For example, national statistical agencies should make census data available at the lowest geographic aggregation that does not compromise data privacy. Sample surveys should be designed with some consideration of geography to ensure sufficient spatial coverage as well as statistical significance of survey data at relatively low levels of geographic aggregations. This requires a combination of population based sampling with a spatial sampling design. Mapping as a research tool Information on the spatial distribution of poor people can significantly improve the design of projects aimed at poverty alleviation. In the long term, however, the goal needs to be to identify and address the root causes of poverty.
Individualistic explanations assume that people are highly mobile.
Poor people tend to remain in poor areas because of specific wage or price incentives, or because they believe that they have a higher chance of making a living in a less competitive environment. In this model, poor areas result from individual behavior. Characteristics of poor areas such as low rents, poor infrastructure, limited services and a lack of economic opportunities are thus considered a reflection of individual decisions by the poor to live in that area. Structural explanations, also termed geographical models, in contrast, argue that there exists a causal link between geography and the level of well being. Mobility is seen as limited and structural differences between regions in terms of natural resource endowment, infrastructure and access to services therefore tend to persist and intensify.