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

Abstract

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.