EquityTool: November 22, 2022

Previous version released: December 17, 2018

Source data: DHS 2019-20

# of survey questions in full wealth index: 39
# of variables in full index: 113

# of survey questions in EquityTool: 9
# of variables in EquityTool: 9

Questions:

Technical notes:

The standard simplification process was applied to achieve high agreement with the original 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:

Respondents in the original dataset were divided into three groups for analysis – those in the 1^st and 2^nd quintiles (poorest 40%), those in the 3^rd quintile, and those in the 4^th and 5^th 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 16.4% are still identified as being in the poorest quintile when we use the simplified index. However, approximately 3.6% 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 nine questions produces results that are not identical to using all 39 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 Gambia DHS 2019-20 wealth index:

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:

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 10.3% of people in Gambia 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 Gambia, 22% of people living in urban areas are in the richest national quintile, compared to only 0.04% 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 regions in Gambia 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 in December 2018 which compared user data to a benchmark of 2013.  A new source survey, the 2019-20 Gambia DHS 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 a similar 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 Gambia, 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.

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 comparisons presented below illustrate how quintile results compare when using the previous EquityTool and the current one. 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 support@equitytool.org

Technical comparison between the current and previous EquityTool

Some of the questions and response options for the previous EquityTool were not included in the new 2019-20 Gambia DHS source data. This limits our ability to compare the two versions of the EquityTool and two different data sources.

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

1. Using the same 16 questions and response options, and scoring system as in the previous EquityTool, with two different benchmark populations

This analysis simulates results if the only thing which changes is the benchmark against which respondents are compared. In the graph below, the previous EquityTool, derived from the 2013 Gambia DHS, is applied to the 2013 data and the newer 2019-20 DHS data. In 2013, the proportion of households in each of the 5 quintiles is very close to 20%. Similarly, in 2019, households are roughly equally apportioned to each of the five quintiles. We do not see within this relatively short interval between surveys a systematic shift of households into the wealthier quintiles. However, despite observing similar performance by the previous EquityTool in classifying households by wealth quintile in the 2013 and 2019-20 survey datasets, The Gambia continues to experience economic development and declines in the share of households living below the international poverty line [3]. This suggests that gradually over time the previous EquityTool will lose its ability to accurately classify households by relative wealth quintile.

2. Comparing the previous 16 questions and scores, and the new EquityTool (9 questions)

This analysis simulates how the new and previous Gambia EquityTools compare relative to one another in classifying households from the 2019-20 Gambia DHS into five wealth quintiles. The rightmost column and bottom rows show that the new and previous EquityTools both roughly evenly divide the sample into five equal groups. The cells within the table indicate how respondents are categorized, if measured using the two different tools. Of those categorized as quintile 1 using the current EquityTool, 68% of them would have been considered the poorest quintile in the previous tool (see the first row).

While both the current and previous versions of the EquityTool perform well against this sample, there are two important reasons that your organization should consider adopting the newest version of the Gambia EquityTool. First, as previously mentioned, citizens of The Gambia continue to experience economic development. These economic improvements, over time, will reduce the previous Gambia EquityTool’s ability to accurately assign households to their most correct wealth quintile. Second, because of changes to the underlying wealth index in the 2019-20 Gambia DHS, this latest version of the Gambia EquityTool does not require you to identify each respondent as living in an urban or rural area at the time of administering the survey. This change, along with a reduced number of questions, makes the current EquityTool easier to administer than the previous version.

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 support@equitytool.org and we will assist you.

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

[2] From the DHS dataset household recode, available at http://dhsprogram.com/

[3] From https://www.worldbank.org/en/country/gambia/overview, The World Bank in The Gambia Overview