Modelling the Determinants of House Prices Using Generalized Linear Models with Gamma Distribution and Log Link: A Case Study of Nigeria

Résumé

Housing is one of the most critical elements of economic and social development as both a fundamental human need and an important investment tool. The prices of houses differ significantly in Nigeria because of the differences in structural features, demand, and economic factors. The determinants of these price variations are essential to effective policymaking, investment choices, and regulation in housing markets. This study explores the determinants of house prices in Nigeria by employing a Generalized Linear Model (GLM) with a Gamma distribution and log link function because of the highly skewed house price data. This study uses a dataset of 24,326 properties across Nigeria's geopolitical zones. The research examines the influence of structural attributes bedrooms, bathrooms, toilets, and parking spaces, and regional variations. Findings reveal that bedrooms, parking spaces, and location are key drivers of house prices, while the number of toilets is statistically insignificant. The South West emerges as the most expensive region, with other zones exhibiting significantly lower prices.