Towards the development of a predictive rent model in Nigeria and South Africa

• Main Author: Oladeji, Jonathan Damilola
• Other Authors: Wall, Kevin
• Language: en
• Published: University of Pretoria 2020
• Subjects: Real Estate; Rent model; Predictive modelling; Investment analysis; Macroeconomic indicators; UCTD
• Online Access: http://hdl.handle.net/2263/73164

This research aimed to identify reliable economic data for predictive rent modelling in South Africa and Nigeria, as a contribution towards the growing debate on real estate rental forecasting from the African perspective. The data were obtained from the Iress Expert Database, Stat SA, the Central Bank of Nigeria database (CBN), the National Bureau of Statistics and World Bank. The South African economic data comprised time series for a fifteen-year period between Quarter 1 (Q1), 2003 and Quarter 4 (Q4), 2018. The Nigerian data comprised time series for a ten-year period between Quarter 1 (Q1), 2008 and Quarter 4 (Q4), 2018. The logit model was proposed among others as a macroeconomic modelling approach that captures the future rental directions based on the general economic movements and likely turning points. The model is particularly useful due to its reliance on macroeconomic and indirect/listed real estate data which are more readily available to real estate investment decision-makers. This study identified that coincident indicators and the exchange rate both have positive significant relationships with Johannesburg Stock Exchange (JSE) listed real estate as compelling indicators for the South African market. For the Nigerian listed real estate market indicator, the model also responded to interest rate, the consumer price index and the Treasury Bill Rate (TBR) as reliable indicators. In addition to this, analysis revealed the logit regression framework as an improvement to naïve or ordinary linear rent models in these emerging African real estate markets. The use of macroeconomic modelling proved to be a viable alternative to scarce comparable transaction data which serve as the bedrock of traditional real estate investment appraisal. Thus, a forecasting model for early detection of turning points in commercial real estate rental values in South Africa and Nigeria was developed for use in real estate investment decisions. The study concluded that not all economic indicators lead the listed real estate market. The relationship between the macroeconomy and listed real estate is largely significant, but this could be a positive or negative relationship. === Dissertation (MSc)--University of Pretoria, 2019. === African Real Estate Research (AFRER) for IREBS Foundation. === Construction Economics === MSc === Unrestricted