A break down of residential crime trends in South Africa

Update: This article has been updated with further clarity from Lightstone on how its data was compiled. A previous headline put focus on suburbs, which needs to be read in wider context of the original report.

Property group, Lightstone, has released a report on the effect of crime on property prices in South Africa, with some surprising data on the most crime-affected residential suburbs in the country.

The data is based on annual crime data provided by the SAPS, grouped into statistics on a more granular level.

The report focuses on residential crime, which includes malicious damage to residential property and home burglary. Burglary, shoplifting and robbery at non-residential premises is classified as non-residential crime, not represented in this data.

As a result, the rates have been standardised per thousand households to show crime relative to the size of the population.

Provincial level

According to Lightstone, the Western Cape has the highest average residential crime rate per thousand households.

“While the rate has dropped slightly in the past two years, the crime rate is still much higher than that of the next most crime-ridden province, the Northern Cape,” noted the report.

“Gauteng and the Free State showed similar rates per thousand households in 2016.”

In contrast Limpopo has the lowest provincial crime rate, although it has seen progressive increases over the past four years. This trend does not necessarily mean that the province is bucking the trend, however, said the report.

“It could rather be the result of an increase in access to police stations in the province’s developing rural areas. More police stations mean easier access for residents to report crime, which would show up in the numbers as more incidents.”

According to Lightstone these are the provinces in SA, listed from most to least residential crime cases per 1,000 households:

  1. Western Cape
  2. Northern Cape
  3. Gauteng
  4. Free State
  5. Eastern Cape
  6. KwaZulu-Natal
  7. Mpumalanga
  8. North West
  9. Limpopo

Click on images to enlarge.


Suburbs 

Drilling deeper into the crime rates per suburb we gain a better understanding of possible
contributory factors to crime rates and the effect it might have on the economy.

Most suburbs are inside a major metropolis which is characterised as the economic hub of a region and it is expected that people in these areas will generally have valuable assets and wealth that would be appeal to the criminally inclined.

Suburbs in the city have the highest residential crime rates, followed by those in isolated urban areas and in the wider metropolis.

This is not surprising as the residents of these areas usually have higher population densities with economically active residents. Suburbs classified as rural have the lowest residential crime rates.

[Graph with suburb-specific data has been removed at the request of Lightstone]


How the data was compiled [UPDATE]

Following feedback and queries submitted regarding the article, Lightstone has provided a more detailed explanation of how it compiled its data, which was published in the original report.

“In this case we are only focusing on residential crime which only includes malicious damage to residential property and home burglary in the figures. All other crimes are excluded from the modelling,” the group said.

“Our focus was to measure the impact of crime to residential property house price growth, and the suburb specific information was shared as a spin-off article to that. The intention for the granular spatial modelling from a police district level is to give an indication of crime relative to previous years and the size of the population in the area.”

Suburb specific data may be surprising without this context, Lightstone said.

According to Lightstone, the reason why these specific suburbs featured, is because they are in large police districts that service quite diverse areas.

“If there is a police district that serves both a low crime and a high crime area it is very difficult to statistically split the two, but we are constantly working on ways to better do that.”

 


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