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House Price Forecasting from Investment Perspectives

Author

Listed:
  • Song Shi

    (School of the Built Environment, University of Technology Sydney, Sydney, NSW 2007, Australia)

  • Vince Mangioni

    (School of the Built Environment, University of Technology Sydney, Sydney, NSW 2007, Australia)

  • Xin Janet Ge

    (School of the Built Environment, University of Technology Sydney, Sydney, NSW 2007, Australia)

  • Shanaka Herath

    (School of the Built Environment, University of Technology Sydney, Sydney, NSW 2007, Australia)

  • Fethi Rabhi

    (School of Computer Science and Engineering, University of New South Wales, Sydney, NSW 2052, Australia)

  • Rachida Ouysse

    (School of Economics, University of New South Wales, Sydney, NSW 2052, Australia)

Abstract

Housing market dynamics have primarily shifted from consumption- to investment-driven in many countries, including Australia. Building on investment theory, we investigated market dynamics by placing investment demand at the center using the error correction model (ECM). We found that house prices, rents, and interest rates are cointegrated in the long run under the present value investment framework. Other economic factors such as population growth, unemployment, migration, construction activities, and bank lending were also important determinants of the housing market dynamics. Our forecasting results show that the Sydney housing market will continue to grow with no significant price decline in the foreseeable future.

Suggested Citation

  • Song Shi & Vince Mangioni & Xin Janet Ge & Shanaka Herath & Fethi Rabhi & Rachida Ouysse, 2021. "House Price Forecasting from Investment Perspectives," Land, MDPI, vol. 10(10), pages 1-17, September.
    • Handle: RePEc:gam:jlands:v:10:y:2021:i:10:p:1009-:d:643593
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    References listed on IDEAS

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    2. Nuri Hacıevliyagil & Krzysztof Drachal & Ibrahim Halil Eksi, 2022. "Predicting House Prices Using DMA Method: Evidence from Turkey," Economies, MDPI, vol. 10(3), pages 1-27, March.

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