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The Economics of Style: Measuring the Price Effect of Neo†Traditional Architecture in Housing

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  • Edwin Buitelaar
  • Frans Schilder

Abstract

Vintage effects have received considerable attention from economists in the context of house prices. Although strongly related, the impact of architectural building styles on prices has not been studied yet. Using a cross†sectional hedonic price analysis including building styles of recently developed homes in the Netherlands we find a significant price premium for housing with neo†traditional architecture. Extensive intervention by local authorities on the supply side of the housing market seems the most probable explanation of this effect. The decreasing price premium over time reflects the impact of supply restrictions on price, but also indicates that style does matter.

Suggested Citation

  • Edwin Buitelaar & Frans Schilder, 2017. "The Economics of Style: Measuring the Price Effect of Neo†Traditional Architecture in Housing," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 45(1), pages 7-27, February.
  • Handle: RePEc:bla:reesec:v:45:y:2017:i:1:p:7-27
    DOI: 10.1111/1540-6229.12137
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    Cited by:

    1. Wayne Xinwei Wan & Thies Lindenthal, 2023. "Testing machine learning systems in real estate," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 51(3), pages 754-778, May.
    2. Rolheiser, Lyndsey & van Dijk, Dorinth & van de Minne, Alex, 2020. "Housing vintage and price dynamics," Regional Science and Urban Economics, Elsevier, vol. 84(C).
    3. Liao, Wen-Chi & Jing, Kecen & Lee, Chaun Ying Rachel, 2022. "Economic return of architecture awards: Testing homebuyers’ motives for paying more," Regional Science and Urban Economics, Elsevier, vol. 93(C).
    4. Lyndsey Rolheiser & Dorinth van Dijk & Alex van de Minne, 2018. "Does Housing Vintage Matter? Exploring the Historic City Center of Amsterdam," DNB Working Papers 617, Netherlands Central Bank, Research Department.
    5. Wan, Wayne Xinwei & Lindenthal, Thies, 2022. "Towards accountability in machine learning applications: A system-testing approach," ZEW Discussion Papers 22-001, ZEW - Leibniz Centre for European Economic Research.

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