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EquityTool: Update released October 30, 2017
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 The original version is no longer active but is available upon request.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: December 9, 2015
Source data: India Human Development Survey II 2012
# of survey questions in original wealth index: 51
# of variables in original index: 102
# of survey questions in EquityTool: 11
# of variables in EquityTool: 11
|Question||Option 1||Option 2|
|Q1||Do you own… a colour T.V.?||Yes||No|
|Q2||… cable / dish T.V.?||Yes||No|
|Q3||… a pressure cooker?||Yes||No|
|Q4||… a refrigerator?||Yes||No|
|Q5||… a mixer/ grinder?||Yes||No|
|Q6||… air cooler?||Yes||No|
|Q7||… a motorcycle/ scooter?||Yes||No|
|Q8||For heating, lighting or cooking, does your household use…kerosene?||Yes||No|
|Q11||Does your household have a toilet of its own?||No facility belonging to household||Yes (flush, semi-flush, latrine, or any other facility)|
Question Q2 refers to whether or not the household receives television channels that require additional payment, versus only receiving government owned Doordarshan stations. Question Q6, air cooler, is distinct from an air conditioner, and refers to an evaporative water cooler.
The data source for this EquityTool is the India Human Development Survey (IHDS) II, a publicly available survey and dataset conducted by the University of Maryland and the National Council of Applied Economic Research, New Delhi. The IHDS is a nationally representative survey of households across India, administered in 2004-5. The IHDS II was administered in 2012, and is the second round of surveys administered to households that were interviewed as part of the first IHDS. The survey was designed to measure changes in education, health, and livelihoods of Indian households over time.
To replace households lost to attrition from the first survey (~ 16%), households in the same neighborhood were randomly selected to refresh the sample. The sample was drawn from urban and rural areas throughout India, with the exception of Andaman, Nicobar and Lakshwadeep Islands.
Unlike other source data used in the creation of the EquityTool, the IHDS does not include a variable on household wealth as calculated through their ownership of assets. It does include information on their total income and expenditures. In order to remain comparable to other EquityTool surveys, we created an asset index from variables available in the household and women's surveys of the IHDS II. The full asset index for India was created in a process similar to that used for DHS surveys, detailed here. Categorical variables, such as drinking water source, type of toilet, and household construction materials were dichotomized. Missing or unknown values for household asset ownership variables were recoded to 0 ('No'). Variables indicating the number of livestock owned were recoded to dichotomous categories, by type of livestock ('None', '1 to 4', '5 to 9', '10 or more'). Notably different than the DHS surveys, variables for household fuel use were not constructed to be mutually exclusive in the IHDS surveys. Respondents were able to indicate all fuel sources used in the household, and those variables were used in the present analysis as such. Principal components analyses were conducted for urban and rural households separately, and including all variables which are logically associated with wealth for each area. This resulted in a score for each household (Uscore if urban and Rscore if rural). In the third, common, analysis for all respondents, variables for livestock ownership, which were found to be differentially associated with wealth in urban and rural areas, were excluded. The results from the urban and rural analyses were regressed against the common index (common), and combined to make one national score (NatScore), using the formulas below:
common=b1Uscore + a1
common=b2Rscore + a2
Where Urban=1 if respondent lives in urban area and 0 if otherwise, and Rural =1 if respondent lives in rural area and 0 if otherwise.
Subsequent to the creation of a full wealth index, the standard simplification process, detailed in this article, was applied. The goal of simplification is to reduce the number of questions and variables, while achieving high agreement with a full wealth index constructed in the IHDS II dataset. Kappa was greater than 0.75 for the national and urban indices. The data used to identify important variables comes from the factor weights extracted during the generation of the full asset index. A full list of all variables used in the analysis and accompanying factor weights is available upon request.
Level of agreement:
We compared the quintile distribution based on the full asset index to that obtained using the simplified asset index. The level of agreement between the two quintile distributions is assessed using the Kappa statistics, which must be greater than 0.75 for both the national and urban indices. For this comparison, respondents were assigned to one of three groups by both the full wealth index and the simplified wealth index –those in the 1st and 2nd quintiles (poorest 40%), those in the 3rd quintile, and those in the 4th and 5th quintiles (richest 40%). Agreement between the full asset index and the simplified index is presented below.
|Urban only population
What does this mean?
When shortening and simplifying the full wealth 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 full wealth index.
The graph below illustrates the difference between the EquityTool generated index and the full wealth index. Among all of those people (20% of the population) originally identified as being in the poorest quintile, approximately 15.4 % are still identified as being in the poorest quintile when we use the simplified index. However, approximately 4.5% 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 11 questions produces results that are not identical to using all 51 questions in the original survey.
The following table provides the same information on the movement between national quintiles when using the EquityTool versus the full wealth index:
|EquityTool National Quintiles|
|Quintile 1||Quintile 2||Quintile 3||Quintile 4||Quintile 5||Total|
|Full Wealth Index National Quintiles||Quintile 1||15.4%||4.5%||0.1%||0.0%||0.0%||20%|
The following graph provides information on the movement between urban quintiles when using the EquityTool versus the full wealth index:
The following table provides the same information on the movement between urban quintiles when using the EquityTool versus the full wealth index:
|EquityTool Urban Quintiles|
|Quintile 1||Quintile 2||Quintile 3||Quintile 4||Quintile 5||Total|
|Full Wealth Index Urban Quintiles||Quintile 1||16.7%||3.1%||0.2%||0.0%||0.0%||20%|
Data interpretation considerations:
- 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 31.1% of people in India live below $1.90/day. This information can be used to put relative wealth into context.
- People who live in urban areas are more likely to be wealthy. In India, 16.0% of people living in urban areas are in the richest national quintile, compared to only 6.9% of those living in rural areas.
- 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.
- Some districts in India are wealthier than others. It is important to understand the country context when interpreting your results.
- 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 on December 9, 2015 which compared user data to a benchmark of 2005. A new source survey, the IHDS II was recently released, and allows us to benchmark 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. In creating the previous EquityTool for India, an exception was made to our standard of using a survey collected in 2010 or later. Given known changes in wealth, and to mitigate the age of the survey, variables on mobile phone ownership were removed, because mobile phone ownership is known to have changed dramatically in the years since the survey was conducted. This updated EquityTool for India is benchmarked to a more recent, nationally representative population.
For those who have not previously conducted an EquityTool based study in India, the remainder of this section is not particularly relevant. For those who have used the previous EquityTool, you may be interested in the following practical considerations.
|Previous EquityTool||Current EquityTool|
|Source Data||DHS 2005-06||IHDS II 2012|
|# of questions in EquityTool||13||11|
|# of questions in full wealth index||40||51|
|Wealth Index Construction||Available in source dataset||Generated using DHS methodology|
|Kappa statistic (EquityTool vs full wealth Index)
for 3 groups
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.
Generally, there is a partial shift down in quintiles when using a more recent EquityTool. In other words, the current EquityTool will usually put some respondents into a lower quintile than the previous one would.
We recommend using the current version 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 version.
If conducting a follow-up survey to a baseline that used the previous EquityTool, and the most important result is change from baseline, it may be preferable to continue to use the previous EquityTool for comparability. If you need to do this, please contact us at firstname.lastname@example.org.
Unfortunately, differences in the questionnaire design for the two source datasets—the 2005 India DHS and the 2012 IHDS II—limit the utility of more detailed technical comparisons between the current and previous EquityTool, so we do not offer them here.
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 email@example.com and we will assist you.
 From povertydata.worldbank.org, reporting Poverty headcount ratio at $1.90/day at 2011 international prices.
 From the India Human Development Survey dataset household recode, available at http:/ihds.info/