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Implicit House Prices: Variation over Time and Space in Spain

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  • Stanley McGreal
  • Paloma Taltavull de La Paz

Abstract

Asking price has a fundamental influence on market behaviour and understanding how attributes affect the perceived price of housing. This paper employs a large database of houses from the Spanish housing market to estimate the role of attributes in asking price formation. STAR methodology and GLM with random effects are used to extract the price of attributes and the spatial and time pattern. Results show that the pricing of attributes varies by geographical region and over time with property size and economic and demographic attributes being the key variables explaining asking price formation.

Suggested Citation

  • Stanley McGreal & Paloma Taltavull de La Paz, 2013. "Implicit House Prices: Variation over Time and Space in Spain," Urban Studies, Urban Studies Journal Limited, vol. 50(10), pages 2024-2043, August.
    • Handle: RePEc:sae:urbstu:v:50:y:2013:i:10:p:2024-2043
    DOI: 10.1177/0042098012471978
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    Cited by:

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    2. Raul-Tomas Mora-Garcia & Maria-Francisca Cespedes-Lopez & V. Raul Perez-Sanchez & Pablo Marti & Juan-Carlos Perez-Sanchez, 2019. "Determinants of the Price of Housing in the Province of Alicante (Spain): Analysis Using Quantile Regression," Sustainability, MDPI, vol. 11(2), pages 1-33, January.
    3. Xiaoqi Zhang & Yanqiao Zheng & Lei Sun & Qiwen Dai, 2019. "Urban Structure, Subway Systemand Housing Price: Evidence from Beijing and Hangzhou, China," Sustainability, MDPI, vol. 11(3), pages 1-23, January.
    4. Yuan, Feng & Wu, Jiawei & Wei, Yehua Dennis & Wang, Lei, 2018. "Policy change, amenity, and spatiotemporal dynamics of housing prices in Nanjing, China," Land Use Policy, Elsevier, vol. 75(C), pages 225-236.
    5. Roberto Cervelló-Royo & Marina Segura & Regina García-Pérez & Baldomero Segura-García del Río, 2021. "An Analysis of Preferences in Housing Demand by Means of a Multicriteria Methodology (AHP). A More Sustainable Approach," Sustainability, MDPI, vol. 13(14), pages 1-16, July.
    6. Raul-Tomas Mora-Garcia & Maria-Francisca Cespedes-Lopez & V. Raul Perez-Sanchez, 2022. "Housing Price Prediction Using Machine Learning Algorithms in COVID-19 Times," Land, MDPI, vol. 11(11), pages 1-32, November.
    7. IKM Mokhtarul Wadud & Omar H. M. N. Bashar & Huson Joher Ali Ahmed & William Dimovski, 2022. "Property price dynamics and asymmetric effects of economic policy uncertainty: New evidence from the Australian capital cities," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 62(4), pages 4359-4380, December.
    8. Katharina Pijnenburg, 2017. "The spatial dimension of US house prices," Urban Studies, Urban Studies Journal Limited, vol. 54(2), pages 466-481, February.
    9. Jorge Chica-Olmo & Rafael Cano-Guervos & Mario Chica-Rivas, 2019. "Estimation of Housing Price Variations Using Spatio-Temporal Data," Sustainability, MDPI, vol. 11(6), pages 1-21, March.
    10. Paloma Taltavull de La Paz & V. Raul Perez-Sanchez & Raul-Tomas Mora-Garcia & Juan-Carlos Perez-Sanchez, 2019. "Green Premium Evidence from Climatic Areas: A Case in Southern Europe, Alicante (Spain)," Sustainability, MDPI, vol. 11(3), pages 1-29, January.
    11. Eddie Chi Man Hui & Cong Liang & Ziyou Wang & Yuan Wang, 2016. "The roles of developer’s status and competitive intensity in presale pricing in a residential market: A study of the spatio-temporal model in Hangzhou, China," Urban Studies, Urban Studies Journal Limited, vol. 53(6), pages 1203-1224, May.

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