National Household Travel Survey 2020
South Africa, 2020
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Reference ID
ZAF_2020_NHTS_v01_M
Producer(s)
Statistics South Africa
Collection(s)
Metadata
Created on
Jul 20, 2022
Last modified
Jul 20, 2022
Page views
742
Downloads
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Identification
Survey ID Number
ZAF_2020_NHTS_v01_M
Title
National Household Travel Survey 2020
Country/Economy
| Name | Country code |
|---|---|
| South Africa | ZAF |
Study type
Other Household Survey [hh/oth]
Abstract
The National Household Travel Survey (NHTS) 2020 is the third round of the survey series designed to assess domestic transport and tourism travel patterns of South African households as well as their attitudes about transport. The NHTS collects data on general household characteristics, travel patterns of households, and attitudes about transport.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
Households and individuals
Version
Version Description
Version 01: Edited, anonymized dataset for public distribution.
Version Date
2021
Scope
Notes
Household: household characteristics, socio-economic circumstances of households.
Individual: demographic information (sex, age, race), domestic transport and tourism travel patterns, and attitudes concerning transport
Individual: demographic information (sex, age, race), domestic transport and tourism travel patterns, and attitudes concerning transport
Coverage
Geographic Coverage
National coverage
Geographic Unit
The lowest level of geographic aggregation covered by the data is District Municipality.
Universe
The target population of the survey consists of all private households in all nine provinces of South Africa and residents in workers' hostels. The survey does not cover other collective living quarters such as students' hostels, old-age homes, hospitals, prisons and military barracks.
Producers and sponsors
Primary investigators
| Name | Affiliation |
|---|---|
| Statistics South Africa | Government of South Africa |
Sampling
Sampling Procedure
The sample design for the NHTS was based on a master sample (MS) that used a two-stage, stratified design with probability-proportional-to-size (PPS) sampling of PSUs from within strata, and systematic sampling of dwelling units (DUs) from the sampled primary sampling units (PSUs). A self-weighting design at provincial level was used and MS stratification was divided into two levels, primary and secondary stratification. Primary stratification was defined by metropolitan and non-metropolitan geographic area type. During secondary stratification, the Census 2001 data were summarized at PSU level. The following variables were used for secondary stratification, household size, education, occupancy status, gender, industry and income.
Census enumeration areas (EAs) as delineated for Census 2001 formed the basis of the PSUs. The following additional rules were used:
• Where possible, PSU sizes were kept between 100 and 500 dwelling units (DUs);
• EAs with fewer than 25 DUs were excluded.
• EAs with between 26 and 99 DUs were pooled to form larger PSUs and the criteria used was same settlement type;
• Virtual splits were applied to large PSUs: 500 to 999 splits into two; 1000 to 1499 splits into three; and 1500 plus split into four PSUs; and
• Informal PSUs were segmented.
A Randomized Probability Proportional to Size (RPPS) systematic sample of PSUs was drawn in each stratum, with the measure of size being the number of households in the PSU. Altogether approximately 3080 PSUs were selected. In each selected PSU a systematic sample of dwelling units was drawn. The number of DUs selected per PSU varies from PSU to PSU and depends on the Inverse Sampling Ratios (ISR) of each PSU.
Census enumeration areas (EAs) as delineated for Census 2001 formed the basis of the PSUs. The following additional rules were used:
• Where possible, PSU sizes were kept between 100 and 500 dwelling units (DUs);
• EAs with fewer than 25 DUs were excluded.
• EAs with between 26 and 99 DUs were pooled to form larger PSUs and the criteria used was same settlement type;
• Virtual splits were applied to large PSUs: 500 to 999 splits into two; 1000 to 1499 splits into three; and 1500 plus split into four PSUs; and
• Informal PSUs were segmented.
A Randomized Probability Proportional to Size (RPPS) systematic sample of PSUs was drawn in each stratum, with the measure of size being the number of households in the PSU. Altogether approximately 3080 PSUs were selected. In each selected PSU a systematic sample of dwelling units was drawn. The number of DUs selected per PSU varies from PSU to PSU and depends on the Inverse Sampling Ratios (ISR) of each PSU.
Data Collection
Dates of Data Collection
| Start | End |
|---|---|
| 2020-01-27 | 2020-03-20 |
Data Collection Mode
Face-to-face [f2f]
Data Collectors
| Name |
|---|
| Survey Solutions |
Questionnaires
Questionnaires
The survey questionnaire consisted of 9 sections:
Section 1: General health and functioning, social grants and social relief
Section 2: General travel patterns
Section 3: Education and education-related travel patterns
Section 4: Work-related travel patterns (age 15 years and above)
Section 5: Business trips
Section 6: Other travel patterns
Section 7: General household information
Section 8: Household attitudes and perceptions about transport
Section 9: Survey officer questions
Section 1: General health and functioning, social grants and social relief
Section 2: General travel patterns
Section 3: Education and education-related travel patterns
Section 4: Work-related travel patterns (age 15 years and above)
Section 5: Business trips
Section 6: Other travel patterns
Section 7: General household information
Section 8: Household attitudes and perceptions about transport
Section 9: Survey officer questions
Access policy
Contacts
| Name | Affiliation | URL | |
|---|---|---|---|
| DataFirst Helpdesk | University of Cape Town | support@data1st.org | Link |
Access conditions
Public access data, available to all
Citation requirements
Statistics South Africa. National Household Travel Survey 2020 [dataset]. Version 1. Pretoria: Statistics South Africa [producer], 2021. Cape Town: DataFirst [distributor], 2021. DOI: https://doi.org/10.25828/NRVJ-1663
Access authority
| Name | Affiliation | URL | |
|---|---|---|---|
| DataFirst | University of Cape Town | support@data1st.org | Link |
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.
Copyright
Copyright, Statistics South Africa
Metadata production
DDI Document ID
DDI_ZAF_2020_NHTS_v01_M
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| DataFirst | University of Cape Town | Metadata Producer | |
| Development Economics Data Group | DECDG | The World Bank | Metadata adapted for Microdata Library |
Date of Metadata Production
2021-11-24
DDI Document version
Version 01: This metadata was downloaded from the DataFirst website (https://www.datafirst.uct.ac.za/dataportal/index.php/catalog/central). The following two metadata fields were edited - Document and Survey ID.