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Online Prediction of Berlin Single-Family House Prices

Author

Listed:
  • Rainer Schulz
  • Hizir Sofyan
  • Axel Werwatz
  • Rodrigo Witzel

Abstract

Single-family houses are typically the most important component in their owners’ portfolios. Buying a home is a major financial transaction for most households. Yet, unlike assets traded in financial markets, getting a quote for the current market value of a house is not an easy task because houses are very heterogenous assets. They differ, among other things, in size, location, age and maintenance. In this paper, we describe a web-based, almost realtime prediction of prices for single family homes in Berlin, Germany. Based on an extended hedonic regression model and estimated from a rich data set covering all house transactions in Germany’s capital, this online service delivers predictions for homes with user-specified characteristics. We describe the statistical model and how its predictions are implemented on the computer to allow seamless interaction between its users and the data base containing the model estimates. Copyright Physica-Verlag 2003

Suggested Citation

  • Rainer Schulz & Hizir Sofyan & Axel Werwatz & Rodrigo Witzel, 2003. "Online Prediction of Berlin Single-Family House Prices," Computational Statistics, Springer, vol. 18(3), pages 449-462, September.
    • Handle: RePEc:spr:compst:v:18:y:2003:i:3:p:449-462
    DOI: 10.1007/BF03354609
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    References listed on IDEAS

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    Cited by:

    1. Hizir Sofyan & M. Shabri Abd. Majid & Moh. Rizky Rahmanda, 2019. "Modeling Dynamic Causalities between the Indonesian Rupiah and Forex Markets of ASEAN, Japan and Europe," Contemporary Economics, University of Economics and Human Sciences in Warsaw., vol. 13(1), March.
    2. Clapp, John M. & Eichholtz, Piet & Lindenthal, Thies, 2013. "Real option value over a housing market cycle," Regional Science and Urban Economics, Elsevier, vol. 43(6), pages 862-874.

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