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Internet Offer Prices for Flats and Their Determinants: A Cross Section of Large European Cities


  • Konstantin A. Kholodilin


In this paper, we construct a data set of Internet offer prices for flats in 48 large European cities from 24 countries. The data are collected in January - April 2012 from 33 websites, where the advertisements of flats for sale are placed. Using these data we investigate the determinants of the flat prices. Four factors are found to be relevant for the flats' price level: income per capita, population density, unemployment rate, and Gini index. The results are robust both to excluding variables and to applying two alternative estimation techniques: OLS and quantile regression. Based on our estimation results we are able to identify the cities, where the prices are overvalued, and those, where the prices are undervalued. This is a useful information that allows analyzing and comparing the housing markets in large European cities.

Suggested Citation

  • Konstantin A. Kholodilin, 2012. "Internet Offer Prices for Flats and Their Determinants: A Cross Section of Large European Cities," Discussion Papers of DIW Berlin 1212, DIW Berlin, German Institute for Economic Research.
  • Handle: RePEc:diw:diwwpp:dp1212

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    References listed on IDEAS

    1. Mantu Kumar Mahalik & Hrushikesh Mallick, 2011. "What Causes Asset Price Bubble in an Emerging Economy? Some Empirical Evidence in the Housing Sector of India," International Economic Journal, Taylor & Francis Journals, vol. 25(2), pages 215-237.
    2. Balázs Égert & Dubravko Mihaljek, 2007. "Determinants of House Prices in Central and Eastern Europe," Comparative Economic Studies, Palgrave Macmillan;Association for Comparative Economic Studies, vol. 49(3), pages 367-388, September.
    3. Ozanne, Larry & Thibodeau, Thomas, 1983. "Explaining metropolitan housing price differences," Journal of Urban Economics, Elsevier, vol. 13(1), pages 51-66, January.
    4. James M. Poterba, 1991. "House Price Dynamics: The Role of Tax Policy," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 22(2), pages 143-204.
    5. Clapp John M. & Giaccotto Carmelo, 1994. "The Influence of Economic Variables on Local House Price Dynamics," Journal of Urban Economics, Elsevier, vol. 36(2), pages 161-183, September.
    6. Çağlayan Ebru & Arikan Eban, 2011. "Determinants of house prices in Istanbul: a quantile regression approach," Quality & Quantity: International Journal of Methodology, Springer, vol. 45(2), pages 305-317, February.
    7. Koenker,Roger, 2005. "Quantile Regression," Cambridge Books, Cambridge University Press, number 9780521845731, March.
    8. Konstantin A. Kholodilin & Andreas Mense, 2011. "Can Internet Ads Serve as an Indicator of Homeownership Rates?," Discussion Papers of DIW Berlin 1168, DIW Berlin, German Institute for Economic Research.
    9. Michal Hlavacek & Lubos Komarek, 2009. "Property Price Determinants in the Czech Regions," Occasional Publications - Chapters in Edited Volumes,in: CNB Financial Stability Report 2008/2009, chapter 0, pages 82-91 Czech National Bank, Research Department.
    10. Konstantin A. Kholodilin & Andreas Mense, 2012. "Internet-Based Hedonic Indices of Rents and Prices for Flats: Example of Berlin," Discussion Papers of DIW Berlin 1191, DIW Berlin, German Institute for Economic Research.
    11. Karol Jan Borowiecki, 2009. "The Determinants of House Prices and Construction: An Empirical Investigation of the Swiss Housing Economy," International Real Estate Review, Asian Real Estate Society, vol. 12(3), pages 193-220.
    12. Vahram Stepanyan & Tigran Poghosyan & Aidyn Bibolov, 2010. "House Price Determinants in Selected Countries of the Former Soviet Union," IMF Working Papers 10/104, International Monetary Fund.
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    Cited by:

    1. Thomschke, Lorenz, 2015. "Changes in the distribution of rental prices in Berlin," Regional Science and Urban Economics, Elsevier, vol. 51(C), pages 88-100.
    2. Konstantin Kholodilin, 2015. "Speculative Bubbles in Urban Housing Markets in Germany," ERSA conference papers ersa15p67, European Regional Science Association.

    More about this item


    Internet ads; flats' prices; large European cities; fundamental prices;

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • 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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