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Variation Across Price Segments and Locations: A Comprehensive Quantile Regression Analysis of the Sydney Housing Market

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  • Sofie R. Waltl

Abstract

Standard house price indices measure average movements of average houses in average locations belonging to an average price segment and hence obscure spatial and cross‐sectional variation of price appreciation rates even within a single metropolitan area. This article combines penalized quantile regression techniques with the hedonic imputation approach to reveal such kind of variation. The method is applied to house transactions from Sydney between 2001 and 2014. The analysis finds significant variation across sub‐markets over time and in particular during the boom‐and‐bust cycle peaking in 2004. Appreciation rates were highest for suburban, low‐priced and lowest for inner‐city, high‐priced houses.

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  • Sofie R. Waltl, 2019. "Variation Across Price Segments and Locations: A Comprehensive Quantile Regression Analysis of the Sydney Housing Market," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 47(3), pages 723-756, September.
    • Handle: RePEc:bla:reesec:v:47:y:2019:i:3:p:723-756
    DOI: 10.1111/1540-6229.12177
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    Cited by:

    1. Kholodilin, Konstantin A. & Limonov, Leonid E. & Waltl, Sofie R., 2021. "Housing rent dynamics and rent regulation in St. Petersburg (1880–1917)," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 81.
    2. Mats Wilhelmsson, 2019. "Energy Performance Certificates and Its Capitalization in Housing Values in Sweden," Sustainability, MDPI, vol. 11(21), pages 1-16, November.
    3. Anthony Lepinteur & Sofie R. Waltl, 2020. "Tracking Owners’ Sentiments: Subjective Home Values, Expectations and House Price Dynamics," Department of Economics Working Papers wuwp299, Vienna University of Economics and Business, Department of Economics.
    4. Robert J. Hill & Norbert Pfeifer & Miriam Steurer & Radoslaw Trojanek, 2021. "Warning: Some Transaction Prices can be Detrimental to your House Price Index," Graz Economics Papers 2021-11, University of Graz, Department of Economics.
    5. Mateusz Tomal & Marco Helbich, 2023. "A spatial autoregressive geographically weighted quantile regression to explore housing rent determinants in Amsterdam and Warsaw," Environment and Planning B, , vol. 50(3), pages 579-599, March.
    6. HILL Robert J. & STEURER Miriam & WALTL Sofie R., 2018. "Owner Occupied Housing in the CPI and Its Impact On Monetary Policy During Housing Booms and Busts," LISER Working Paper Series 2018-05, Luxembourg Institute of Socio-Economic Research (LISER).
    7. Trojanek, Radoslaw & Gluszak, Michal, 2022. "Short-run impact of the Ukrainian refugee crisis on the housing market in Poland," Finance Research Letters, Elsevier, vol. 50(C).
    8. Fuad Ganbarov & Klaudia Smoląg & Rashad Muradov & Konul Aghayeva & Rumella Jafarova & Yashar Mammadov, 2020. "Sustainable Development of the Mortgage Market in Azerbaijan: Commercial Risks of Housing Construction, Social Vision, and State Influence," Sustainability, MDPI, vol. 12(12), pages 1-18, June.
    9. Meng Yuan & Hongjuan Wu, 2024. "Positive or Negative: The Heterogeneities in the Effects of Urban Regeneration on Surrounding Economic Vitality—From the Perspective of Housing Price," Land, MDPI, vol. 13(5), pages 1-27, May.
    10. Augustinas Maceika & Andrej Bugajev & Olga R. Šostak, 2019. "The Modelling of Roof Installation Projects Using Decision Trees and the AHP Method," Sustainability, MDPI, vol. 12(1), pages 1-21, December.
    11. McMillen, Daniel & Shimizu, Chihiro, 2017. "Decompositions of Spatially Varying Quantile Distribution Estimates: The Rise and Fall of Tokyo House Prices," HIT-REFINED Working Paper Series 74, Institute of Economic Research, Hitotsubashi University.
    12. Jose Torres-Pruñonosa & Pablo García-Estévez & Camilo Prado-Román, 2021. "Artificial Neural Network, Quantile and Semi-Log Regression Modelling of Mass Appraisal in Housing," Mathematics, MDPI, vol. 9(7), pages 1-16, April.
    13. Willem P Sijp & Anastasios Panagiotelis, 2024. "Estimating granular house price distributions in the Australian market using Gaussian mixtures," Papers 2404.05178, arXiv.org.
    14. Antonio Nesticò & Marianna La Marca, 2020. "Urban Real Estate Values and Ecosystem Disservices: An Estimate Model Based on Regression Analysis," Sustainability, MDPI, vol. 12(16), pages 1-15, August.
    15. Robert J. Hill & Miriam Steurer & Sofie R. Waltl, 2020. "Owner Occupied Housing, Inflation and Monetary Policy," Graz Economics Papers 2020-18, University of Graz, Department of Economics.
    16. Ismail, Muhammad & Warsame, Abukar & Wilhelmsson, Mats, 2020. "Measuring Gentrification with Getis-Ord Statistics and Its Effect on Housing Prices in Neighboring Areas: The Case of Stockholm," Working Paper Series 20/19, Royal Institute of Technology, Department of Real Estate and Construction Management & Banking and Finance.
    17. Daniel McMillen & Chihiro Shimizu, 2021. "Decompositions of house price distributions over time: The rise and fall of Tokyo house prices," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 49(4), pages 1290-1314, December.
    18. repec:grz:wpaper:2019-05 is not listed on IDEAS

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