Tanzania - Measuring Living Standards within Cities, Dar es Salaam 2014-2015

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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. These geo-referenced surveys provide information on urban living standards at an unprecedented level of granularity: they can be compared across different geographic levels within the cities, and between areas of ‘regular’ and ‘irregular’ settlement patterns. They also respond to the need to increased understanding of specifically ‘urban’ dimensions of quality of living: housing attributes, access to basic services, and commuting patterns, among others.

Acronym: 
DAR-LSMS 2014-2015
Type: 
Microdata
Topics: 
Topic not specified
Languages Supported: 
English
Geographical Coverage: 
Tanzania
Reference ID: 
TZA_2014_DAR-LSMS_v01_M
Release Date: 
January 10, 2019

Harvest Source

Harvest Source: 
Microdata

Harvest Source ID

Harvest Source ID: 
10298

Last Updated

Last Updated: 
January 10, 2019
Study Type: 

Living Standards Measurement Study [hh/lsms]

Disclaimer: 
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.
Primary Investigator Name, Affiliation: 
World Bank
Questionnaires: 
Response Rates: 
Non-response rate: 13%
Sampling Procedure: 
SAMPLE FRAME 16,000 EAs generated by the Tanzania National Bureau of Statistics (NBS) for the 2012 Census. STAGE ONE 200 EAs sorted into four strata. The central strata was divided into ‘central core, shanty’ and ‘central core, non-shanty’. Two EAs were replaced with reserve EAs as the original EAs were found to be inaccessible. STAGE TWO 12 households randomly selected by systematic equal-probability from updated listing of each EA. LISTING METHODOLOGY The listing exercise took place between the first and the second stage of sampling. The household listing operations were implemented with computer assisted paperless interviewing (CAPI) techniques, which generates electronic files directly. Enumerators collected basic information about household: the name of the household head name, phone number and total number of household members living in the dwelling. Enumerators also recorded the GPS location of all structures,18 defined the type of structure, and aimed to provide measurement of structure size. Listing was preceded by community sensitisation in both cities. In Dar es Salaam, enumerators visited the local chief (Mjumbe) of their assigned EA two days in advance of listing and on the day of listing. Enumerators were equipped with maps created on Google My Maps to display shapefiles for the listing exercise. Hardcopies of their respective EA maps were also provided to be use in case of network failure. In Dar es Salaam, enumerators conducted a listing of all households in each of the selected EAs. The listing exercise was conducted by 30 enumerators, each of which was assigned between 3 and 9 EAs for listing (enumerators were selected on the basis of performance from a group of 35 that were trained for listing). Enumerators were allocated EAs based on: (i) distance from enumerators’ homes in order to minimize transport time and cost; (ii) distance between the EAs; and (iii) safety and response rate considerations. SURVEY IMPLEMENTATION The surveys were fielded over the course of several months. The Dar es Salaam survey was implemented between November 2014 and January 2015. Cases were assigned to interviewers using Survey Solutions. Interviewers were provided with both an electronic and hardcopy map, as well as a printed completion form, and could contact the listing manager through email, WhatsApp, or google hangouts if they were unable to find the assigned house. Completing the survey often required repeat visits. This is because the survey required input from up to three separate respondents: the main respondent, who could be any present household member, and answered questions on household composition, basic information on members, assets, remittances, grants, housing, properties and consumption; the household head, who answered questions on residential history, satisfaction, employment, time use and commuting; and a random respondent, who was randomly selected from household members over the age of 12 (not including the head), who responded questions on satisfaction, employment, time use and commuting. Enumerators visited each house at least twice before a component could be marked as unavailable - in many cases, however, more than two visits were conducted. Quality assurance procedures included: (i) In-interview feedback from CAPI, which provided a check that modules or questions were not missing, and alerted interviewers to mistakes and inconsistencies in given answers, so that these could be addressed while the interviewer was still with the respondent; (ii) Aggregate checks conducted using the Survey Solutions Supervisor application, which allows supervisors to identify common mistakes (applied to all initial interviews, and then through spot checks); interviewer performance and completion monitoring conducted by the implementing firm, through interviewer and EA level summaries of response rates, interview completion, and progress; (iii) weekly summaries of key indictors provided by the World Bank team (following each data delivery); (iv) direct observation of fieldwork; and (v) back check interviews. A key lesson learned is that the portion of back check interviews should be agreed in advance with the implementing firm: in Dar es Salaam back checks were conducted on 5% of the sample.
Series Information: 
Unit of Analysis: 
- Household - Individual
Version Description: 
Version 01
Weighting: 
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 Dar es Salaam weights thus 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 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.

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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 Example: The World Bank. Tanzania- Measuring Living Standards within Cities, Dar es Salaam (DAR-LSMS) 2014-2015, Ref. TZA_2014_DAR-LSMS_v01_M. Dataset downloaded from [URL] on [date].

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. These geo-referenced surveys provide information on urban living standards at an unprecedented level of granularity: they can be compared across different geographic levels within the cities, and between areas of ‘regular’ and ‘irregular’ settlement patterns. They also respond to the need to increased understanding of specifically ‘urban’ dimensions of quality of living: housing attributes, access to basic services, and commuting patterns, among others.

FieldValue
Modified Date
2019-01-17
Release Date
Identifier
af9ecae8-42bf-417d-af14-5cf9a5f7ca0e
License
License Not Specified
Contact Email
Public Access Level
Public
Rating: 
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No votes yet
Reference ID: 
TZA_2014_DAR-LSMS_v01_M
Acronym: 
DAR-LSMS 2014-2015
Type: 
Languages Supported: 
Access Authority Name, Affiliation, Email: 
Disclaimer: 
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.
Response Rates: 
Non-response rate: 13%
Weighting: 
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 Dar es Salaam weights thus 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 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.
Primary Investigator Name, Affiliation: 
World Bank
Version Description: 
Version 01
Unit of Analysis: 
- Household - Individual
Geographical Coverage: 
Data Classification of a Dataset: 
Series Information: 
Sampling Procedure: 
SAMPLE FRAME 16,000 EAs generated by the Tanzania National Bureau of Statistics (NBS) for the 2012 Census. STAGE ONE 200 EAs sorted into four strata. The central strata was divided into ‘central core, shanty’ and ‘central core, non-shanty’. Two EAs were replaced with reserve EAs as the original EAs were found to be inaccessible. STAGE TWO 12 households randomly selected by systematic equal-probability from updated listing of each EA. LISTING METHODOLOGY The listing exercise took place between the first and the second stage of sampling. The household listing operations were implemented with computer assisted paperless interviewing (CAPI) techniques, which generates electronic files directly. Enumerators collected basic information about household: the name of the household head name, phone number and total number of household members living in the dwelling. Enumerators also recorded the GPS location of all structures,18 defined the type of structure, and aimed to provide measurement of structure size. Listing was preceded by community sensitisation in both cities. In Dar es Salaam, enumerators visited the local chief (Mjumbe) of their assigned EA two days in advance of listing and on the day of listing. Enumerators were equipped with maps created on Google My Maps to display shapefiles for the listing exercise. Hardcopies of their respective EA maps were also provided to be use in case of network failure. In Dar es Salaam, enumerators conducted a listing of all households in each of the selected EAs. The listing exercise was conducted by 30 enumerators, each of which was assigned between 3 and 9 EAs for listing (enumerators were selected on the basis of performance from a group of 35 that were trained for listing). Enumerators were allocated EAs based on: (i) distance from enumerators’ homes in order to minimize transport time and cost; (ii) distance between the EAs; and (iii) safety and response rate considerations. SURVEY IMPLEMENTATION The surveys were fielded over the course of several months. The Dar es Salaam survey was implemented between November 2014 and January 2015. Cases were assigned to interviewers using Survey Solutions. Interviewers were provided with both an electronic and hardcopy map, as well as a printed completion form, and could contact the listing manager through email, WhatsApp, or google hangouts if they were unable to find the assigned house. Completing the survey often required repeat visits. This is because the survey required input from up to three separate respondents: the main respondent, who could be any present household member, and answered questions on household composition, basic information on members, assets, remittances, grants, housing, properties and consumption; the household head, who answered questions on residential history, satisfaction, employment, time use and commuting; and a random respondent, who was randomly selected from household members over the age of 12 (not including the head), who responded questions on satisfaction, employment, time use and commuting. Enumerators visited each house at least twice before a component could be marked as unavailable - in many cases, however, more than two visits were conducted. Quality assurance procedures included: (i) In-interview feedback from CAPI, which provided a check that modules or questions were not missing, and alerted interviewers to mistakes and inconsistencies in given answers, so that these could be addressed while the interviewer was still with the respondent; (ii) Aggregate checks conducted using the Survey Solutions Supervisor application, which allows supervisors to identify common mistakes (applied to all initial interviews, and then through spot checks); interviewer performance and completion monitoring conducted by the implementing firm, through interviewer and EA level summaries of response rates, interview completion, and progress; (iii) weekly summaries of key indictors provided by the World Bank team (following each data delivery); (iv) direct observation of fieldwork; and (v) back check interviews. A key lesson learned is that the portion of back check interviews should be agreed in advance with the implementing firm: in Dar es Salaam back checks were conducted on 5% of the sample.
Release Date: 
Thursday, January 10, 2019
Last Updated Date: 
Thursday, January 10, 2019
Questionnaires: 
Harvest Source: 
Harvest Source ID: 
10298
Citation Text: 
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 Example: The World Bank. Tanzania- Measuring Living Standards within Cities, Dar es Salaam (DAR-LSMS) 2014-2015, Ref. TZA_2014_DAR-LSMS_v01_M. Dataset downloaded from [URL] on [date].
Modified date: 
17906
Study Type: 
Living Standards Measurement Study [hh/lsms]
Primary Dataset: 
Yes

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