Microsimulation in Australia: lessons from NATSEM

1. Microsimulation in Australia: lessons from NATSEM Presentation to ESRC/BSPS UK Microsimulation: Bridging the Gaps Seminar Sussex University, September 11 2009 Justine McNamara

2. Acknowledgements • Thanks to Ann Harding and other senior management and staff at NATSEM for their contributions to this presentation • Thanks to ESRC/BSPS

3. Background • Australia • NATSEM • Defining ‘success’

4. Outline of presentation Establishment of NATSEM Self-funding Development of modelling capabilities Cross-model synergies Extending models Public policy applications Staffing KEY SUCCESS FACTORS

5. History of NATSEM • National Centre for Social and Economic Modelling (NATSEM) established 1993 at University of Canberra • First academic research centre to specialise in microsimulation modelling in Australia • Key role of Ann Harding

6. History of NATSEM • Had 5 years of core funding from then Department of Health, Housing and Community Services (1993-1997) • Participation of govt on NATSEM Advisory Board • Early establishment of STINMOD model (static tax transfer model) • STINMOD now maintained by NATSEM for govt • STINMOD actively used by Treasury & other depts (e.g. in Budget papers)

7. Establishment of NATSEM success factors • Visionary leader • Close connections with government/policy process • Got in first

8. History of NATSEM Transferred from government funding to self-funding over 3 years • Reflected changing funding environment (short-term, competitive) • STINMOD pivotal in making this transfer successful • Very close internal monitoring of budgets/timelines (eg TRS)

9. Self-funding success factors • Very strong emphasis on deliverables • Some ongoing STINMOD funding • Close collaboration with government officials • Marketing/awareness/reputation • Expanding vision • Staff with ability to bring in funds • Government departments that use microsimulation models Also many challenges

10. Development of modelling capabilities • STINMOD • DYNAMOD • Health modelling (MediSIM, CareMOD, Diabetes) • ChildMOD • HouseMOD • SpatialMSM • APPSIM

13. MediSim: The Australian Pharmaceutical Benefits Scheme • PBS aims to provide affordable access to prescription medicines • MediSim constructed on top of National Health Survey microdata and simulates changes in • the drugs listed under the PBS • drug prices • the rules (settings) of the PBS – copayments and safety net thresholds • costs to government and consumers • the distributional impacts

14. % of PBS outlays received by each income quintile of Australians *Source: Harding et al, 2004

15. Building modelling capabilities success factors • Joining up with powerful partners who can provide funding, including private sector organisations • Starting small and building out • Developing cross-disciplinary linkages where microsim is part of a larger project focused on particular subject area Challenges include: • Pros and cons of advisory boards/steering committees • Over-committing

16. Cross-model synergies/extending models • STINMOD often key • Spatial microsimulation methodology used for health, housing, broader socioeconomic modelling • Dynamic modelling, spatial modelling can be linked to STINMOD • APPSIM may inform dynamic dementia model • Some micro/macro collaborations

17. CHILDMOD STINMOD DYNAMOD SPATIALMSM APPSIM HOUSEMOD CAREMOD DYNOPTA Links between models (examples)

18. CHILDMOD – An alternative child support scheme • A recent STINMOD extension • Child Support Scheme requires separated parents to each contribute to the costs of raising their children • Many concerns about Scheme -> Ministerial Task Force established to review scheme in 2004 • Govt accepted Ministerial Task Force recommendations: new scheme started July 08 • NATSEM built the Taskforce a ‘hypothetical’ (illustrative families) model (see Harding and Percival, 2007)

19. Proposed Scheme:Payments of Non-Resident Parent

20. Extending models success factors • Agenda management and agenda setting • Taking advantage of opportunities (needs sufficient flexibility) • Look ahead and identify possible issues, then approach potential partners Challenges include: • Model maintenance

21. Cross-model synergies success factors • Acceptance by key policy players of STINMOD • Being able to see possibilities and identify possible connections • Sometimes co-operation with other agencies’ models falls short of actually joining models up Challenges include: • IP issues

22. Public policy applications examples STINMOD – tax reform, welfare to work SpatialMSM – pension reform HouseMOD – housing assistance

23. The Great Australian tax reform debate, 1998-2000 • Introduction of 10% goods & services tax (like VAT) • Removal of existing inefficient indirect taxes (wholesale sales tax) • Major cuts in income tax • Large increases in social security to compensate poor • Question for Senate: how to ensure tax reform package is fair? • Answer: assess its distributional impact using microsimulation models -> use NATSEM • Compensation to poor increased after NATSEM analysis

24. Welfare to Work reforms, 2005 budget announcement • Move to make sole parents on welfare get jobs • Those on Parenting Payment Single before 1 July 2006 remain ‘pensioners’ (relatively generous payment) • Those commencing after 1 July 2006: • Go on PPS if youngest child aged < 6 years • Moved onto Newstart when youngest child turns 6 • Start on Newstart immediately if youngest child aged 6 yrs + • NATSEM commissioned by welfare groups to analyse impact of change (see Harding et al, 2005) • Age of child later changed to 8 years after public debate

25. Public policy applications success factors • Close links with policy makers and an understanding of how policy is made • Need to undertake research for organisations across the political spectrum • ARC Linkage grants • AMP-NATSEM reports • Reputation for impartiality and quality • Reputation for delivering • Microdata analysis as well as microsimulation

26. Staffing success factors (and challenges) • Collegiate environment • Strong support for researchers from non-academic senior staff member • Multidisciplinary Ongoing challenges • recruitment • loss of trained staff

27. Key success factors • Visionary leader • Willingness to evolve/innovate • Involvement with agenda setting • True collegiate/team environment and senior support • Public/media interested in distributional analyses • Staff with skills/focus on bringing in money Continuing challenges: • Balance between academic/soft money priorities • Funding • Staffing

28. Selected references STINMOD and STINMOD applications (static tax-benefit model) Toohey, M and Beer, G, 2004, Financial incentives to work for married mothers under A New Tax System’, Australian Journal of Labour Economics, vol. 7, no. 1, p. 53–69, January Harding, A., Warren, N., Robinson, M. and Lambert, S., 2000, ‘The Distributional Impact of the Year 2000 Tax Reforms in Australia’, Agenda, Volume 7, No 1, pp 17-31. McNamara, J, Lloyd, R, Toohey, M and Harding, A, 2004, Prosperity for all? How low income families have fared in the boom times, Report commissioned by the Australian Council of Social Service, the Brotherhood of St Laurence, Anglicare NSW, Family Services Australia, Canberra, October.* A. Harding, R. Lloyd & N. Warren, 2006, "The Distribution of Taxes and Government Benefits in Australia", in Dimitri Papadimitriou. (ed), The Distributional Effects of Government Spending and Taxation, Chapter 7, Palgrave Macmillan, New York., pp. 176-201. Harding, A, Vu, Q.N, Percival, R & Beer, G, “ Welfare-to-Work Reforms: Impact on Sole Parents” Agenda, Volume 12, Number 3, 2005, pages 195-210 (www.agenda.anu.edu) Harding, A., Payne, A, Vu Q N and Percival, P., 2006, ‘Trends in Effective Marginal Tax Rates, 1996-97 to 2006-07’, ,AMP NATSEM Income and Wealth Report Issue 14, September (available from www.amp.com.au/ampnatsemreports) Lloyd, R, 2007, ‘STINMOD: Use of a static microsimulation model in the policy process in Australia’, in Harding, A and Gupta, A., Modelling Our Future: Population Ageing, Social Security and Taxation (eds), North Holland, Amsterdam. Harding, A., Payne, A., Vu, Q.N., and Percival, R. ‘Interactions between Wages and the Tax / Transfer System’. Report to the Australian Fair Pay Commission, September 2006 (available from http://www.fairpay.gov.au/fairpay/Research/Research2006/Research2006.htm ) CHILDMOD (static child support model) Ministerial Taskforce on Child Support, 2004, In the Best Interests of Children – Reforming the Child Support Scheme, Report of the Ministerial Taskforce on Child Support, May (see Chap 16 for output from CHILDMOD) (http://www.facsia.gov.au/internet/facsinternet.nsf/family/childsupportreport.htm) Harding, A. and Percival, R. 2007, ‘The Australian Child Support Reforms: A Case Study of the Use of Microsimulation Modelling in the Policy Development Process’. Australian Journal of Public Administration, Vol. 66, No. 4, December, pp 422-437

29. Selected references MediSim (static model of the Pharmaceutical Benefits Scheme) Brown. L., Abello, A., Phillips, B. and Harding A., 2004, "Moving towards an improved microsimulation model of the Australian PBS' Australian Economic Review., 1st quarter Abello, A., Brown, L., Walker, A. and Thurecht, T., 2003, An Economic Forecasting Microsimulation Model of the Australian Pharmaceutical Benefits Scheme, Technical Paper No. 30, National Centre for Social and Economic Modelling, University of Canberra.* Harding, A., Abello, A., Brown, L., and Phillips, B. 2004 The Distributional Impact of Government Outlays on the Australian Pharmaceutical Benefits Scheme in 2001-02, Economic Record, Vol 80, Special Issue, September Brown, L., Abello, A. and Harding, A.2006. Pharmaceuticals Benefit Scheme: Effects of the Safety Net. Agenda, vol. 13, no. 3, pp211-224 Diabetes Model Thurecht, L, Brown, L. and Yap, M. (2007) Economic Modelling of the Prevention of Type 2 Diabetes in Australia. Paper presented at the International Microsimulation Association Conference, Vienna, August 2007. Brown, L., Harris, A., Picton, M., Thurecht, L., Yap, M., Harding, A. Dixon, P. and Richardson, J. (2007) Linking Microsimulation and Macro-Economic Models to Estimate the Economic Impact of Chronic Disease Prevention. Paper presented at the International Microsimulation Association Conference, Vienna, August 2007.

30. Selected references APPSIM (dynamic Australian Population and Policy Simulation Model ) Keegan, M. (2009) Mandatory superannuation and self-sufficiency in retirement: An application of the APPSIM dynamic microsimulation model. Paper presented at the 2nd General Conference of the International Microsimulation Association, Ottawa, Canada, June 2009 Keegan, M. and Kelly, S. (2009) Dynamic microsimulation modelling of social security and taxation. Online Working Paper 14. Lymer, S. (2009) Population ageing and health outlays: assessing the impact in Australia during the next 40 years. Paper presented at the 2nd General Conference of the International Microsimulation Association, Ottowa, Canada, June 2009. Pennec, S. (2009) APPSIM - Cohort component population projections to validate and align the dynamic microsimulation model APPSIM. Online Working Paper - WP12 Percival, R. (2007) APPSIM - Software Selection and Data Structures. Online Working Paper - WP3  SpatialMSM (static spatial microsimulation model) Chin, S-F, Harding, A., Lloyd, R., McNamara, J., Phillips, B. & Vu, Q.N. (2005). Spatial microsimulation using synthetic small-area estimates of income, tax and social security benefits. Australasian Journal of Regional Studies, Vol 11, No. 3., 303-344 McNamara, J., Gong, C., Miranti, R., Vidyattama, Y., Tanton, R, Harding, A. and Kendig, H. (2009). ‘Two Worlds of Ageing: Spatial Microsimulation Estimates of Small Area Advantage and Disadvantage Among Older Australians’. Paper presented at the 2nd General Conference of the International Microsimulation Association, Ottawa, Canada, June 8 – 10, 2009. Miranti, R., McNamara, J., Tanton, R. and Harding, A. (2008) “Poverty at the Local Level: National and Small Area Poverty Estimates by Family Type for Australian in 2006’. Paper presented at Small Area Estimation Workshop, University of Canberra, September 2008 Tanton, R., Vidyattama, Y, McNamara, J., Vu, Q.N. and Harding, A. (2008) ‘Old, Single and Poor: Using Microsimulation and Microdata to Analyse Poverty and the Impact of Policy Change Among Older Australians’. Paper presented at UNU-WIDER Conference on Frontiers of Poverty Analysis, Helsinki, 26-27 September 2008.