Predicting Housing Value: A Comparison of Multiple Regression Analysis and Artificial Neural Networks

This paper compares the predictive performance of artificial neural networks (ANN) and multiple regression analysis (MRA) for single family housing sales and concludes that ANN performs better than MRA when a moderate to large data sample size is used.

Abstract

This article compares the predictive performance of artificial neural networks (ANN) and multiple regression analysis (MRA) for single family housing sales. Multiple comparisons are made between the two data models in which the data sample size, the functional specification and the temporal prediction are varied. ANN performs better than MRA when a moderate to large data sample size is used. For the application, this moderate to large data sample size varied from 13% to 39% of the total data sample (506 to 1,506 observations out of 3,906 total observations). The results give a plausible explanation why previous papers have obtained varied results when comparing MRA and ANN predictive performance for housing values.