The primary aim of the Victims of Crime Survey is to establish the prevalence of particular kinds of crime within a certain population. This may be victimisation experienced by individuals or households. Data from victimisation surveys can be used to supplement official crime statistics. The objectives of the survey are to:
• Provide information about the dynamics of crime from the perspective of households and the victims of crime.
• Explore public perceptions of the activities of the police, prosecutors, courts and correctional services in the prevention of crime and victimisation.
• Provide complimentary data on the level of crime within South Africa in addition to the statistics published annually by the South African Police Service.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
The units of analysis in the study were individuals and households
v1: Edited, anonymised dataset for licensed access
Version 1 of the dataset was downloaded from Statistics South Africa's website on the 26th of January 2015.
The VOCS 2013/14 focuses on people's perceptions and experiences of crime, as well as their views regarding access to and effectiveness of the police and justice system. Households are also asked about community responses to crime. The survey profiled different aspects of crimes, such as their location and timing, the use of weapons and the nature and extent of the violence that occurred. Sections of the questionnaire covered the following topics:
Flap: Demographic information
Section 1 Household-specific characteristics (education, economic activities and household income sources)
Section 2 General thinking / beliefs on crime
Section 3 Individual and community response to crime
Section 4 Victim support and other interventions
Section 5 Citizen interaction or community cohesion
Section 6 Perception of the police service
Section 7 Perception of the courts
Section 8 Perception of correctional services
Section 9 Corruption experienced by the household
Section 10 Experience of household crime (screening table)
Section 11 Theft of car experienced by a household member(s) in the past 12 months
Section 12 Housebreaking or burglary when no one was at home in the past 12 months
Section 13 Home robbery (including robbery often around or inside the household's dwelling) experienced by a household member(s) in the past 12 months
Section 14 Theft of livestock, poultry and other animals in the past 12 months
Section 15 Theft of crops planted by the household in the past 12 months
Section 16 Murder experienced by a household member(s) in the past 12 months
Section 17 Theft out of the motor vehicle experienced by a household member(s) in the past 12 months
Section 18 Deliberate damaging/burning or destruction of dwelling experienced by a household member(s) in the past 12 months
Section 19 Motor vehicle vandalism or deliberate damage of a motor vehicle experienced by a household member(s) in the past 12 months
Section 20 Theft of bicycle experienced in the past 12 months
Section 21 Experiences of individual crimes (screening table) in the past 5 years and in the past 12 months
Section 22 Theft of personal property experienced in the past 12 months
Section 23 Car hijacking (including attempted hijacking) experienced in the past 12 months
Section 24 Robbery (including street robberies and other non-residential robberies, excluding car or truck hijackings, and home robberies) experienced in the past 12 months
Section 25 Assault experienced in the past 12 months
Section 26 Sexual offences (including rape) experienced in the past 12 months
Section 27 Consumer fraud experienced by the individual experienced in the past 12 months
Section 28 Corruption (when someone is in a position of authority fails to do something he/she is required to do and solicits a bribe)
law enforcement [5.2]
legal systems [5.3]
The survey had national coverage. The lowest level of geographic aggregation of the data is Province.
The lowest level of geographic aggregation covered by the data is province
The target population of the survey consists of all private households in all nine provinces of South Africa, as well as 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. It is only representative of non-institutionalised and non-military persons or households in South Africa.
Producers and sponsors
Statistics South Africa
Government of South Africa
The sample design for the VOCS 2013-2014 used a master sample (MS) originally designed for the Quarterly Labour Force Survey (QLFS) as a sampling frame. The MS is based on information collected during the 2001 Population Census conducted by Stats SA. The MS has been developed as a general-purpose household survey frame that can be used by all household-based surveys irrespective of the sample size requirement of the survey. The VOCS 2013/14, like all other household-based surveys, uses an MS of primary sampling units (PSUs) which comprise census enumeration areas (EAs) that are drawn from across the country.
The sample for the VOCS 2013/14 used 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. The sample was designed to be representative at provincial level. A self-weighting design at provincial level was used and MS stratification was divided into two levels. Primary stratification was defined by metropolitan and non-metropolitan geographic area type. During secondary stratification, the Census 2001 data were summarised at PSU level. The following variables were used for secondary stratification: household size, education, occupancy status, gender, industry and income. The Master Sample is based on 3 080 PSUs.
A Probability Proportional to Size (PPS) systematic sample of PSUs was drawn in each stratum, with the measure of size being the number of households in the PSU. The sample size for the VOCS 2013/14 had 31 390 dwelling units from 3 052 PSUs. 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 and the number of dwelling units in that PSU.
The sampling weights for the data collected from the sampled households are constructed in such a manner that the responses could be properly expanded to represent the entire South African households.
The base weight for each sampled household is equal to the reciprocal of the probability of selection, which is simply the inverse of the sampling rate. The sampling rate has been assigned at province level, i.e. all design strata within a province have been sampled at the same rate. Thus, the initial base weight (or design weight) assigned to each household in a province is simply the inverse sampling rate (ISR) for the province. The first adjustment was applied to account for informal and/or growth PSUs. The second adjustment was applied to account for the EAs with less than 25 households, and the third was the non-response adjustment. In addition, there were two types of non-response adjustments: PSU non-response adjustment and household non-response adjustment. In general, the non-response adjustment will be applied at the PSU level. Only in those cases where the non-response at the PSU level is too large, the non-response adjustment will be applied at the stratum level.
Final survey weights
The final survey weights were constructed by calibrating the non-response-adjusted design weights to the known population estimates as control totals using the 'Integrated Household Weighting' method. The lower bound for the calibrated weights was set equal to 50 when computing the calibrated weights with the StatMx software (Statistics Canada software). The VOCS 2013/14 sample was calibrated using the Population Estimate of Mid May 2013 (based on the 2010 series). The final weights were benchmarked to the known population estimates of 5-year age groups by population groups by gender at national level, and broad age groups at province level. The calibrated weights are constructed such that all persons in a household would have the same final weight. Records for which the age, population group or gender had item non-response could not be weighted and were therefore excluded from the dataset. No additional imputation was done to retain these records.
Dates of Data Collection
Data Collection Mode
Statistics South Africa
The VOCS 2013/14 questionnaire was based on the questionnaires used in the International Crime Victim Survey (ICVS) and previous VOCSs conducted by the Institute for Security Studies (ISS) and Statistics SA.
Sections 10 to 20 of the questionnaire relate to household crimes. A proxy respondent (preferably head of the household or acting head of household) answered on behalf of the household. Section 21 to 28 of the questionnaire about crimes on individuals were asked of a household member who was selected using the birthday section method. This methodology selects an individual who is 16 years or older, whose birthday is soonest after the survey date.
The VOCS 2013-2014 is comparable to the previous VOC surveys because several questions have remained unchanged over time. Where comparisons were possible, thi is indicated in the report provided with the data. The current survey can provide for more accurate estimates at provincial level. Caution should be exercised when running cross tabulations of different crimes by provinces with other variables, however. For several crimes the reported experienced cases were too few to allow for extensive analysis.
Because VOCS 2013-2014 is the first in a new continuous data collection series it covers estimates of crimes as from April 2012 to February 2014, which is more years than covered by previous VOC surveys conducted by Statistics SA.
University of Cape Town
University of Cape Town
Public use data, available to all
Statistics South Africa. Victims of crime survey 2013-2014 [dataset]. Version 1. Pretoria: Statistics South Africa [producer], 2014. Cape Town: DataFirst [distributor], 2015.