Measuring Living Standards within Cities, Durban 2015
The Measuring Living Standards in Cities (MLSC) survey is a new instrument designed to enhance understanding of cities in Africa and support evidence based policy design. The instrument was developed under the World Bank's Spatial Development of African Cities Program, and was piloted in Dar es Salaam (Tanzania) and Durban (South Africa) over the course of 2014/15.
Kind of data
Sample survey data [ssd]
The survey covered households in Durban, South Africa.
Unit of analysis
Producers and sponsors
Oxford Policy Management
Collaborated in the implementation of the survey
Funded the survey
The total nominal sample of 2400 households in Durban was, selected in four stages rather than two. These were: (i) selection of 200 EAs with probability proportional to size; (ii) large EAs were segmented into area units of roughly the same size (using GIS data), and one segments was selected randomly with equal probability; (iii) following listing of buildings, 15 were selected using systematic equal probability sampling; (iv) households in the 15 selected buildings were listed so that 12 households could then be selected per EA by systematic equal probability sampling. This approach reduced the need to enter as many buildings as would otherwise have been necessary, without reducing the representativeness of the sample.
For further details on sampling strategy, see Survey Methodology section of World Measuring Living Standards within Cities report.
The refusal and non-completion rate was 41 percent.
Sample weights were designed to deliver unbiased estimates from the sample. The 'raw sampling weight' is a raising factor applied to each household that is equal to the inverse of its selection probability. Any given household's selection probability is the product of the probability of selection at each stage of the sampling. The weights reflect the probability of selecting the EA in the first stage of the sampling, and the conditional probability of selecting the household in the second stage. The approach in Durban is the same, but the weights account for the additional steps after selecting the EA of: selecting that segment of the EA, if it was subdivided; selecting the building within the EA; and selecting the household within the building.
The raw sampling weights are then further adjusted to account for non-response rates. To account for non-response rates, the number of 'usable households' in each EA is calculated. Non-response rates were so high that EA groupings had to be made before a weighting could be calculated. The weights were further adjusted through benchmarking to allow for post-stratification by ethnicity, considering high levels of non-response among white households.
For further details, please see Annex 1 of World Measuring Living Standards within Cities report.
Dates of collection
Mode of data collection
Computer Assisted Personal Interview [capi]
Use of the dataset must be acknowledged using a citation which would include:
- the Identification of the Primary Investigator
- the title of the survey (including country, acronym and year of implementation)
- the survey reference number
- the source and date of download
Disclaimer and copyrights
The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses.