Song Shi

• Associate Professor, Property Economics, University of Technology Sydney

Dr Song Shi is a property academic with an interest in housing market analysis and price forecasting. His current research focuses on housing policy debates, sustainable urban development, and environmental risk reduction. As a first-generation Chinese, he has a growing interest in studying Chinese immigrants regarding their studies, work, and life in Australia.

Song's work examines both theoretical and empirical innovations in this cross-disciplinary field. His current research includes housing market forecasting, the impact of perceived earthquake and flood risk on property values, solar panel adoption and energy transitions, and the performance of Chinese agents and developers in Australia and China. His latest work, "How Much Did Chinese Investors Drive Up Sydney Home Prices?", published in Housing Studies and The Conversation, has had a significant social impact on the debate over foreign investment and housing affordability in Australia, with 37,850 reads.

Previous notable projects include funded industry research exploring long-term house price forecasting for NSW Landcom ($127,954) and high-profile research articles. To date, Song has produced more than 115 research outputs, including 1 book chapter, 33 refereed academic journal articles, 5 professional articles, 5 commissioned reports, 32 conference papers, 19 invited seminars/keynote presentations, and 22 media interviews. Among the academic journal articles, 2 papers were published in A* journals, and 13 have been published in A or Q1 journals. Key publications include research on the effectiveness of using interest rates to control house prices published in the Journal of Banking and Finance, capturing animal spirits in the housing market published in Real Estate Economics, the ripple effect of local house price movements published in the Journal of Property Research, and house price-volume dynamics published in the Journal of Real Estate Research.

Currently, he is working on fully automating the forecast using AI, with the aim of commercialising it in the future. The forecast can provide a much-needed tool for property investors, homeowners and buyers, real estate agents, property professionals, and policymakers, allowing for real-time checks of housing market status. This will enable users to view and understand the heat and cold housing spots, as well as future price, rent, and interest rate trajectories for each local suburb across all the capital cities in Australia.

Song is a leading property researcher at UTS. He won the DAB Faculty Award for Highest Impact Research Project or Achievement in 2023, the UTS Australia-China Relations Institute Research Grants in 2020 and 2022, and the UrbanGrowth NSW University Roundtable Research Grant in 2019. He is on the editorial board of Property Management, Journal of Regional Economics, International Journal of Housing Market and Analysis, and Pacific Rim Property Research Journal. He is the keynote speaker for the PhD colloquium at the 31st Pacific Rim Real Estate Society Conference and has been invited to many seminars and workshops for research and keynote presentations. He regularly appears on SBS Mandarin Radio for housing market commentary.

• –present Associate Professor, University of Technology Sydney

• 2009 Massey University, PhD

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