Author
Listed:
- Udoekanem Namnso
(Department of Estate Management and Valuation, Federal University of Technology, Minna, Niger State, Nigeria)
- Ighalo James
(Department of Estate Management, Bells University of Technology, Ota, Nigeria)
- Sanusi Yekeen
(Department of Urban and Regional Planning, Federal University of Technology, Minna, Niger State, Nigeria)
Abstract
This study examined the drivers of office rents in selected districts of Abuja, Nigeria. These districts are Asokoro, Maitama and Utako. Primary and secondary data were utilized for the study. Primary data include office rental levels and office space data in the study areas for the period 2001-2012, and were obtained through structured questionnaires administered to real estate surveying and valuation firms which are active in the commercial property markets in the study areas. Secondary data for the study were obtained from the National Bureau of Statistics (NBS) and the Central Bank of Nigeria (CBN), and consist mainly of macroeconomic variables in Nigeria during the study period. Using single-equation regression analysis, the developed office rent model accounted for 76%, 72% and 75% of the variation in office property rents in the commercial property market of the Asokoro, Maitama and Utako districts respectively. The study also revealed that real GDP growth and vacancy rate are the major determinants of rental growth in the office property market in the districts of Asokoro and Maitama, while real GDP growth is the major driver of office rents in the Utako district. The socioeconomic implication of the findings is that the government can generate substantial revenue from property rate through sustained commercial property rental performance in the study areas. Such revenue can be deployed to provide and maintain public infrastructure, thereby improving the wellbeing of the citizenry.
Suggested Citation
Udoekanem Namnso & Ighalo James & Sanusi Yekeen, 2015.
"Predictive Modeling Of Office Rent In Selected Districts Of Abuja, Nigeria,"
Real Estate Management and Valuation, Sciendo, vol. 23(4), pages 95-104, December.
Handle:
RePEc:vrs:remava:v:23:y:2015:i:4:p:95-104:n:10
DOI: 10.1515/remav-2015-0040
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