(Updated: 24 August 2018)
Housing affordability is generally a function of three things: (1) a household’s income (2) the price of the house that is available for sale, and (3) the terms of the mortgage loan for which the household qualifies. In these two calculators, we have taken mortgage lending data that we collected from major banks and lenders across Africa, and household income estimates using consumption data in PPP$ from CGIDD, and used these to calculate an estimate of housing affordability by country. In these two calculators, you can either (1) input a “house price” and downpayment amount (%) to see what it would cost to service a mortgage loan for that house in each country depending on the mortgage instrument that exists; or (2) input a “monthly income” and see what price of house a household with that income could afford with a standard mortgage in that country.
The housing affordability calculations make use of: the average costs of an affordable housing unit in each country, prevailing minimum mortgage rates, typical mortgage terms, and the distribution of household incomes in both urban and rural areas. The house costs, down-payment and household incomes are all valued in PPP dollars using exchange rates drawn from the World Bank database.
Play with the two calculators and let us know what the results mean for you. For a summary of the methodology, scroll down, below the two calculators.
Using PPP$ to calculate and compare housing affordability in Africa
In 2017, CAHF began converting affordability calculations into international purchasing power parity (PPP) dollars to avoid some of the distortions caused by using prevailing market exchange rates which seldom reflect inflation differentials.
A PPP dollar is a notional currency that reflects the rate at which the currency of one country would have to be converted into that of another country to buy the same amount of goods and services in each country. Consistent use of PPP dollars over time significantly reduces the volatility inherent in the previous US$-based calculations, therefore providing a more accurate reflection of the relative affordability in each of the African countries included in the analysis – both in a particular year, and over time.
Estimates of household income are based on declared household expenditure (or consumption) rather than declared incomes sourced from C-GIDD. Household expenditure data takes account of informal income and is generally regarded as a more accurate measure because survey respondents are less inclined to undercount their expenditure than they are their incomes.
The calculators assume that households could have access to Mortgage finance. These calculations based on household consumption may not translate into mortgage access, however. Lenders still need to learn how to underwrite for informal incomes and are more likely to determine mortgage affordability on the basis of formal wage income.
We all think comfortably in US Dollars and in Local Currency. PPP$ are hard to get one’s head around. To use the PPP$ household income data, therefore, we had to do the following:
For the first calculator
1. The user enters the house price in US$
2. We convert this into the PPP$ equivalent for each country, using the World Bank PPP$ Exchange Rate
3. We then calculate the mortgage repayment amount in PPP$ on the basis of the PPP$ house price
4. And then calculate the percent of households who can afford such a repayment against the PPP$ income distribution
For the second calculator
1. The user enters the household income in US$
2. We then convert this into the PPP$ equivalent for each country, using the World Bank PPP$ Exchange Rate
3. We then calculate the PPP$ house price that a household with this PPP$ income could afford
4. And then convert back into US$ the house price that is reflected on the map
US$ conversions are very time sensitive, and so, are the weakest link in the calculator. In time, we will have a live converter, but in the meantime, we do it as often as possible. Please feel free to contact Miriam Maina on firstname.lastname@example.org with any questions.
- Mortgage Terms – CAHF 2016/17 survey data. www.housingfinanceafrica.org
- PPP$ and US$ Exchange Rates data draw from the World Bank database (Accessed 25 July, 2018)
- Annual Household income data drawn from C-GIDD (Canback Global Income Distribution Database). (Accessed 2018).
Centre for Affordable Housing Finance. 2018 Dashboard: Calculating Mortgage and Housing Affordability in Africa. www.housingfinanceafrica.org