IDEAS home Printed from https://ideas.repec.org/a/zbw/ifweej/201528.html
   My bibliography  Save this article

Urban house prices: A tale of 48 cities

Author

Listed:
  • Kholodilin, Konstantin A.
  • Ulbricht, Dirk

Abstract

In this paper, the authors construct a unique data set of Internet offer prices for flats in 48 large European cities across 24 countries. The data collected between January and May 2012 from 33 websites, are drawn from Internet advertisements of dwellings. Using the resulting sample of more than 1,000,000 announcements, the authors compute the quality-adjusted city-specific house prices. Based on this information, they investigate the determinants of the apartment prices. Four factors are found to be relevant for the dwelling price level using Bayesian Model Averaging: Population density, mortgage per capita, income inequality, and unemployment rate. The results are robust to applying two alternative estimation techniques: OLS and quantile regression. Based on the auhors' estimation results they are able to identify cities where the prices are overvalued. This is a useful indication of a build-up of house price bubbles.

Suggested Citation

  • Kholodilin, Konstantin A. & Ulbricht, Dirk, 2015. "Urban house prices: A tale of 48 cities," Economics - The Open-Access, Open-Assessment E-Journal, Kiel Institute for the World Economy (IfW), vol. 9, pages 1-43.
    • Handle: RePEc:zbw:ifweej:201528
    DOI: 10.5018/economics-ejournal.ja.2015-28
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.5018/economics-ejournal.ja.2015-28
    Download Restriction: no
    File URL: https://www.econstor.eu/bitstream/10419/120918/1/836118812.pdf
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. 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.
    2. Nicodemo, Catia & Raya, Josep Maria, 2012. "Change in the distribution of house prices across Spanish cities," Regional Science and Urban Economics, Elsevier, vol. 42(4), pages 739-748.
    3. 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.
    4. Hort, Katinka, 1998. "The Determinants of Urban House Price Fluctuations in Sweden 1968-1994," Journal of Housing Economics, Elsevier, vol. 7(2), pages 93-120, June.
    5. Koenker,Roger, 2005. "Quantile Regression," Cambridge Books, Cambridge University Press, number 9780521845731, December.
    6. Henger, Ralph & Voigtländer, Michael, 2014. "Transaktions- und Angebotsdaten von Wohnimmobilien. Eine Analyse für Hamburg," IW-Trends – Vierteljahresschrift zur empirischen Wirtschaftsforschung, Institut der deutschen Wirtschaft (IW) / German Economic Institute, vol. 41(4), pages 85-100.
    7. Konstantin A. Kholodilin & Claus Michelsen & Dirk Ulbricht, 2014. "Speculative Price Bubbles in Urban Housing Markets in Germany," Discussion Papers of DIW Berlin 1417, DIW Berlin, German Institute for Economic Research.
    8. 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.
    9. Eloisa T. Glindro & Tientip Subhanij & Jessica Szeto & Haibin Zhu, 2011. "Determinants of House Prices in Nine Asia-Pacific Economies," International Journal of Central Banking, International Journal of Central Banking, vol. 7(3), pages 163-204, September.
    10. 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.
    11. Luc Anselin & Nancy Lozano-Gracia, 2008. "Errors in variables and spatial effects in hedonic house price models of ambient air quality," Empirical Economics, Springer, vol. 34(1), pages 5-34, February.
    12. Ozanne, Larry & Thibodeau, Thomas, 1983. "Explaining metropolitan housing price differences," Journal of Urban Economics, Elsevier, vol. 13(1), pages 51-66, January.
    13. 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.
    14. 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.
    15. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    16. 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.
    17. Bernhard Faller & Christoph Helbach, & Andreas Vater & Reiner Braun, 2009. "Möglichkeiten zur Bildung eines Regionalindex Wohnkosten unter Verwendung von Angebotsdaten," RatSWD Research Notes 34, German Data Forum (RatSWD).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Kholodilin, Konstantin A. & Michelsen, Claus & Ulbricht, Dirk, 2018. "Speculative price bubbles in urban housing markets," EconStor Open Access Articles, ZBW - Leibniz Information Centre for Economics, pages 1957-1983.
    2. Ahfeldt, Gabriel M. & Pietrostefani, Elisabetta, 2017. "The compact city in empirical research: A quantitative literature review," LSE Research Online Documents on Economics 83638, London School of Economics and Political Science, LSE Library.
    3. Jean-Charles Bricongne & Alessandro Turrini & Peter Pontuch, 2019. "Assessing House Prices: Insights from "Houselev", a Dataset of Price Level Estimates," European Economy - Discussion Papers 2015 - 101, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    4. Konstantin A. Kholodilin & Irina Krylova & Darya Kryutchenko, 2017. "Finding the Consumer Center of St. Petersburg?," HSE Working papers WP BRP 165/EC/2017, National Research University Higher School of Economics.
    5. Konstantin A. Kholodilin & Julien Licheron, 2017. "Macroeconomic Effects of Rental Housing Regulations: The Case of Germany in 1950-2015," Discussion Papers of DIW Berlin 1649, DIW Berlin, German Institute for Economic Research.
    6. Ahlfeldt, Gabriel M. & Pietrostefani, Elisabetta, 2019. "The economic effects of density: A synthesis," Journal of Urban Economics, Elsevier, vol. 111(C), pages 93-107.
    7. Kajuth, Florian, 2020. "The German housing market cycle: Answers to FAQs," Discussion Papers 20/2020, Deutsche Bundesbank.
    8. Gabriel M. Ahfeldt & Elisabetta Pietrostefani, 2017. "The Compact City in Empirical Research: A Quantitative Literature Review," SERC Discussion Papers 0215, Spatial Economics Research Centre, LSE.
    9. Konstantin A. Kholodilin & Irina Krylova & Darya Kryutchenko, 2017. "Where Is the Consumer Center of St. Petersburg?," Discussion Papers of DIW Berlin 1666, DIW Berlin, German Institute for Economic Research.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Akosah, Nana Kwame & Alagidede, Imhotep Paul & Schaling, Eric, 2020. "Testing for asymmetry in monetary policy rule for small-open developing economies: Multiscale Bayesian quantile evidence from Ghana," The Journal of Economic Asymmetries, Elsevier, vol. 22(C).
    3. Paul Hewson & Keming Yu, 2008. "Quantile regression for binary performance indicators," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 24(5), pages 401-418, September.
    4. Asongu, Simplice A. & Odhiambo, Nicholas M., 2021. "Inequality, finance and renewable energy consumption in Sub-Saharan Africa," Renewable Energy, Elsevier, vol. 165(P1), pages 678-688.
    5. Aboura, Sofiane & Chevallier, Julien, 2016. "Spikes and crashes in the oil market," Research in International Business and Finance, Elsevier, vol. 36(C), pages 615-623.
    6. Trojanek, Radoslaw & Huderek-Glapska, Sonia, 2018. "Measuring the noise cost of aviation – The association between the Limited Use Area around Warsaw Chopin Airport and property values," Journal of Air Transport Management, Elsevier, vol. 67(C), pages 103-114.
    7. Paulo M.M. Rodrigues & Rita Fradique Lourenço, 2015. "House prices: bubbles, exuberance or something else? Evidence from euro area countries," Working Papers w201517, Banco de Portugal, Economics and Research Department.
    8. Giovanni Bonaccolto & Massimiliano Caporin & Sandra Paterlini, 2018. "Asset allocation strategies based on penalized quantile regression," Computational Management Science, Springer, vol. 15(1), pages 1-32, January.
    9. Abeliansky, Ana & Krenz, Astrid, 2015. "Democracy and international trade: Differential effects from a panel quantile regression framework," Center for European, Governance and Economic Development Research Discussion Papers 243, University of Goettingen, Department of Economics.
    10. Muller, Christophe, 2018. "Heterogeneity and nonconstant effect in two-stage quantile regression," Econometrics and Statistics, Elsevier, vol. 8(C), pages 3-12.
    11. Mayya Zhilova, 2015. "Simultaneous likelihood-based bootstrap confidence sets for a large number of models," SFB 649 Discussion Papers SFB649DP2015-031, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    12. Otto-Sobotka, Fabian & Salvati, Nicola & Ranalli, Maria Giovanna & Kneib, Thomas, 2019. "Adaptive semiparametric M-quantile regression," Econometrics and Statistics, Elsevier, vol. 11(C), pages 116-129.
    13. Fan, Yanqin & Liu, Ruixuan, 2016. "A direct approach to inference in nonparametric and semiparametric quantile models," Journal of Econometrics, Elsevier, vol. 191(1), pages 196-216.
    14. Deborah A. Cobb-Clark & Sonja C. Kassenboehmer & Mathias G. Sinning, 2013. "Locus of Control and Savings," Ruhr Economic Papers 0455, Rheinisch-Westfälisches Institut für Wirtschaftsforschung, Ruhr-Universität Bochum, Universität Dortmund, Universität Duisburg-Essen.
    15. Chuliá, Helena & Guillén, Montserrat & Uribe, Jorge M., 2017. "Spillovers from the United States to Latin American and G7 stock markets: A VAR quantile analysis," Emerging Markets Review, Elsevier, vol. 31(C), pages 32-46.
    16. Narula, Subhash C. & Wellington, John F. & Lewis, Stephen A., 2012. "Valuating residential real estate using parametric programming," European Journal of Operational Research, Elsevier, vol. 217(1), pages 120-128.
    17. Yayan Hernuryadin & Koji Kotani & Tatsuyoshi Saijo, 2020. "Time Preferences of Food Producers: Does “Cultivate and Grow” Matter?," Land Economics, University of Wisconsin Press, vol. 96(1), pages 132-148.
    18. Klomp, Jeroen, 2013. "Government interventions and default risk: Does one size fit all?," Journal of Financial Stability, Elsevier, vol. 9(4), pages 641-653.
    19. Chesher, Andrew, 2017. "Understanding the effect of measurement error on quantile regressions," Journal of Econometrics, Elsevier, vol. 200(2), pages 223-237.
    20. Lima, Luiz Renato & Néri, Breno Pinheiro, 2007. "Comparing Value-at-Risk Methodologies," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 27(1), May.

    More about this item

    Keywords

    internet advertisements; housing prices; large European cities; fundamentalprices;
    All these keywords.

    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:zbw:ifweej:201528. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (ZBW - Leibniz Information Centre for Economics). General contact details of provider: http://edirc.repec.org/data/iwkiede.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.