Why use Purchasing Power Parity (PPP) dollars to compare housing affordability in different African countries?

The task of comparing housing affordability across different African countries is made more difficult because the cost of houses, and the incomes used to pay for them, are usually denominated in the local currency of the countries included in the analysis. For this reason, previous editions of the CAHF Housing Finance in Africa Yearbook converted relevant elements of the affordability calculations into a single, internationally-accepted currency – the United States dollar – using prevailing market exchange rates. However, some countries have fixed or pegged official exchange rate systems that operate in conjunction with parallel or “black market” rates that often provide a more accurate reflection of economic fundamentals. For example, at the start of 2018, Angola had an official exchange rate of approximately Kz165/US$ and a parallel market rate of more than Kz400/US$. Those importers able to import at the official rate had a substantial advantage over those that had to use the parallel market.

In addition, exchange rate movements are seldom consistent with inflation differentials, and market exchange rates tend to be far more volatile over time than both house prices and incomes expressed in local currency terms. This is especially true of countries – of which there are a number of examples in Africa – with comparatively narrow export bases whose currencies are unduly affected by the prevailing prices of their primary export commodities on international markets. Nigeria is a good example of this. Between May 2016 and May 2017, the Naira weakened against the US dollar by more than 58 percent, but over the same period inflation in Nigeria was more than 16 percent while in the United States it was less than 2 percent. To reflect relative purchasing power, the Naira should only have weakened against the US dollar by approximately 14 percent. If house prices in Nigeria moved in tandem with consumer prices over this period, they would have increased by 16.3 percent in local currency, but in US dollar terms they would have dropped by 27 percent. In the subsequent twelve months (May 2017 to May 2018), the Naira weakened by a further 14 percent against the US dollar while the inflation differential between the two countries dropped to just under 9 percent. In local currency terms, house prices would have increased by 11.6 percent if they matched CPI inflation, but in US dollar terms they would have dropped by a further 2 percent.

Because of the distortions that the use of prevailing market exchange rates can give rise to, it was decided to convert the affordability calculations in the 2018 Yearbook into international purchasing power parity (PPP) dollars. 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 will not only significantly reduce the volatility that was inherent in the previous US$-based calculations, but will also provide a more accurate reflection of the relative affordability of housing in each of the African countries included in the analysis – both in a particular year, and over time. Comparing the relative affordability of housing across different African countries will also be more accurate and meaningful.

The housing affordability calculations in the 2018 Yearbook make use of the average costs of an affordable housing unit in each country, prevailing minimum downpayment requirements and mortgage rates, typical mortgage terms and the distribution of household incomes in both urban and rural areas. The house costs, downpayment and household incomes are all valued in PPP dollars using exchange rates calculated by the World Bank. Furthermore, CAHF uses the Canback Global Income Distribution Database (CGIDD) to calculate the affordability graphs in this Yearbook. For more information, or to download the data directly, visit www.cgidd.com