UTAS IRP - Predicted Proportion of Underinsurance (SA1) 2016

Dataset extent


This dataset presents the footprint of the proportion of underinsurance across Australia. The data is aggregated to Statistical Area Level 1 (SA1) geographic areas from the 2016 Australian Statistical Geography Standard (ASGS). House and contents underinsurance is understood as homeowners having no house insurance and renters having no contents insurance to cover adverse events.

To create this dataset, researchers developed a method to extrapolate the patterns of underinsurance evident in the 2015 Australian Survey of Social Attitudes (AuSSA), an omnibus postal survey of Australian adults (Blunsdon, 2016). To do this, they combined the results of the full model of underinsurance with the 2016 Socio-Economic Indexes for Areas (SEIFA) (Australian Bureau of Statistics, 2019). For this spatial mapping, regression coefficients were converted to probabilities by taking the exponent of each coefficient to generate the odds ratio and then using the formula: probability = odds/(1+odds). For each SA1 unit (containing approximately 150 households), the proportion of residents or households was determined for each predictor variable from raw census data. The level of underinsurance (proportion of people predicted not to have insurance) was then predicted separately for renters and owner-occupiers for every SA1 and a single map generated by weighting the predictions by the proportion of renters and owner-occupiers per SA1.

For further information about this dataset and its creation, please refer to the publication: Booth, K., & Kendal, D. (2019). Underinsurance as adaptation: Household agency in places of marketisation and financialisation. Environment and Planning A: Economy and Space.

Please note:

  • The researchers acknowledge some limitations with the data, including the lack of data on rental properties. They do not know whether these properties are insured by landlord-investors and how this may be associated with sociodemographic variables and contribute to the mapping.

  • This research was in part supported by the Australian Government through the Australian Research Council Discovery Program (DP170100096).


Additional Info

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Field Value
Source https://adp.aurin.org.au/geoserver/wfs
Last Updated June 28, 2023, 08:54 (UTC)
Created June 28, 2023, 08:54 (UTC)
ADP ID datasource-UTAS_IRP-UoM_AURIN_DB:utas_irp_underinsurance_sa1_2016
Access Level Open Access
Aggregation Level sa1_2016
Attribute List Area (sqkm), GCCSA Code, GCCSA Name, Geometry, Proportion of Underinsurance, SA1 7-Digit Code, SA1 Main Code, SA2 5-Digit Code, SA2 Main Code, SA2 Name, SA3 Code, SA3 Name, SA4 Code, SA4 Name, State Code, State Name
Attribution University of Tasmania - Insurance Research Program, (2019): UTAS IRP - Predicted Proportion of Underinsurance (SA1) 2016; accessed from AURIN on [date of access].
Coordinate Ref. System EPSG:4283 (GDA_1994)
Copyright Notice © University of Tasmania 2021
Data Disclaimer The Under-insurance Mapping Project is the product of analysis of data from the Australian Survey of Social Attitudes 2015 and the authors acknowledge Australian Consortium for Social and Political Research Incorporated as the original depositors of this work in the Australian Data Archive. Those who carried out the original analysis and collection of the data bear no responsibility for the further analysis or interpretation of it.
Geometry Field wkb_geometry
Key sa1_main16
Type dataset
spatial {"type": "Polygon", "coordinates": [[[96.82, -43.74], [168.0, -43.74], [168.0, -9.14], [96.82, -9.14], [96.82, -43.74]]]}