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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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    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. Robert J. Hill & Miriam Steurer & Sofie R. Waltl, 2017. "Owner Occupied Housing in the CPI and Its Impact On Monetary Policy During Housing Booms and Busts," Graz Economics Papers 2017-12, University of Graz, 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. 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.
    6. 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.
    7. Lepinteur, Anthony & Waltl, Sofie R., 2020. "Tracking Owners' Sentiments: Subjective Home Values, Expectations and House Price Dynamics," Department of Economics Working Paper Series 299, WU Vienna University of Economics and Business.
    8. 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.
    9. 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.
    10. 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.
    11. Willem P Sijp & Anastasios Panagiotelis, 2024. "Estimating granular house price distributions in the Australian market using Gaussian mixtures," Papers 2404.05178, arXiv.org.
    12. 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.
    13. Robert J. Hill & Miriam Steurer & Sofie R. Waltl, 2019. "Owner-Occupied Housing, Inflation, and Monetary Policy," Graz Economics Papers 2019-05, University of Graz, Department of Economics.
    14. 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.
    15. 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).
    16. 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.
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    18. 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.

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    More about this item

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • R31 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Housing Supply and Markets

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