would affect prices in a more functional market, such as flood risk, not being internalized.

# **5 Conclusions**

This paper investigates the relationship between flood exposure and rents in Accra, Addis Ababa, Antananarivo, and Dar es Salaam, using a hedonic property price approach with four cross-sectional household surveys complemented with data on job density. Flood exposure is measured using self-reported information from households on whether they have been affected by flooding. Flood risk is measured with self-reported information on the perception of the risk of future flood exposure.

The results suggest that flood exposure/risk is associated with lower rents in three of the four cities studied. The willingness to pay to avoid flood exposure is between 14 percent (in Accra and Antananarivo) and 56 percent (in Addis Ababa) of average rents. In contrast, in Dar es Salaam, flood exposure/risk is associated with higher rents. The relationship between flood exposure and rents is made more complex by the close correlation between tenure and flood exposure, the lack of public awareness on flood risk, high transaction costs of housing and the importance of omitted variables, such as cultural and historical importance, presence of community networks, access to green spaces and other amenities which potentially could encourage people to move to areas with high flood risk.

The paper uses a novel way to measure access to jobs, based on data on the spatial distribution of amenities and economic activities. In Accra and Addis Ababa, rents are negatively correlated with job density, which is an unexpected finding for an efficient housing market. In Antananarivo, a more monocentric city compared with the other three cities, areas with high job density are more expensive, on average. No relationship between job density and rent is found for Dar es Salaam. When interacting job density with flood exposure/risk for each city, the negative effect of job density on rents is higher when flood exposure/risk is high in Accra and Addis Ababa, and the positive effect of job density on rents becomes negative when flood exposure/risk is high in Antananarivo. The result indicates that job access is a driving factor for households settling in flood prone areas. In addition to flood exposure/risk, it is found that housing conditions and public services are important determinants of rents. It is inherently difficult to measure flood risk using self-reported data. For example, if a binary variable is used to distinguish affected from non-affected populations, no differentiation is made between households that have experienced a one-off flood event and those that experience frequent. However, self-reported data on flood exposure have two advantages compared to frequently used flood risk maps: 1) household survey data are more often available than flood risk maps particularly in the case of data scarce environments, and 2) information on actually affected households and their expectation about the risk of future flooding are more likely to influence the value households assign to housing than data that is rarely known to the public. The different results for different cities indicate that the ability of people to internalize flood risks through rents is context specific. This study contributes to our understanding of this issue for four cities in Africa. The findings for the relationship between flood risk and rents are economically significant despite the limits related to measuring flood risk, property pricing, and accessibility to jobs. They provide some important insights on how households assign value to amenities including flood protection, in low- income, highly informal contexts. They can help policy makers estimate the potential value that 19