Model for assessing variation in property taxation and infrastructure in Ibadan Metropolis
Abstract
Property tax is a major source of public income in both developed and developing counties. Consequent upon several researches, the use of empirical models for residential property taxation has been suggested, hence identifying suitable empirical models for residential property taxation has become worrisome over the years. However, the determination of suitable parameters to be used as the dependent variables remains a research problem that is best solved by examination of the prevalent situation of the area concerned as no generalized model can best describe all situations. The study therefore developed a model for assessing variation in property taxation and infrastructure in Ibadan metropolis. The model advances the Gleaser model by integrating property tax with population, Land value, owner’s income, other taxes paid on land and financial allocation expended on Infrastructure. Quantitative research design approach was adopted in this study. A structured questionnaire was administered to residents of residential properties using a purposive sampling technique. A cubic model was used, and it yielded suitable R 2 values ranging from 58.1 to 95.4 in all the local governments within the Ibadan metropolis. Gleaser model was then used to integrate the property tax with population, Land value, owner’s income, other taxes paid on land and financial allocation expended on Infrastructure within the area. The study found out that the generation of property tax may not automatically lead to an increase in financial allocation. It was therefore concluded that the developed model is robust, efficient and a best fit for the Nigerian scenario.
Fields of Study & Subjects
Local Government Finance and Decentralization
Economic and Fiscal Studies
Fiscal Policy and Economic Growth
Publication details
- Journal / source
- Environmental Technology and Science Journal
- Volume
- 16
- Issue
- 2
- Pages
- 39–47
- Publication date
- 10 February 2026
- Language
- EN