Land is one of the most valuable assets in Australia and the way it is valued impacts the taxes everyday citizens pay, and the locations valuable public resources like schools and hospitals are placed.
Attaching a value to land that is fair and equitable has presented a key challenge to local and state governments and getting this exercise wrong creates inequities for everyday Australians.
To make this process fairer for citizens and to decrease the burden for governments, Professor Alicia Rambaldi is building new economic models to tackle this challenge.
“Historically it has been very challenging to value land accurately,” Professor Ramabaldi said.
“Land revaluations present a significant risk to state government revenues, yet a reliable modelling framework to predict land values has been notably absent.
“One of the duties of universities is to produce research and tools which can address major challenges to help the broader community – it is our hope that the suite of tools we are creating will do this,” she said.
The new models seek to use various data sources to ensure accurate models are formulated for each area that help explain and identify potential issues.
“By partnering with government on this project we hope to develop a comprehensive robust and user-friendly set of modelling tools,” she said.
Current economic models for land valuations don’t help us understand why particular areas of a city sometimes have variations in land prices – for example if there are delays in development which influence pricing.
“From a planning perspective, this is inefficient. Models need to better capture other data sources which explain movements of people and fluctuations in prices,” Professor Ramabaldi said.
“We need to understand what creates price fluctuations and accurately value property to help the government determine where new assets such as hospitals and railways should be best placed.
“We also need better valuations because they help the government develop optimum taxation – so that taxes aren’t unfairly high or low in a certain area.
“Essentially, with these models, we hope to create a fairer system,” Professor Ramabaldi said.