The Benin 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.
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EquityTool: Update released October 13, 2022


The EquityTool has been updated based upon new source data. The original version is no longer active but is available upon request.


Previous version released: December 9, 2015


Source data: DHS 2017-18

# of survey questions in full wealth index: 43

# of variables in full index: 152

# of survey questions in EquityTool: 10

# of variables in EquityTool: 12




 QuestionOption 1Option 2Option 3
Q1Does this house household have electricity?YesNo 
Q2…a television?YesNo 
Q3…a VCD/DVD player?YesNo 
Q4Does any member of your household have a bank account?YesNo 
Q5Does any member of your household own a watch?YesNo 
Q6…own land usable for agriculture?YesNo 
Q7What is the primary material used in the construction of the exterior walls of your dwelling?CementEarthOther
Q8What is the primary material used in the construction of the floor of your dwelling?CementEarth/sandOther
Q9What type of fuel does your household primarily use for cooking?WoodOther 
Q10What kind of toilet do members of your household usually use?No facility/bush/fieldOther 


Technical notes:

During the initial steps of creating this EquityTool it was discovered that the urban and rural sample sizes provided within this DHS’s supporting documentation did not correspond to those found within the dataset itself. These discrepancies limited our ability to validate many of the descriptive statistics we consider for inclusion during the EquityTool creation process and also raised questions about how the wealth index provided in the dataset was produced. For these reasons, we chose to recreate the wealth index and to use our newly recreated wealth index as the standard against which we would later compare interrater reliability of the simplified EquityTool wealth index. The standard simplification process was applied to achieve high agreement with the recreated wealth index. Kappa was greater than 0.75 for the national and urban indices. Details on the standard process can be found in this article. The data used to identify important variables comes from the factor weights released by ICF.

Level of agreement:


National household sample


Urban household only sample


% agreement86.5%85.6%
Kappa statistic0.7890.775

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 DHS. 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 DHS wealth index.

The graph below illustrates the difference between the EquityTool generated index and the full DHS wealth index. Among all of those people (20% of the population) originally identified as being in the poorest quintile, approximately 15.6% are still identified as being in the poorest quintile when we use the simplified index.  However, approximately 3.8% 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 10 questions produces results that are not identical to using all 16 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 Benin DHS 2017-18 wealth index:

  EquityTool National Quintiles
  Quintile 1Quintile 2Quintile 3Quintile 4Quintile 5Total
Original DHS National QuintilesQuintile 1 15.6% 3.9% 0.5% 0.0% 0.0%20%
Quintile 2 4.8% 11.7% 3.3% 0.2% 0.0%20%
Quintile 3 0.2% 3.7% 13.7% 2.3% 0.0%20%
Quintile 4 0.0% 0.1% 3.1% 14.2% 2.6%20%
Quintile 5 0.0% 0.0% 0.1% 2.9% 17.1%20%
Total 20.7% 19.4% 20.7% 19.6% 19.7%100%

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

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

  EquityTool Urban Quintiles
  Quintile 1Quintile 2Quintile 3Quintile 4Quintile 5Total
Original DHS Urban QuintilesQuintile 1 16.9% 2.9% 0.2% 0.0% 0.0%20%
Quintile 2 3.1% 14.0% 2.9% 0.1% 0.0%20%
Quintile 3 0.0% 3.0% 12.9% 3.9% 0.2%20%
Quintile 4 0.0% 0.0% 3.8% 11.6% 4.5%20%
Quintile 5 0.0% 0.0% 0.3% 5.0% 14.7%20%
Total 20.1% 20.0% 20.1% 20.5% 19.3%100%

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 World Bank indicates that 53.2% of people in Benin 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 Benin, 40.7% of people living in urban areas are in the richest national quintile, compared to only 6% of those living in rural areas [2].
  3. 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.
  4. 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.
  5. Some departments in Benin are wealthier than others. It is important to understand the country context when interpreting your results.
  6. 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.

Changes from the previous EquityTool

 We released an EquityTool on December 9, 2015, which compared user data to a benchmark of Benin DHS 2011-12 survey data.  A new source survey, the Benin DHS 2017-18 has since been released, and allows us to benchmark results to a more recent population. This is important, because wealth generally increases over time, and comparing your respondents to an old benchmark population will lead to over-estimating the relatively wealthy in your survey.  The new EquityTool was generated using the exact same methodology as the previous version, and in generating the new EquityTool, no attempt was made to account for the fact that a previous version existed. In other words, we did not explicitly try to keep the same questions or response options as the previous tool.

For those who have not previously conducted an EquityTool based study in Benin, the remainder of this section is not particularly relevant.  For those who have used the previous EquityTool, you may be interested to know how the two versions compare.

Source DataBenin DHS 201-12Benin DHS 2017-18
# of questions in EquityTool610
# of questions in full wealth index4043
Kappa statistic (EquityTool vs full wealth Index) for 3 groups

National:  0.764   _

Urban:   0.768   _

National:   0.789 _

Urban:   0.775 _

Practical considerations for users of the previous EquityTool

Comparing the results of surveys that used the previous EquityTool against those that use the current EquityTool is difficult. It will not always be clear whether any difference is because of actual differences in the wealth level of the respondents or because the EquityTool has changed.

The technical comparison section below, particularly the 2nd comparison, illustrates how quintile results compare when using the previous EquityTool and the current one. Generally, there is a partial shift down in quintiles when using a more recent EquityTool. In other words, the current EquityTool will usually put some respondents into a lower quintile than the previous one would.

It is generally best to use the current version of the EquityTool, since it will give a more accurate quintile estimates. If you are currently collecting data, it is best to continue to use the previous tool. Note that if you have created a survey in the EquityTool web application using the previous EquityTool, that survey will continue to use the previous EquityTool.

If conducting a follow-up survey to a baseline that used the previous EquityTool, and the most important result is change from the baseline, it may be preferable to continue to use the previous EquityTool for comparability. If you need to do this, please contact us at

Technical comparison between the current and previous EquityTool

All of the questions and response options for the previous EquityTool are found in the new source data. This makes comparison between the two versions of the EquityTool, and two different data sources, easier.

The comparison will be assessed in three different ways, described below.

  1. Using the same six questions, response options, and scoring systems as in the previous EquityTool with two different benchmark populations.

 This analysis simulates results of comparing two different benchmark populations against a single measure of relative wealth – the 2012 Benin EquityTool. In the graph below, the previous EquityTool, derived from the 2011-12 Benin DHS, is applied to the 2011-12 DHS data and the newer 2017-18 DHS data.

From this graph, you can tell that, in general, the previous EquityTool produces uneven wealth quintiles and categorizes many respondents that should have been placed in the second wealth quintile into the first quintile. This “lumpiness” is likely due to an insufficient number of asset questions, resulting in an inability to adequately evaluate each respondent’s household assets. Despite this, one observes that in 2017-18 survey data, the previous EquityTool categorizes households slightly more evenly into the five quintiles, with fewer households assigned to the first quintile and more assigned to the second and third quintiles. This more even distribution indicates that Beninese households have accumulated more assets suggestive of wealth over the intervening five years, and so have moved into higher wealth quintiles when measured against the previous EquityTool.

  1. Keeping the same six questions and response options as the previous EquityTool, but calculating scores based upon the 2017-18 data.

As an alternative to adopting the newer Benin EquityTool, one might wish to use the same questions as the previous tool but update the weighting. This seems reasonable, as the relative contribution of each asset towards overall wealth may have changed over time. Using new weights, but the same variables as the previous tool, we can see how well the resulting quintiles compare to the quintiles of our recreated wealth index.

The table below presents the agreement between the quintiles created from the full wealth index in the Benin DHS 2017-18 dataset and the quintiles created by the previous EquityTool, the previous EquityTool variables with updated weighting, and the current EquityTool. As with the agreement statistics described earlier in this factsheet, these figures are for the bottom two quintiles, the middle quintile, and the top two quintiles.

 2012 EquityTool2012 questions, 2018 scoring2018 EquityTool

The current EquityTool has the best agreement with the full wealth index quintiles and is the only one that exceeds our minimum kappa statistic of 0.75. The previous tool, even when the scoring is updated, falls short of this standard. The reason for this difference is because these six questions are no longer the best predictors of the overall wealth distribution.

  1. Comparing the previous six questions and scores, and the new EquityTool (10 questions).

 Although all of the questions in the previous EquityTool are found in the current EquityTool, we found that the six questions in the previous Benin EquityTool were insufficient for accurately categorizing survey respondents into their respective wealth quintiles. We needed to change and add more questions to differentiate people and households more accurately.

The table below shows how the previous and current EquityTool compare, using the same population. This is analogous to a comparison of the two versions of the EquityTool on the population you surveyed using our previous EquityTool.

  Previous EquityTool Quintiles
  Quintile 1Quintile 2Quintile 3Quintile 4Quintile 5Total
Current EquityTool QuintilesQuintile 1 17.6% 0.0% 3.1% 0.0% 0.0%20.7%
Quintile 2 11.7% 1.4% 5.4% 0.9% 0.0%19.4%
Quintile 3 1.5% 7.7% 8.5% 2.9% 0.0%20.7%
Quintile 4 0.0% 0.2% 3.1% 14.5% 1.7%19.6%
Quintile 5 0.0% 0.0% 0.0% 2.0% 17.6%19.7%
Total 30.8% 9.3% 20.1% 20.4% 19.4%100%

The rightmost column indicates that the current EquityTool does in fact evenly divide the population into roughly five equal groups. The bottom row shows that the older EquityTool does not divide the population into equal quintiles – it’s insufficient number of questions limits its ability to evenly distribute respondents into the lowest two quintiles. The cells within the table indicate how respondents are categorized, if measured using the two different tools. Of those who are categorized as quintile 1 using the current tool, 85.0% of them would have been considered in the poorest quintile in the previous tool (see the first row). Similarly, for those currently categorized as in the third quintile, 14.0% would have previously been categorized as being in the fourth quintile. If you had used the previous EquityTool, you could expect that with the current version, your respondents would be more evenly distributed between quintiles. This reflects the reality that we are measuring them against a more accurate benchmark.

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 [citation] dataset household recode, available at