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.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
The units of analysis in the Domestic Tourism Survey are households and individuals
v1.1: Edited, anonymised dataset for public distribution
Version 1.0 of the Domestic Tourism Survey 2016 was downloaded from Statistics South Africa's website on 2 January 2018.
Version 1.1 is mostly the same as the original except DataFirst fixed some variables with mislabelled values. This relabelling was according to the publically available metadata and questionnaires (also included as external resources in this dataset).
The scope of the Domestic Tourism Survey 2016 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.
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.
Producers and sponsors
Statistics South Africa
Government of South Africa
The DTS 2016 collection was based on the 2013 Master Sample. This Master Sample is based on information collected during the 2011 Census conducted by Stats SA. In preparation for Census 2011, the country was divided into 103 576 enumeration areas (EAs). The census EAs, together with the auxiliary information for the EAs, were used as the frame units or building blocks for the formation of primary sampling units (PSUs) for the Master Sample, since they covered the entire country and had other information that is crucial for stratification and creation of PSUs. There are 3 324 primary sampling units (PSUs) in the Master Sample with an expected sample of approximately 33 000 dwelling units (DUs). The number of PSUs in the current Master Sample (3 324) reflect an 8,0% increase in the size of the Master Sample compared to the previous (2008) Master Sample (which had 3 080 PSUs). The larger Master Sample of PSUs was selected to improve the precision (smaller coefficients of variation, known as CVs) of the DTS estimates.
The Master Sample is designed to be representative at provincial level and within provinces at metro/non-metro levels. Within the metros, the sample is further distributed by geographical type. The three geography types are Urban, Tribal and Farms. This implies, for example, that within a metropolitan area, the sample is representative of the different geography types that may exist within that metro.
The sample for the DTS is based on a stratified two-stage design with probability proportional to size (PPS) sampling of PSUs in the first stage, and sampling of dwelling units (DUs) with systematic sampling in the second stage an even spread of DUs per stratum for each month.
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 full sample and replicate weights were calibrated using the population control totals for the cells defined by the cross-classification Age-Group x Population-Group x Gender at the national level, and broad Age Groups at the province level. These are the same population control totals that are used for constructing the calibrated weights for the Quarterly Labour Force Survey and the other household surveys.
Dates of Data Collection
Data Collection Mode
The data was collected with a household questionnaire