300.0

400.0

500.0

600.0

700.0

800.0

1980 1985 1990 1995

60all India

0.0

100.0

200.0

300.0

400.0

500.0

600.0

700.0

800.0

1980 1985 1990 1995 2000

biomasselectricityLPGall India

0.0

100.0

200.0

300.0

400.0

500.0

600.0

700.0

800.0

1980 1985 2000

60all India

Figure 5. Mean value of the total monthly per capita expenditure in constant 199394 Rupees per month (left: access

levels, right: user segments).

2098 WORLD DEVELOPMENTsegments seen in combination with the overallincrease of the PCE mean value and the bigchange in the size of the groups (see Figure 4)implies that the dynamics with respect toPCE stems from households switching fromone group to another and not from changesin average expenditure levels within eachgroup. The lack of any change for groups atthe BIO level in combination with the trendof increasing mean for the whole of India sug-gests that those living in households that havehigher PCE shift to higher access levels. Theincreasing mean for the whole of India com-bined with the lack of change or slight decreasein the mean PCE for the other two accesslevel implies that within these groups the per-centage of relatively less well-o householdshas risen and that access to better energysources has become increasingly available toeven relatively less well o households (seeFigure 6).0

10

20

30

40

50

60

70

1980 1985 1990 1995 2000

biomasselectricityLPGall India

1

2

3

4

5

6

7

0

10

20

30

40

50

60

70

1980 1985 1990 1995 2000

biomasselectricityLPGall India

1

2

3

4

5

6

7

Figure 6. Percentage of people living in households with an ilIt has to be noted that within the groups thespread of PCE is considerable. In part, thismight be due to the fact that there have beenno corrections made to this variable to accountfor economies of scale in household size. Inaddition, it is due to the inclusion of noncom-mercial energy in household energy consump-tion, which leads to a far less pronouncedcorrelation of PCE and energy consumptionthan if only commercial energy is taken intoconsideration. This is also reected in Table 3,where the within-group percentage of peopleliving below the ocial monetary poverty lineis indicated. The numbers for the earliest round(38) and the most recent round (55) are pre-sented in the table. In general, the energy poorgroups are also poor in monetary terms andthere has been a slight decline in the share ofmoney poor people for each group during19832000. The only exception being, those inthe L, U and T consumption segments for the0

0

0

0

0

0

0

0

1980 1985 1990 1995 2000

60all India

0

0

0

0

0

0

0

0

1980 1985 1990 1995 2000

60all India

literate head (left: access levels, right: user segmentation).

of his approach. The amount of energy con-sumed resembles the functioning vector and

yly

m

ENERGY POVERTY IN INDIAN HOUSEHOLDS 2099LPG access level, but this is due to the fact thatthere were practically no people in these groupsin 1983.

(c) Changes in illiteracy and other indicatorsof well-being

As is the case with the other variables dis-cussed above, the groups widely dier in thepercentages of illiterate people for all the yearsas well. The development of the percentage ofilliterate people in the groups shows thatalthough for India as a whole illiteracy isdecreasing, it is increasing in the groups at theELEC and LPG levels. This again suggests thatthese more ecient energy sources becomeavailable also to households that, being illiter-ate, tend to have lower levels of well-being. Thistrend is even more pronounced if due attentionis paid to the change in size of these groups (seeFigure 4). For the consumption segments, thereis no trend that illiteracy in better-o segmentsincreases, but it does not decrease either, as isevident for the whole of India. There does seemto be a tendency for it to decrease in the bot-tom energy consumption segment. In general,within access levels and consumption segments,

Table 3. Percentage of people below the monetarand 272/month (urban), respective

Bottom segment Lower seg

BIO

1983 69.6 54.8

1999 57.2 45.1

ELEC

1983 44.8 27.9

1999 36.1 28.1

LPG

1983 8.6 2.5

1999 2.2 3.1the percentage of illiterates changes only slightlyover the years. This indicates that the dynamicsof this variable again stems predominantlyfrom households shifting between groups andnot from within group changes, which is simi-lar to the picture that emerges from analyz-ing the trends in development of mean percapita expenditure across accessconsumptiongroups.In order not to be repetitive, we do not pre-

sent the analogous data for other indicatorsof living conditions like the availability of tapwater and ush toilets. These indicators alsodier considerably from group to group in theenergy access the capability space. Even ifone does not have the money to use any elec-energy accessconsumption matrix but hardlychange over time within individual groups.

7. CONCLUSION

In this paper we rst reviewed a number ofways of measuring energy poverty. One methodis based on engineering type calculations thatcan either be used for setting a normative pov-erty line or can serve as an illustration of whatenergy service a certain amount of useful en-ergy may provide, in the average. Informationof this type, coupled with that on the accessof households to dierent energy sources is thencombined to develop the energy accesscon-sumption matrix.This two-dimensional energy based poverty

measure complements monetary poverty indi-cators in three ways:

The two dimensions are not synonymouswith Sens functioning vector and capabilityspace, but they are constructed in the spirit

poverty line of per capita Rs. 219/month (rural)(real values, base year 199394)

ent Upper segment Top segment

36.7 28.7

26.4 12.7

10.8 4.8

9.9 2.1

0.0 0.0

0.7 0.1tricity, to have access to it gives one the pos-sibility to some day use it and with itperhaps the hope for a better life.Including noncommercial energy avoidsthe mistake of disregarding well-beingaccrued from self-production and bartereconomy. This is often neglected by incomebased measures alone.Describing development as the net move-ment of households from one situation, i.e.from one of the 12 groups in the accesscon-sumption matrix, to another, aords a novelquantitative perspective. The fact that socio-economic variables, like literacy, remain in

2100 WORLD DEVELOPMENTthe average more or less constant withineach group over the examined period19832000 shows that the movementbetween the groups has signicance beyondenergy itself. As Table 3 shows, however,energy poverty is not to be equated withmonetary poverty in general.Applying the accessconsumption matrix to

the data furnished by the NSSO for 198399shows a rapidly developing sub-continent. Forinstance, the number of people living in desper-ately energy poor households having access toonly biomass and kerosene and using barely en-ough of it to cook a full meal a day (top left cellof the matrix shown in Figure 4) decreased from38% to 14% of the population, whereas thenumber of people living in households havingaccess to electricity and possibly LPG and usingmore than is necessary to cook two full meals aday (all four cells near the bottom right of thematrix together) increased from 3.5% to 35%.Figure 4 reveals not only that the number of

energy poor is rapidly decreasing, but also thatinequality in the distribution of energy con-sumption and access is increasing. In 1999 thevery energy poor, (the top left-hand group)were not quite half of what they were in 1983,(about 1.24 million people in 1999), whereasthe numbers in the three relatively well ogroups in terms of energy (T segment at theELEC level and the U and T segments at theLPG level), grew from three million in 1983to 160 million people in 1999. This inequalitywithin India has, however, to be seen in thecontext of global inequality. The direct con-sumption of useful energy in industrializedcountries is far o the scale of the Indian ac-cessconsumption matrix. 15

There are large dierences apparent in gen-eral levels of well-being of persons, as reectedin the indicators we examine, especially acrossdierent access levels. In general, access tohigher-quality energy sources is clearly associ-ated with much higher expenditure levels andimproved living standards. A similar observa-tion holds for the consumption segments, butonly from the mid-1980s or early 1990s on-ward. Prior to this, the dierences in well-beingof persons belonging to dierent consumptionsegments were less pronounced.The general picture of development drawn by

the variables assessed above shows thatimprovements in access to higher quality energysources is taking place at a slightly faster pacethan changes in other socio-infrastructural

characteristics of households. Generally, thedevelopment of these variables indicates thatthe dynamics can be approximated by the netmovement of households from one group to an-other. By dening the matrix according to ac-cess and consumption groups, we allow for thefact that development can be viewed as havingcontinuous and discrete aspects simultaneously.It is important to be cautious in espousing en-

ergy poverty alleviation as an eective means oferadicating overall poverty and improving thewell-being of the worst o population groups.Yet, investments in the provision of clean andecient energy to the poorest to meet their basicneeds often does lead to large improvements intheir well-being (see Toman & Jemelkova,2003 for an overview and theoretical discus-sion). In addition, evidence provided in thispaper points to the fact that in India energypoverty, as dened by our two-dimensionalmeasure, is declining at a faster rate than otherindicators of well-being improve, such as liter-acy and per capita expenditures. This seems tosuggest that the provision and use of energyservices may be an important driver of overalldevelopment. In particular, the provision of bet-ter energy services is clearly associated with sig-nicant economic and social benets for thosewho are most deprived. This association and at-tempts at estimating some of these benets havebeen highlighted in recent studies for the Philip-pines (UNDP/WB, 2002), India (Barnes, Fitz-gerald, & Peskin, 2002), and Peru (World Bank,1999). Yet, the provision of energy, by itself,cannot improve well-being in every case, and itis clearly important that other concerted actionsand direct policies and measures be imple-mented to improve the lives of the poor throughthe spread of literacy, healthcare, employmentand other income generating options.While a signicant reduction in energy pov-

erty in India is evident from our analysis, en-ergy poverty is still widely prevalent andparticularly so in rural areas of the country.During 19832000, whereas the number of peo-ple in the Bottom energy consumption segmentdid decline, there was only a 5% reduction inthe total number of people in the Bottom andLower consumption segments taken together(from 545 million to 516 million). Improvingthe well-being of these sections of the popula-tion will require signicant additional eortsand large investments in infrastructure expan-sion in the next years. Ensuring that this is donein a sustainable and ecient way will be amajor challenge to Indias policy makers, plan-

ners and economic players.

TRavallion (2003), Sundaram and Tendulkar (2003) and

been explored in literature as well. A quote from

(199394) and 55 (199900). There is some controversy B and L segments is to some extent due to misreporting.

ENERGY POVERTY IN INDIAN HOUSEHOLDS 2101concerning the quality of the consumption data in round Household responses to the questions on quantity andShakespeares King Lear provides an illustrationRegan, daughter to Lear: What need one?

Lear: O reason not the need! Our basest beggars

Are in the poorest thing superuous.

Allow not nature more than nature needs,

Mans life is cheap as beasts.Thou art a lady;If only to go warm were gorgeous,

Why, nature needs not what thou gorgeous wearst,Which scarcely keeps thee warm. But, for true need,

You heavens, give me that patience, patience I need!

3. Energy in this context refers to energy, from the

level of primary energy to energy services, associated

with man-made systems. Energy in form of the caloric

content of food or the energy content in sun rays (both

the heat and the electromagnetic radiation) are such

basic necessities for life on earth, that we take them for

granted.

4. It is for this reason that many countries have their

own poverty lines reecting, dierent social, economic

and climatic conditions, as discussed in the OECDsDAC poverty reduction guidelines (OECD, 2001).

5. We would like to remind the reader that strictly

speaking, energy is not consumed, but rather is con-

verted into dierent forms. When most people speak of

consuming energy, the process they are describing is the

conversion of energy to useful work to meet the demand

for certain energy services.

6. Following Goldemberg, we use the unit of power

(energy per unit time) in watt (W = J/s), when referring

to energy needs per person. This should not be

confused with the installed power of equipment or

appliances.

7. The analyses presented in this paper uses unit-level

data from four of the large quinquennial rounds of the

survey, including the rounds 38 (1983), 43 (198990), 50Datt and Ravallion (2002) for a discussion on the recent

debate over the extent of poverty reduction in India

during the decade of the 1990s.

2. The controversial nature of the word needs hasNO

1. Estimates as to the exact extent of poverty in India

dier among authors and depend on the specic deni-

tion and measure of poverty used. See Datt, Kozel, and55 for certain groups of items (see Sen, 2000). This doesES

not aect our analysis, as the controversy does not refer

to the energy related variables. Total household expend-

iture per capita, however, might be aected, yet we do

not make any corrections for this and this has to be kept

in mind while reading Section 5.

8. If for electric light bulbs customary conversion

factors of about 0.10.025 had been used, then the

obtained useful energy would have been absurdly low

compared with the useful energy for cooking. To

overcome this problem, we dene in this article useful

energy to be synonymous with useful energy for

cooking. For all electric energy services we used only

one conversion factor for converting from end-use to

useful energy (0.75). Also for kerosene energy services,

only one conversion factor was used (0.45), knowing

that for lighting the real eciency would actually be

much lower. Thus we have the advantage of not

rendering the useful energy for lighting irrelevant, as

would have been done by applying the very low

conversion factors.

9. Data from the NSS rounds 38, 50 and 55 were used

for both approaches.

10. To describe the household composition the NSS

variable total consumer unit, which is the sum of the

household members individual consumer units, wasused. The average total consumer unit divided by

household size was for all household sizes around 0.8.

The variable consumer unit was only available for

Round. 55.

11. In general, estimates of physical energy consump-

tion from the sample data are likely to be underesti-

mates. It is also likely that the cut o values for useful

energy intervals constructed from the engineering calcu-

lations are underestimates, since in practice the dierent

end-use devices might be left running beyond the time of

use assumed and the eciencies ofoften not well

functioning equipmentmight be lower than that of the

equipment measured.

12. Such a measure is likely to be a lower bound to the

real access enjoyed by a household. Such a measure is

still preferable, however, to one based on ocial

estimates of coverage, which overestimate access by a

large margin.

13. It is possible that the very small number of persons

at the LPG level in the early years and especially for theexpenditure on LPG also appear to be somewhat

clustered around values corresponding to about 15kg. 15. In Swiss households, for instance, the direct con-

E

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2104 WORLD DEVELOPMENT

On Measuring Energy Poverty in Indian HouseholdsIntroductionPoverty, basic needs and minimum energy needsDefining energy consumption at the household level and the appropriateness of useful energy for poverty measurementThe importance of noncommercial energy

Approaches to measuring energy povertyEconomics-based approachesEngineering-based approachesPoverty and access to energy

Data sourcesConstructing a novel two-dimensional measure of energy poverty and distributionEstimating basic energy needs for theaverage householdCorrecting for household size economiesof scaleGrouping households by the amount of energy they consumeGrouping households with respect to their access to different energy carriersThe energy access ndash consumption matrix

Changes in energy poverty and the energy distribution pattern between 1983 and 2000Shifting shares of people across the access ndash consumption matrix over timeChanges in per capita expenditure (PCE) across the matrix and across timeChanges in illiteracy and other indicatorsof well-being

ConclusionAcknowledgementReferences