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The contribution of statistical models in the field of real estate valuation

Author

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  • Tothăzan Helga Flavia

    (Department of Accounting, Faculty of economics and Business Administration, Babes-Bolyai University Cluj-Napoca, Cluj-Napoca, Romania)

Abstract

Testing a model in property evaluation can be a difficult task due to the large variety of these models. The most popular models used in valuation are regression and neural networks. This paper applied a systematic review study and presents 11 types of regression models and 9 types of neural network models applied in real estate valuation. Our aim is to provide a tool for model selection applied in real estate valuation. The selection criteria were based on their applicability, user preferences and price estimation performance. The findings were slightly different from our expectations. Multi-Layer Perceptron (MLP) and Multiple Linear Regression (GLM) are the most applied and popular models in valuation.

Suggested Citation

Handle: RePEc:vrs:timjeb:v:15:y:2022:i:1:p:111-126:n:1007
DOI: 10.2478/tjeb-2022-0007
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Keywords

Regression models; ANN; Performance; Real estate; Models;
All these keywords.

JEL classification:

  • J08 - Labor and Demographic Economics - - General - - - Labor Economics Policies
  • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
  • J68 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Public Policy

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