Household and Small Business ICT Access and Usage Survey 2011-2012
Botswana, Cameroon, Ethiopia, Ghana, Kenya, Mozambique, Namibia, Nigeria, Rwanda, Tunisia, Tanzania, Uganda, South Africa, 2011 - 2012
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Reference ID
AFR_2011_RIAS_v01_M
Producer(s)
Research ICT Africa
Metadata
Created on
Sep 04, 2019
Last modified
Apr 27, 2021
Page views
21137
Downloads
387
Identification
Survey ID Number
AFR_2011_RIAS_v01_M
Title
Household and Small Business ICT Access and Usage Survey 2011-2012
Country/Economy
| Name | Country code |
|---|---|
| Botswana | BWA |
| Cameroon | CMR |
| Ethiopia | ETH |
| Ghana | GHA |
| Kenya | KEN |
| Mozambique | MOZ |
| Namibia | NAM |
| Nigeria | NGA |
| Rwanda | RWA |
| Tunisia | TUN |
| Tanzania | TZA |
| Uganda | UGA |
| South Africa | ZAF |
Study type
Other Household Survey [hh/oth]
Abstract
Research ICT Africa (RIA) is a non-profit, public interest, research entity which undertakes research on how information and communication technologies are being accessed and used in African countries. The aim is to measure the impact on lifestyles and livelihoods of people and households and to understand how informal businesses can prosper through the use of ICTs. This research can facilitate informed policy-making for improved access, use and application of ICT for social development and economic growth. RIA collects both supply-side and demand-side data. On the demand-side nationally representative surveys are conducted on ICT use and demand in African countries. This survey dataset consists of data collected by household and business surveys in thirteen African countries in 2011-2012.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
Households and individuals
Version
Version Description
Version 01: Edited, anonymised dataset for licensed distribution
Version Date
2012
Version Notes
Version 01 of the dataset was received from Research ICT Africa in July 2015.
Scope
Notes
Data collected on households includes: Dwelling type, household expenditure, access to electricity, ownership of goods, data on postal address and bank accounts, access to, use of, and expenditure on internet and landline, as well as household remittances.
Data collected on household members includes: Age, sex, relationship to household head, marital status, highest education level, main economic activity, income and other earnings, and mobile phone ownership. A household member was selected at random to provide more detailed data. Data collected on the Randomly Selected Individual includes: Contribution to household expenses, literacy, language, ownership of CD/MP3 player/ipod, social networks, money and banking, use of TV, radio, public phones, work phone, internet, detailed data on mobile phone usage.
Data collected on household members includes: Age, sex, relationship to household head, marital status, highest education level, main economic activity, income and other earnings, and mobile phone ownership. A household member was selected at random to provide more detailed data. Data collected on the Randomly Selected Individual includes: Contribution to household expenses, literacy, language, ownership of CD/MP3 player/ipod, social networks, money and banking, use of TV, radio, public phones, work phone, internet, detailed data on mobile phone usage.
Coverage
Geographic Coverage
The surveys had national coverage. Survey countries included Botswana, Cameroon, Ethiopia, Ghana, Kenya, Mozambique, Namibia, Nigeria, Rwanda, South Africa, Tanzania, Uganda, and Tunisia.
Universe
The data is nationally representative on a household and individual level for individuals 16 years of age or older.
Producers and sponsors
Primary investigators
| Name |
|---|
| Research ICT Africa |
Sampling
Sampling Procedure
The random sampling was performed in four steps for households and businesses, and five steps for individuals.
• Step 1: The national census sample frames was split into urban and rural Enumerator areas (EAs).
• Step 2: EAs were sampled for each stratum using probability proportional to size (PPS).
• Step 3: For each EA two listings were compiled, one for households and one for businesses. The listings serve as sample frame for the simple random sections.
• Step 4: 24 Households and 10 businesses were sampled using simple random sample for each selected EA.
• Step 5: From all household members 15 years or older or visitors staying the night at the house one was randomly selected based on simple random sampling.
• Step 1: The national census sample frames was split into urban and rural Enumerator areas (EAs).
• Step 2: EAs were sampled for each stratum using probability proportional to size (PPS).
• Step 3: For each EA two listings were compiled, one for households and one for businesses. The listings serve as sample frame for the simple random sections.
• Step 4: 24 Households and 10 businesses were sampled using simple random sample for each selected EA.
• Step 5: From all household members 15 years or older or visitors staying the night at the house one was randomly selected based on simple random sampling.
Weighting
Three weights were constructed, for households, individuals and for small businesses. The weights are based on the inverse selection probabilities and gross up the data to national level when applied.
Data Collection
Dates of Data Collection
| Start | End |
|---|---|
| 2011 | 2012 |
Data Collection Mode
Face-to-face [f2f]
Access policy
Contacts
| Name | URL | |
|---|---|---|
| DataFirst Support | support@data1st.org | support.data1st.org |
Access conditions
Licensed use files, available with restrictions
Citation requirements
Research ICT Africa. RIA ICT Access Survey 2011-2012 [dataset]. Version 1. Cape Town: RIA [producer], 2013. Cape Town: DataFirst [distributor], 2015. 10.25828/mef4-3810
Access authority
| Name | Affiliation | URL | |
|---|---|---|---|
| DataFirst | University of Cape Town | support@data1st.org | support.data1st.org |
Disclaimer and copyrights
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.
Metadata production
DDI Document ID
DDI_AFR_2011_RIAS_v02_M
Producers
| Name | Affiliation | Role |
|---|---|---|
| DataFirst | University of Cape Town | Metadata producer |
Date of Metadata Production
2019-06-26
DDI Document version
DDI Document - Version 02 - (04/27/21)
This version is identical to DDI_AFR_2011_RIAS_v01_M but country field has been updated to capture all the countries covered by survey.
Version 01 (September 2019): This DDI is identical to 'zaf-ria-rias-2011-2012-v1' which was downloaded from the DataFirst website.
This version is identical to DDI_AFR_2011_RIAS_v01_M but country field has been updated to capture all the countries covered by survey.
Version 01 (September 2019): This DDI is identical to 'zaf-ria-rias-2011-2012-v1' which was downloaded from the DataFirst website.