Research in progress.
Project last updated on: 22 Oct 2015.
Low cost housing for Africa’s cities? The impact of the Government Condominium Scheme in Ethiopia
Cities in Africa face severe shortages of affordable formal housing. It is estimated that Ethiopia’s current housing deficit in urban areas is about a million units, and that only 30 percent of the current housing stock is in decent condition. Many of the capital city’s inhabitants live in sub-standard housing conditions without access to important urban services. In order to address this shortage of housing supply, and to ensure that the poor are able to access decent housing conditions, the Ethiopian government has implemented the Integrated Housing Development Programme (IHDP) to provide high-density condominium housing at subsidised rates to eligible urban households, on an enormous scale. Over 100,000 housing units have been allocated in Addis Ababa alone, with another 50,000 expected to be allocated in 2015.
However, households moving into new housing will have their existing neighbourhood communities disrupted. The sites of the new houses are often far from jobs in the city centre, and lack existing urban services, such as transport links, schools, and market places. They will move in with new neighbours who will not be of their choosing.
The aim of this project is to measure the impacts of this housing on lottery winning households, by exploiting the randomised lottery system by which housing is allocated. Detailed household surveys will allow us to compare households who win the housing lottery and move into housing to a “control” group who do not get housing.
Baseline data will also allow us to compare households who will not win the lottery to households who have already won housing and may adjust their behaviour in anticipation of moving into the housing, as well as to households who had not won the lottery at baseline but will win in the coming 6 months.
We will look at the impact of receiving the physical housing asset on health, education, employment, and household savings behaviour. In addition, we will follow households closely to see if, and in fact, when households move into the housing, and to look at why some households choose not to move in, or find it more profitable to rent out the housing instead of moving in.
We will also exploit variation in the location of new housing for lottery winners on their endline outcomes, to look at the impact of location on economic outcomes. In addition, random allocation to corridors and even house numbers in the lotteries will generate random variation in the composition of neighbours amongst winners. By stratifying our baseline sampling we will be able to look at the impact of neighbourhood composition on employment, community involvement, and social attitudes.