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The demand for education: The impacts of good schools on property values in Brisbane, Australia

Author

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  • Rajapaksa, Darshana
  • Gono, Marcel
  • Wilson, Clevo
  • Managi, Shunsuke
  • Lee, Boon
  • Hoang, Viet-Ngu

Abstract

The demand for education is partly revealed by a higher demand for properties around good schools, which has been the basis for a number of empirical studies. This research attempts to explore the nexus of school quality and the property market when school ranking is clearly available to the public. The spatial hedonic property valuation method was employed to analyze selected Brisbane public (state) and private schools consisting of those with high, middle and low ranking in terms of average student academic school performance. The results imply the capitalization of school values in both property and rental prices. The research also demonstrates the spillover impacts of school development. Such impacts are higher in comparison to previous studies, which are supported by the average school performance considered in individual assessments. The results of this study can be a valuable input into school policy reforms. (JEL: H23, I20, I28, R21)

Suggested Citation

  • Rajapaksa, Darshana & Gono, Marcel & Wilson, Clevo & Managi, Shunsuke & Lee, Boon & Hoang, Viet-Ngu, 2020. "The demand for education: The impacts of good schools on property values in Brisbane, Australia," Land Use Policy, Elsevier, vol. 97(C).
    • Handle: RePEc:eee:lauspo:v:97:y:2020:i:c:s0264837719322562
    DOI: 10.1016/j.landusepol.2020.104748
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Chao Zhang & Mimi Xiong & Xuehui Wei & Zongmin Lan, 2023. "Spatial heterogeneity of marginal willingness to pay for air quality in PM2.5: analysis of buyers’ housing price in Beijing through hedonic price, spatial regression, and quantile regression models," Asia-Pacific Journal of Regional Science, Springer, vol. 7(3), pages 697-720, September.
    2. Sun, Wenwen & Jin, Hongyu & Chen, Yan & Hu, Xin & Li, Zhuoran & Kidd, Akari & Liu, Chunlu, 2021. "Spatial mismatch analyses of school land in China using a spatial statistical approach," Land Use Policy, Elsevier, vol. 108(C).
    3. Sihyun An & Yena Song & Hanwool Jang & Kwangwon Ahn, 2025. "Asymmetric impacts of artificial intelligence on housing price valuation across education levels," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 12(1), pages 1-16, December.
    4. Lirong Hu & Shenjing He, 2024. "Entrance opportunity vs. academic performance: unpacking the nonlinear capitalization effects of multidimensional school qualities on housing sales and rental prices," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 11(1), pages 1-13, December.
    5. Gyeongcheol Cho & Younyoung Choi & Ji-Hyun Kim, 2020. "Investigating the Unintended Consequences of the High School Equalization Policy on the Housing Market," Sustainability, MDPI, vol. 12(20), pages 1-9, October.
    6. Mathur, Shishir, 2022. "Non-linear and weakly monotonic relationship between school quality and house prices," Land Use Policy, Elsevier, vol. 113(C).
    7. Doko Tchatoka, Firmin & Varvaris, Vanessa, 2021. "Neighbourhood, school zoning and the housing market: Evidence from New South Wales," Journal of Housing Economics, Elsevier, vol. 54(C).

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    More about this item

    Keywords

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    JEL classification:

    • H23 - Public Economics - - Taxation, Subsidies, and Revenue - - - Externalities; Redistributive Effects; Environmental Taxes and Subsidies
    • I20 - Health, Education, and Welfare - - Education - - - General
    • I28 - Health, Education, and Welfare - - Education - - - Government Policy
    • R21 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Housing Demand

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