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Wealth Quintile

Indicator Phrasing

% of the target population in the bottom wealth quintile of the national population
See indicator in other languages

Indicator Phrasing

English: % of the target population in the bottom wealth quintile of the national population

French: % de la population cible dans le quintile bas de richesse de la population du pays

Spanish: % de la población objetivo en el quintil de riqueza más bajo de la población nacional

Portuguese: % da população-alvo no quintil inferior de riqueza da população nacional

Czech: % členů cílové skupiny, kteří jsou v ekonomicky nejslabší pětině národní populace

What is its purpose?

The indicator shows the percentage of the target population in the bottom national wealth quintile (i.e. it compares the wealth status of your target group to the wealth status of the country’s population). The data can be used in two ways: 1) for disaggregating and analyse your M&E data by wealth categories; or 2) for assessing the impact of longer-term livelihoods projects with a strong income/assets-generation component.

How to Collect and Analyse the Required Data

The indicator’s value is determined by asking a representative sample of the target group members a set of country-specific questions about the ownership of various assets. The EquityTool offers relevant questionnaires for more than 40 countries. On average, each respondent is asked 12 easy-to-understand questions. The main steps of the data collection and analysis process include:

 

1) Verify whether the survey dataset (questionnaires, data analysis guidance) is available for the country where you intend to conduct the survey on the EquityTool’s website. If not, you have two options:

  • if you are not in a rush, contact Metrics for Management to explore opportunities to create an EquityTool for your country (keep it mind that this will take some time and other resources)
  • if you cannot wait, review other indicators and choose the one that best fits your needs

 

2) Choose your data collection platform, such as the EquityTool’s app or your own system (such as KoBo software or paper questionnaire).

 

3) If you do not use the EquityTool’s app, download an Excel file with instructions and questions and transfer the questions to your data collection platform (online or paper questionnaire).

 

4) Collect the required data by conducting interviews with a representative sample of the target household representatives.

 

5) Analyse the data in Excel, STATA, SPSS or any other platform by following the guidance provided at EquityTool’s website.

 

6) To calculate the indicator’s value, divide the number of households in the lowest wealth quintile of the national population by the total number of the surveyed households. Multiply the result by 100 to convert it to a percentage.

Important Comments

1) By including the set of country-specific questions in your health, WASH, agriculture or any other survey, you will be able to disaggregate the collected data by wealth. For example, you will be able to see whether the quality of diet consumed by children from the poorest households (i.e. from the bottom wealth quintile) significantly differs from the average quality of children’s diets in general.  

 

2) EquityTool can also be used to show you and your donors the extent to which you target poor households (the higher the indicator’s value, the higher is the proportion of the project beneficiaries that are actually poor).

 

3) EquityTool is based on collecting information about the respondents’ assets. However, assets do not change much over short time. For example, if a household increases its income, it may not necessarily invest it into one of the surveyed assets. This means that this indicator might be less reactive to your intervention. Therefore, if you need to measure changes in the households’ economic status, use this indicator only if:

   - your intervention has a strong income/assets-generation focus; and

   - it is implemented over a longer period of time (at least 2-3 years), so that you can record any changes in the households’ ownership of assets

Otherwise, you risk that this indicator will not be able to show the recorded positive changes, even if your project is successful.

 

4) EquityTool shows you how your target households compare to the rest of the country (it is also possible to have a comparison to the urban population only – see here). The data for the “rest of the country” is gained from the most recent Demographic and Health Survey (DHS), or other nationally representative survey. The DHS usually takes place about once in five years, and EquityTool’s versions are updated as new DHS datasets are released. This allows users to benchmark their results to a more recent national population.

Sometimes, a user may wish to conduct a follow-up survey to a baseline that used a previous version of an EquityTool, and will need to decide which benchmark population (i.e. EquityTool version) to use:

  - i) The version used at baseline (i.e. the same benchmark population used at baseline) – if your main aim is to assess the change in wealth from baseline, use the version that was used during the baseline survey; however, since wealth generally increases over time, comparing the respondents using an old benchmark might result in them appearing wealthier than they are. If you use this option, document the original baseline calculations for later replication or contact Metrics for Management to access the EquityTool’s version that was used for the baseline survey.

  - ii) The latest version – you will be comparing the current wealth of your target households against the current benchmarks of wealth (i.e. not against benchmarks that were valid several years ago); if you use this option, you can always use the latest benchmarks available on the EquityTool’s website.

 

5) As much as possible, correlate the data with the data gained from measuring households’ indebtedness. This will show you, for example, whether households that appear wealthy (based on the type of assets they own) are or are not heavily indebted.

 

6) When interpreting the findings, consider the context in which the data was collected (e.g. poor vs. better-off areas; areas nearby larger towns vs. remote areas).


 

Take advantage of additional tips and guidance provided on EquityTool’s website.

Access Additional Guidance

This guidance was prepared by People in Need ©

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