zaf-statssa-dts-2014-v1
Domestic Tourism Survey 2014
Name | Country code |
---|---|
South Africa | zaf |
Household Survey
Statistics South Africa collects data on foreign tourism from the South African Department of Home Affairs. Data on domestic tourism is also needed to measure its contribution to the national economy. The Domestic Tourism Survey (DTS) is aimed at addressing this need by collecting data on the travel behaviour and expenditure of South African residents travelling within and outside the borders of South Africa. This survey provides data on domestic tourism activity during the period January to December 2014.
Sample survey data
Households and individuals
v1: Edited, anonymised dataset for public distribution
2014
Version 1 of the Domestic Tourism Survey 2014 was downloaded from Statistics South Africa's website on 19 January 2016.
The scope of the Domestic Tourism Survey 2014 includes: household characteristcs, education of household members, tourism employment, and day/overnight trips by the respondent and/or other household members. These include travel for business, recreation, entertainment, sports and nature based travel, religious and medical travel, type of transport used and expenditure on this type of travel.
Topic | Vocabulary | URI |
---|---|---|
leisure, tourism and sport [13.4] | CESSDA | http://www.nesstar.org/rdf/common |
The survey had national coverage
The lowest level of geographic aggregation covered by the data is municipality.
The target population of the survey consists of all private households and residents in workers' hostels in the nine provinces of South Africa. The survey does not cover other collective living quarters such as students' hostels, old age homes, hospitals, prisons and military barracks.
Name |
---|
Statistics South Africa |
For the Domestic Tourism Survey SSA used a household survey master sample of 3 080 primary sampling units from the 80 787 enumeration areas (EAs) created for the 2001 Population Census. The master sample 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 2001 data were summarised at PSU level. The following variables were used for secondary stratification; household size, education, occupancy status, gender, industry and income.
Sampling weights for the data collected from the sampled households are constructed so that responses can be expanded appropriately to represent the entire population of South Africa. The weights are the result of calculations involving several factors, including design weights, adjustment for non-response, and benchmarking to known population estimates. The final survey weights are constructed by calibrating the adjusted base weight to the known population counts at national and provincial levels, cross-classified by 5-year age groups, gender and race. The calibrated weights are constructed to ensure that all persons in a household have the same final weight (integrated weighting).
Household Questionnaire: This includes sections on:
Household characteristcs, household listing, education, tourism employment, trips taken, day trips, overnight trips, barriers to taking trips, business and professional trips, recreation entertainment, sports trips, nature based trips, religious trips, medical trips, type of transport, expenditure on trips, social activites
Start | End |
---|---|
2014-01 | 2014-12 |
Name | Affiliation | URL | |
---|---|---|---|
DataFirst | University of Cape Town | http://support.data1st.org | support@data1st.org |
Public access data for use under a Creative Commons CC-BY (Attribution-only) License
Statistics South Africa. Domestic Tourism Survey 2014 [dataset]. Version 1. Pretoria: Statistics South Africa [producer], 2015. Cape Town: DataFirst [distributor], 2016.
(c) 2012 , Statistics South Africa
Name | Affiliation | URL | |
---|---|---|---|
DataFirst Helpdesk | University of Cape Town | support@data1st.org | http://support.data1st.org/ |
ddi-zaf-ssa-dts-2012-v1
Name | Affiliation | Role |
---|---|---|
DataFirst | University of Cape Town | Metadata producer |
2016-01-19
Version 1