1. Spatial Microsimulation and Policy Analysis Robert Tanton (CRICOS) #00212K

2. Outline Description of spatial microsimulation Applications of spatial microsimulation Future of spatial microsimulation Further reading (CRICOS) #00212K

3. The need for spatial microsimulation Policy makers want small area estimates – Ex Social Inclusion Unit – spatial estimates are one of priorities – “Communities” of interest (CRICOS) #00212K

4. 4 Collecting small area information National sample surveys Census of Popn & Housing ? Subject Matter detail HighMediumHigh Geographic detail LowHigh

5. Applications of spatial microsimulation Small area indicators in a cross-tabulation – Poverty rates for older people living alone – Used to inform policy on service provision to small areas Projections – Use ABS small area population projections and Treasury labour force projections to apply changes in demographics – Derive projections of service populations for policy makers Small area effects of a policy change – Model national policy change using STINMOD Tax/Transfer model – Model national change using a CGE model and a Tax/Transfer microsimulation model Look at effect for each area using regional weights (CRICOS) #00212K

6. For older people living alone Small area indicators of poverty

7. 7 What are the poverty rates for older people living alone?

8. 8 Projections Projections of key variables for small areas – Using population and labour force projections from Commonwealth – Regression for each of the benchmark tables to get projected benchmarks – Reweight survey data to projected benchmarks Examples – Where childcare places are going to be needed in future; where aged care places are going to be needed in future

9. 9 Growth from 2006 – 2027 in the number of 3 – 4 year old children with all parents working, Queensland

10. 10 Small area policy analysis – Link to NATSEM’s tax/transfer microsimulation model – uses same datasets – Spatial weights linked to STINMOD to get small area effects of STINMOD modelling Examples – Small area effects of changes in tax or transfer system; Small area effect of the 2014 Budget

11. 11 Small Area Policy Analysis Small area effects of changes in transfer system – Change to FTB Income tapers – First income taper reduced from 20 to 10 per cent; second left at 30 per cent

12. 12 Spatial Effect of a change to FTB

13. 13 Small Area reduction in incomes in 2017-18 as a result of the 2014-15 Budget

14. Link between CGE model, STINMOD and SpatialMSM – CGE model provides national change in incomes by industry; STINMOD applies this to individuals in each industry; SpatialMSM regionalises STINMOD – Effect of a change in the Terms of Trade Boomed from 2009 to 2011 but decreasing from 2011 to Dec 2013 (when this analysis was done) What is the spatial effect? Small area policy analysis

15. Small area effect of a change in the Terms of Trade

16. Limits to what variables can extract reliably – Limitations due to benchmarking process Validation difficult Difficult to calculate confidence intervals – Ongoing work at NATSEM Limitations of spatial microsimulation

17. 17 The future of spatial microsimulation Synthetic populations for an entire country – Already done for Japan 127.3 million people – Looking at doing at NATSEM for indicators of individual level disadvantage Add confidence intervals – Work being done at the moment at NATSEM Add dynamic elements – Better projections – Very data intensive – longer term NATSEM project

18. 18 The future of spatial microsimulation Decision Support Systems – Resource limited demographic projection ABS - 650,000 people in ACT by 2056 Really? Where are they going to live? How many jobs will we need? How much water? Electricity? Transport? – Help planners to make planning decisions – Recent paper on modelling decision support system using SpatialMSM went to US Regional Science conference Book chapter soon

19. Further Reading Policy modelling – Harding, Vu, Tanton and Vidyattama (2009). “Improving Work Incentives and Incomes for Parents: The National and Geographic Impact of Liberalising the Family Tax Benefit Income Test.” Economic Record 85 (s1): S48–S58. – Vidyattama, Rao and Tanton (2014). “Modelling the Impact of Declining Australian Terms of Trade on the Spatial Distribution of Income.” International Journal of Microsimulation 7: 100–126. Projections – Harding, Vidyattama and Tanton (2011). “Demographic Change and the Needs-Based Planning of Government Services: Projecting Small Area Populations Using Spatial Microsimulation.” Journal of Population Research 28: 203–224. Spatial Microsimulation – Tanton and Edwards (2013). Spatial Microsimulation: A Reference Guide for Users. Edited by Robert Tanton and Kimberley Edwards. Springer Netherlands. – Tanton (2011). “Spatial Microsimulation as a Method for Estimating Different Poverty Rates in Australia.” Population, Space and Place 17 (3): 222–235. – Tanton (2014). “A Review of Spatial Microsimulation Methods.” International Journal of Microsimulation 7 (1): 4–25. (CRICOS) #00212K