The Mali EquityTool country factsheet and file downloads on this page are licensed under CC BY-NC 4.0

 The simplest method of collecting EquityTool data is to sign up to our web app. To use the EquityTool in DHIS2 or another data collection platform, you will need to download the supporting file. Click on your preferred data collection method and complete the form to receive the file via email. Please check your junkmail folder if you do not receive an email from us.

    Agree to the Terms and Conditions

      Agree to the Terms and Conditions

      EquityTool: Released July 2, 2019

      Source data: Mali MICS 2015


      # of survey questions in original wealth index: 61

      # of variables in original index: 144


      # of survey questions in EquityTool: 19

      # of variables in EquityTool: 22



       QuestionOption 1Option 2Option 3
      Q1In your house, do you have… electricity?YesNo 
      Q2… a television?YesNo 
      Q3… a bed?YesNo 
      Q4… a fan?YesNo 
      Q5… a cupboardYesNo 
      Q6… a CD/DVD player?YesNo 
      Q7… a refrigerator?YesNo 
      Q8… a chair?YesNo 
      Q9… a motorcycle or scooter?YesNo 
      Q10In your house, do you have soap, washing powder, or ash/sand/dirt for washing your hands?YesNo 
      Q11Does any member of this household have a bank account?YesNo 
      Q12Where is your principal source of drinking water located?Outside of the plot, but less than 30 minutes round-tripWithin the plot, OR more than 30 minutes round-trip 
      Q13Main material of exterior walls of the house?BrickOther 
      Q14Main material of roof of house?CementMud with woodOther
      Q15Main material of floor of house?Earth/sand floorCeramic tile floorOther
      Q16In your house, what is the main fuel used for cooking?CharcoalWoodOther
      Q17Does your household own…. Any pigs?NoYes 
      Q18… Any camels or dromedaries?NoYes 
      Q19… Any Guinea fowl, ducks, turkeys or geeseNoYes 

      Technical notes:

      We were unable to achieve agreement of kappa>=0.75 between the original MICS wealth index and a simplified index using our standard simplification process, detailed in this article. Using a revised approach, described below, high agreement (kappa>=0.75 for both urban and national indices) was achieved.

      To create the EquityTool, we simplify the original full wealth index that is found in the relevant benchmark dataset, usually using published factor weights. In the case of MICS data, the factor weights are not publicly available, however UNICEF has shared the original syntax files used to create wealth indices with us. We attempted to recreate the original wealth index, following the original syntax files.  In this process, we discovered inconsistencies in the provided files, deviating from the stated logic. These inconsistencies were found in two important areas of the wealth index creation: in the creation of 3 variables which form part of the original wealth index, and in the decisions made during principal components analysis on exclusion of variables. We therefore recreated the full wealth index using a process in line with guidance from ICF. We used the factor weights derived from this recreated wealth index to identify important variables, and as the basis for scoring in our EquityTool analysis. Syntax and factor weights available upon request.

      In our standard process, we prioritize variables which appear in the common principal components analysis, indicative of wealth irrespective of urban or rural residence. In the Mali EquityTool, this approach did not result in a simple index, and we included animal ownership in order to better differentiate wealth among urban residents.  Only 26% of urban dwellers own any farm animal, however animal ownership is more common among poorer residents. Inclusion of these variables improved identification of those who are relatively less wealthy.

      The 2015 MICS survey in Mali was conducted in all regions of the country, with the exception of 28 enumeration areas within the regions of Timbuktu and Gao.


      Level of agreement:


      National Population


      Urban only population


      % agreement84.3%84.1%
      Kappa statistic0.7550.752

      Respondents in the original dataset were divided into three groups for analysis – those in the 1st and 2nd quintiles (poorest 40%), those in the 3rd quintile, and those in the 4th and 5th quintiles (richest 40%). After calculating their wealth using the simplified index, they were again divided into the same three groups for analysis against the original data in the full MICS survey. Agreement between the original data and our simplified index is presented above.


      What does this mean?

      When shortening and simplifying the index to make it easier for programs to use to assess equity, it no longer matches the original index with 100% accuracy. At an aggregate level, this error is minimal, and this methodology was deemed acceptable for programmatic use by an expert panel. However, for any given individual, especially those already at a boundary between two quintiles, the quintile the EquityTool assigns them to may differ to their quintile according to the original wealth index.

      The graph below illustrates the difference between the EquityTool generated index and the full wealth index. Among all of those people (20% of the population) originally identified as being in the poorest quintile, approximately 75% are still identified as being in the poorest quintile when we use the simplified index.  However, approximately 21% of people are now classified as being in Quintile 2.  From a practical standpoint, all of these people are relatively poor. Yet, it is worthwhile to understand that the simplified index of 19 questions produces results that are not identical to using all 61 questions in the original survey.



      The following table provides the same information on the movement between national quintiles when using the EquityTool versus the original wealth index:


        EquityTool National Quintiles
        Quintile 1Quintile 2Quintile 3Quintile 4Quintile 5Total
      Original National QuintilesQuintile 115.07%4.38%0.54%0.01%0.00%20.01%
      Quintile 24.57%11.30%3.95%0.18%0.00%20.00%
      Quintile 30.37%4.17%12.38%3.06%0.02%20.01%
      Quintile 40.04%0.19%3.11%14.50%2.16%20.00%
      Quintile 50.00%0.00%0.02%2.15%17.81%19.98%


      The following graph provides information on the movement between urban quintiles when using the EquityTool versus the original wealth index:


      The following table provides the same information on the movement between urban quintiles when using the EquityTool versus the original wealth index:


        EquityTool Urban Quintiles
        Quintile 1Quintile 2Quintile 3Quintile 4Quintile 5Total
      Original Urban QuintilesQuintile 117.54%2.47%0.00%0.00%0.00%20.01%
      Quintile 22.47%13.34%4.06%0.12%0.00%19.99%
      Quintile 30.01%4.07%12.19%3.74%0.00%20.01%
      Quintile 40.00%0.10%3.44%12.60%3.96%20.10%
      Quintile 50.00%0.02%0.30%3.58%15.99%19.90%


      Data interpretation considerations:

      1. This tool provides information on relative wealth – ‘ranking’ respondents within the national or urban population. The most recent available data from the WorldBank indicates that 50% of people in Mali live below $1.90/day[1]. This information can be used to put relative wealth into context.
      2. People who live in urban areas are more likely to be wealthy. In 2015, 65% of people living in urban areas were in the richest national quintile, compared to only 7.8% of those living in rural areas[2].
        1. If your population of interest is predominantly urban, we recommend you look at the urban results to understand how relatively wealthy or poor they are, in comparison to other urban dwellers.
        2. If the people you interviewed using the EquityTool live in rural areas, or a mix of urban and rural areas, we recommend using the national results to understand how relatively wealthy or poor they are, in comparison to the whole country.
      3. Some “cercles” in Mali are wealthier than others. It is important to understand the country context when interpreting your results.
      4. In most cases, your population of interest is not expected to be equally distributed across the five wealth quintiles. For example, if your survey interviewed people exiting a shopping mall, you would probably expect most of them to be relatively wealthy.


      Metrics for Management provides technical assistance services to those using the EquityTool, or wanting to collect data on the wealth of their program beneficiaries. Please contact and we will assist you.

      [1] From, reporting Poverty headcount ratio at $1.90/day at 2011 international prices.

      [2] From the Mali MICS 2015 Final Report, available from