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Risk and Vulnerability Considerations in Poverty An

Recent Advances and Future Directions

Carlo Cafiero and Renos Vakis

October 2006


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Risk and vulnerability considerations in poverty analysis:

Recent advances and future directions

Carlo Cafiero1

and Renos Vakis2

Abstract

In the recent past, growing attention has been devoted to the attempt to correctlysiderations of exposure to risk in the discussions on poverty reduction and, m

economic and social development. The purpose of this article is to take stock o

forts and to reconsider the relationship between poverty and exposure to risk. short review of current practices of vulnerability measurement to discuss how

is truly consistent with an ex-ante view of assessing the true consequences of rWe argue that one way of addressing this inconsistency is by adding an estimat

ance cost needed to guarantee a socially accepted minimum level of welfare t

consumption expenditure taken as a benchmark to identify the poor. In other wfine an augmented poverty line where the traditional absolute poverty bench

marked up by the estimated cost of insuring against what are considered socia

able risks. We then discuss the practical implications for implementing such afuture research directions.

Keywords: Poverty, Risk, Vulnerability, InsuranceJEL-Codes: I3, G22, O12


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I. INTRODUCTIONInrecentyears,agrowingattentionhasbeendevotedtotheattemptto

cludeconsiderationsrelatedtotheexposuretoriskinthediscussionsonpove

and,moregenerally,onsocialandeconomicdevelopment.Thatexposuretori

oughttobeanundisputedfact.Manyhaverecognizedthatoneoftherecurre

ofhumanactivity isanattempttoreducethedegreeofuncertaintythatsurr

ture.Inthecontextofeconomicdevelopment,ithasalsobeenwidelyrecogni

attemptsmaysometimeshavenegativeconsequencesintermsofgrowthpoten

tialthatcouldbemorefullyexpressedifonlybetterwaystodealwiththeunc

available.

Inthissense,twojustificationsforpublicinterventionsaimedatreduc

suretoriskand/ortheconsequencesofshocksemerge.First,sinceinsecurity

ducing,publicactionstoensureaminimumlevelofsecurityforeveryonemay

Second,privateactionstoreduceexposureortocopewiththeconsequences

eventsmight

be

too

costly

and

inefficient

from

asocietal

point

of

view.

Whilethereiswidespreadagreementonthemeritsofthesetwojustifi

moredisputedseemstobehowtoactuallymeasureboththedegreeofexposu

whatistypicallytermedvulnerability)anditsnegativeconsequencesinterm

Inorder tomeasure these,onewouldneed toassesswho ismore exposeda

givenprospect

is.

Such

quantitative

measures

are

required

to

assess

issues

lik

costattributedtorisk,distributionalconsequencesandtargeting.

Theaimofthispaperistwofold.First,wediscusstheconceptualproble

be confrontedwhen trying todefine thewelfare cost of exposure to risk, an


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therealizationofshocks.Lackingsuchidentificationimpliesmakinganincom

tentially

incorrect

assessment

about

risk

exposure

and

policy

directions.

Second,weintroduceaconceptuallysimpleapproachtoincluderiske

siderations within poverty indicators. We argue thatby directly embeddin

measurementofpoverty, such ameasurebecomes truly forward looking an

manyassumptionsusedintheexistingmethodologies.Whilethepracticalde

plementingsuch

an

approach

are

indeed

great,

we

discuss

directions

for

futu

researchondata collectionandanalysis that canbedone to simplifyandm

tional.

Thepaper isorganizedas follows.Section2reviews theexisting liter

nerability indicators.Twoconcernsare identified.First,andperhaps less imp

taindegree

of

confusion

seems

to

permeate

the

practical

uses

of

the

terms

po

nerability.Such confusion shouldbe resolvedbeforegoingdeeper into speci

measurement,whichisdiscussedinsection3.Second,andmoreimportant,w

fully consistentwayofaddressing thewelfare consequencesof the exposure

therefore to correctly provide guidance forwelfare increasing policies in un

ronments,is

yet

to

be

found.

Section

4,

introduces

asimple

concept

of

an

aug

erty linewhich integrates risk inpovertymeasurement.Section5discusses

implicationsofestimatingsuchameasureandhowfutureworkcanbedirecte

andbroadenitsimplementation.Section6concludes.

II. POVERTY AND VULNERABILITYMerriam Webster Dictionary (on line version, 2005) defines poverty as

one who lacks a usual or socially acceptable amount of money or material posse


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social and political rights and to a wide array of other non material basic nee

most recent attempts to include consideration related to security (World Bank,

This view recognizes, at least in principle, that insecurity is in itself a

comfort and hence it causes a reduction of welfare or well-being.6 Such a view

cepted, and very few now seem to dispute that any civilized society should gran

access to the means and opportunities to reduce the level of insecurity up to

ceptable level. Such an (equity) argument could and should be considered a

tification for the provision of social protection, which thus become an essential

any development oriented policy.

Nonetheless, a well designed and correctly targeted social protection sys

be a factor to boost economic growth (Dercon, 2005). The rationale behind such

that, to try and eliminate uncertainty, the poor are often forced to employ th

sources they possess in activities with low returns, but which assure a minimum

sumption. By providing them with more security, they could mobilize resourc

ties with higher returns, thus effectively promoting growth. This argument is al

to skeptics of social protection, who question the efficiency of costly social pro

ventions in the context of limited financial resources, which they claim - co

invested instead in more efficient activities.

Nonetheless, none of the justifications above explain what a well d

correctly targeted social protection system is. A debate has therefore forme

have been devoted to try and understand how to design policies aimed at red

3The most influential work on the broadening of the view of poverty can be traced back to A

but many have been contributing to the process so that a comprehensive list of references wou

be put here.4

Poverty is hunger. Poverty is lack of shelter. Poverty is being sick and not being able to se

erty is not having access to school and not knowing how to read. Poverty is not having a job, i

ture, living one day at a time. Poverty is losing a child to illness brought about by unclean w

l l k f i d f d (Th W ld B k 2001)


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tainty and how to target them so that they would be efficient in terms of prom

and growth.

Within such debate, the word vulnerability has come to widespre

though sometimes in ways that may lead to confusion.7 Two main definitions

in a broad sense, vulnerability is considered as the condition of being at risk

tially harmful event, and, as such, it is something that should be avoided. In such

nerability reduction objectives are distinct and as legitimate as poverty reducti

Taken from this perspective, although there might be synergies among the two o

example through considerations such as that the poor are more vulnerable), suc

not necessary to justify a role for social protection.

A second definition uses the word vulnerability in a narrower sense to

ability to poverty, i.e. the possibility of becoming or remaining materially poor

Therefore, the fundamental policy objective remains that of reducing poverty

tended more as potential rather than current poverty and social protection becom

also on the grounds that it remove constraints to growth.8

It is this second view which permeates the recent work aimed at meas

ability, as recently reviewed by Hoddinott and Quisumbing (2003), Ligon a

(2004), and criticized by Elbers and Gunning (2003). We do not duplicate their

rather, we note that even an optimistic survey of this literature leaves the reade

eral sense of skepticism on the possibility to use any of the existing measures of

in a fully satisfactory way.

Following Hoddinott and Quisumbing (2003), individual measures of

can be classified as: (a) indexes of expected poverty (VEP), i.e., the probabilityvidual household will fall below the poverty line, (b) indexes of expected utilit

the distance between the utility that would be achieved by receiving an appropr

level of consumption with certainty and the expected utility of the household gi


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utable to past shocks. Each of the three types of measures has its own merits a

as exhaustively described by Hoddinott and Quisumbing (2003) and by Ligon

(2004). Nonetheless, all the proposed measures have two key problems that

solved.

First, in any conceivable practical implementation, the use of observ

from the past will be needed to infer the future distribution of events, which

strong assumptions are made on the unobserved behavior.9 To deal with this, th

proaches give up the possibility of estimating behavioral parameters, and assum

fication purposes, that the structure of the preferences is known either explici

VEP and VEU measures) or implicitly (as in the VER measures).10

As Ligon a

(2004) note: One claim advanced for (at least utility-based) vulnerability me

they avoid the paternalism inherent in poverty measures by reflecting the prefe

household themselves. However, while theres working consensus in the empiri

on what functions usefully reflect household risk preference (the HARA cla

leaves at least one free parameter. [] Estimating preference parameters wi

analyst to observe the outcomes of household decisions (e.g. savings decisions,

etc.) which depend in part on risk attitudes. Even the innovative procedure o

dynamic structural model of households behavior (suggested by Elbers and Gu

does not solve the problem of estimating the distribution of future events to be u

ure vulnerability.

Second, to implement them in practice, these techniques need to rely (t

grees) on assumptions of stationarity and measurement error. That is, to be ab

future distribution of all possible outcomes from the observation of past realizatlyst would have to assume that the future is going to be similar to the past

world).Even if one did not want to assume this, there is a big practical problem

to evaluate the stationary (or not) nature of the distribution of consumption ne


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confounded with the stationarity assumption is the existence of measurement

sumption data which is assumed away in many of the approaches. These are k

that make existing techniques difficult to apply them operationally.

A crucial point of these issues is that, at least the way in which they h

plied so far, all these measures are truly backward-looking. This is unsatisfactor

very concept of vulnerability is a forward-looking one: it should capture the w

quences ofexposure to risk, not that ofhaving been subject to shocks. The exis

and type of available data used cannot identify between these two elements, in

using utility theory for identification. As put by Alwang, Siegel and Jrge

While it is possible to measure losses ex-post [], these are only the static o

continuous process of risk and response. Vulnerability is the continuous for

state of expected outcomes. Ex post welfare losses are neither necessary nor suff

existence of vulnerability. Welfare losses, in and of themselves, are not sufficien

household as vulnerable.

Perhaps what it is truly at the heart of this impasse is the fact that all at

bedding the concept of vulnerability within poverty analysis have not explicitly

the concept of poverty at its roots. In this sense, the natural direction of embe

poverty seems to be one that unifies the view of vulnerability and poverty. The

explores this further.

III. VULNERABILITY AS POVERTYAs discussed above, vulnerability has up to now been defined in either

general condition of being exposed to potentially harmful events or by focusing

sure and its impact onfuture poverty i.e. the risk of remaining or becoming poo

usually refers to a well defined low level of consumption). Still, the existing att

a practical working definition to vulnerability have maintained a distinction be


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Westressinsteadthatsuchadistinctionismisleading:apersonwhoca

forthemeanstoappropriatelymanageriskoughttobeconsideredpoor.Inoth

makenofundamentaldifferencebetweentheconceptofpovertyandthatof

Thatis,apersonispoorpreciselybecausehedoesnotpossesssufficientresou

againstalltheriskswhosepossibleconsequencesaredeemedassociallyintole

ofsuchrisks,farfrombeingabsolutelydefinedinbothgeographicalandhist

sions,

always

starts

with

the

risk

of

dying

of

starvation,

but

grows

to

include

overtime,societiesrecognizeasnolongeracceptable.Inaway,thetermdev

couldbeintendedasthejointprocessofenlargingthelistofintolerablerisksa

sionofthemeanstoinsureagainstthemtothegreatestpossiblenumberofpeo

Thisviewalsorecognizesthatpovertymustbeconsideredanexante

lookingconcept

(indeed

aview

that

is

shared

by

the

recent

work

on

vulner

whatmatters isnot the futurepotential outcomeper se,but rather the con

whichpeople arebound to face theiruncertain future.The simple awarene

shocksisinitselfacauseofdistressorsuboptimalbehaviorandthereforeim

farecost.Thefactthatashockdidnotrealizedoesnotimplythatpeoplewer

ableto

its

risk.

In

this

sense,

the

observation

that

people

have

been

lucky

thattheydidnotsufferawelfareloss.Assuch,toprovidethemwiththeme

moresecuremustbeconsideredawelfareimprovingaction,andtoidentifyth

forwhateverreason lessequippedtofacetheiruncertainfutureandfeeling

likeagoodwayoftargetingpolicies.

Oneconsequenceofthisisthatvirtuallyallmeasuresofvulnerabilityth

proposedsofarneedtobequestioned.Evenwheninprincipletheycanbepre

wardlooking(asonecouldtake,forexample,theconceptoftheprobability

i th f t ) th th li d i b d th b ti f t


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If the inability to insureagainst risk ispoverty,allweneed todo is

measurethemonetarycoststhatwouldbenormallyrequiredinagivenenvir

sureagainstthemostdangerousandfrequentrisks.Thisonlyrequiresacalc

costofinsurance,notthecostsofriskexposure,thefirstonebeing,atbest,alow

thesecond.

IV. THE AUGMENTEDPOVERTY LINEIntegrating the inability to insure against risk directly into poverty me

ceptually simple: it amounts to redefining the typical poverty line to account f

insurance. In this sense, it is equivalent to the exercise of choosing the comp

typical basket of goods and services (as is done in current poverty work) by

cost of insuring against unacceptable risks. An augmented poverty line can be

fined as the:

poverty line that includes the minimum amount of consumption requ

achieve basic needsplus the cost needed for acquiring enough insurance

`Enough means sufficient to cover the exposure to those risks that are

cially unacceptable, while insurance must be intended in a broader sense t

market-traded formal insurance contract, as including all actions which, in exch

sort of either implicit or explicit monetary payment, will eliminate most or all

consequences of the events being considered. The value added (at least from th

point of view) of such a definition is that it directly embeds risk exposure a

costs into the definition of poverty.

In this setting, measuring the consumption gap for household i (that is, th

a ho ehold con mption from the a gmented po ert line) i gi en b


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wherez is the traditional poverty benchmark (that includes food and non-food

the (idiosyncratic) cost of insurance against the predetermined set of risks that

is not able to insure, andyi is household is measured consumption expenditure.

Given ig~ , traditional measures of poverty in the tradition of Foster et a

be simply calculated in the usual way:

P(y, ,z) = =

+

q

i i

i

z

g

n 1

~1

where n is the total population and q is the population below the augmented pov

i).

The observation that i can be (to a large extent) strictly idiosyncra

practical complication: can one really measure i? While there are a number of

doing so (discussed below), they are conceptually not very different from encou

isting poverty measurement methodologies. For example, poverty lines often

typical baskets, like distinguishing between the extreme (focusing on the inab

a basic food basket) and general (which adds to the cost of the food basket the

tial non-food items). Similarly, different poverty lines can arise when considerin

geneous costs and composition of typical baskets across regions (e.g. betw

urban areas). In this sense, the observation that poverty lines have a large idios

ponent is not new and as such, our proposal to add a new component (i.e. risk)

ral extension of existing practices.13

12As an extreme example, consider two identical households (1 and 2) with the exact same

tary wealth, living in the same natural and economic environment, thus facing the same natur

hazards. According to our criterion, they could be located differently relative to the augmen

because of their different ability to manage risk due, for example, to different average levels

this context, a targeted educational program would be the best way to tackle the issue as it woul

its effect of reducing the uninsured cost of risk management (i) for the less educated househo13

Distinguishing idiosyncratic from covariate risk is indeed complicated. In principle, idios


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Still, the fundamental problem that remains to be addressed is ho

measure the cost of insurance to be added to the static poverty line. Conceptual

guish the following three steps:

1. Identify the possible risks to be included in the poverty measure;2. Estimate the cost of insurance for such risks for each household i;3. Calculate ig~ for each i and determine the aggregate poverty indicato

Risk identification

In general, the insurance cost i will be the sum of various risks: over

nomic risk; covariate, village level risk (such as weather risk); and household

syncratic risk (such as health risk), and it can be constructed accordingly by co

type of risk at a time. Cataloguing and incorporating all possible risks is of c

reach both in terms of data requirements but also from a practical point of vie

that it is not necessary to embed all possible risk components before being able

sible conclusions on the relevance of specific risks.

A first step is therefore to identify which risks are considered socially

and therefore insurance against which should be considered part of the basic n

there will still be large inter and intra country differences in how one should

simple review of existing poverty and vulnerability analyses suggests that it m

difficult.14 Indeed, recent use of risk modules in household level analysis cou

guide as to what is considered an important risk. For example, droughts and ma

haps two of the most easily identifiable and frequently reported shocks facing tions in many countries. Assessments to incorporate risk in poverty work wo

include weather and malaria risk for rural populations in the poverty line calcula

The cost for insurance


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arise from both the idiosyncratic nature of risk exposure and from the fact tha

tings (especially in developing countries), such a cost will at best be a simulate

the absence of formal insurance markets for that specific risk. Fortunately, a

exists that has addressed such problems, which we think can be explored to ta

these issues.

Theoretically, the cost to be considered should be analogous to what in

literature is defined as an actuarially fair premium. Where formal insurance

and are well developed, the prevailing market premiums can be used as proxi

premium, possibly after adjustments for transaction costs due to problems o

and/or lack of competition in the supply of insurance.15

In the most common cases where formal insurance markets are not we

the analysis will need to focus on simulating an insurance market. To do so, a

the following will be needed: (a) the probability distribution of the risky event

associated loss for all households exposed to the risk. The hypothetical actuar

mium can then be calculated as the average expected loss, i.e., the premium tha

a market with complete risk sharing.

Information needed to estimate the distributions and the potential losse

ardous events can be sought for in the records of past outcomes, although we m

the losses and probability of events should be measured separately and as mu

possible, trying to avoid the need to impose unjustified behavioral assumptions

tion purpose. The point is that past outcomes carry only partial information o

might havehappenedbut did not happen and the anticipation of which likely af

15In many cases, when households have bought a specific insurance (e.g. health insurance

premiums paid can be potentially included in the aggregate expenditure measure yi (a common


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ior. Moreover, this partial information is necessarily confounded with the effe

which happen to materialize but that had not been anticipated.16

Once this premium, call it i, is estimated, it must be compared to th

cost of eliminating the negative consequences of the same event by engaging in

actions, such as, for example, by changing cropping patterns (risk skewing ac

fined by Dercon, 2005) or by investments.

As an example, consider a situation where the only relevant risk is that o

avoid damages, a farmer could either diversify its crops (i.e., by selecting the

resistant ones) or invest in digging a well. Both actions imply a cost. The min

diversification, say C1, could be assessed through the calculation of the foregon

come when cultivating the best feasible drought resistant crop instead of the m

drought susceptible crop. Data should usually be available on both types of cr

veys of farms in the region or in similar regions. On the other hand, the effectiv

ting irrigation water by digging a well might depend on such things as the depth

water can be found; the nature of the soil; the available digging technology;

quality of water, and so on. The total cost of the investment should then be ann

an interest rate which is representative of the prevailing credit conditions to get

ble annual cost C2. The opportunity cost of insuring against drought, OCi coul

termined as OCi=min{C1, C2}. Then, the (conservative) measure, i, to be ad

come benchmark will be:

i = min{i, OCi}

Once i is calculated for each household i, the gap ig~ and the aggregate poverty

can be then computed using Eq. 2.

V. DISCUSSION AND IMPLICATIONS FOR FUTURE RESEARCHThere are a number of benefits associated with this approach. First, t


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the class of the P measures of Foster et al. (1985), and that, therefore, doe

abandoning the wealth of developed expertise and data in poverty analysis.17

Second, the method clearly distinguishes between the ex ante exposure t

ex post effects of shocks. Only the ex-ante exposure to risk is included as a

poverty. What we add to the traditional poverty line is notan estimate of the

come loss or of a monetary measure of the expected utility loss, which would d

the commonly available data, both on past actions taken and realizations of sh

i we suggest to use ought to represent the cost of uninsurable risk exposure

flecting the ex-ante perception of what the risk might imply.18

Third, we do not need to devise a set of new indicators, and therefore w

to come up with arbitrary ways of weighing them. For targeting purposes, the

one is an indicator of poverty. Any policy could then be targeted to the poor, a

according to whether or not its implementation might reduce some measure of

dence (which now incorporates risk as well). Similarly, sincez and i are calcu

rately, one could compare the relative importance of each, facilitating targetin

design.

Forth, the paradox of households that, based on a concept like vulner

pected poverty, would be considered non poor, yet vulnerable to risk is resolcost of insurance is assessed, no ambiguity exists in classifying a household

and therefore poor, or not.

Fifth, poverty reducing programs can also be evaluated based on their

ment capacity. That is, they could be ranked simply in terms of the extent to w

duce the broadly defined poverty measure which now incorporates risk. For e

17For example, to report on the importance of considering risk related issues and assessin

Kamanou and Murdoch (2002) compare their aggregate vulnerability index with the change in

d l d h h b d h i h di i l h d f b i


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grams that directly provide free insurance opportunities to the poor, by reducin

insurance to be added to the poverty benchmark, would certainly decrease pover

Nonetheless, the feasibility of calculating i remains a huge concern. W

tually the approach is simple, there are a number of constraints and challenge

make it operational. For one, the mere concept of trying to calculate i for e

risk in a given context seems impractical (if not impossible). The data requirem

considering the following demands: (i) deriving a list of risks to be considere

for each household; (ii) the need of information on risk premiums, somethin

complicated in many settings where insurance markets do not exist; (iii) costi

risk prevention instruments that can then be compared to insurance. At the same

of assumptions and data challenges for many of these issues are not qualitati

that those done in existing poverty measurement work. Below, we outline so

where further research could address some of these concerns.

Targeting and aggregation

The idiosyncratic nature ofi implies a huge information cost in its cal

direction to address this is to conduct such calculations at a more aggregate leve

simplification would be to consider large covariate risks (such a weather variatitheir nature affect a large number of households. In this case, we could calcula

minimum cost of weather insurance premiums or irrigation) for all (potentially

holds within a particular region exposed to weather variation.

Such an aggregation concept is akin to poverty mapping methodolo

developed that aim at measuring poverty rates at lower administrative units (lik

ties) by aggregating household level poverty estimates, thus improving precisi

ing the weather example, data on rainfall variation (collected from weather sta

used to define drought prone regions, while rainfall insurance premium inform

t f th ti i t t (lik th t f ll) b bt i d


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made with the opportunity cost of eliminating the negative consequences of th

by engaging in preventative actions.

With the minimum cost i calculated (now i referring to a specific regi

pality), it can be added to a regional poverty line (which by definition affects a

in that region). Further modifications and adjustments can be made to improve

example by excluding non-farm households or households that already have t

manage rainfall risk. In such an example, regional poverty estimates would dir

for the risk of drought and therefore provide an instrument for targeting which

risk and non-risk welfare considerations.

Data requirements and future directions

Much of the data required to do the calculations we discuss are indeed

example, existing consumption expenditure data such as those available throu

Standard Measurement Surveys (LSMS) is already used to assess the welfare

household. In addition, existing data on the production structure of the househ

either within the same LSMS or through other farm/family business surveys,

useful in estimating some of the insurance costs parameters delineated above (

ple on drought). In particular, two conceptually separated pieces of informatiotracted, namely the probability of the events occurring, and the loss caused by

larly, data collected from ongoing existing and pilot programs aiming at promo

ment of insurance instruments in developing countries might also be very helpf

potentially include information like the willingness to pay for insurance, marke

ance information or data to assess insurance premiums.

A number of new areas of research in survey design can also facilita

with respect to welfare and risk. For example, new modules on shocks and ris

included in a handful of household surveys. While more work needs to be don

fi th d l d l i th f th ld f ilit t thi b ll i t


19/31

In addition, recall questions may be used to construct a households hist

sion making process along various dimensions (including decisions under unce

can be done either by revisiting households from an existing household surve

retrospective questions during the collection of new data. Such modules can als

perception modules that could be used to construct risk distributions.21

Simil

work on subjective welfare may be used to incorporate risk in measuring welfar

While none of these approaches are without limitations, they seem to

range of options that can be used to implement our approach and incorporate ri

poverty measurement.

Experimental and evaluation work

Even beyond the construction of a risk inclusive poverty measure, there

need to better understand the welfare consequences of risk and its impact on h

groups. As discussed above, we know very little about how uninsured risk exp

behavior.23 Indeed, at the heart of the problem is one of reverse causality: the

ability in outcomes that we may observe will be the result of actions taken by a

avoidall risks, including those that we did not observe. As such, observed shoc

not be taken as a proxy of the ex-ante uncertainty to which the response was mby observing outcomes it is impossible to assess the risks that people have

choosing their actions or risks that people did no action but did not materializ

At best we can assess what people did for risks that we observe ex-post (as realiz

In this sense, programs that promote guaranteed payout schemes coul

ter understand how behavior changes with increased security (and hence lower

idea behind such intervention is that beneficiaries know ex ante that they will r

cific support (the payout) if a particular risk they are exposed (but cannot insure

terializes into a shock. This does not only involve market based insurance schem


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any intervention that can guarantee a payout if a shock occurs. Existing ongoin

experimental evaluation designs like providing rainfall insurance, income dive

guaranteed employment schemes are indeed exciting new directions to better u

havior under risk and the impact of improved security.

VI. CONCLUDING REMARKSA general agreement seems to exist that exposure to risk is an integr

poverty and that it is inherently a forward looking concept. A short review of

available methods for measuring vulnerability to risk has revealed some concep

tical limitations to address uninsured risk as a direct element of poverty. We pro

way of addressing the problem of directly including risk into poverty analysis

poverty indicators based on consumption gaps measured against a benchmark w

an estimate of the cost of insuring against the risks which are considered socia

able. Such a proposal is consistent with a view of poverty which considers secu

tial element of the wellbeing of households and individuals. In this sense, to

becomes synonymous of beingpoor.

While the practical implications of such an approach raise a number of

lenges, we discuss some directions for future work to address them. These inclu

of integrating aggregate measures of risk beyond the household level in the pov

improved data collection and new pilots to explore ex ante behavior under uncer

directions are needed in order to truly integrate risk exposure in poverty analysi

ion paper will subsequently develop an empirical application of this approach

plore its operational implications.


21/31

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Social Protection Discussion Paper Series Titles

No. Title

0609 Comparing Individual Retirement Accounts in Asia: Singapore, ThaHong Kong and PRCby Yasue Pai, September 2006 (online only)

0608 Pension System Reformsby Anita M. Schwarz, September 2006 (online only)

0607 Youth Labor Market in Burkina Faso: Recent Trendsby Daniel Parent, July 2006

0606 Youth in the Labor Market and the Transition from School to Work Tanzaniaby Florence Kondylis and Marco Manacorda, July 2006

0605 Redistributing Income to the Poor and the Rich: Public Transfers in America and the Caribbeanby Kathy Lindert, Emmanuel Skoufias and Joseph Shapiro, August (online only)

0604 Uninsured Risk and Asset Protection: Can Conditional Cash TransfePrograms Serve as Safety Nets?by Alain de Janvry, Elisabeth Sadoulet, Pantelis Solomon and Reno

June 2006

0603 Examining Conditional Cash Transfer Programs: A Role for IncreasInclusion?by Bndicte de la Brire and Laura B. Rawlings, June 2006 (online

0602 Civil-service Pension Schemes Around the Worldby Robert Palacios and Edward Whitehouse, May 2006 (online only

0601 Social Pensions Part I: Their Role in the Overall Pension Systemby Robert Palacios and Oleksiy Sluchynsky, May 2006 (online only

0543 Complementing Natural Disasters Management: The Role of Social


25/31

by Alain de Janvry, Frederico Finan, Elisabeth Sadoulet, Donald NeKathy Lindert, Bndicte de la Brire and Peter Lanjouw, December(online only)

0541 Japans Pension Reformby Junichi Sakamoto, December 2005 (online only)

0540 Demographic Alternatives for Aging Industrial Countries: IncreasedFertility Rate, Labor Force Participation, or Immigration

by Robert Holzmann, December 2005 (online only)

0539 Disability, Poverty and Schooling in Developing Countries: ResultsHousehold Surveysby Deon Filmer, November 2005 (online only)

0538 Food Aid and Food Security in the Short- and Long Run: Country Efrom Asia and sub-Saharan Africa

by Carlo del Ninno, Paul A. Dorosh and Kalanidhi Subbarao, Novem2005 (online only)

0537 The New Pensions in Kazakhstan: Challenges in Making the Transitby Richard P. Hinz, Asta Zviniene and Anna-Marie VilamovskaSeptember 2005 (online only)

0536 Households Vulnerability to Shocks in Zambia

by Carlo del Ninno and Alessandra Marini, September 2005 (online

0535 Linking Community Empowerment, Decentralized Governance, andService Provision through a Local Development Frameworkby Louis Helling, Rodrigo Serrano, David Warren, September 2005 only)

0534 Youth Employment in the MENA Region: A Situational Assessmenby Nader Kabbani and Ekta Kothari, September 2005

0533 Measuring Risk Perceptions: Why and Howby Joachim De Weerdt, July 2005
http://siteresources.worldbank.org/SOCIALPROTECTION/Resources/0532.pdfhttp://siteresources.worldbank.org/SOCIALPROTECTION/Resources/0532.pdf


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0530 Sistema de Identificacin de la Poblacin Objetivo: SIPO en CostaRicaby Roxana M. Vquez, June 2005 (online only)

0529 Targeting Social Spending To the Poor with ProxyMeans Testing:Colombia's SISBEN Systemby Tarsicio Castaeda, June 2005 (online only)

0528 Focalizacin De Programas En Chile: El Sistema CASby Osvaldo Larraaga, June 2005 (online only)

0527 Reforming Brazil's Cadastro nico to Improve the Targeting of the Famlia Programby Bndicte de la Brire and Kathy Lindert , June 2005 (online onl

0526 Designing and Implementing Household Targeting Systems: LessonLatin American and The United Statesby Tarsicio Castaeda and Kathy Lindert, with Bndicte de la Brir

Fernandez, Celia Hubert, Osvaldo Larraaga, Mnica Orozco and RViquez, June 2005 (online only)Also available in Portuguese.

0525 Unequal Prospects: Disparities in the Quantity and Quality of Labouin sub-Saharan Africaby John Sender, Christopher Cramer and Carlos Oya, June 2005

0524 Pension Supervision: Understanding International Practice and CounContextby Richard P. Hinz and Anca Mataoanu, May 2005

0523 Social Security Coverage in Latin Americaby Rafael Rofman, May 2005

0522 A Technology White Paper on Improving the Efficiency of Social S

Program Delivery in Low Income Countries: An Introduction to Avand Emerging Mobile Technologiesby Mike Gallaher, May 2005 (online only)

0521 Aging and Poverty in Africa and the Role of Social Pensionsby Nanak Kakwani and Kalanidhi Subbarao May 2005 (online only
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by Robert Holzmann, Johannes Koettl and Taras Chernetsky, May 2(online only)

0518 Who Has the Yam, and Who Has the Knife? Social Action Funds anDecentralization in Malawi, Tanzania, and Ugandaby N. Mungai Lenneiye , May 2005

0517 Household Vulnerability and Childrens Activities: Information Nee

Household Surveys to Measure their Relationshipby Diane Steele, May 2005 (online only)

0516 The Effect of Child Labor on Mathematics and Language AchievemLatin Americaby Mario A. Sanchez, Peter F. Orazem, and Victoria Gunnarsso, Ma

0515 The Inter-Generational Persistence of Child Labor

by Patrick M. Emerson and Andr Portela Souza, May 2005

0514 How Does Working as a Child affect Wage, Income and Poverty as Adult?by Nadeem Ilahi, Peter F. Orazem, and Guilherme Sedlacek, May 20

0513 Dynamics of Child Labor: Labor Force Entry and Exit in Urban Braby Suzanne Duryea, Jasper Hoek, David Lam and Deborah Levison

20050512 The Responses of Child Labor, School Enrollment, and Grade Repe

the Loss of Parental Earnings in Brazil, 1982-1999by Marcelo Crtes Neri, Emily Gustafsson-Wright, Guilherme SedlaPeter F. Orazem, May 2005

0511 Child Labor, Schooling, and Poverty in Latin Americaby Guilherme Sedlacek, Suzanne Duryea, Nadeem Ilahi, and MasaruMay 2005

0510 Changing Patterns of Child Labor around the World since 1950: TheIncome Growth, Parental Literacy and Agriculture


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0508 Social Funds: A Review of Public Sector Management and InstitutioIssuesby Mukhmeet Bhatia, May 2005

0507 Pension Reform in El Salvadorby Rodrigo Acua, April 2005

0506 How Changes in Benefits Entitlement Affect Job- Finding: Lessons Slovenian Experimentby Jan van Ours and Milan Vodopivec, April 2005

0505 A Guide to Multisector Labor Market Modelsby Gary S. Fields, April 2005

0504 Multinational Enterprises and Training Revisited: Do International SMatter?by Niels-Hugo Blunch and Paula Castro, March 2005

0503 Community-Based Health Insurance & Social Protection Policy

by Steven Tabor, March 2005 (online only)

0502 Towards a Better Understanding of the Nature, Causes and ConsequYouth Labor Market Disadvantage: Evidence for South-East Europeby Alexandre Kolev and Catherine Saget, March 2005 (online only)

0501 A Lecture on the Political Economy of Targeted Safety Netsby Lant Pritchett, January 2005

0420 Can Conditional Cash Transfer Programs Improve Social Risk ManLessons for Education and Child Labor Outcomesby Elisabeth Sadoulet, Frederico Finan, Alain de Janvry and Renos VDecember 2004

0419 Measuring Welfare for Small but Vulnerable Groups. Poverty and Din Uganda

by Johannes G. Hoogeveen, September 2004

0418 Institutional Analysis Toolkit for Safety Net Interventionsby Inke Mathauer, August 2004


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0415 Shocks and Coffee: Lessons from Nicaraguaby Renos Vakis, Diana Kruger and Andrew D. Mason, July 2004

0414 Costs of Projects for Orphans and other Vulnerable Children: Case sEritrea and Beninby Menahem Prywes, Diane Coury, Gebremeskel Fesseha, GilberteHounsounou, and Anne Kielland, July 2004

0413 Disability Employment Policyby Daniel Mont, July 2004

0412 Child Labor, Education, and Childrens Rightsby Gordon Betcherman, Jean Fares, Amy Luinstra, and Robert Prou2004

0411 Challenges and Opportunities of International Migration for the EUMember States, Neighboring Countries and Regions: A Policy Noteby Robert Holzmann and Rainer Mnz, June 2004

0410 Evaluating Different Approaches to Estimating Vulnerability

by Ethan Ligon and Laura Schechter, June 2004

0409 Transferring Cash Benefits Through the Banking Sector in Colombiby Maria Teresa Lafaurie V. and Claudia A. Velasquez Leiva, May

0408 Mitigating Social Risks in Kyrgyz Republicby Emil Tesliuc, April 2004

0407 Toward a Reformed and Coordinated Pension System in Europe: Raand Potential Structureby Robert Holzmann, April, 2004

0406 Boosting Productivity Via Innovation and Adoption of New TechnoAny Role for Labor Market Institutions?by Stefano Scarpetta and Thierry Tressel, March 2004

0405 Mitigating the Social Impact of Privatization and Enterprise Restrucby David H. Fretwell, March 2004

0404 Risk and Vulnerability in Guatemala: A Quantitative and QualitativAssessment


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0402 Impacts of Active Labor Market Programs: New Evidence from Evawith Particular Attention to Developing and Transition Countriesby Gordon Betcherman, Karina Olivas and Amit Dar, January 2004

0401 Consumption Insurance and Vulnerability to Poverty: A Synthesis oEvidence from Bangladesh, Ethiopia, Mali, Mexico and Russiaby Emmanuel Skoufias and Agnes R. Quisumbing, January 2004

To view Social Protection Discussion papers published prior to 2004, plea

www.worldbank.org/sp.


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About this series...Social Protection Discussion Papers are published to communicate the results of The World Bank's workto the development community with the least possible delay. The typescript manuscript of this paper thereforehas not been prepared in accordance with the procedures appropriate to formally edited texts. The findings,interpretations, and conclusions expressed herein are those of the author(s), and do not necessarily reflectthe views of the International Bank for Reconstruction and Development / The World Bank and its affiliatedorganizations, or those of the Executive Directors of The World Bank or the governments they represent.

The World Bank does not guarantee the accuracy of the data included in this work. For free copies of thispaper, please contact the Social Protection Advisory Service, The World Bank, 1818 H Street, N.W., RoomG7-703, Washington, D.C. 20433-0001. Telephone: (202) 458-5267, Fax: (202) 614-0471, E-mail:[email protected] or visi t the Social Protection website at www.worldbank.org/sp.

Summary Findings

In the recent past, growing attention has been devoted to the

attempt to correctly include considerations of exposure to risk in

the discussions on poverty reduction and, more generally, economic

and social development. The purpose of this article is to take

stock of all these efforts and to reconsider the relationship between

poverty and exposure to risk. We present a short review of current

practices of vulnerability measurement to discuss how none of

them is truly consistent with an ex-ante view of assessing the true

consequences of risk exposure. We argue that one way of

addressing this inconsistency is by adding an estimate of the

insurance cost needed to guarantee a socially accepted minimum

level of welfare to the level of consumption expenditure taken as

a benchmark to identify the poor. In other words, we define anaugmented poverty line where the traditional absolute poverty

benchmark level is marked up by the estimated cost of insuring

against what are considered socially unacceptable risks. We then

discuss the practical implications for implementing such a measure

and future research directions.

HUMAN DEVELOPMENT NETWORK

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