South Pacific Studies Vol.33, No.1, 201225

Poverty Analysis in Vanuatu:
A Critical Review and Alternative Formulation
NARSEY Wadan Lal

Research Center for the Pacific Islands, Kagoshima University
Korimoto 1-21-24, Kagoshima, 890-8580 Japan
Email: wadan.narsey@gmail.com

Abstract
This paper examines the most recent analysis of poverty in Vanuatu by the Vanuatu National Statistics
Office (VNSO) in 2009 using the Vanuatu 2006 Household Income and Expenditure Survey (HIES).
VNSO (2009) comes to the conclusion that the urban incidence of poverty (in Vila and Luganville) is threetimes higher than rural poverty, a quite implausible result. This paper outlines apparent weaknesses andinconsistencies in the methodology of the VNSO (2009) study, specifically in the construction of the Food
Poverty Line (FPL) using a Food Energy Intake (FEI) method, and the multiplier method to obtain the NonFood Poverty Line (NFPL) and Basic Needs Poverty Line (BNPL) values, which are shown to be largely
responsible for the incongruous results for the incidence of poverty and poverty gaps in rural and urban
Vanuatu. This paper presents alternative methodologies for the construction of the FPL food baskets, andhence the BNPL values, to be arrived at by consensus amongst local stakeholders in poverty analysis. Given
that there has been no social consensus on the appropriate values to use for the BNPL in Vanuatu, this paper
presents data in a convenient tabular form so that stakeholders can easily estimate the incidence of poverty
in rural and urban Vanuatu using their own choice of values for the FPL and BNPL. The paper explains why
the statistics on income distribution given by VNSO (2009) are highly unreliable given the likely serious
under-reporting of incomes and expenditures of Chinese and European ethnic minorities.
Key words: Asian Development Bank (ADB), food poverty line, United Nations Development Program(UNDP), World Bank

Introduction
Vanuatu is a set of small islands in the west of the Pacific, with a land mass of justover 12 thousand square kilometers, and a current total population of around 253,0001,
comprising largely Melanesians, but also small proportions of Europeans, Chinese andother Pacific Islanders. The modern economy is largely dominated by the minority
people of European and Chinese origin. The largest urban area is the capital, Port Vila
Received: 23 June, 2012
Accepted: 13 September, 2012
1 Vanuatu National Statistics Office website: http://www.vnso.gov.vu/.

26South Pacific Studies Vol.33, No.1, 2012(referred to from now on as Vila) on the island of Efate, while the other major urban
town is Luganville on the larger island, Santo. Vanuatu is a low income developing
country with a Gross National Income per capita of around US$2,600, but it is richin land and sea resources. Vanuatu, like other Pacific island countries, faces a strong
tendency for rural-urban migration, although it has not developed to the extent it has
in other Pacific countries like Fiji, the Solomon Islands and Papua New Guinea. Some
78% of the population lives in rural areas, with some 16% in Port Vila (the capital) and
6% in Luganville.
As with all other Pacific countries, Vanuatu also recognizes that poverty, while
not as severe as in other least developed countries in Asia or Africa, is neverthelessbecoming an important policy issue, and national development policies also havestrong themes for poverty alleviation.
For sound national policy on poverty alleviation, it is critical for government
to understand the quantitative dimensions of poverty, by all the disaggregatedvariables that are of interest to poverty stakeholders in the country. The most common
international practice is to obtain such data through a national household income andexpenditure survey (HIES2).
In 2006, the Vanuatu National Statistics Office carried out such a survey which
is now the most authoritative source for any national analysis of poverty in Vanuatu.
This survey’s data have also been used by a recently published paper on the incidenceof poverty in Vanuatu (VNSO 2009).3 The same HIES data at the household level
was also made available to this author by the Acting Government Statistician for the
purposes of this analysis.
By first outlining the usual method of quantitative poverty analysis, this study
explains the VNSO (2009) methodology and its weaknesses in the Vanuatu context,
specifically in relation to the estimation of the food poverty line and the non-foodpoverty line. The paper then explains some of the survey limitations, which constrain
the conclusions that may be made about overall income and expenditure distribution
in Vanuatu. The study then suggests an alternative methodology for the analysis ofpoverty in Vanuatu and gives some broad indicative results. This paper then presents
data to enable poverty stakeholders in Vanuatu to estimate the incidence of poverty in
Vila, Luganville and rural Vanuautu, using their own values for food poverty line andbasic needs poverty line. The paper suggests an initiative for stakeholders in poverty
analysis in Vanuatu to devise more appropriate values for the food poverty line, thenon-food poverty line and the basic needs poverty line, which can enable more accurate
and useful estimates of the incidence of food poverty and basic needs poverty. Lastly,
the paper gives warnings on the unreliability of the Gini coefficients presented in
VNSO (2009).
2 Some abbreviations are used in the text, tables, and figures because of the frequency of their occurrence. Please see the
Appendix 1 for more details.
3 Report on the estimation of basic needs poverty lines, and the characteristics of poverty in Vanuatu. Vanuatu National
Statistics Office, Asian Development Bank and UNDP, Suva Regional Office, 2009. The main author of the report was
Kim Robertson, although others from ADB, UNDP and VNSO are also acknowledged in the report.

NARSEY: Poverty Analysis in Vanuatu: A Critical Review and Alternative Formulation

27

The Quantitative Analysis of Poverty
Poverty cannot be understood without a thorough understanding of all its
multidimensional aspects, such as outlined by T OWNSEND (1993) or S EN (1999).
The necessity for this multidimensional approach is reinforced by the international
acceptance of the need to measure and track progress on all the Millennium
Development Goals, with their dozens of indicators.
However, some simple basic quantitative assessments of poverty have to be
the foundation for further qualitative analysis, for a number of reasons: to assist
stakeholders to better target their poverty reduction strategies nationally (whether byregions, ethnicity, gender, employment characteristics, etc.) and internationally; to beable to assess how much public resources would be required to eliminate poverty or
reduce it to target levels; to evaluate the effectiveness of institutions whose goal it is
to help the poor; to monitor the state of poverty over time, so as to assess the degreeof success or failure of past policies; and to keep the poor and poverty on the agenda,
if poverty is considered a serious enough problem. The basic quantitative resultson poverty, however, need to be consistent with the broader indicators of poverty,
especially in rural and urban relativities.
To obtain the basic robust quantitative results possible and necessary for future
long-term accurate comparisons, the “poor” are usually defined by reference to thebasic needs poverty line (BNPL), which is the monetary value of goods and services
that a household needs to consume as a minimum, so as to achieve what society accepts
as representing a ‘minimum decent standard of living’ for any chosen country.
The basic needs poverty line methodology and the various alternatives practised
throughout the developing world may be read in RAVILLION (1998), WORLD BANK
(2003), THORBECKE (2004), UNITED NATIONS STATISTICS DIVISION (2005) and ASIAN
DEVELOPMENT BANK (2006). The most recent is HAUGHTON and KHANDKER (2009)
also a World Bank publication and extremely relevant to this paper. Most studies
acknowledge that small changes in methodology can result in significant changes in
the assessment of the incidence of poverty amongst different groups within the country(KAKWANI 2003).
The BNPL may be defined in many different ways, broadly categorised into“relative” poverty lines and “absolute” poverty lines. The relative approach defines
the poverty line in relation to some “average” standard of living enjoyed by a society(KAKWANI 2003: 2). But that “average” can also be defined in different ways. One
approach simply sets the value of the BNPL as 50% or 60% of the median4 householdincome of the country.
Of course, such “relative” poverty standards change over time, depending on thechanges in median income, usually the outcome of broad changes affecting the bulk
4 The median is preferred because it is more stable over time than the ‘mean’, which can be affected by the extreme values
at both the upper and lower ends of the income distribution.

28

South Pacific Studies Vol.33, No.1, 2012of the people in the middle classes. Such relative standards will therefore not be usefulfor understanding progress over time. For developed countries, however, this relative
standard is preferred to absolute standards, which as used internationally, usually are so
low as to make the analysis of poverty in developed countries somewhat meaningless,
especially when relative deprivation is the focus.
Absolute standards commonly used at the international level are the US$1 per day5
or US$2 per day at purchasing power parity (or PPP), although there is considerable
debate about its consistency and usefulness within countries, and across countries.
Such international standards, which may be useful for Bangladesh or India, would not
be considered to be appropriate for the Pacific.
For country-specific poverty analysis especially for low to middle income
countries, absolute standards attempt to use the concept of “minimum standards ofliving” based on two components: the food poverty line (FPL) and the non-foodpoverty line (NFPL).
The FPL is the value of a basic basket of foods that are typically consumed by the
population, with the objective of satisfying the minimum nutritional requirements of astandard household, simplified usually to one criterion: 2,100 calories per person perday.
The NFPL is the value of the essential non-food items (such as education, health,transport, rent etc.) required for the subsistence of the household. The BNPL is then thesum of the two components (FPL + NFPL). The incidence of poverty (or head countratio) is then estimated as the proportion of the population in households whose income
is below this BNPL.

Income or Expenditure as the Criterion?
To determine whether a household is “poor” or “not poor”, one may use either
incomes of the household or expenditure. Since the Vanuatu HIES results indicatethat there has been significant under-reporting of incomes (clarified further below), it
is sensible to use household expenditure as the criterion for estimating the incidenceof poverty, as is done by the ADB/UNDP study. There are several other goodreasons for doing so. It is generally held that in developing countries, it is harder toconceal expenditure than income of the poor from the interviewers. Moreover, actual
expenditure is a firmer indication of the realized standard of living than is income.
Nevertheless, there is always the problem that some households may have a highincome, but consciously choose to save more. If the resulting expenditure is lower
than the poverty standard being used, such a household would be labeled “poor” eventhough its potential for expenditure and a higher standard of living could be muchhigher given the higher income.
5 This was originally given as US$1 per capita per day in 1985 US dollars, then revised to US$1.08 in 1993 prices, andUS$1.31 in 2004 prices.

NARSEY: Poverty Analysis in Vanuatu: A Critical Review and Alternative Formulation

29

VNSO (2009) also made the decision to exclude expenditures on kava, alcoholand tobacco as these items were under-reported in the HIES. Unfortunately, excludingthese expenditures would tend to produces a downward bias in the welfare criterion,
and possibly identify some households as “poor” when the HIES data would haveindicated that they are not poor.

Adjusting for Household Size
While economic analysis typically focuses on individuals, poverty analysis
usually uses the “household” as the unit of analysis. It can be argued that their incomes
and total household expenditure is assumed to be collectively and equally enjoyed by
all in the household―adults, children and elderly alike. This may clearly not be thecase, as there can be very unequal internal distribution of resources, linked to gender,
age or the nature of family connection of individuals concerned.6
It is also generally accepted that the standard of living of a household depends notjust on the expenditure enjoyed, but on the number of persons in the household whoneed to be supported by that income. So for ranking purposes, the total expenditure of
the household is usually standardized by adjusting for household size.7
There are different methods of adjusting for household size. The simplest method
is to divide the household expenditure by the number of persons in the household,obtaining the usual ‘expenditure per capita’ measure. This effectively treats each personin the household as requiring equivalent resources. It is, however, thought that children
and the elderly do not normally require as many resources as adults of working age.
Another approach therefore converts the number of persons in the household to ‘adultequivalents’ by some formula. Different formulae are possible in discounting children
and adults.
The UN approach is to treat each child between the ages 0 and 14 as equivalent
to half an adult, and any person over the age of 14 as 1 adult.8 This paper uses the UN
method of calculating adult equivalents because of its widespread use, although it does
have a weakness in that it does not allow for economies of scale, the impact of which
can be significant. This study uses the UN approach and converts total household
expenditure to expenditure pAE, which then reflects that household’s implicit “standardof living”, and is used to rank households from the “poorest” to the “richest”. This has
also been the method followed in the ADB/UNDP analysis of poverty in Vanuatu.
6 It is quite common in the Pacific, for extended family members to be part of the household for long periods of time,often because of better employment opportunities or better health services. Often, too, children are sent to urban families
because of the better schools in urban areas.
7 Many poverty studies in the Pacific have wrongly used ranking of households by total income or total expenditure to
determine “poor” and “non-poor” households.
8 This was the approach used by GOVERNMENT OF FIJI and UNITED NATIONS DEVELOPMENT PROGRAMME (1997).

30South Pacific Studies Vol.33, No.1, 2012

VNSO (2009) Values for the Basic Needs Poverty Lines and the Results
It should first of all be noted that should the same values be used for the basic
needs poverty line (BNPL) for rural Vanuatu, Vila and Luganville, then the incidenceof poverty would be highest for Rural Vanuatu, then for Luganville and then for Vila,in that order―at any BNPL value chosen (Fig. 1). But the ADB/UNDP estimatedvery different FPL and BNPL values for Vila, Luganville and the other islands which
comprise rural Vanuatu (Table 1). Their value for FPL pAE pm for Vila is 1.9 times
that for rural Vanuatu, the value for NFPL pAE pm for Vila is a massive 7.8 times thevalue for rural Vanuatu, and the eventual BNPL pAE pm value for Vila is 3.3 times thatfor rural Vanuatu (last row of Table 1).

Fig. 1. Head count ratio or the incidence of poverty at the same basic needs poverty line (BNPL) value (%).

Table 1. The ADB/UNDP estimates of values for food poverty lines pAE pm, non-food poverty lines pAE
pm and basic needs poverty lines pAE pm.
Food poverty linepAE pmNon-food poverty
line pAE pm

Basic needs poverty
line pAE pm

Rural
Luganville

2589
3594

777
2516

3366
6110

Vila
VanuatuVila:Rural ratio

5034
3064
1.9

6041
1651
7.8

11075
4715
3.3

Area

NARSEY: Poverty Analysis in Vanuatu: A Critical Review and Alternative Formulation

31

Table 2. ADB/UNDP results for head count ratio or percentage of population
below the values for BNPL pAE pm as in Table 1.
Area

Head count ratio or percentage of population
below the values for BNPL pAE pm

Rural Vanuatu
Luganville

11%
11%

Vila
Vanuatu33%
16%

It is not surprising, therefore, that with such relatively high FPL, NFPL and BNPL
values for Vila, the head count ratios or the incidence of poverty estimated by the ADB/UNDP study is much higher for Vila than it is for rural Vanuatu. Table 2 indicates thatthe head count ratio was estimated by ADB/UNDP as about 11% for rural Vanuatu andLuganville, while that for Vila was estimated at 33%. The national estimate of the headcount ratio was then seen as 16%.9
These results are quite anomalous given that the general understanding ofstandards of living in Vanuatu are that rural areas are extremely poor compared to urban
areas. One indicator is the continued rural-urban migration. The more important reason
for concern arises out of the implication for the sharing of poverty alleviation resources
between rural and urban areas. While not estimated by the ADB/UNDP report, thepoverty gap estimates will also give a disproportionate share of poverty alleviation
resources to urban households and less to rural households. This must inevitably
worsen the rural-urban migration by making urban areas even more attractive.
It is extremely important for poverty alleviation policies, therefore, that theincidence of poverty estimates and the methodology be examined very critically toensure that the results are indeed appropriate and may be used for poverty alleviation
policies. This paper argues that both the methodology used to estimate the food poverty
lines and the non-food poverty lines (and hence the basic needs poverty lines) areinappropriate, leading to incorrect results.

Why the Significant Differences in Food Poverty Line Values?
Why would the food poverty line value for Vila be estimated at almost twice thatof rural Vanuatu? While lower rural food prices for domestically produced foods may
be part of the explanation, this is unfortunately not enough, since the prices of bought
food items (mostly imported) are higher in the rural areas.
The most sensible method of estimating the FPL value is by first drawing up a
weekly or two-weekly menu (for urban areas and rural areas separately) for a typical
9 It would seem that the ADB/UNDP study used the weighted BNPL values for rural Vanuatu, Luganville and Vila, toarrive at a “national estimate” for the BNPL. Unfortunately, the resulting head count ratio of 16% is inconsistent withthe more correct method of estimating the number of “poor” people in Vanuatu, by aggregating the poor people in Vila,
Luganville and Rural Vanuatu, and taking that as a proportion of the total population. This latter value comes to 14%.

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South Pacific Studies Vol.33, No.1, 2012

household (of say four adult equivalents) comprising a basket of foods that delivers aminimum nutritional content. The menu should be such as not to reflect what would be
consumed by the middle classes or the affluent, nor the absolutely poverty stricken: i.e.
it should represent what the society considers as comprising a minimum decent diet forthe poor.10 Such a menu would then be costed in local prices and divided by 4 to obtainthe food poverty line value per adult equivalent. The ADB/UNDP study did not takethis approach for Vanuatu.
The massive differences in FPL values are explained largely by the methodology
adopted by the VNSO (2009) study for estimating the FPL values (VNSO 2009: 2526). While there is discussion in the report about the ideal starting point being a model
menu of basic food items, this approach is not taken, although there is a passing
reference to another study, with a similar methodology, for the Solomon Islands
supposedly finding no difference with the “model menu” approach.11
The VNSO (2009) study proceeded as follows in an extremely complicatedfashion (quoting directly from the report):
 “ The food expenditure from the diaries of households in the lowest three
expenditure deciles in each of the regions was analysed; all the food expenditures
were then converted into per capita adult equivalent values and per capita adultequivalent daily cost of these diary expenditure items; the reported diary foodexpenditure values were grossed up to the total recorded food; expenditure from thesurvey for the bottom three expenditure deciles, by the appropriate; factor to givea notional total food expenditure based on the listed items; each item was priced
using the urban CPI for all purchased items adjusted for home produced items,
and the observed diary prices/values for items of own production; the implied unit
volume consumed of each item in the diary was calculated; the Kcal (energy) value
from the South Pacific Food Composition Tables was applied to each of the items
to give a total Kcal value for recorded consumption; the daily per capita adultequivalent Kcal consumption values represented by each item was then calculated;the daily cost of each item according to its share in the overall daily food intake wasestimated; and finally, the daily cost of each item according to its Kcal value per day
per a.e. was estimated.”
The results are summarised here in Table 3. There is very little difference in thecosts per day per adult equivalent between rural Vanuatu (102 vatu), Luganville (125vatu) and Vila (114 vatu). However, it is the second column of resulting K Cals thatbrings about the sharp differences: rural Vanuatu food consumption resulted in 2,470
K Cals per adult equivalent, while the Vila food consumption resulted in only 1,431 K
Cals. With the ideal or minimum consumption objective being 2,100 K Cals per adult
10 Of course, there has to be much subjectivity about this. Such concerns can only be decided by ‘social consensus’
amongst all the stakeholders.
11 A detailed reading of the report on the Solomon Islands finds little justification for this claim.

NARSEY: Poverty Analysis in Vanuatu: A Critical Review and Alternative Formulation

33

Table 3. Derivation of food poverty line values.
Area
Rural Vanuatu
LuganvillePort Vila

Cost per daypAE (vatu)
102
125
114

K CalsScale factor

2470
2193
1431

0.85
0.96
1.47

FPL per daypAE (vatu)
86
120
168

FPL pAE pm(vatu)
2589
3594
5034

Source: ADB/UNDP report.

equivalent, the ADB/UNDP study then took a really questionable step of scaling down
the rural cost by 0.85 to arrive at a FPL per month value of 2,589 vatu; while the Vilacost was scaled upwards by a factor of 1.47 to arrive at a FPL per AE month value of
5,034 vatu.
One needs to ask why the Vila food consumption would result in such low K
Cal values while the rural consumption resulted in relatively higher values. From theTables given in the report, the urban people in Luganville (ADB/UNDP report, p. 28,
Table 15) and Vila (ADB/UNDP report, p.29, Table 16) were purchasing relatively
more foods which would not normally be considered “basic food items” and whichhave much lower food value, while the converse was true for rural Vanuatu (ADB/
UNDP report, Table 14). This methodology effectively “rewards” bad urban foodconsumption patterns by increasing their FPL values, while it “penalizes” the rural
good consumption patterns by reducing the FPL values. This methodology is theantithesis of the “model menu” method of determining the food poverty line values,
contrary to the claim that the two methods produce similar results.
The net result of the ADB/UNDP methodology seems to be that the FPL estimatesfor Vila and Luganville are significantly biased upwards in comparison to the estimatesfor rural Vanuatu. This must inevitably push upwards the values of the BNPL and theestimated incidence of poverty for Vila and Luganville, or conversely, push it lower forrural Vanuatu.
The contradiction in the ADB/UNDP methodology may be seen in its statement inparagraph 72 where it states:
 “ Table 17 indicates that a household in the lowest three expenditure deciles living
in Port Vila would need to“ spend” considerably more on food, VT24,163 per month,compared to a similar bottom three decile household in rural areas, VT11,392; 47%
the value of Port Vila. This reflects the higher basic FPL in Port Vila (VT168 p.c.a.e.
per day) compared with rural areas, VT86 p.c.a.e. per day, as well as the larger
household size in Port Vila (4.8 persons a.e) compared to rural areas (4.4 personsa.e), see also Table 1. The amounts required to be “spent” on food include both thepurchased items and those non-cash items of consumption of own produce.”
Yet the VNSO (2009) own data on actual food expenditure shows for the bottom
3 deciles, the monthly household food expenditures were (Table 8 in the ADB/UNDP
report):34

South Pacific Studies Vol.33, No.1, 2012

Rural Vanuatu:
Luganville:Vila:

14,701 vatu;
18,450 vatu;
18,490 vatu.

These are differences of a mere 25% - not 100% as indicated by the FPL values. Thevery large differences in the FPL values between rural and urban Vanuatu are therefore
extremely inappropriate, and logically lead to over-estimated values for the BNPL
for urban Vanuatu, and hence, result in the inappropriately high incidence of poverty
results for Vila and Luganville.
A minor point may also be made that when the consumption patterns of the bottom
3 deciles of rural and urban households are used to derive FPL values, the implicit
assumption is that they are equivalent in standards of living. This may be true in somesocieties where the gap between rural and urban households is not large. This would
not be true in countries like Vanuatu where the gaps appear to be very large indeed
and where the bottom 3 deciles of rural Vanuatu would almost definitely be amongst
the poorest of the poor, while the bottom 3 deciles in urban areas may be consideredrelatively better off. It is then necessary to ask what ought to be more appropriate
values for the FPL in urban and rural Vanuatu. This question is addressed towards theend of this paper.

Why Such Large Differences in Non-Food Poverty Line Values
As the VNSO (2009) states, “the costs of non-food basic needs might include
expenditure for housing/shelter, essential transport and communications, school feesand other education related costs, medical expenses and clothing.” Certainly, housing
costs would be lower in rural areas. However, virtually all other costs would be justas high or even higher. VNSO (2009) adopts one of the World Bank approaches andmultiplies the FPL values derived earlier, by a “factor” to give the non-food basic
needs values. The report states that “For this analysis and to be consistent with otheranalyses undertaken for Pacific Island countries the average non-food expenditure forhouseholds in the lowest four deciles is taken as the non-food factor” (p.31). These
factors, and the derivation of the basic needs poverty lines are given here in Table 4.
Table 4. Derivation of non-food poverty lines (NFPL) and basic needs poverty lines (BNPL).
Area
Rural
Luganville
Vila
Vanuatu total
Vila:Rural ratio

FPL pAE
2589
3594

Rate up factor
0.30
0.70

NFPL pAE
777
2516

BNPL pAE
3366
6110

5034
3064
1.9

1.20
0.54

6041
1651
7.8

11075
4715
3.3

Source: ADB/UNDP report, Table 18, p.31.

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35

There are a number of questions that may be raised about this whole methodology.
First, the comparison of the bottom four decile ratios of Vila with the bottom fourof the rural households assumes implicitly that they have similar standards of living:when they clearly may not. Second, the ADB/UNDP report applies the actual non-foodto food ratios derived from the bottom four deciles, to the estimated FPL values whose
Vila-Rural ratios are about 2. In reality, the HIES data reveals that the food expenditure
per adult equivalent ratio between Vila and Rural households, is a mere 1.1.
It is not surprising therefore that the resulting NFPL values for Vila and rural
households results in an incredibly large ratio of 7.8 to 1, giving a grossly inflated value
for Vila and a grossly deflated value for rural Vanuatu. This may be contrasted with theactual Vila:rural ratios for non-food per adult equivalent of only around 4.
It may be noted that the low NFPL pAE value of a mere 777 vatu per month iswhat would be spent by a household just at the margin of the first and second deciles inrural Vanuatu, while the actual average for the bottom 4 deciles is 1,230 vatu (Table 5).
Conversely, what is derived for Vila (6,041 vatu) is roughly what is actually spent byhouseholds at the bottom of the third decile in Vila, while the actual average for thebottom four deciles is a lower 5,449 vatu.
The relatively high values derived for the non-food poverty lines for Vila andLuganville, or conversely the relatively low figures used for rural households, are notjustified even by actual expenditure patterns. What is really a symptom of poverty (i.e.
low expenditures on non-food items) is being used by the ADB/UNDP as the standard
for poverty. While some reference decile value has to be used, there is a need to ensurethat the regional differences do not depart significantly from the actual values thatprevail on the ground.
Table 5. Non-food expenditure per adult equivalent (vatu) (for regional deciles of households).
RHHDecLuganvillePort Vila

Rural

Vila:Rural
ratio

RHD1
RHD2

1604
2931

2231
4484

558
1042

4.0
4.3

RHD3

3920

6497

1576

4.1

RHD4

5004

8910

1874

4.8

RHD5

6501

11360

2361

4.8

RHD6

8477

12304

3089

4.0

RHD7

10147

17208

3689

4.7

RHD8

13243

20306

5067

4.0

RHD9
RHDt

20641
42073

29653
69616

9249
21364

3.2
3.3

All
Lower 4D

9990
3322

14985
5449

4332
1230

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South Pacific Studies Vol.33, No.1, 2012

World Bank Warnings against the Food Energy Intake Method
It is interesting that while VNSO (2009) states that they are using World Bank
methodology in poverty analysis, a most recent World Bank publication by HAUGHTON
and KHANDKER (2009) advises very clearly that “Unfortunately, the food energy intake
method is seriously flawed, and should not be used for comparisons across time, oracross regions, or between urban and rural areas, unless the alternatives are infeasible.”
HAUGHTON and KHANDKER (2009) referred to extremely relevant findings by
R AVALLION and B IDANI (1994), who computed headcount poverty measures forIndonesia using the SUSENAS (Indonesia’s National Socioeconomic Survey) data for
1990, using both the cost of basic needs and the food energy intake methods. The moststriking finding was that “while the cost of basic needs method shows rural poverty to
be more than twice as great as urban poverty, the food energy intake method indicates(implausibly) that poverty is higher in urban than in rural areas.” The major problem
was the differences between rural and urban areas in the composition of food being
consumed.
HAUGHTON and KHANDKER noted (2009: 56-59): “Rural households can obtainfood more cheaply, both because food is typically less expensive in rural areas and also
because they are more willing to consume foodstuffs that are cheaper per calorie (suchas cassava rather than rice); urban consumers are more likely to buy higher quality
foodstuffs, which raises the cost per calorie.” Hence, for a given level of food energy
intake, the poverty line in the rural area will be lower than in the urban area. This was
not a problem if it only reflected the differences in the cost of living. But if the gap
exceeds the differences in the cost of living, then urban poverty can appear to be higher
than rural poverty: “a completely implausible result.” This was precisely the problem
with VNSO (2009) for Vanuatu.12

Indirect Indicators of Deciles Affected by Poverty
The basic quantitative analysis of poverty focuses on BNPL values which areused to separate the “poor” from the “not poor”. However, there are many indicatorsof poverty, given there is consensus now that poverty needs to be defined in
multidimensional ways, not just as the “inequality of conditions”, but as “inequalityof opportunities and capabilities” (SEN 1999). Thus TOWNSEND (1993: 36) defined
it as “relative deprivation” where a poor person “cannot obtain, at all or sufficiently,
the conditions of life-that is, the diets, amenities, standards and services ―whichallow them to play the roles, participate in the relationships and follow the customary
behaviour which is expected of them by virtue of their membership of society” (i.e.
12 Effectively, VNSO (2009) used the food energy intake method while articulating their methodology as a “cost of basic
needs” approach.

NARSEY: Poverty Analysis in Vanuatu: A Critical Review and Alternative Formulation37

deprivation not just at work, but also at home, in the neighbourhood, travel and all
arenas for the fulfilment of social obligations). Such thinking permeates the policies ofinternational and regional organisations that set the global and national poverty agenda.
Thus, one could examine at which deciles there begin to be increases in expenditure
on discretionary items, which on a priori grounds are equally valued in urban and rural
areas. The items of expenditure examined here are education, health, clothing, alcoholand tobacco, and non-essential items.

Fig. 2. Non-food expenditure per adult equivalent per month.

Fig. 3. Expenditure per AE pm on household items.

38South Pacific Studies Vol.33, No.1, 2012

Fig. 4. Medicine expenditure per AE pm.

Fig. 5. Education expenditure per 6 to 20 year old (vatu).

Fig. 6. Expenditure on alcohol and tobacco per AE pm.

NARSEY: Poverty Analysis in Vanuatu: A Critical Review and Alternative Formulation

39

Fig. 7. Expenditure pAE pm on junk food.

Figure 2 gives the non-food expenditure per adult equivalent per month byregional deciles of population.13 It is evident that in rural Vanuatu, the values are flatright up to the 7th decile, and the large increases begin from the 8th decile onwards. In
Vila, the large increases begin right from the first decile, with larger increases taking
place after the 7th decile. One can see that the non-food expenditure (which does
not include any home or subsistence consumption) at the 8th decile in rural Vanuatu,
barely matches that of the 3rd decile in Vila. Figure 3 (expenditure on household items)
follows the same patterns as for total non-food expenditure.
Figure 4 indicates that Vila households begin to increase their expenditure on
medicine after the 6th decile while that in rural Vanuatu begins to increase after the 8th
decile. Figure 5 indicates that while education expenditure per 6 to 20 year old begins
to rise steadily from the 1st decile in Vila, the increase in rural areas does not begin tillafter the 7th decile. Figure 6 gives the graph for alcohol and tobacco products, and Fig.
7 for junk food expenditures. These all indicate that large increases in consumption in
Vila occurs some 3 to 4 deciles lower than the levels in rural areas. Similar trends may
be seen in expenditures on health, personal care items, and virtually all main non-food
expenditure items, suggesting that decile for decile, rural Vanuatu is much poorer in“standards of living” than in Vila.
It is extremely anomalous therefore to have incidence of poverty or head countratio results, which suggest that poverty in Vila is three times higher than that in rural
Vanuatu. All other indicators suggest that rural poverty is far more extreme than urban
poverty. The above results might also suggest that it is not correct to take the non-foodpoverty line values from the same sets of deciles in Vila and rural Vanuatu.

13 There are deciles of population estimated separately for rural Vanuatu and for Vila. The patterns are very similar for
Luganville, which is left out to simplify the graphs.

40South Pacific Studies Vol.33, No.1, 2012

Might There Be More Appropriate Values for FPL, NFPL and BNPL?
It is suggested here that local poverty stakeholders need to estimate more
appropriate values for the food poverty lines (FPL), non-food poverty lines (NFPL)
and basic needs poverty lines (BNPL). It is suggested that the food poverty line values
be estimated by selecting food baskets that are “appropriate” for households who are
not in utter poverty and who are not well-off either. Of course, choosing ‘appropriate’
food baskets is easier said than done. Ideally, there should be some consensus amongst
poverty stakeholders in Vanuatu for what items should comprise such a food basket.
Such food baskets must be checked through a proper menu approach designed for ruraland urban Vanuatu, and properly costed at local prices. Table 6 here gives a simulationof what a possible FPL basket for rural and urban Vanuatu might look like. This
simulation is based on quantities consumed by rural and urban Melanesian Fijians,
adapted to the diets of rural and urban Ni-Vanuatu, and using the prices that were usedin the ADB/UNDP study. This results in the FPL values given in Table 7 with an ruralurban ratio of around 1.5 as opposed to the ratio of around 2 for the FPL values used by
the ADB/UNDP study.
Then there needs to be consensus on what would be appropriate dollar values forthe non-food poverty lines, again differentiated between rural and urban Vanuatu. It
needs to be kept in mind that while there will be differences due to differences in costsof housing and transport, that used to represent education, health, clothing etc, ought
to be of similar magnitudes given that rural people’s needs in these areas are as equallyintense as urban peoples’ needs. The mistake should not be made of using actual low
expenditures in rural areas that arise out of lack of cash income, as the standard tojudge poverty in rural areas. Just for rough estimation, I use here the values for the
NFPL given in Table 7, with the rural NFPL set arbitrarily at just 60% of the urban
NFPL.
As usual, the sum of the two (FPL + NFPL) gives the simulated BNPL values.
These values, used on rankings by expenditure per adult equivalent per month, give therural incidence of poverty as 41%, which is somewhat higher than the urban estimateof around 33%.
Vanuatu stakeholders in poverty might wish to use their own model menus toconstruct more appropriate food poverty line baskets which may be costed using urban
and rural prices. They may also reach consensus on what ought to be appropriate nonfood poverty line values to be used for rural and urban Vanuatu.
It should be noted that there needs to be consensus amongst all the stakeholders
in reaching appropriate values for the basic needs poverty lines, as there are significant
implications for policy on allocations of poverty alleviation resources (both in termsof total quantity and distribution between rural and urban areas, and between different
island groups), as well as for other policy areas such as minimum wages guidelines tobe advised by the government. The experience of Fiji has been that when minimum

NARSEY: Poverty Analysis in Vanuatu: A Critical Review and Alternative Formulation

41

Table 6. Simulation using Vanuatu foods and Fijian Urban and Rural menus for 2 weeks for family of four
adult equivalents.
Vila
Price/unit
ROOTCROPS
Island taro
Bananas cooking
ManiocYam
KumalaLaplapWater taro
Breadfruit
Menu total
CEREALS
Rice
Bread
Noodles
Doughnuts
Flour
Biscuits buns
Menu total
Cereals plus root crops total
MEATS
Chicken local
Tinned tuna
Beef
Reef fish
Menu total
VEGETABLES
Island cabbage
Coconut/copra
Tomatoes
Bowl cabbage
OnionsCarrots
Peanuts
Chinese cabbage
Menu total
FRUIT
Pawpaws
Green coconut
BananasMenu total
CONDIMENTS
Sugar
Salt
Soft drink
Menu total
OILS/FATS
Butter/magerine
Cooking oil
Menu total
Cost for 4 AE per week
Cost of FPL for 1 AE per month
Arbitrary NFPL pAE pm
BNPL pAE pm

70
58
45
96
70
300
167

Vila
Unit

Vila
Qtty Kg

Vila
Cost

Rural
Price/unit

Rural
Unit

Rural
Qtty kg

Rural
Cost

1
1
1
1
1
1
1

2
2
2
1
2
1
1

140
116
90
96
140
300
167

55
35
25
60
35
100
65
50

1
1
1
1
1
1
1
1

4
3
3
3
1
1
1
1
17

220
105
75
180
35
100
65
50
830

11

1049

119
100
38
30
100
198

1
1
0.09
0.1
1
0.25

6
3
0.27
0.3
2
0.5
12.1
23.1

714
300
10
9
200
99
1332

133
250
45
30
150
180

1
1
0.09
0.1
1
0.25

3
1
0.09
0.3
2
0.75
7
24.1

399
250
4.05
9
300
135
1097

600
110
415
450

1
0.35
1
1

1
0.7
1
1
3.7

600
77
415
450
1542

200
180
200
250

1
0.35
1
1

1
0.7
1
1
3.7

200
126
200
250
776

58
28
443
300
176
200
200
200

1
1
1
1
1
1
1
1

1
1
1
1
1
1
1
1
8

58
28
443
300
176
200
200
200
1605

35
30
100
100
250

1
1
1
1
1

35
30
100
100
250

200
150

1
1

1
1
1
1
1
1
1
1
8

200
150
865

68
27
60

1
1
1

1
1
1
3

68
27
60
155

30
25
60

1
1
1

1
1
1
3

30
25
60
115

113
188
172

1
1
1

1
0.25
1

113
47
172
332

180
200
200

1
1
0.35

1
0.25
0.35

180
50
70
300

181
267

0.25
1

0.25
1

45
267
312
6328
6779
5000
11779

250
250

0.25
1

0.25
1

63
250
313
4296
4602
3000
7602

42

South Pacific Studies Vol.33, No.1, 2012

Table 7. Simulated values for FPL, NFPL, BNPL and resulting incidence ofpoverty for rural and urban Vanuatu using expenditure pAE.
FPL pAE pm (vatu)
NFPL pAE pm (vatu)

Rural
4602
3000

Urban
6779
5000

BNPL pAE pm (vatu)

7602

11779

Incidence of poverty byexpenditure pAE pm (%)

41%

33%

wages guidelines are set, there is usually strong reaction from affected employers thatthe BNPL values are too high. Government usually then has to justify the values used
for the FPL, NFPL, and the BNPL. The ADB/UNDP approach would be a nightmare
to explain to poverty stakeholders in Vanuatu. The “model menu” approach is far more
understandable and transparent, as any objectors could be asked to suggest what they
think a model menu ought to be that costs less in Vanuatu.

Implications for Poverty Alleviation Policies
While the criticisms above may seem like a purely academic exercise,
unfortunately, the results have a very strong bearing on policy guidelines for resources
allocation for the alleviation of poverty in Vanuatu. VNSO (2009) estimates theincidence of poverty (head count ratio). It also has a Table 20 (p.33) which estimates
the poverty gap index (depth of poverty) and squared poverty gap (severity of poverty)
as follows:
Poverty gap index14
Vila
10.4
Luganville
2.9
Rural
3.8

Squared poverty gap15
5.1
1.2
2.0

Both these indicators would suggest that Vila requires much greater attention forpoverty alleviation and resources, than does rural Vanuatu. This is again questionable.
One statistic that poverty analysts must estimate, and was not done by VNSO
(2009), is the approximate value of the “poverty gaps” and their distribution around thecountry. For any household, the “poverty gap” is the difference between their actual
household income per adult equivalent and the basic needs poverty line relevant forthat household―in other words the dollar value which would be required to raise that
14 VNSO (2009) (p.33): “The formula calculates the mean distance below the basic needs poverty line as a proportionof the poverty line where the mean is taken over the whole population, counting the non-poor as having zero poverty
gap.”
15 VNSO (2009) (p.33): “Through the process of squaring the index the SPGI gives greater weight to those at the lowest
consumption/income levels and thus better reflects the severity of the poverty gap.”

NARSEY: Poverty Analysis in Vanuatu: A Critical Review and Alternative Formulation

43

household to reach the BNPL. Some households will be just below the BNPL andrequire little resources, while others may be well below the BNPL and require larger
resources.
When these individual household poverty gaps are added up for each grouping(urban/rural, islands, etc.), the results give an objective guideline to national poverty
stakeholders as to the appropriate proportions of sharing of poverty alleviation
resources, based purely on “need”. Such guidelines, devised by neutral economists
or HIES specialists, can go a long way towards reducing the political tensions that
inevitably arise over questions of the sharing of development or poverty alleviation
resources and projects.
Given the VNSO (2009), what would the poverty gap results suggest for thenational sharing of resources? Table 8 gives some estimates using the ADB/UNDP
values for the basic needs poverty lines, as well as estimates using the author’s
simulations. Naturally, the choices of the BNPL values will determine how muchpoverty alleviation resources will be required in vatu terms. The ADB/UNDP values
for the BNPL result in a total resource requirement of about 599 million vatu orroughly 1.2% of Vanuatu’s GDP in 2006. The poverty gap estimates using the author’s
BNPL values, result in a much higher estimate of 2,461 million vatu or 5.1% of GDP,quite understandable given that the author’s BNPL values for rural households is muchhigher than that used by the ADB/UNDP study. The former poverty alleviation target
would be considered manageable, while the latter would not. This significant differencein national resource requirements for poverty alleviation (5.1% of GDP as opposed to
1.2% of GDP) emphasises how important it is to ensure that the values selected forpoverty lines are sensibly chosen and in line with national conditions.

Table 8. Estimates of poverty gaps and sharing of poverty alleviation resources for Vanuatu (by province).
Using ADB/UNDP study
BNPLs

Using author’s simulation of BNPLs

Province

Poverty gap(m vatu)Perc. share

Poverty gap(m vatu)

Luganville

18

3

185

8

Malampa

16

3

273

11

Perc. share

Penama

17

3

233

9

Port Vila

386

64

463

19

Sanma Rural

7

1

201

8

Shefa Rural

54

9

353

14

Tafea

78

13

564

23

Torba

23

4

189

8

Vanuatu

599

100

2461

100

Urban

404

67

648

26

Rural

195

33

1813

74

44

South Pacific Studies Vol.33, No.1, 2012

Table 9. Incidence of poverty for different values of BNPL pAE pm (by provinces).
BNPL pAE pm*
3000-3100
3100-3200
3200-3300
3300-3400
3400-3500
3500-3600
3600-3700
3700-3800
3800-3900
3900-4000
4000-4100
4100-4200
4200-4300
4300-4400
4400-4500
4500-4600
4600-4700
4700-4800
4800-4900
4900-5000
5000-5100
5100-5200
5200-5300
5300-5400
5400-5500
5500-5600
5600-5700
5700-5800
5800-5900
5900-6000
6000-6100
6100-6200
6200-6300
6300-6400
6400-6500
6500-6600
6600-6700
6700-6800
6800-6900
6900-7000
7000-7100
7100-7200
7200-7300
7300-7400
7400-7500
7500-7600
7600-7700
7700-7800
7800-7900
7900-8000

Torba
20.0
21.2
22.2
23.2
24.4
26.4
28.0
28.7
29.5
29.9
30.9
31.6
32.4
33.6
35.9
37.2
38.2
39.1
39.9
41.2
41.9
43.3
43.7
44.5
45.8
47.0
47.4
48.6
49.3
50.0
51.3
53.1
53.4
54.4
55.4
55.7
56.3
57.1
57.6
58.3
59.7
60.4
61.2
61.8
63.3
64.2
64.7
65.1
65.3
67.1

Sanma
2.7
4.0
4.4
4.4
4.7
4.7
5.0
5.0
5.7
6.1
6.6
7.1
7.6
8.4
9.6
9.8
10.4
10.4
11.8
13.7
14.0
15.2
15.9
16.4
17.4
18.2
19.6
20.7
21.4
22.1
22.8
23.5
24.4
25.1
25.9
26.6
27.1
28.3
29.1
30.4
32.7
34.9
36.2
37.0
38.2
39.2
40.9
42.2
43.2
44.4

Malampa Penama
4.5
3.5
4.6
3.8
4.9
3.8
5.2
3.9
5.5
4.3
5.9
4.9
6.6
5.6
7.7
5.6
8.5
6.3
9.4
6.7
10.1
7.3
11.8
7.6
12.5
8.2
13.6
8.7
15.1
9.4
15.3
10.4
15.7
11.0
16.2
11.2
17.1
12.2
17.5
12.4
18.4
12.7
18.9
13.8
19.6
14.8
20.0
16.2
20.5
17.1
21.0
17.1
21.1
17.5
22.1
18.7
23.3
19.8
24.0
20.4
24.6
21.3
25.3
22.0
26.2
23.6
27.0
23.8
27.5
23.9
28.2
24.8
28.8
25.0
29.4
25.3
30.5
26.0
30.8
26.6
31.5
27.3
32.0
28.3
32.4
28.9
33.0
29.1
34.1
29.9
34.8
30.8
35.5
32.2
37.2
33.0
38.1
33.3
38.9
34.2

Shefa
13.6
14.2
14.5
15.1
15.3
15.6
15.7
17.1
17.4
17.9
18.8
18.8
19.6
20.7
20.9
21.2
21.5
22.0
22.4
23.0
23.0
23.3
24.4
25.5
25.8
25.8
26.6
27.6
28.1
29.4
30.1
30.2
30.9
31.7
33.4
33.5
34.2
35.5
35.8
36.8
37.1
38.4
38.8
39.5
40.5
41.1
41.5
42.1
43.6
44.7

Tafea
16.4
16.8
17.1
18.1
18.9
19.3
20.2
21.0
22.1
22.5
23.0
23.7
24.8
24.9
25.1
26.7
27.0
29.2
30.9
32.2
32.4
33.6
34.5
35.7
36.1
37.4
38.2
39.2
40.3
41.2
41.4
42.0
42.7
43.6
44.9
45.5
45.9
47.8
48.3
48.8
49.4
49.6
50.2
50.6
51.6
52.3
52.3
53.3
53.8
54.6

Luganville Port Vila Vanuatu
1.8
1.9
7.4
1.8
1.9
7.9
1.8
1.9
8.1
2.1
2.4
8.6
2.1
2.4
8.9
2.5
2.4
9.3
2.5
3.0
9.9
2.7
3.2
10.5
2.7
3.2
11.0
2.7
3.2
11.4
2.9
3.2
11.9
2.9
3.2
12.5
3.2
3.2
13.1
4.2
3.5
13.8
4.7
3.7
14.5
5.0
3.7
15.1
5.4
4.4
15.6
5.9
4.7
16.2
5.9
5.1
17.1
6.5
5.5
17.9
6.5
5.8
18.3
6.8
6.1
19.0
7.1
6.1
19.7
7.1
6.9
20.6
7.6
7.2
21.2
8.3
7.2
21.6
8.7
7.2
22.2
8.9
7.2
23.0
8.9
8.4
24.0
9.9
8.6
24.7
9.9
8.9
25.2
10.7
8.9
25.8
10.7
9.2
26.5
11.3
10.3
27.3
12.1
10.3
28.0
12.3
10.3
28.5
13.5
10.7
29.0
13.5
10.9
29.9
14.4
11.6
30.5
15.1
12.3
31.3
16.4
12.6
32.1
16.7
13.8
33.1
16.7
13.8
33.6
17.4
13.8
34.0
18.8
14.5
35.0
19.6
15.4
35.8
19.8
16.3
36.6
20.0
16.3
37.4
21.1
16.3
38.1
21.4
17.4
39.1

Rural
9.0
9.5
9.8
10.3
10.7
11.2
11.8
12.5
13.2
13.7
14.4
15.1
15.8
16.5
17.4
18.1
18.6
19.3
20.4
21.3
21.6
22.6
23.4
24.3
25.0
25.5
26.2
27.3
28.2
29.0
29.7
30.3
31.2
31.9
32.8
33.4
33.9
34.9
35.6
36.3
37.2
38.2
38.8
39.4
40.4
41.2
42.0
43.1
43.8
44.8

* To obtain BNPL values for a standard household of four adult equivalents per month, multiply the first column by 4.

NARSEY: Poverty Analysis in Vanuatu: A Critical Review and Alternative Formulation

45

Table 9. Continued.
BNPL pAE pm*

Torba

Sanma Malampa Penama

Shefa

Tafea

8000-8100

67.8

46.2

40.3

35.0

45.1

54.8

Luganville Port Vila Vanuatu
22.3

17.4

39.8

Rural
45.7

8100-8200

68.9

46.6

40.6

35.8

45.3

54.8

22.9

17.5

40.2

46.1

8200-8300

69.6

47.7

41.1

36.7

46.1

55.5

24.1

17.8

40.9

46.9

8300-8400

69.8

48.5

42.2

38.4

46.8

56.0

24.7

18.3

41.7

47.8

8400-8500

70.8

49.1

42.9

38.9

46.8

57.0

25.3

18.4

42.3

48.4

8500-8600

71.4

50.2

43.3

39.8

47.4

57.7

26.2

18.4

42.9

49.1

8600-8700

72.1

50.7

43.7

39.8

47.7

58.8

26.3

19.3

43.4

49.6

8700-8800

72.5

51.9

44.0

40.8

48.4

60.2

26.7

19.7

44.2

50.5

8800-8900

72.5

53.3

44.6

41.1

49.1

60.9

27.7

20.0

44.8

51.2

8900-9000

72.5

53.8

45.3

41.4

49.3

62.0

27.7

21.3

45.5

51.7

9000-9100

73.1

54.3

45.9

43.0

49.3

62.4

27.7

22.7

46.2

52.4

9100-9200

73.1

55.0

47.2

44.2

50.0

63.1

28.8

23.8

47.1

53.2

9200-9300

74.3

55.7

47.6

45.2

50.0

63.8

29.6

23.8

47.6

53.8

9300-9400

75.0

55.9

48.0

45.3

50.0

64.4

30.5

24.5

48.0

54.1

9400-9500

75.0

56.9

49.4

45.7

50.8

64.5

30.7

24.5

48.6

54.8

9500-9600

76.6

57.3

49.4

46.8

52.0

64.9

31.3

25.0

49.2

55.5

9600-9700

76.6

57.8

50.1

47.0

52.2

65.2

31.8

25.0

49.5

55.8

9700-9800

77.1

57.9

50.2

47.0

52.2

65.6

32.6

25.3

49.7

56.0

9800-9900

77.3

58.4

51.3

47.6

52.4

66.2

32.9

25.6

50.3

56.6

9900-10000

77.7

59.2

52.0

48.5

52.8

66.4

33.5

25.8

50.8

57.2

10000-10100

78.2

60.0

52.6

49.4

53.9

66.4

34.5

26.2

51.4

57.8

10100-10200

78.2

60.9

53.3

50.4

55.1

66.9

34.5

26.7

52.1

58.6

10200-10300

78.7

61.3

53.7

51.0

55.3

66.9

34.8

26.8

52.4

58.9

10300-10400

79.2

62.5

53.9

51.9

55.4

67.3

35.6

27.3

53.0

59.5

10400-10500

79.8

63.3

54.2

52.6

55.6

68.3

35.8

27.4

53.4

60.0

10500-10600

80.0

64.1

54.8

53.6

55.9

68.3

36.0

28.4

54.0

60.6

10600-10700

80.1

64.2

55.2

54.7

56.5

68.7

36.1

29.2

54.5

61.1

10700-10800

80.6

64.5

56.1

55.1

57.1

69.0

38.0

29.4

55.1

61.6

10800-10900

81.0

65.0

56.4

55.9

57.1

69.1

38.3

29.8

55.4

61.9

10900-11000

81.4

65.9

56.4

56.2

57.7

69.5

38.5

30.8

55.9

62.4

11000-11100

81.8

66.9

56.7

56.5

57.7

70.0

39.6

30.8

56.3

62.8

11100-11200

82.5

67.6

57.3

57.8

58.0

70.5

40.3

31.6

57.0

63.4

11200-11300

83.0

68.1

57.8

57.8

58.5

71.0

41.4

32.2

57.5

63.8

11300-11400

83.8

68.8

58.8

58.7

59.0

71.4

41.9

32.2

58.0

64.5
64.9

11400-11500

83.9

69.6

58.9

58.9

59.7

71.6

42.7

32.8

58.5

11500-11600

84.9

70.3

59.1

59.8

60.2

71.9

42.7

32.8

58.9

65.5

11600-11700

85.2

70.7

59.5

59.9

61.2

71.9

42.9

32.8

59.2

65.8

11700-11800

85.4

71.4

59.8

60.9

62.1

73.4

43.2

32.8

59.9

66.7

11800-11900

86.0

71.5

60.2

61.0

62.7

74.0

43.2

33.6

60.3

67.0

11900-12000

86.0

71.9

60.2

61.2

63.3

74.2

43.8

34.0

60.6

67.3

* To obtain BNPL values for a standard household of four adult equivalents per month, multiply the first column by 4.

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South Pacific Studies Vol.33, No.1, 2012

Fig. 8. Incidence of poverty (by provinces) (percentage of population below BNPL).

The more important policy issue here, however, is not the absolute amounts, but
the relative amounts―i.e. the sharing percentage guidelines suggested for the urban
areas and the rural provinces. These percentages will be fairly stable between the rural
provinces, whatever the level of BNPL chosen for the rural households. However, therural-urban sharing percentage will solidly depend on the relative values of the BNPL
for Vila and Luganville, compared to the rural households. Table 8 here indicates that
the ADB/UNDP relativities in BNPL lead to the strong policy guideline that urbanhouseholds (in Vila and Luganville) should receive 67% of all poverty alleviation
resources (whatever is allocated by the Vanuatu Government) and that rural households
receive only 33% of the resources. If, however, the author’s simulated values for BNPL
are used, then the guidelines are more than reversed: rural households should receive
74% of all poverty alleviation resources, with only 26% going to urban households.
Table 8 indicates that there are very significant differences in the poverty alleviation
resource guidelines between the two sets of choices for the BNPL for all the islands.
The methodology of poverty analysis is critical in understanding these different results.

Stakeholders’ Own Estimates of Incidence of Poverty
This section presents the Vanuatu HIES data in such a form that all stakeholders
may be able to derive their own estimates of the incidence of poverty given their own
choice of values for the FPL and the BNPL in urban and rural areas, using expenditure
per adult equivalent rankings. Table 9 gives the incidence of poverty (or head countratio) for the full range of values of expenditure per adult equivalent per month.
Whatever BNPL pAE pm is selected, the grid gives the incidence of poverty. Figure 8

NARSEY: Poverty Analysis in Vanuatu: A Critical Review and Alternative Formulation

47(which graphs the data in Table 9) indicates that the order of poverty amongst the rural
areas in the provinces is pretty much the same, regardless of the value of the BNPL
chosen: the most poor are rural households on Torba, followed by Tafea and Shafea
Rural. The lowest is Penama.16

A Warning on VNSO (2009) Results on Income Distribution
VNSO (2009) gives some Gini coefficients as indicators of “income distribution”
in Vanuatu (although their statistics appear to be the distribution of “expenditure” not“income”):
Vanuatu:Port Vila:
Luganville:
Rural:

0.41
0.46
0.41
0.40

The relativity between rural areas and Vila appear to be correct but the absolutevalues for Vila is probably under-estimated because the 2006 HIES was not at all able
to capture in the HIES sample, enough of Chinese and European households. There is,therefore, likely to be very serious under-reporting of incomes at the upper end both for
Chinese and European households.
Overall, the HIES estimated total household income as 31,554 million vatu, which
is only 65% of the gross domestic product of 48,426 million vatu estimated for 2006.17
Average household incomes estimated from the HIES are given in Table 10, whichindicates that while average household incomes for Ni-Vanuatu was only 59 thousand
vatus per month and 357 thousands for European households, that for Chinese wasestimated to be a mere 54 thousand vatus―a completely implausible result given thewell-known dominance of the economy by Chinese households.18 The HIES estimateof the Chinese share of total household income was therefore a mere 0.1%―clearlysignificantly under-estimated.
Table 10. Average household incomes, expenditures and shares of totals (by ethnicity).
Ni-Vanuatu European
Average household income pm(000 vatu)

59

Average household expenditurepm (000 vatu)

52

ChineseOthers

All

357

54

145

61

352

85

128

54

Percentage of saving (%)

12

1

-57

12

11

HIES percentage of total income
HIES percentage of total expenditure

96.6
96.3

2.3
2.5

0
0

1.1
1.1

100
100

16 There is one “crossing over”―the graph for Sanma Rural.
17 Vanuatu National Statistics Office website: http://www.vnso.gov.vu/.
18 An extremely large part of the urban wholesale and retail economy are owned by Chinese.

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South Pacific Studies Vol.33, No.1, 2012

Table 11. Survey responses and comparisons with 1999 census results (by ethnicity).
Ni-Vanuatu
3856
42931

European
11167

Chinese2
11

Others
16
203

All
3885
43312

HIES estimated number of
persons

201952

480

17

780

203229Count in sample
Estimated number of households

HIES proportions of persons

99.37

0.24

0.01

0.38

100

1999 census proportions of
persons

98.52

0.78

0.15

0.55

100

Rate up factor required

0.99

3.28

17.65

1.44

Table 11 gives an indication of the source of the problems: while there were
11 European households in the HIES sample, there were only 2 Chinese. Given the
proportions of persons estimated in the HIES and given the proportions estimatedby the 1999 census on population, the numbers for European total incomes andexpenditures would need to be, very roughly, scaled upwards by a factor of 3.28. That
for Chinese would need to be scaled up by a factor of 18―although such a procedure
would still give totally inaccurate results given that the HIES estimate of average
Chinese incomes is unrealistically low.
All urban Gini coefficients are therefore likely to be very severely underestimated and HIES estimates of the rural-urban shares of total household income andexpenditure are also likely to be grossly under-estimating the urban shares and overestimating the rural shares.

Conclusion
This paper has critically examined the VNSO (2009) analysis of the incidence ofpoverty in Vanuatu. It has shown that the study’s results for the incidence of basic needs
poverty are inappropriate because of weaknesses in the methodology of estimating
food poverty and non-food poverty lines. VNSO (2009) results in inappropriate
recommendations for the national sharing of resources for poverty alleviation, with abias towards urban areas (Vila and Luganville) and bias against rural areas.
This paper shows that more appropriate values for the food poverty lines and nonfood poverty lines would give opposite indications: the incidence of poverty is higher
in rural areas than in urban areas. Moreover, the share of poverty alleviation resourcesthat should be going to rural areas (74%) is totally reversed from that indicatedimplicitly by the ADB/UNDP report, a mere 33%. Rural areas (a mere 33%). This has
major policy implications for poverty alleviation guidelines in Vanuatu.
It needs not be emphasised enough that were the VNSO (2009) results on poverty
relativities to be used to guide the distribution of poverty alleviation resources, aperverse cycle would be set in motion. An already poor rural sector would be deprived

NARSEY: Poverty Analysis in Vanuatu: A Critical Review and Alternative Formulation

49

further while standards of living in urban areas would be improved, thereby leading
to a strengthening of the rural-urban drift, and further increasing pressures on poverty
alleviation resources for the urban areas. More appropriate poverty results for rural andurban Vanuatu would lead to greater effort at poverty alleviation in rural areas, thereby
discouraging rural-urban drift.
This study has presented data in an easy to use tabular form, which should allow
poverty stakeholders in Vanuatu to estimate values for the incidence of poverty using
their own estimated values for the FPL, NFPL and BNPL for Vila, Luganville andRural Vanuatu. It is suggested that Vanuatu poverty stakeholders initiate an exercise toarrive at a more appropriate definition of food poverty line baskets for Vila, Luganvilleand Rural Vanuatu and to select more appropriate values for the non-food poverty line(and hence the basic needs poverty line). This paper warns against the uncritical useof income distribution statistics such as Gini coefficients given that the 2006 Vanuatu
HIES was not able to adequately capture the Chinese households in the sample, and toa lesser extent, the European households. Such income distribution estimates will need
to wait for another more comprehensive HIES.

References
A SIAN D EVELOPMENT B ANK 2006. Poverty Handbook, Analysis and Processes to
Support ADB Operations: A Working Document, 118 pp., Asian Development
Bank, Manila, Philippines.
HAUGHTON, J. and KHANDKER, S. R. 2009. Handbook on Poverty and Inequality, 446
pp., The World Bank., Washington, D.C., USA.
KAKWANI, N. 2003. Issues on Setting Absolute Poverty Line. Poverty and Social
Development. Papers, No. 3, June, 37 pp., Asian Bank of Development Bank,
Manila, Philippines.
R AVILLION , M. 1998. Poverty Lines in Theory and Practice, Living Standards
Measurement Study Working Paper No. 133, 35 pp., World Bank, Washington,
D.C., USA.
RAVALLION, M. and BIDANI, B. 1994. How Robust is a Poverty Profile? World Bank
Economic Review, 8: 75-102.
SEN, A. 1999. Development as Freedom, 384 pp., Oxford University Press, Oxford,
UK.
THORBECKE, E. 2004. Conceptual and Measurement Issues in Poverty Analysis. United
Nations University (UNU), World Institute for Development Economic Research(WIDER). Discussion Paper No.2004/4, 15 pp., UNU-WIDER, Helsinki, Finland.
T OWNSEND , P. 1993. The International Analysis of Poverty, 291 pp., Harvester
Wheatsheaf, New York, USA.
G OVERNMENT OF F IJI and U NITED N ATIONS D EVELOPMENT P ROGRAMME 1997. Fiji
Poverty Report, 156 pp., Government of Fiji, Suva, Fiji.

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UNITED NATIONS STATISTICS DIVISION 2005. Handbook on Poverty Statistics: Concepts,
Methods and Policy Use. Special Project on Poverty Statistics, 378 pp., UN
Statistics Division, Washington, USA.
VANUATU NATIONAL STATISTICS OFFICE 2009. Report on the Estimation of Basic Needs
Poverty Lines, and the Incidence and Characteristics of Poverty, 62 pp., Vanuatu
National Statistics Office, Port Vila, Vanuatu.
WORLD BANK 2003. A User’s Guide to Poverty and Social Impact Analysis, 90 pp.,
World Bank, Poverty Reduction Group (PRMPR) and Social Development
Department (SDV), Washington, D.C., USA.

NARSEY: Poverty Analysis in Vanuatu: A Critical Review and Alternative Formulation

Appendix 1. Abbreviations in the text, tables, and figures.
Abbreviation

Meaning

ADB

Asian Development BankAE

Adult equivalent (children less than 15 years old = half an adult)

BNPL

Basic needs poverty line

BNPL pAE

Basic needs poverty line per adult equivalent

CPI

Consumer prices index

FPL

Food poverty line

GDP

Gross domestic product

Gini

The Gini coefficient, which is commonly used as a measure of inequalityhhHousehold

HIES

Household income and expenditure survey

Incidence of Poverty
or Head Count Ratio

Percentage of the population below the BNPLIMFInternational monetary fund

NFPL

Non-food poverty line

OECD

Organisation for economic co-operation and developmentpa

per annumpc

per capita

pAE

per adult equivalentpm

per monthpw

per week

Poverty Gap

The resources required to bring all poor households up to BNPL

SPCSecretariat of the Pacific Community

UNDP

United Nations Development Programme

USP

The University of the South Pacific

WB

World Bank

51

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South Pacific Studies Vol.33, No.1, 2012