Determinants of Residential Property Value in Nigeria – A Neural Network Approach

Abstract

This study investigated, by means of artificial intelligent system, the
influence of residential real estate property characteristics on property
values (prices) in Nigeria, using two major cities (Benin and Lagos) as
examples. It revealed a high positive linear correlation between property
characteristics and the property market values; an indication that these
characteristics reasonably predict property market values. The study
demonstrated that although several property characteristics can be
identified with residential real estate properties, only are few important
ones have significant impact on the market values of such properties. It
identified nine (9) property characteristics that have relatively strong
impact on market values (prices) and to that extent influence the sales
and purchase decisions of sellers and buyers in Nigeria. The results of
the study should enable Real Estate Professionals to make fair estimates
of the market values of residential real estate properties given the features/characteristics of such housing units. This would aid rapid
valuation, help to improve housing quality and make possible mass
evaluation of properties. The study recommends to real estate
practitioners and other professionals, amongst others, to use the
knowledge of significant property features/characteristics for more
efficient valuation, improved quality of their sales/purchase decisions
and proper management of residential housing units.