A machine learning approach to small area estimation: predicting the health, housing and well-being of the population of Netherlands

Abstract Background Local policymakers require information about public health, housing and well-being at small geographical areas. A municipality can for example use this information to organize targeted activities with the aim of improving the well-being of their residents. Surveys are often used to gather data, but many neighborhoods can have only few or even zero respondents. In that case, estimating the status of the local population directly from survey responses is prone to be unreliable. Methods Small Area Estimation (SAE) is a technique to provide estimates at small geographical level... Mehr ...