Handbook of Research Methods and Applications in Spatially Integrated Social Science
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Handbook of Research Methods and Applications in Spatially Integrated Social Science

Edited by Robert Stimson

The chapters in this book provide coverage of the theoretical underpinnings and methodologies that typify research using a Spatially Integrated Social Science (SISS) approach. This insightful Handbook is intended chiefly as a primer for students and budding researchers who wish to investigate social, economic and behavioural phenomena by giving explicit consideration to the roles of space and place. The majority of chapters provide an emphasis on demonstrating applications of methods, tools and techniques that are used in SISS research, including long-established and relatively new approaches.
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Chapter 25: Policy and people at the small-area level: using micro-simulation to create synthetic spatial data

Ann Harding and Robert Tanton


While micro-simulation has established itself across the industrialized world as a useful tool for estimating the distributional impacts of policy change upon households and individuals, such models have typically provided results at the national level. Particularly during the past decade or so, there have been renewed attempts within the field of small-area estimation to use reweighting techniques to establish synthetic small-area population micro-data and to construct micro-simulation models replicating the rules of tax and welfare programmes on top of such micro-data. This chapter describes a programme of research at the National Centre for Social and Economic Modelling (NATSEM) in Australia that has now continued for more than a decade. The research has resulted in a set of relatively well-established procedures for reweighting sample survey micro-data to census small-area targets, with the resultant creation of a synthetic micro-database of individuals and households for each small area. This micro-database has been successfully linked with NATSEM’s STINMOD static tax and transfer micro-simulation model, and then used for the analysis of such characteristics as poverty and housing stress at the neighbourhood level, as well as for the evaluation of the geographical impact of changes in tax and welfare policy.

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