In this spotlight, we used Victoria Police recorded data to 31 March 2021 to examine long-term Property and deception-related offence trends.
We found that despite a 16 year increasing trend for Victorian crime statistics Property and deception-related offences had decreased by 11.0%. In the last 12 months, the overall recorded crime offence count has dropped 1.8%, driven by the dramatic decrease in acquisitive crime crimes in Property and deception offences, which were down 59,773 offences or 19.1%. The recent decline in Victorian recorded crime coincides with COVID-19-related disruptions, possibly reflecting changes in the guardianship of property as people were at home more often and mobility in the community was reduced, changing criminal offending opportunities for some crime types.
The overall decrease in acquisitive crime types in the last 12 months was driven by Theft (down 44,402 offences or 23.4%) and Burglary/Break and enter offences (down 12,739 offences or 29.3%). Most of the recorded stolen property items for these offence types were taken from residential locations. The decrease in the last 12 months in the Residential non-aggravated burglary offence type has contributed to less stolen property reports (down 30.9%).
The property items stolen that hold their value, such as cash, continue to be stolen in Victoria. On the other hand, items such as computers started to be stolen less frequently as they were replaced by other devices such as a laptop/tablet, which increased. Similar trends are evident for Photographic equipment, Mobile phones, MP3 player/iPod, TV/VCR and Video game categories, which all increased when new models were introduced to the market and desirability for these items and their value was highest, but over time the numbers of these items stolen have decreased, especially as newer technologies replaced them.
The full spotlight findings are available in the attached files and details about the property items stolen are included in the data visualisations.
Property Items and Farm Crime - Data Visualisation
This work is licensed under a Creative Commons Attribution 4.0 International License .