Transcript Household Vulnerability Index (HVI) for Quantifying Impact

Piloting the Household Vulnerability Index to Improve
Resilience of Vulnerable Rural Households in Lesotho,
Swaziland and Zimbabwe
Presentation by :
Tendayi Kureya
Development Data,
[email protected]
FANRPAN Partners meeting,
Pretoria
23 June 2009
Context
Policies backed by evidence are required to transform
the lives of the poorest in a regional context of:
• Increasing food prices
• Limited food production or access
• Declining global food availability
• Climate change, need for bio-fuels,
• HIV and AIDS,
• dynamic communities (gender , power, politics)
About the pilot project
In February 2008, WVI in partnership with FANRPAN agreed on a
2-year project to assess household vulnerability and improve
resilience using the Household Vulnerability Index (HVI) in
three pilots of WVI’s development programmes.
 The goal of the project is to:
apply the HVI to improve development responses in three pilot
Area Development Programmes (ADPs) in Lesotho, Swaziland
and Zimbabwe.
Results expected
1. Database and index that is community owned and
regularly updated to:



Improve targeting
Facilitate integration of interventions and actors
Provide evidence base
2. Paradigm shift/change of mindsets


Evidence based community participation in development, focusing
on ownership, collaboration and sustainability
Govt, Civil society and academia integration in development work
3. Policy options


Prioritizing limited resources
Assessment of Impact
A brief note about the HVI
 It is a powerful statistical index for measuring vulnerability.
 It categorizes a household by assessing “external” vulnerability
that is introduced by shocks and “internal” vulnerability or
inability of such a household to withstand shocks, then classifies
the household as coping, acute, or in an emergency situation,
depending on the household’s ability to prevail.
 It was developed between 2004-7 using thorough statistical
research methods on data from seven (plus three) countries.
 It uses Fuzzy logic on 15 variable classes or dimensions to explore
the relationships between vulnerability and households’ access
to and use of 5 capital assets. (In English: It assesses a combination
of truths about a household's behaviour on the capital assets to
conclude on its degree of vulnerability or resilience).
Coping- able to
adjust and prevail
Households
The theoretical HVI model:
Each with different
Natural, Physical,
Human, Social and
Financial Capita assets
Shock such as
HIV and AIDS
Acute- able to meet
minimum requirements
with some help
Emergencyunable to meet
requirements
External
vulnerability
X
Internal
vulnerability
=
Resultant impacts
Database
 Developed as an advanced standalone software
capable of storing, retrieving and searching
million of records
 Available as self-installing software on CD, and
soon to be on FANRPAN website
 User-friendly menu system employed, with
ongoing tweaking to increase usability.
 Data analysis done using most common statistical
applications (SPSS, Epi Info, SAS etc)
Swaziland Example
 Dynamic database with 3212 Households’ data and >18,000
occupants.
 Data collected using enumerators form target community,
with significant support from the Central Statistical Office,
local authority, NERCHA and CANGO.
 High level of support from local politicians, community
leaders, and community members (8/3212 households
refused to be interviewed- 5 because head was away and left
instruction not to talk to strangers).
 Data entry and analysis nearing completion, and some
results are ready for sharing
Selected Results from Swaziland
Swaziland context
 > 60% rural is into subsistence farming,
 cattle are status symbols
 land area of 17364 sq.km but only 11% is arable
 69% of the population lives in poverty: on less than US$1 a day.
 Overgrazing, soil depletion, drought and floods are problems
 Life expectancy dropped to 33 years down from 49 years in 1975
 52% have access to clean water and sanitation
 below-five infant mortality rate is 156 per 1000 births.
 16 doctors for every 100.000 people
 world’s highest HIV prevalence rate- 33.4% of 15 and 49s.
1. New data has allowed us to correct
flawed planning data available
 Population for Mpolonjeni was estimated at 24, 000. It
actually is 18,947
 73.6 percent of the population was said to be females and
26.4 percent males. Actually, 51.2% are females, and 48.9%
are males.
 3,230 households. (3212 from the census)
 33.7 percent households headed by women (32.4% from
census)
2. New Data has helped magnify the
size of the development challenge
 Literacy levels are low (26% are illiterate, 34% have some primary
education). 2% have some university or college education.
 Only 7% fully rely on own production of staple foods, 60% purchase,
24% rely on donations. 85% indicate they have no reliable secondary
source of food.
 2506/3212 (78%) have received food aid, of which 46% were within
the last month
 30% of households have a salaried household member
 As many as 88% of individuals indicate they have no reliable source
of income (this includes half of those with a salaried household
member)
Example Question: how is food aid assisting or stifling own production
or other sustainable efforts?
Main Income sources
Income source
Household incomes
Not specified
Trading
Salary
Remittances
Other
Livestock sales
Informal work
Government allowances
Donations from NGOs
Crop sales
6.9
6.4
30.8
12.5
1.4
2.7
Percent
23.5
12.9
0.7
2.3
Frequency
3. Development Responses have not always
been logical
Example:
 More than 90% of households have a reliable water
source, yet 33% have no toilets!
 To solve the urgent sanitation problem means
constructing 1000 pit latrines (with community input)
for US$ 300,000 cost which is the same cost as 50
boreholes or 1000 tones of food aid (US$300/t)
(enough to feed this community for 5 and half
months!)
4. Development responses have not necessarily
been responsive to expressed needs
 80% of parents express need for support with school
fees, but do not always get this support.
 Parents (48%) and Government (35%) are paying most
fees.
 Result? Literacy levels are low (26% are illiterate, 34%
have some primary education). Only 2% have some
university or college education.
Who is sponsoring school fees?
World Vision’s
primary focus is
under five mortality
5. Using the HVI, we can get even more
detailed insights…
•Viable/Coping level Households: HVI<47 Total: 41.3%
•Acute level Households: 47<HVI<63.1 Total:54.2%
•Emergency level Households: HVI>63.1 Total 4.5%
Capital
Human
Natural
Minimum for Coping level households
 Household is headed by an economically
active household member
 Dependency ratio is low, less sick
household members and no orphans.
 At least two economically active
household members.
Minimum for Acute level households
 Household is headed by an economically
in active, elderly or child
 Dependency ratio is high, more orphans
and sick household members.
 Economically active household members
are few.

Household use both inorganic and
organic fertilizers
Medium agriculture activity
Utilize much land for subsistence farming
They can fairly manage the environment

May receive some means of support from
NGO’s and government
More knowledgeable on agric and
HIV/AIDS and issues are discussed
regularly in homes
Have a diversified income source
Household income is used on a balance of
needs (farming inputs, education, health,
recreation etc)
Own important livestock eg cattle, in
sustainable numbers
Have labor for farm and off farm work
Receive some agricultural extension
services




Social


Financial 

Physical







Organic fertilizers are the main sources
of fertilizers
Low agriculture productivity
Utilize less land for subsistence farming
They cannot manage the environment
well
Receive support from NGO’s and
government
Most of the support goes to food and
health


Have no basic source of income
Most of the household income is used on
food and medicines

Own cattle, a very important livestock in
agricultural production
No labor for farm and of farm work
Do not own farm implements
Do not regularly eat three times a day



HVI categories based on poverty as the shock
(generic model):
Coping level
Households:
HVI<47
a) Total: 41.3%
b) 60% are
cultivating a
proportion of their
land
c) 25% headed by
women or children
Acute level
Households:
47<HVI<63.1
a) Total:54.2%
b) 72%
c) 33%
Emergency level
Households: HVI>63.1
a) Total 4.5%
b) 85% are cultivating
only a proportion of
their land
c)45% headed by
women or children
Conclusions
 Now we are able to pinpoint vulnerable households
with accuracy
 There is overwhelming evidence in support for a
paradigm shift regarding what we believe communities
need, how to integrate programmes, and on choices
given limited available resources,
 We can then plan in advance, and implement
objectively
 The possibilities for further data analysis are limitless
 Over time, we are able to assess impact
Selected Lessons
 Project pace unavoidably determined by levels of



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stakeholder engagement- significant resources ($, time etc
required for mobilisation)
Resistance and fear of data require champions
Communication/visioning of the HVI approach is different
for different stakeholder groups-messages needed to be
carefully developed
Clients (WVI) have conflicting priorities given the macro
environment. (flexibility is key)
MDGs reporting requires this level of detailed analysis (at
least)
Gaps
 Resources not adequate- financial, equipment, human
capacity
 Pace not entirely determined by FANRPAN
 Different components (University input,
communication etc still need to be better coordinated)
Thank you