There is often very limited data on rental market activity, apart from commercial property or high-end residential market segments. CAHF commissioned research into quantifying residential rental markets in Africa to address this lack of information. The primary aim of the research was to lay the foundation for improved data and analytics on rental markets going forward. This data in turn should highlight rental market investment opportunities, and thereby generate increased interest by investors in the sector.

The research focused on four countries of interest; Cote d’Ivoire, Senegal, Tanzania and Uganda. In each of these countries the team identified, collected and analysed existing data including household survey data and CPI data generated by national statistical bureaus, and indicator data published by the World Bank. Numerous data gaps were identified through this process. To fill these gaps the team tested various methodologies.

One of these techniques involved web scraping an online rental classified website to access data on available rental properties in Dar es Salaam. Scraped data includes information on the location of the property, making it possible to analyse the data at a suburb level, whereas survey data typically only allows for analysis at a city or regional level. The team also ran online surveys with estate agents in Angola and Uganda, mobile surveys with small-scale landlords in Uganda and young professionals in Cote d’Ivoire, and in-depth interviews with small scale landlords and banks in Uganda.

In the countries explored, significant data gaps for quantifying rental markets were identified. Piloting data collection methodologies has provided useful insights into the strengths and weaknesses of various ways of collecting data, as well as country-specific insights which can be found in the country focus notes below.

Aside from the secondary data sources accessed as part of this research, municipal data, data on employer-linked housing, student rental housing data, data on state owned rental stock and credit bureaus data could be explored and leveraged where it exists. Although mystery shopping was not explored as part of this project, it could be explored as a means of collected useful primary data for quantifying rental markets in future.