Abstract
This chapter outlines some of the limits of static spatial microsimulation models. There are four issues covered in this chapter, being data limitations; how adding different benchmark tables affects the results; issues with non-converging areas when too many benchmark tables are specified; and how a non-representative sample for the survey data affects results.
Our conclusions are that the main data limitation is getting two comparable datasets; that increasing the number of benchmarks makes the final weights more generalisable but increases the number of non-converging areas; and that using within-area records may give slightly better results for some areas, but not for all areas.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
ABS. (2002). Information paper: Labour force sample design (Cat # 6269.0). Canberra: ABS.
ABS. (2004). Household income and income distribution 2002–03 (Cat # 6523.0). Canberra: ABS.
ABS. (2005). Household income and income distribution 2003–04 (Cat # 6523.0). Canberra: ABS.
ABS. (2009). Household income and income distribution 2007–08 (Cat # 6523.0). Canberra: ABS.
Anderson, B. (2007). Creating small-area income estimates: Spatial microsimulation modelling. Communities. http://www.communities.gov.uk/documents/communities/pdf/325286.pdf. Accessed Aug 2011.
Ballas, D., Clarke, G., Dorling, D., Eyre, H., Thomas, B., & Rossiter, D. (2005). SimBritain: A spatial microsimulation approach to population dynamics. Population, Space and Place, 11(1), 13–34. http://dx.doi.org/10.1002/psp.351
Birkin, M., & Clarke, M. (1988). SYNTHESIS – A synthetic spatial information system for urban and regional analysis: Methods and examples. Environment and Planning A, 20(12), 1645–1671.
Birkin, M., & Clarke, M. (1989). The generation of individual and household incomes at the small area level using synthesis. Regional Studies: The Journal of the Regional Studies Association, 23(6), 535–548.
Procter, K., Clarke, G., Ransley, J., & Cade, J. (2008). Micro-level analysis of childhood obesity, diet, physical activity, residential socio-economic and social capital variables: Where are the obesogenic environments in Leeds? Area, 40(3), 323–340.
Tanton, R., & Vidyattama, Y. (2010). Pushing it to the edge: Extending generalised regression as a spatial microsimulation method. International Journal of Microsimulation, 3(2), 23–33.
Tanton, R., Vidyattama, Y., Nepal, B., & McNamara, J. (2011). Small area estimation using a reweighting algorithm. Journal of the Royal Statistics Society Series A. doi:10.1111/j.1467-985X.2011.00690.x
Vidyattama, Y., & Tanton, R. (2011). Estimating the spatial distribution and characteristics of households in Tasmania. Final Report, Tasmanian Department of Premier & Cabinet: Hobart.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer Science+Business Media Dordrecht.
About this chapter
Cite this chapter
Tanton, R., Edwards, K.L. (2012). Limits of Static Spatial Microsimulation Models. In: Tanton, R., Edwards, K. (eds) Spatial Microsimulation: A Reference Guide for Users. Understanding Population Trends and Processes, vol 6. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-4623-7_10
Download citation
DOI: https://doi.org/10.1007/978-94-007-4623-7_10
Published:
Publisher Name: Springer, Dordrecht
Print ISBN: 978-94-007-4622-0
Online ISBN: 978-94-007-4623-7
eBook Packages: Humanities, Social Sciences and LawSocial Sciences (R0)