Russell Buzby

When Western Australia introduced its bushfire prone area maps in 2015, the maps delivered a surprise that had nothing to do with any individual property. They showed that roughly 90% of the state sat inside a bushfire prone area. From that point, estate agents were obliged to tell prospective buyers whether a property carried the designation, and a recent study has measured what that single disclosure requirement did to the market. Properties inside a bushfire prone area sold at a 4.2% discount compared with those outside it.

The figure is interesting on its own. What makes it useful is the reason behind it. Gonzalez Valencia and colleagues used a regression discontinuity design, comparing properties just inside the mapped boundary with those just outside it. They found the discount was driven by the information shock of the new maps rather than by pre-existing risk perception or stricter building codes. The market had not already priced this risk, with the maps merely confirming it. The market began pricing the risk because the maps made it visible. Buyers who would otherwise have paid full price adjusted once they were told, and the adjustment held at the boundary where the only thing that changed was the designation.

That distinction is the whole point, because it identifies the mechanism as disclosure rather than coercion. Coercion is what governments usually reach for, whether a tax or a mandated retrofit. Here the state did neither. It simply required that a fact already known to it be shared with the buyer, and the property market did the rest. Disclosure internalised a risk that had been external to the transaction, and it did so at close to zero fiscal cost, which is a combination rare enough in policy to study closely.

The result also sharpens a broader argument I have made about climate repricing and the insurance protection gap. Insurers are repricing bushfire risk through premiums, sometimes to the point where cover becomes unaffordable in the highest-risk areas. The WA maps show the same risk being repriced through property values instead. These are two market signals pointing at one underlying hazard, and they reinforce each other. A buyer who sees both a bushfire prone designation and a quoted premium is getting a far clearer picture of lifetime cost than a buyer who sees neither, which is closer to how an efficient market for risk is supposed to behave.

Disclosure has one serious limit. A risk map can only price the risk it measures, and the WA maps measure building exposure to fire. They say nothing about the downstream hazards that a fire sets in motion, and new research is filling in how large those can be. A Canadian study of sediment cores from a drinking water reservoir found that past wildfires caused significant geochemical changes in the water source, with some elemental disturbances persisting for more than a century. That finding aligns with what emerged after the 2023 Maui fires and with broader United States Forest Service work on wildfire and water security, where post-fire contamination of source water is a compounding risk that supply managers are only beginning to build into long-term planning. None of that risk appears on a bushfire prone area map, yet it can outlast the house the map was drawn to protect.

The inputs to these maps are improving at the same time, which matters because a disclosure tool is only as honest as the model underneath it. A study using terrestrial mobile LiDAR to measure fuel connectivity in South Australian coastal mallee produced vertical and horizontal connectivity metrics that outperform canopy height alone in predicting fire spread and crown-fire risk. Better fuel metrics make for better hazard mapping, and better hazard mapping makes the disclosure more accurate. The chain runs from the science through the map to the buyer, and a weak link anywhere upstream shows up as a mispriced house downstream.

This is the same caution I raised about wildfire risk models more generally, where a single update to a national simulation moved estimated exposure for an entire region by more than half. A bushfire prone area map carries the same air of authority and the same hidden dependence on its inputs. When the underlying fuel science or climate data shifts, the map shifts with it, and every disclosure made on the old map was priced against a risk picture that has since moved. Disclosure is powerful precisely because the market trusts the map, which places a heavy obligation on whoever maintains it to keep it current.

The efficiency story can obscure an equity dimension. A 4.2% discount is a transfer. It lands on the owner who bought before the map existed and now sells into a market that has repriced their asset, and it raises the barrier for anyone whose wealth is concentrated in a home that has just been designated. Disclosure shifts risk onto the people closest to it, which is efficient in market terms and uncomfortable in distributional ones. A government reaching for this lever should reach for it with that trade-off named rather than assumed away, because the households absorbing the discount are rarely the ones with the most capacity to mitigate the underlying hazard.

None of this diminishes the core finding, which deserves to travel well beyond fire policy. Australian governments spend a great deal of effort on regulation that is expensive to design and harder to enforce, while a cheaper instrument sits underused. Telling people the truth about their risk, in a form they encounter at the moment of decision, changes behaviour at a fraction of the cost of mandating it. The WA experience puts a number on that effect for the first time, and 4.2% is a large return for the price of an honest map. The instrument works. The responsibility it creates is making sure the map keeps telling the truth as the risk it describes keeps changing.

References

Gonzalez Valencia, [et al.]. (2026). A discontinuity analysis of the 2015 introduction of bushfire prone area maps. Risk Analysis. https://doi.org/10.1111/risa.70276

Wildfire-induced elemental changes in drinking water reservoir sediments. (2026, June 1). Natural Hazards Research.

Measuring fuel connectivity in coastal mallee shrublands using terrestrial mobile LiDAR. (2026, June 3). Fire Ecology.