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EquityTool: Update released December 4, 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 The original version is no longer active but is available upon request.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: Cambodia DHS 2021-22
# of survey questions in original wealth index: 32
# of variables in original index: 144
# of survey questions in EquityTool: 8
# of variables in EquityTool: 11
Questions:
Question | Option 1 | Option 2 | Option 3 | |
Q1 | Does your household have a refrigerator? | Yes | No | |
Q2 | Does your household have a television? | Yes | No | |
Q3 | Does any member of your household own a watch? | Yes | No | |
Q4 | Does any member of your household have an account in a bank or other financial institution? | Yes | No | |
Q5 | In your household, what type of cookstove is mainly used for cooking? | Three stone/open fire | Liquefied Petroleum Gas (LPG) / cooking gas stove | Other cookstove |
Q6 | What type of fuel or energy source is used for cooking? | Wood | Other fuel source | |
Q7 | What is the main material of your dwelling’s exterior walls? | Wood planks / shingles | Cement | Other material |
Q8 | What is the main material of your dwelling’s floor? | Wood planks | Ceramic tiles | Other floor material |
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:
National Population (n=20806) | Urban only population (n=7059) | |
% agreement | 85.2% | 84.7% |
Kappa statistic | 0.768 | 0.761 |
Respondents in the original dataset were divided into three groups for analysis – those in the 1st and 2ndquintiles (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 67% are still identified as being in the poorest quintile when we use the simplified index. However, approximately 28.65% 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 8 questions produces results that are not identical to using all 32 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:
EquityTool National Quintiles | |||||||
Quintile 1 | Quintile 2 | Quintile 3 | Quintile 4 | Quintile 5 | Total | ||
Original DHS National Quintiles | Quintile 1 | 13.40% | 5.73% | 0.82% | 0.05% | 0.00% | 20% |
Quintile 2 | 7.75% | 9.14% | 2.90% | 0.21% | 0.00% | 20% | |
Quintile 3 | 0.25% | 3.80% | 12.70% | 3.22% | 0.02% | 20% | |
Quintile 4 | 0.00% | 0.04% | 3.47% | 14.26% | 2.23% | 20% | |
Quintile 5 | 0.00% | 0.00% | 0.00% | 2.29% | 17.71% | 20% | |
Total | 21.40% | 18.71% | 19.91% | 20.03% | 19.96% | 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 1 | Quintile 2 | Quintile 3 | Quintile 4 | Quintile 5 | Total | ||
Original DHS Urban Quintiles | Quintile 1 | 17.49% | 2.42% | 0.10% | 0.00% | 0.00% | 20% |
Quintile 2 | 2.69% | 13.45% | 3.83% | 0.04% | 0.00% | 20% | |
Quintile 3 | 0.00% | 3.83% | 12.53% | 3.63% | 0.00% | 20% | |
Quintile 4 | 0.00% | 0.15% | 3.53% | 11.71% | 4.59% | 20% | |
Quintile 5 | 0.00% | 0.00% | 0.12% | 4.63% | 15.24% | 20% | |
Total | 20.18% | 19.85% | 20.11% | 20.01% | 19.84% | 100% |
Changes from the previous EquityTool
We cannot directly compare the recent EquityTool (DHS 2021) with the old EquityTool (DHS 2014) due to the absence of certain variables in the recent DHS 2021 data. For instance, the variable CD/DVD Player was not included in the recent DHS 2021 dataset. Additionally, certain variables were either consolidated or recoded into other variables in the current DHS 2021.
For those who have used the previous EquityTool, you may want to use the new EquityTool 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. If you have any questions about appropriate use, please email support@equitytool.org
Data interpretation considerations:
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 Karamba, Wendy; Tong, Kimsun; Salcher, Isabelle. 2022. Cambodia Poverty Assessment: Toward a More Inclusive and Resilient Cambodia. © World Bank, Washington, DC. http://hdl.handle.net/10986/38344License: CC BY 3.0 IGO.”
[2] From the Cambodia DHS 2021 dataset household recode, available at http://dhsprogram.com/