The Household Economy Approach (HEA): ‘regular’ and ‘lite’

The agenda:

3. The method:getting the informationusing the information

1. Background: exchange entitlements.

2. The criteria for a useful method.

4. Other uses and ‘lite’.

Until the1970s, the ‘cause’ of famine was still a mystery. For example it was observed that:

Despite widespread and sometimes deepening poverty, famine was rare. In the 20 years to 1990, & not including siege, perhaps 10 -15 cases, some very local.

Famine mortality was low – typically 3-5% above expected mortality.

Although most famines were preceded by production failure, production failure rarely led to famine. Some famines were not preceded by production failure.

The explanation was provided in two parts:

1. Sen’s (1981) theory of ‘exchange entitlements’ which provided a theoretical framework capable of explaining all famines.

The observation that, when possible, people took steps to protect themselves against production failure and other shocks – so called ’coping strategies’.

Source: NASA

NDVI, Africa, June 1984

‘Coping strategies’. People:

keep food stocks, cash savings, livestock and other goods, which can be exchanged for food.

have systems of mutual insurance – ‘gift, reciprocity and obligation’

and may be able to survive by:

expanding existing sources of income e.g wild foods, paid work, reducing non-food / food consumption

‘Exchange entitlements’:

A household (or person)'s ability to acquire food depends upon its ‘entitlement set‘

in practical terms essentially the sum of its current income, food stocks, and the exchange value of its labour and other assets.

This is independent of the adequacy of aggregate food supply.

‘Coping strategies’ are a way in which households seek to maintain entitlement.

The corollary to entitlement theory is that

the prediction of the effect of a ‘shock’ on the ability of an individual or household to acquire food requires a knowledge of that person’s or household’s entitlement.

A difficulty: the value of entitlements may change as a result

of a shock e.g. the collapse of livestock/ labour prices and a rise in the price of food.

Sorgum and goat prices, El Fasher, Sudan, 1990

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Sorghum

Goat

2. Criteria. An operationally useful method is one which :

can discriminate between and within populations (the poor, better off) at an operationally useful level of disaggregation.

is practical i.e. can be used on large areas of diverse economy, in war zones, at reasonable cost, by ‘non specialists’

provides output in terms which are useable by governments and donors

works i.e. produces accurate output

works in the context of the (usually) low quality of official data on crop production and other shocks.

The logical solution was to see if it was possible to develop a model of rural economy based on current quantitative economic descriptions, obtained using ‘rapid’ field methods, to simulate the relationship between a shock and an outcome. Subject to:

the model being comprehensible to the user - not a ‘black box’

for uncertainty in prediction – an analysis yields a hypothesis which predicts changes which should be monitored and observed if the hypothesis is correct e.g. if an analysis suggested that people will sell livestock people should be observed doing this.

This approach had the potential advantages of allowing

complex multivariate problems to be managed in an agreed framework, while retaining scope for disagreement about matters of fact. Different users might obtain a different estimates from the same data.

different interventions to be tested e.g. the effect on access of holding down cereal prices can be tested

Data required to estimate household entitlement

The minimum data set includes:

the household’s sources of food and non-food (usually cash) income in a reference year.

household assets - food stocks, cash savings, livestock & other tradable assets.

A description of the relationship between the household and the wider economic context: • the market for food, labour and other goods• the ‘commons’ - hunting, fishing, wild foods• other households - gifts & other ‘non-market’ exchange

For SCF, the central interest was to see if a model could be developed which was sufficiently sensitive to reliably predict the effects of shocks ‘short of starvation’ i.e. when households

reduce non-food expenditure (education, health, fuel, clothes) to meet food costs.

are impoverished, as assets are exchanged for food.

Getting the information:

Defining the population(s)

Choosing the locations for interviews

Defining wealth groups at each location

Collecting household budgets for each wealth group

Analysis

The techniques have much in common with ordinary survey techniques. An HEA assessment typically has 5 stages:

Populations are defined as:

Populations of households which share a ‘reasonably similar economy’: boundaries often follow agro-ecological zones.‘Reasonably’ is defined by the purpose of the assessment.

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Arusha Region

Sing ida Reg io n

T an g a Reg io n

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Sampling:

Is purposive, not random

Up to 10-15 sites may be visited in each defined population

At each location in each area a wealth distribution is established with key informants. The definition of wealth is that used locally

Household interviews are conducted with a group drawn from a wealth group:

Allows people to discuss a ‘typical’ household from their wealth group. This avoids the need to discuss the income and expenditure of a specific family.

Groups typically include men and women. In addition, children are sometimes interviewed.

Calendar of agricultural and other productive activities, Lower Kitui District, Kenya 2000. (SC

(UK))

The reference or baseline year

In areas subject to continuous disruption e.g. parts of South Sudan, the reference year is usually the year preceding the interview.

Group interviews refer to to a defined reference year.

This may be an actual year, or (particularly in areas where income fluctuates markedly from year to year) a spread of years which, taken together, make a ‘reference period’.

Data quality.

In any interview, income and expenditure should balance.

Food income should be in reasonable balance with household energy requirements.

Transactions – chiefly paid work and gifts – should balance between suppliers (mostly

‘the rich’) and the recipients (chiefly ‘the poor’).

Analysis:

Uses a simple arithmetic model to relate a ‘problem’ - a description of an ‘economic shock’ to an outcome. The likely effect of the shock on the ability of households in each wealth group to acquire food and non-food goods.

The model can be used by hand, on a spreadsheet, or for large data sets using purpose designed software - ‘RiskMap’.

Ranges

Data from household interviews in the same population and wealth group are resolved into ranges. For example:

Barley production in the ‘very poor’ wealth group’ in population X is

35-45% of annual household requirement.

3 steps in analysis:

1. Defining the problem or ‘shock’

3. Estimating the ability of each household type to compensate for any deficit in step 2.

2. Calculating the immediate effect of the problem on the ability of each household type to meet its requirement for food and non food goods

Step 1: Defining the problem (1)This has been the greatest difficulty. In most countries:

Crop statistics are, at best, rough estimates.

Information on other types of production e.g. rangeland conditions, fishing, is rarely gathered at all.

There may be little information on levels of country/ regional food stocks, imports, & donor intentions to supply food. It may be difficult to estimate the market supply of food.

Step 1: Defining the problem(2)

The problem is usually defined from local estimates of:

likely production deficits, where possible based on prior examples of similar e.g. climatic, situations.

probable price changes, given a particular level of production.

Several ‘scenarios’ may be developed to cover a range of possible situations e.g. with and without price support.

Step 2. Calculating the deficit

For example, if a household usually gets 50% of its income from food crops, a 50% fall in food crops will lead to a 25% fall in household income.

Sources of food

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green beans

avocado

sw eetpotatoes

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green maize

Sources of cash income

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casuallabour

brew ing

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Expenditure

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tobacco / drink

education

health

diesel

firewood

soap

matches

dried fish

salt

oil

cabbage

beans

sweet potatos

maize

rent

Step 2. Deficit calculation

Huambo 2000. Household of 6

Step 3. Estimating the ability of a household to overcome the deficit.

This requires making allowance for:

Household food stocks (by addition).

The possible expansion of income from wild foods & gifts (arithmetic).

Additional income from the sale of livestock, labour and other non-food production (arithmetic or using a linear supply/ price model.

Output

The aim of analysis is to develop an argument about the likely effect of a shock, where the argument is :

based on a ‘complete’ information set and areas of uncertainty e.g. the quality of specific data items, are revealed.

open to test and if necessary revision as events develop and if predicted events do not occur e.g. asset sales, reduction in meal frequency, falling nutritional status

transparent and open to dispute

The aim of HEA is to allow the user to think through and systematically manage a complex problem.

Where is HEA used? Who uses it?

SCF with WFP/FAO

National programmes

SCF

Method adopted by FEWSNET, SADC,WFP

+ many area/ refugee assessments

+ Afghanistan

Costs

The largest cost is in establishing the baseline economic description.

Maintaining a system is relatively cheap. The actual cost depends chiefly on who is doing the work, being comparatively higher where fieldwork is done byexpatriates: much lower when by national staff.

Predicted food needs, Malawi, 2002.

Using all ‘coping’ steps 10,600 - 18,000 MT

RiskMap: %

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Using no ‘coping’ steps16,000 - 29,000 MT

Estimated deficit for Malawi 2002 = 580,000 metric tonnes

1. HEA provides a way of measuring ‘vulnerability’ to food insecurity, where vulnerability is defined as:

the effect of a defined event (e.g. a price rise) on the ability of a household/ population to access sufficient food.

Other uses of HEA

2. HEA has proved to be a very effective way of teaching non-specialist staff the elements of rural economy.

3. HEA has been used to evaluate food aid interventions.

4. HEA can be used to show the effect of other economic changes on livelihoods. Trials are currently underway in Kenya to see if HEA can effectively show the effect of changes :

to textile import tariffs on populations partly dependent on employment in the textile industry.

in international coffee prices on small scale producers

HEA ‘Lite’Most of the time and cost of HEA is in acquiring the data.

Data can be obtained entirely from ‘key informants’ with large savings in cost and time.

On current evidence (chiefly a national database in Malawi) data quality suffers only in the loss of detail. Where HEA is used to estimate large changes e.g. crop failure, large price changes, this is unimportant.

HEA also provides a very useful framework for rapid investigation of food security in e.g. single households.