ABSTRACT
This chapter provides an overview of geographic information system (GIS)-related methodological tools that can be used to combine different sets of secondary data in the social sciences in order to estimate small-area information on very important policy-relevant variables that are not typically available from publicly available data sources. It also provides examples of how it is possible to combine national social survey data with geographical data in order to address the paucity of microdata at small-area level. The chapter shows how these methods can be used in a GIS context for what-if policy analysis. It discusses relatively simple methods of estimating income at the small-area level, before moving on to more sophisticated modelling methods. The chapter also then discusses more sophisticated approaches to small-area estimation that are based on suitable statistical analysis that identifies small-area variables that are most likely to be correlated with a 'target' variable to be estimated.
