Somaliland

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EquityTool: Released September 17, 2018

Source data: Somaliland MICS 2011

# of survey questions in original wealth index: 33

# of variables in original index: 82

 

# of survey questions in EquityTool: 12

# of variables in EquityTool: 12

 

Questions:

 

Question Option 1 Option 2
Q1 Does your household have … electricity? Yes No
Q2 … a radio? Yes No
Q3 … a television? Yes No
Q4 … a bed? Yes No
Q5 … a sofa? Yes No
Q6 … a Somali stool? Yes No
Q7 … a sitting cushion / pillow? Yes No
Q8 Does any member of your household own a watch? Yes No
Q9 What type of fuel does your household mainly use for cooking? Yes Other
Q10 What is the main source of drinking water for members of your household? Piped into dwelling Other
Q11 What is the main material of the floor in your household? Earth / sand Other
Q12 What is the main material of the exterior walls of your household? Stone with lime / cement Other

 

Technical notes:

The standard simplification process for the EquityTool relies upon the existence of analyses done separately for urban and rural areas.  The original wealth index for the Somaliland MICS 2011 dataset did not include a separate urban analysis. An urban index was created based on the variables used in the national analysis. The data used to identify important variables comes from the factor weights obtained after reconstruction of the MICS wealth index using analytical syntax provided by UNICEF. Initially, the simplification process produced a simplified questionnaire of only 8 variables with kappa greater than 0.75 for both the national and urban indices when comparing agreement among the bottom 40%, middle 20% and top 40% of the population's wealth; however, this solution provided little separation between the bottom two quintiles. Questions were added such that the simplified questionnaire was able to sufficiently distinguish between Q1 and Q2.  Kappa was greater than 0.75 for the national and urban indices. Details on the standard process can be found in this article.

Level of agreement:

National Population

(n=30,263)

Urban only population

(n=15,950)

% agreement 89.8% 87.9%
Kappa statistic 0.841 0.812

 

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 MICS. 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 MICS wealth index.

The graph below illustrates the difference between the EquityTool generated index and the full MICS wealth index. Among all of those people (20% of the population) originally identified as being in the poorest quintile, approximately 16.2% 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 12 questions produces results that are not identical to using all 33 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 MICS wealth index:

    EquityTool National Quintiles
  Quintile 1 Quintile 2 Quintile 3 Quintile 4 Quintile 5 Total
Original MICS National Quintiles Quintile 1 16.2% 3.8% 0.1% 0.0% 0.0% 20.1%
Quintile 2 5.5% 11.3% 3.4% 0.0% 0.0% 20.1%
Quintile 3 0.2% 3.5% 14.5% 1.5% 0.0% 19.8%
Quintile 4 0.0% 0.0% 1.5% 16.3% 2.2% 20.0%
Quintile 5 0.0% 0.0% 0.0% 2.3% 17.7% 20.0%
Total 22.0% 18.6% 19.4% 20.0% 20.0% 100.0%

 

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

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

    EquityTool Urban Quintiles
  Quintile 1 Quintile 2 Quintile 3 Quintile 4 Quintile 5 Total
Original MICS Urban Quintiles Quintile 1 16.6% 1.1% 0.0% 0.0% 0.0% 17.6%
Quintile 2 3.3% 14.6% 1.0% 0.1% 0.0% 19.0%
Quintile 3 0.0% 4.4% 14.4% 1.8% 0.1% 20.6%
Quintile 4 0.0% 0.0% 4.5% 13.7% 3.2% 21.4%
Quintile 5 0.0% 0.0% 0.2% 4.3% 16.8% 21.3%
Total 19.9% 20.1% 20.1% 19.9% 20.0% 100.0%

 

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 29.7% of people in urban Somaliland and 37.0% of people in rural Somaliland 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 Somaliland, 34.2% of people living in urban areas are in the richest national quintile, compared to only 1.4% of those living in rural areas[2].
    1. 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.
    2. 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 regions in Somaliland 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 support@equitytool.org and we will assist you.

 

[1] From the 2015 Somaliland Poverty Assessment at microdata.worldbank.org, reporting Poverty headcount ratio at $1.90/day at 2011 international prices.

[2] From the Somaliland dataset household recode, available at http://mics.unicef.org/surveys