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​​​​​​FAQs​


▻ Isn’t HEA an early warning tool?

Since the late 1990s, HEA has been adapted for use in various settings and for a range of programming needs. It has been used in rural and urban contexts, in areas prone to food crises as a result of droughts or market shocks, in countries with established, national early warning systems, in emergency and development contexts, and in refugee and IDP contexts. It was originally developed as a tool for early warning of acute food insecurity but is used increasingly in wider program design including social protection and livelihoods programmes.

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Apart from early warning, it has been used for identifying the most effective income generation activities; livelihood programme design; social protection program design (targeting; setting transfer levels; designing monitoring); geographical targeting; monitoring and evaluation of project impact on beneficiaries (pre-/mid-/end project); and resilience measurement.                 

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▻ Does HEA require a high level of technical skill and a lot of training?

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The framework itself is transparent and easy to understand. Expertise is needed in baseline data collection, to ensure rigor and quality, and in performing outcome analysis, which is normally done using one of two Excel-based HEA tools called the Dashboard and the Livelihoods Impact Analysis Spreadsheet (the LIAS).                

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There are tried and tested training programmes for both baseline and outcome analysis. Some HEA applications may also require expertise in monitoring, such as the ability to identify the factors that need to be monitored in an early warning system or during the life cycle of a project, and how that might be done. But an important factor in whether someone becomes a skilled HEA practitioner is the availability of regular opportunities to apply what they’ve learned after the training.                 

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▻ Is HEA valued by donors?


HEA is an internationally recognised livelihoods framework and has been used for over 20 years in around 50 countries by different humanitarian and development agencies and government organisations. Over 540 HEA baselines have been developed by SC and partners (mostly in Africa, but also in Asia and Latin America).                 

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Donors value it as a rigorous, cost-effective approach to identifying when, where, how much and to who assistance should be given. They value its potential to achieve results at scale.                 

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For example, SC’s HEA Sahel Project was funded by ECHO since 2010 and co-funded by OFDA since 2013 and has led to over 90 HEA livelihood profiles in the seven targeted Sahel countries. Outcome analysis is carried out twice per year by HEA Working Groups to inform national and regional early warning frameworks and is one of the key data sources within the analyses.                 

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▻ Who are FEG?

The Food Economy Group (FEG) is a consulting group who play a central role in the implementation and continued development of HEA. They developed the HEA spreadsheet tools (the baseline storage spreadsheet, the Dashboard and the LIAS). They provide HEA services to a range of NGOs (including SC), international agencies and governments. They offer training and expertise in the customisation of HEA for particular purposes and contexts.                 

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▻ Can HEA be used to look at the impact of poverty and shocks on children’s wellbeing?

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While the HEA framework centres on the economic activities of households, it is recognised that, for Save the Children programmes, the focus needs to be on children: their survival, education, health, protection and nutrition. Standard HEA expenditure data includes spending on education and health, and this can be disaggregated further, for example to record specific school expenses (books, uniform, school fees) or healthcare costs for particular household members (girls, boys, adults). Some HEA baselines (e.g. in Ethiopia) incorporate information on who within the household, disaggregated by age and gender, generates most of each food and income source. This could be built on to look specifically at income from child labour.                          

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In a study in the Sahel in 2017-18, a process was designed to calculate ‘sector minimum expenditure baskets’ (sector MEBs) and to modify HEA tools to incorporate MEB resilience analysis. This came about in response to a call for a deeper analysis of household spending in key sectors concerning the welfare of children (such as health, education, sanitation and hygiene) which could be compared with the cost of meeting sector standards.                          

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The sector MEB is based on the cost of internationally accepted standards for health, sanitation, hygiene, shelter, household goods (cooking, lighting, sleeping and being clothed), education, basic livelihood inputs, protection in times of violence, community contributions (“social inclusion”) and a healthy diet. The MEB threshold is typically constructed per person or per household but costs can be separated out by age and gender if an analysis of children’s wellbeing, for instance, is required.                          

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The sector MEB threshold provides a higher measure of the resources needed to live at a certain standard of well-being compared to the HEA livelihood protection threshold.                          

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▻ Does HEA offer the disaggregated information necessary for social protection design and targeting?

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Programme planners may require data that relates to households defined in ways other than by wealth: households with children, pensioner- or female-headed households, or those with orphans or people affected by HIV and AIDS. Is HEA a relevant tool for that purpose?                          

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The HEA framework does not preclude the study of groups of households defined by demographic or other characteristics. Different sampling and analytical methods can be used. The four-way wealth breakdown is not a division that, on its own, meets every information need; determining ways of helping the poorest will commonly require paying more attention to particular subgroups within the ‘very poor’ or ‘poor’ categories. For example, poor female-headed households have been the subject of separate inquiry and have been investigated using purposive sampling.                          

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It is worth pointing out, however, that the detail offered by an HEA analysis that looks at four wealth groups already adds great value to the design and targeting of social protection transfers. The characteristics of the ‘very poor’ or ‘poor’ wealth groups in terms of livestock and land ownership can be turned into targeting criteria, which can then be ‘passed back’ to community leaders or committees to identify individual households eligible for assistance.                          

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Interviews with individual households have also been used in conjunction with other methods to gain a deeper understanding of the extremely poor and of the impact on households of chronic illness. Such in-depth micro-studies can be very effective in complementing existing national datasets such as household budget surveys, and in highlighting ways of helping very poor households.                          

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▻ Can HEA be used in complex emergencies and protracted crises?

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HEA has been used in several complex emergencies, ranging from Burundi to Somalia to Kosovo. While the logic of the HEA framework has been applied no matter what the circumstance, field methods have been adapted so that as much relevant information is collected and interpreted by whatever means are possible in the situation. Where travel for international staff is restricted, for example, it may be possible to train teams centrally and manage the field work remotely.                          

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In contexts that are fluid, unpredictable and potentially inaccessible, a methodology like HEA that allows for scenario-based projections can add value.                          

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HEA does not aim to provide an analysis of the social and political determinants of complex crises, although these are naturally taken into account when looking at livelihoods.                          

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▻ Can HEA be used with Cost of the Diet analysis?

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HEA is often used in conjunction with CotD as their analyses complement each other. CotD allows users to estimate the cost of a diet which has recommended levels of energy, protein, fat and micronutrients, while HEA gives a detailed picture of household income and expenditure. The results from CotD can therefore be compared with HEA data and the affordability of a nutritious diet for each of the wealth groups (very poor, poor, middle and better off) can be estimated. This information can be used:                         

- to assess if poverty prevents poor households from obtaining a varied, nutritious diet                          

- to estimate the size of cash transfers for social protection programmes intending to have an impact on nutrition through the diet                          

- to model the impact of potential interventions on improving the affordability of the diet                         

- to inform ‘Cash Plus’ for nutrition programmes and other livelihood/nutrition programmes.                         

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A review of HEA and CotD studies in Asia provides a useful overview of how information from the two tools complement each other and provide insight into how best to support children in poor households. See ‘How Families Cope with Poverty in Asia: Lessons from a Multi-Country review of Household Economy Analysis and Cost of the Diet Assessments, 2011-15’.                         

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▻ What resources are needed for HEA?

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The main cost in HEA is in doing the baseline assessment. A full HEA baseline takes four weeks and requires about 4-8 people and at least one experienced HEA practitioner.                          

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But a baseline is valid for 5-10 years, during which the data can be used both on its own or as the basis for outcome analyses, to model the effect of change. Its cost-effectiveness should therefore be considered in terms of its utility over this period.                          

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Outcome analysis (or scenario analysis) requires 3-5 days of training. Training in the gathering of monitoring data to feed into the outcome analysis may also be needed.                          

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An HEA baseline involves the following:                          

Week 1: training in concepts and data collection.                          

Weeks 2 & 3: data collection. Involves discussions with key informants at a district or regional level and community-level interviews in 8-12 villages.                          

Week 4: entering and analysing data.                          

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For baselines carried out to inform more localised project work, the coverage of a smaller area may be offset by the need to obtain more disaggregated data or to spend more time doing separate interviews with men and women.                          

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For rapid baselines, usually associated with emergency needs assessments, the number of villages, the number of interviews and the quantity of information collected may all be smaller. But rapid HEA needs to be led by a very experienced HEA practitioner.                          

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Apart from staff and training, other resources for doing a baseline include:                          

- transport to the region and in the field                          

- accommodation for national/international consultants (if required)                          

- expenses and per diems for staff                          

- stationery, paper and printing.                          

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▻ Why does an HEA baseline require so much training? Is it worth it?

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Conducting an HEA investigation in the field is a technically demanding task. This is not a questionnaire system, with enumerators filling in forms and the entire data analysis carried out by someone else later. HEA field workers have to be analysts, checking the information makes sense as it is recorded in the field and asking further questions when it does not.                          

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So HEA does ask a lot from field workers and this means that more time is required for training than for a typical sample survey. But there are benefits. Staff develop a better understanding of the concepts of livelihoods and food security in general, and of the population under investigation in particular. There is also a greater sense of shared ownership of the analysis and output.                          

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In this way, an HEA assessment is not only an exercise in obtaining information but a process of building the confidence and capacity of staff to construct an account of livelihoods for themselves. For staff who are also involved in designing and implementing interventions, these skills can enhance their work considerably.                          

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Investigators in any kind of survey have to understand the basics of the subject and how to do basic cross-checking. The point is not that HEA methods themselves require highly trained staff, but that high-calibre staff are needed by any method that seeks to provide valid data on livelihoods.                          

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▻ Is an HEA baseline expensive?

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A full HEA baseline, including training, involves up to four weeks of staff time, expenses and per diem costs. However, an HEA baseline is usually done using rapid appraisal methods, which tend to be less costly than sample surveys, in which the larger sample size tends to push up both the transport and staff costs. HEA rapid appraisal methods tend to place more emphasis on a small quantity of higher quality data, rather than a large quantity of lower quality data.                          

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In terms of time, experience has shown that the time taken for both HEA field work and analysis is actually short compared with most sample surveys that collect similar information. The results of sample surveys are rarely available until at least a month (and often much longer) after the completion of the field work.                          

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The biggest expense in HEA tends to be that of international consultants. This is true of many approaches to data collection. But HEA is at its best and least expensive when it has become institutionalised and where most activities, including training, are done by national staff. In such cases, international consultants are called on only for quite specific and short tasks.                          

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But the fact is that good quality information has a cost. There is no point in attempting an HEA exercise without the minimum resources to provide a reliable result. Experience has shown time and again that in the long run, the cost of decisions made on the basis of poor information can be very high, in terms of missed opportunities to limit suffering as well as material wastage.                          

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▻ Is HEA always done in the same way?

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HEA is an analytical framework, not a method of information collection. It is not restricted to a single data collection method. HEA baseline data is most commonly gathered using rapid appraisal methods because experience has shown that these methods are an effective and efficient way of gathering and crosschecking the required information, given the time and funding usually allowed. But HEA can use data gathered using a broad range of tools, provided that appropriate measures can be taken to ensure data quality.                          

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While the HEA framework has remained constant, the methodology has been adapted to reflect differences in context, purpose, geographical access and security, and the time, staff and funding available. HEA in urban areas requires a different approach from HEA in pastoral areas in terms of information requirements, sampling methods and analysis, just as an assessment to compare the livelihoods of IDPs and their hosts requires a different approach from the use of HEA in a national early warning system in southern Africa.                          

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For example, evaluations of project impact using HEA commonly use Individual HEA (IHEA), in which interviews are carried out with individual households rather than with focus groups. IHEA has been carried out in Sri Lanka, Indonesia and Lebanon, using a randomised control design based on two-stage sampling and using the probability proportional to size technique.                          

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Rapid HEA is another variant of standard HEA and is used in emergency situations when it is not possible to do a full HEA assessment. The methods used in rapid HEA vary. Some rely heavily on key informant interviews, some use focus groups but with less detail, some use large numbers of short individual household interviews, and some have used a detailed case-study approach with a small number of households or a small sample of villages. Combinations of these have also been used.                          

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▻ Why do a full HEA if you can just do a faster, cheaper rapid assessment?

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Rapid HEAs should not be a first-choice type of assessment because they require significant compromises in the level of detail collected and almost invariably in the reliability of the data. The reduced data-set and number of interviews means there are fewer opportunities for cross-checking the information.                          

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Also, with a standard HEA baseline, you can re-use it year after year and the short-term investment in gathering baseline data pays off over the long run. However, it is not recommended to re-use the baseline gathered in a rapid assessment, and therefore the return on the investment in a rapid assessment over the long term is not high.                          

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▻ How is HEA baseline information collected?

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The technique most commonly used to obtain baseline HEA information is the semi-structured interview. This is an interview in which the interviewer knows exactly what questions ultimately need to be answered but does not obtain the information through a pre-defined list of questions. Rather, they have the flexibility to pose questions in the way and order that they think will be most effective in getting that information, using simply a checklist as an aid.                          

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For example, the interviewer knows that they need details of the interviewee’s income, but may not know all of the ways by which the interviewee earns money. Interviewers are also encouraged to cross-check their information and challenge the interviewee when different pieces of information contradict each other. Although they are more demanding in terms of time, training and the calibre of the interviewer, such interviews have a number of benefits over a questionnaire approach.                          

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For more detail, see Chapter 4 How is HEA done? in HEA: A Guide for Programme Planners; and Chapter 3 Baseline assessment in The Practitioners’ Guide to HEA                          

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▻ If quantitative survey results are statistically valid, doesn’t that mean they are more robust than HEA data?

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Not necessarily. Data quality is not so much related to the method itself, but how the method is implemented in practice. There is good and bad practice in every research method. Statistical validity is an appealing concept, and when the data itself is of good quality then tests of statistical validity are important for demonstrating that the results are reliable. However, it is possible for bad data to be statistically valid, for example if the question was poorly phrased, or if the answers given were subject to some bias. Similarly, good practice in qualitative research can lead to robust data, while poor practice will lead to unreliable information.                          

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For more, see Reliability, representativeness and rigour in HEA: HEA and rapid rural appraisal methods by FEG (2018).                          

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▻ Are livelihood zones of practical use, given that they do not always follow administrative boundaries?

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It is quite common to find different patterns of livelihood within one district, and certainly within one region. In Swaziland, for instance, all four administrative regions contain parts of several different livelihood zones, reflecting lowveld versus middleveld ecologies.                         

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However, decisions on resource allocation and service provision are made on the basis of administrative areas and units, so HEA livelihood zones tend to be aligned as far as possible with lower-level administrative or customary boundaries. In Malawi they have been lined up with Extension Planning Area (EPA) boundaries; in Swaziland with chiefdom boundaries. This way, populations in the livelihood zones can be identified and responded to along administrative lines, and a more disaggregated analysis can be carried out using data relating to lower-level administrative divisions, where it is available.                          

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▻ By including particular coping strategies in the outcome analysis, aren’t you trying to predict how households will behave in a crisis?

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In HEA, the most important characteristic of a response or coping strategy is its cost, where cost is measured in terms of the effect on livelihood assets, on future production by the household, and on the health and welfare of individual household members.                          

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But including a particular coping strategy in the analysis does not imply that households will necessarily follow that strategy. For example, if the analysis takes into account the income that could be earned from the sale of additional livestock, it does not imply that households will necessarily take up that strategy. They may decide instead to employ one or more of the other strategies open to them, including those considered to be damaging in some way; they may reduce food intake, or send a household member away permanently to find work.                          

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The point is that the analysis of household response is not an attempt to model behaviour – that is, to predict which options households will take up in a crisis and which they won’t. Rather, it is an attempt to define a level of access below which households have little choice but to pursue strategies that are likely to be damaging in the long term; in other words, a level of access below which the analysis shows that intervention is appropriate.                          

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▻ Does HEA exclude coping strategies that are damaging for the environment such as firewood sales?

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Outcome analysis allows the user to exclude medium-cost coping strategies which, in the local context, are considered damaging to people, their livelihoods or the environment, or that would affect their ability to recover from a shock. These include increased livestock sales, crop sales and gifts, intensification of local labour and self-employment activities, and increased firewood and charcoal sales.                          

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▻ How frequently should we conduct baselines for a given livelihood zone in contexts that are very fluid?

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In stable circumstances, a baseline is reckoned to be valid for between 5 and 10 years. What may vary is the prevailing level of food or livelihood security, but this is a function of variations in hazard, not variations in the underlying pattern of livelihood.                          

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In unstable circumstances, where, for example, conflict radically changes people’s asset base and the sources of food and cash that they can access, a baseline would need to be redone sooner. However, the investment of a full baseline may not be cost-effective in a context that is extremely fluid and where the baseline data is likely to become invalid after a very short time.                          

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Thus, a baseline conducted during a ‘rapid’ HEA (usually carried out in emergencies) is not valid beyond the year when the assessment is carried out. Rapid HEA tends to involve fewer interviews and a reduced information set.                          

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▻ Is HEA statistically rigorous?

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It is sometimes thought that the only ‘real’ information is that based on statistically based sample surveys. However, statistical approaches are not the only form of ‘rigour’. Statisticians will be the first to point out that random-based or probability statistical sampling may guarantee an equal chance for people to be represented in a given area, but in no way guarantees the accuracy of reported data.                          

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Whether data is collected by means of statistically sampled household interviews or through interviews of carefully identified focus groups, what is important is how well it is done – and what means there are to promote accuracy.                          

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For more, see Reliability, representativeness and rigour in HEA: HEA and rapid rural appraisal methods by FEG (2018).                          

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▻ Shouldn’t HEA consider the non-economic root causes of poverty?

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HEA is an economic analysis and would need to be combined with additional tools to analyse non-economic factors in depth. However, HEA might be considered as one of many approaches or specialisms that have something indirect but important to contribute to such analysis of non-economic factors.                          

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The holistic description of livelihoods strategies and assets offers an acute view of poverty – for instance, of the resource constraints faced by poor people, and how they try to maximise what they can do with what they have. It describes in detail wealth divisions that are often all but invisible to outsiders, but which reflect among other things differential political and social power and influence.                          

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This interface between the economic and the non-economic enables HEA to help identify in broad terms the non-economic root causes of poverty, whether these be political marginalisation and insecurity, as in the Turkana region in Kenya or inequitable land distribution, as in the Thar Desert in Pakistan. Further analysis of such structural determinants of poverty is the province of other specialists.                          

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▻ How was HEA developed?

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It was developed by Save the Children in the early 1990s to improve the analysis of people’s access to food in areas prone to food insecurity or famine. The aim was to provide decision makers in famine early warning with more rigorous and more reliable information with which to judge when and how to assist potentially food insecure populations. Since then it has been adapted for use in a wide range of geographical and programming contexts: in rural and urban areas, in refugee and IDP populations, and in social protection, project design, targeting, and monitoring and evaluation.                          

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For a fuller history of HEA, see ‘Livelihoods at the Limit: The Story of Household Economy Analysis’.