EquityTool: March 7, 2023

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The original version is no longer active but is available upon request.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: November 1, 2016

Source data: DHS 2019-2020

# of survey questions in full wealth index: 49

# of variables in full index: 122

# of survey questions in EquityTool: 11

# of variables in EquityTool: 12

 Questions:

Technical notes:

The standard simplification process was applied to achieve high agreement with the original wealth index. Kappawas 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, especiallythose 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 15.3% are still identified as being in the poorest quintile when we use the simplified index. However, approximately 4.4% 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 11 questions produces results that are not identical to using all 49 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 DHS 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 The most recent available data from the World Bank indicates that 52.01% of people in Rwanda live below $2.15/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 Rwanda, 63% of people living in urban areasare in the richest national quintile, compared to only 11% of those living in rural areas [2].

2a. 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

2b. 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 districts in Rwanda are wealthier than 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 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 November 1, 2016, which compared user data to a benchmark of 2014. A new source survey, the 2019-2020 DHS was recently 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 Rwanda, the remainder of this sectionis 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 comparison section below illustrates 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 estimate. 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 2019-2020 Rwanda 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. 1. 1. Using the same 15 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 arecompared. In the graph below, the previous EquityTool, derived from the 2014- 15 DHS, is applied to the 2014-15 DHS data and the newer 2019-20 DHS data. In 2014-15 the proportion of households in each of the 5 quintiles is very close to 20%. Similarly, in 2019-20, 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 2014-15 and 2019-20 survey datasets, Rwanda continued to experience economic development and declines in the share of households living below the international poverty line during this period [3]. This suggest that gradually over time the previous EquityTool will lose its ability to accurately classify households by relative wealth quintile.

1. 1. 2. Comparing the previous 15 questions and scores, and the new EquityTool (12 questions) This analysis simulates how the new and previous Rwanda EquityTool compare relative to one another in classifyinghouseholds from the 2019-20 Rwanda DHS into five wealth 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 in quintile 1 using the current EquityTool, 75% 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 Rwanda EquityTool. First, as previously mentioned, citizens of Rwanda continue to experience economic development. These economic improvements, over time, will reduce the previous Rwanda EquityTool’s ability to accurately assign households to their most correct wealth quintiles. Second, because of changes to the underlying wealth index in the 2019-20 Rwanda DHS, the latest version of the Rwanda 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 worldbank.org, reporting Poverty headcount ratio at $2.15/day at 2017 international prices.
[2] From the Rwanda DHS 2019-2020 dataset household recode, available at http://dhsprogram.com/
[3] From https://worldbank.org/en/country/rwanda/overview, The World Bank in Rwanda Overview.