Member Profile

Overview
Dr Jinjing LiAssociate Professor

Contact

Address: Building 24 University of Canberra Phone: +61 (0)2 6201 2776

Centre

National Centre for Social and Economic Modelling Modelling (NATSEM)

Organisation

Institute for Governance and Policy Analysis at the University of Canberra

Research Interests

Labour economics; statistical modeling; microsimulation; tax and income issues

Connect with Jinjing

Bio/CV

Dr Jinjing Li has a PhD (PhD, Msc (Computing – Artificial Intelligence), MSc (Economics)) in economic modelling (2011) and is an Associate professor at the NATSEM. He is an internationally recognised expert in microsimulation modelling and serves as a board member of the International Microsimulation Association (IMA). He has more than 10 years of experience developing advanced economic simulation models. In 2018, Dr Li was invited to give evidence on Senate Committee’s Inquiry into the Treasury Laws Amendment for his expertise in tax simulation modelling.

Dr Li led and developed a range of policy simulation models since joining NATSEM and contributed to projects which generated over two million of external funding. He developed Smart and Skilled simulation model which assisted the allocation of billions of dollars’ worth of subsidy from NSW government in the VET sector reform. AIHW in Australia also uses his research software for work on health expenditure analyses. STINMOD+ tax microsimulation model which he designed, is used or referred by a range of government agencies, NGOs, consulting groups and general public in Australia. Internationally, Dr Li has been invited to consult on and contribute to various microsimulation projects worldwide for international organisations, government agencies, NGOs and think tanks.

Publications
  • O’Donoghue, Cathal, Li, Jinjing, Cserháti, Ilona, Elek, Péter, Keresztély, Tibor, & Takács, Tibor. (2018). The Distributional Impact of VAT Reduction for Food in Hungary. International Journal of Microsimulation, 11(3), 2-38.

  • Fowkes, Lisa, & Li, Jinjing. (2018). Designing a remote employment program: lessons from the past and a proposal for the future. Journal of Australian Political Economy, 82, 57-83.

  • Vidyattama, Yogi, Li, Jinjing, & Miranti, Riyana. (2018). Measuring Spatial Distributions of Secondary Education Achievement in Australia. Applied Spatial Analysis and Policy, 1-22.
  • Li, Jinjing. (2017). Rate decomposition for aggregate data using Das Gupta's method. Stata Journal, 17(2), 490-502.
  • Li, Jinjing, Miranti, Riyana, & Vidyattama, Yogi. (2017). What matters in education: a decomposition of educational outcomes with multiple measures. Educational Research and Evaluation, 1-23. doi:10.1080/13803611.2017.1311795
  • Stoker, Gerry, Li, Jinjing, Halupka, Max, & Evans, Mark. (2017). Complacent young citizens or cross-generational solidarity? An analysis of Australian attitudes to democratic politics. Australian Journal of Political Science, 1-18. doi:10.1080/10361146.2017.1298718
  • Zhai, Tiemin, Goss, John, & Li, Jinjing. (2017). Main drivers of health expenditure growth in China: a decomposition analysis. BMC Health Services Research, 17(1), 185. doi:10.1186/s12913-017-2119-1
  • Li, Jinjing. (2016). A Review of Spatial Microsimulation: A Reference Guide for Users. International Journal of Microsimulation, 8(3), 148-151.
  • Li, Jinjing, & Kinfu, Yohannes. (2016). Impact of socioeconomic and risk factors on cardiovascular disease and type II diabetes in Australia: comparison of results from longitudinal and cross-sectional designs. BMJ Open, 6(4). doi:10.1136/bmjopen-2015-010215
  • Vidyattama, Yogi, Cassells, Rebecca, Li, Jinjing, & Abello, Annie. (2016). Assessing the significance of internal migration in drought affected areas: A case study of the Murray Darling Basin, Australia. Australasian Journal of Regional Studies.
  • Li, Jinjing. (2016). Cluster analysis in policy studies. In Gerry Stoker & Mark Evans (Eds.), Evidence Based Policymaking in the Social Science: Methods that matter (pp. 169-185). UK: Policy Press.
  • Li, Jinjing, Duncan, Alan, & Miranti, Riyana. (2015). Underemployment among Mature-Age Workers in Australia. Economic Record, 91(295), 438-462. doi:10.1111/1475-4932.12219
  • Li, Jinjing, Donoghue, Cathal O., & Dekkers, Gijs. (2014). Dynamic Models. In cathal O’Donoghue (Ed.), Handbook of Microsimulation Modelling (Vol. 293, pp. 305-343). UK: Emerald Group Publishing Limited.
  • Li, Jinjing, & O’Donoghue, Cathal. (2014). Evaluating Binary Alignment Methods in Dynamic Microsimulation Models. Journal of Artificial Society and Simulation, 17(1), article. 15.
  • Li, Jinjing, & Sologon, Denisa Maria. (2014). A Continuous Labour Supply Model in Microsimulation: A Life-Cycle Modelling Approach with Heterogeneity and Uncertainty Extension. PLoS ONE, 9(11), e111903. doi:10.1371/journal.pone.0111903
  • Li, Jinjing, Donoghue, Cathal O., Loughrey, Jason, & Harding, Ann. (2014). Static Models. In O. Donoghue Cathal (Ed.), Handbook of Microsimulation Modelling (Vol. 293, pp. 47-75). UK: Emerald Group Publishing Limited.
  • Li, Jinjing, & O’Donoghue, Cathal. (2013). An Overview of Binary Alignment Methods in Microsimulation. In G. Dekkers, M. Keegan, & C. O’Donoghue (Eds.), New Pathways in Microsimulation (pp. 217). Surrey, UK: Ashgate Publishing.
  • Li, Jinjing, & O’Donoghue, Cathal. (2013). A survey of dynamic microsimulation models: uses, model structure and methodology. International Journal of Microsimulation, 6(2), 3-55.
  • Morrissey, Karyn, O'Donoghue, Cathal, Clarke, Graham, & Li, Jinjing. (2013). Using Simulated Data to Examine the Determinants of Acute Hospital Demand at the Small Area Level. Geographical Analysis, 45(1), 49-76.
  • Li, Jinjing, & O’Donoghue, Cathal. (2012). Simulating Histories within Dynamic Microsimulation Models. International Journal of Microsimulation, 5(1), 52-76.

Besides academic paper publications, Dr. Li is the principal author and the collaborator of many economic simulation software. Some of his recent work includes,

  • Australian Dynamic Spatial Population Simulation for the Australian Department of Immigration and Border Control
  • NHMRC workforce simulation model for the National Health and Medicine Research Council Australia
  • STINMOD+, a flexible tax and transfer policy simulation model for Australia, NATSEM
  • “Smart and Skilled” Education policy microsimulation model for the New South Wales Department of Industry
  • Australia Higher Education Reform Policy Simulation Tool for the Australian Labor Party
  • Hungarian Dynamic Microsimulation-CGE model for the Hungarian Ministry of Public Administration and Justice
PhD Supervision

Areas of Supervision:

  • Labour economics
  • Statistical Modeling
  • Microsimulation
  • Tax and income issues

 

 

 

 

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