Australia’s runaway rents by ABC News (Australia)

This project used two decades of data from property portal Domain to reveal how the pandemic triggered Australia’s worst rental crisis in recent memory. The figures, supplied exclusively to the ABC, track median asking rents for more than two decades across nearly 4,000 Australian suburbs.

It is the first time rental price data has been publicly analysed at this level of geographical detail, and across such an extensive time period. This highly granular approach allowed us to not only illustrate the depth and breadth of the crisis, but to also put the unprecedented changes driven by the pandemic into historical perspective.

A key difference was the project’s focus on regional towns and neighbourhoods beyond the major cities. The vast majority of stories about Australia’s rental market rely on summary statistics (medians and averages) aggregated across large geographic areas because this data is readily available. However, this kind of data provides a blunt instrument for analysis. We intentionally sought the most granular data so we could produce a richer, more nuanced and more accurate picture of the distinct ways the crisis has unfolded across different parts of the country.

We kept this granularity “front and centre” of both our reporting and our visualisations, which honed in on smaller towns and regions excluded from other analyses.

To this end, we built two interactive databases allowing users to explore hyper-local data for their region. The first (“Where you can afford to rent”) shows deteriorating affordability in Australia’s capital cities. It is the first public database to present historical data broken down by number of bedrooms – a key determinant of housing suitability.

The second interactive (“How quickly are asking rents rising in your area?”) is the first public database to present annual, disaggregated, suburb-level data spanning 22 years (or as far back as records were available). Covering nearly every suburb in the country's urban centres, including more than 1000 outside capital cities, it is by far the most comprehensive publicly-available tool of its kind.

Our audience metrics show this story achieved the highest average engagement time of any in our team’s history.

An unexpected challenge of working with a 22-year dataset was that both the geographical names and boundaries of the areas we were working with had changed over time, often multiple times. On top of this, the geographical names used in the proprietary dataset did not match the names used in the Australian Statistical Geography Standard, the geographic datasets used to produce the maps in the story.

This meant that in some cases, rental price data for an area that residents would recognise as one neighbourhood/area was separated across multiple area names, and each of these names matched to a different set of geographic boundaries.

Overcoming this data headache required weeks of extra work not apparent in the story itself. It involved matching rental price data to multiple geographic datasets spanning 22 years, and then consolidated each of these datasets into a single “master” dataset.