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Networks Theory for Real Estate Valuation

Author

Listed:
  • Elli Pagourtzi
  • V. Assimakopoulos

Abstract

Real Estate Valuation in urban area is a very difficult task that has absorbed the interest of many academics in the last years. Many qualitative and quantitative variables affect the value of an estate in urban areas. As a result multivariate models are more suitable in the appraisal process. One of the most common approaches is multiple linear regression technique that is always used as a benchmark in various studies. A very promising way of dealing uncertainty in real estate analysis and producing sufficient evaluations is Artificial Neural Networks (ANNs). The purpose of this study is to compare these two approaches using data from the Attica urban area in Greece.

Suggested Citation

  • Elli Pagourtzi & V. Assimakopoulos, 2005. "Networks Theory for Real Estate Valuation," ERES eres2005_280, European Real Estate Society (ERES).
    • Handle: RePEc:arz:wpaper:eres2005_280
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    File URL: https://eres.architexturez.net/doc/oai-eres-id-eres2005-280
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    JEL classification:

    • R3 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location

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