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EquityTool: Released July 20, 2016

Source data: Ghana DHS 2014

 

# of survey questions in original wealth index: 50

# of variables in original index: 154

 

# of survey questions in EquityTool: 13

# of variables in EquityTool: 14

 

Questions:

Question Option 1 Option 2 Option 3
Q1 A color television? Yes No
Q2 Does any member of this household own any agricultural land? Yes No
Q3 A refrigerator? Yes No
Q4 Video deck/DVD/VCD? Yes No
Q5 Does any member of this household have a bank account? Yes No
Q6 Electricity? Yes No
Q7 A wall clock? Yes No
Q8 Cabinet/cupboard? Yes No
Q9 What type of fuel does your household mainly use for cooking? LPG Wood Other
Q10 What kind of toilet facility do members of your household usually use? No facility / bush / field Other
Q11 What is the main source of drinking water for members of your household? Sachet water Other
Q12 What is the main material of the floor in your household? Cement Other
Q13 What is the main material of the exterior walls in your household? Cement Other

 

Technical notes:

The standard simplification process was applied to determine high agreement with the original wealth index. However, a large number of variables (28) was required to achieve the usual minimum level of agreement – a kappa statistic of 0.75 or above for both national and urban quintiles. Since a kappa of 0.7 or higher could be achieved with just 14 variables, a decision was made to accept the lower kappa statistic to achieve a much shorter questionnaire. Individual variables were tested for their contribution to the overall agreement, and the most important were included. The most common source of drinking water in urban areas is sachet water, leading to the inclusion of this variable. Those who would like to administer a longer questionnaire to achieve higher agreement are encouraged to contact us for support.

 

Ghana's EquityTool therefore does not agree to the original DHS wealth quintiles to the same extent as other countries' EquityTools. However, a kappa statistic of 0.7 is still a strong level of agreement. 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=11,835)

Urban only population

(n=5,939)

% agreement 81.4% 80.8%
Kappa statistic 0.709 0.7

 

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 69.5% are still identified as being in the poorest quintile when we use the simplified index.  However, approximately 24.5% 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 13 questions produces results that are not identical to using all 50 questions in the original survey. The level of agreement for the simplified index for Ghana is lower than for other countries. A respondent may move by 1 quintile up or down as compared to using the full DHS index for Ghana.

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 13.90% 4.90% 1.00% 0.20% 0.00% 20%
Quintile 2 5.60% 10.40% 3.60% 0.40% 0.00% 20%
Quintile 3 0.10% 5.10% 11.00% 3.60% 0.20% 20%
Quintile 4 0.00% 0.00% 4.30% 12.00% 3.60% 20%
Quintile 5 0.00% 0.00% 0.00% 3.80% 16.20% 20%
Total 19.60% 20.40% 20.00% 20.00% 20.00% 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 16.60% 2.60% 0.70% 0.20% 0.00% 20%
Quintile 2 3.50% 12.30% 3.60% 0.60% 0.00% 20%
Quintile 3 0.00% 4.90% 10.90% 3.90% 0.30% 20%
Quintile 4 0.00% 0.20% 4.50% 10.80% 4.60% 20%
Quintile 5 0.00% 0.00% 0.30% 4.60% 15.10% 20%
Total 20.00% 20.00% 19.90% 19.90% 20.10% 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 WorldBank indicates that 25.1% of people in Ghana 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 Ghana, 39.2% of people living in urban areas are in the richest national quintile, compared to only 1.1% of those living in rural areas[2].
    • 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.
    • 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 Ghana 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 equitytool@m4mgmt.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 Ghana DHS 2014 dataset household recode, available at http://dhsprogram.com/