How SuburbLens computes the Residency Shift Index, how suburbs map to ABS statistical areas, and the years, sources and limitations behind every dataset.
Prices and rents in the Census age badly — a "median mortgage" can reflect a loan taken out a decade ago. Tenure — whether homes are owned outright, owned with a mortgage, or rented — is a structural signal that does not go stale the same way. The Residency Shift Index compresses the direction of that change into one number: a weighted sum of the percentage-point change in each tenure share between the 2016 and 2021 Censuses — minus 1.0 times the change in rented share (rising rental = investor-driven, the main signal), plus 0.8 times the change in owned-with-mortgage share (young families entering), plus 0.3 times the change in owned-outright share (stabilising). Scores map to five bands from strong ownership shift to strong rental shift. It is a heuristic for putting one number on a trend — useful for a glance, not a scientific measure — and is always labelled "SuburbLens Custom" in the interface.
You search by Suburb and Locality (SAL) — the name people recognise — but the ABS publishes most Census tables against Statistical Area Level 2 (SA2), a slightly coarser unit. SuburbLens matches each suburb to its primary SA2 and shows that SA2's data, so a figure can fold in a neighbouring area. Every suburb page notes which SA2 its cross-year data comes from.
Tenure, language at home, country of birth and education come from the ABS Census Time Series Profile (tables T01, T10, T08, T29) for 2011, 2016 and 2021. Crime is from the Victoria Crime Statistics Agency, recorded incidents, Greater Melbourne only, and is ranked by volume rather than a per-capita rate. Coverage is Greater Sydney and Greater Melbourne only. The Census is a five-yearly, self-reported snapshot and the ABS randomly adjusts very small counts to protect privacy, so tiny numbers are approximate.