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SimPaths: an open-source microsimulation model for life course analysis

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Listed:
  • Richiardi, Matteo
  • Bronka, Patryk
  • van de Ven, Justin
  • Kopasker, Daniel
  • Vittal Katikireddi, Srinivasa

Abstract

SimPaths is a family of models for individual and household life course events, all sharing common components. The framework is designed to project life histories through time, building up a detailed picture of career paths, family (inter)relations, health, and financial circumstances. It builds upon standardised assumptions and data sources, which facilitates adaptation to alternative countries – versions currently exist for the UK and Italy, and are under development for Hungary, Poland and Greece. Careful attention is paid to model validation, and sensitivity of projections to key assumptions. The modular nature of the SimPaths framework is designed to facilitate analysis of alternative assumptions concerning the tax and benefit system, sensitivity to parameter estimates and alternative approaches for projecting labour/leisure and consumption/savings decisions. Projections for a workhorse model parameterised to the UK context are reported, which closely reflect observed data throughout a validation window between the Financial crisis (2011) and the Covid-19 pandemic (2019).

Suggested Citation

  • Richiardi, Matteo & Bronka, Patryk & van de Ven, Justin & Kopasker, Daniel & Vittal Katikireddi, Srinivasa, 2023. "SimPaths: an open-source microsimulation model for life course analysis," Centre for Microsimulation and Policy Analysis Working Paper Series CEMPA6/23, Centre for Microsimulation and Policy Analysis at the Institute for Social and Economic Research.
    • Handle: RePEc:ese:cempwp:cempa6-23
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    as
    1. Richard Blundell & Monica Costa Dias & Costas Meghir & Jonathan Shaw, 2016. "Female Labor Supply, Human Capital, and Welfare Reform," Econometrica, Econometric Society, vol. 84, pages 1705-1753, September.
    2. Dr Justin van de Ven, 2011. "A Structural Dynamic Microsimulation Model of Household Savings and Labour Supply," National Institute of Economic and Social Research (NIESR) Discussion Papers 385, National Institute of Economic and Social Research.
    3. Lee, Bong-Soo & Ingram, Beth Fisher, 1991. "Simulation estimation of time-series models," Journal of Econometrics, Elsevier, vol. 47(2-3), pages 197-205, February.
    4. Richard Blundell & Monica Costa-Dias & David Goll & Costas Meghir, 2021. "Wages, Experience, and Training of Women over the Life Cycle," Journal of Labor Economics, University of Chicago Press, vol. 39(S1), pages 275-315.
    5. Matteo Richiardi & Ross E. Richardson, 2017. "JAS-mine: A new platform for microsimulation and agent-based modelling," International Journal of Microsimulation, International Microsimulation Association, vol. 10(1), pages 106-134.
    6. Gallant, A. Ronald & Tauchen, George, 1996. "Which Moments to Match?," Econometric Theory, Cambridge University Press, vol. 12(4), pages 657-681, October.
    7. van de Ven, Justin, 2011. "A structural dynamic microsimulation model of household savings and labour supply," Economic Modelling, Elsevier, vol. 28(4), pages 2054-2070, July.
    8. Altonji, Joseph G. & Martins, Ana Paula & Siow, Aloysius, 2002. "Dynamic factor models of consumption, hours and income," Research in Economics, Elsevier, vol. 56(1), pages 3-59, June.
    9. Martin Browning & Annamaria Lusardi, 1996. "Household Saving: Micro Theories and Micro Facts," Journal of Economic Literature, American Economic Association, vol. 34(4), pages 1797-1855, December.
    10. van de Ven, Justin, 2011. "A structural dynamic microsimulation model of household savings and labour supply," Economic Modelling, Elsevier, vol. 28(4), pages 2054-2070, July.
    11. Martin Browning & Mette Ejrnæs, 2009. "Consumption and Children," The Review of Economics and Statistics, MIT Press, vol. 91(1), pages 93-111, February.
    12. Ieva Skarda & Miqdad Asaria & Richard Cookson, 2021. "LifeSim: A Lifecourse Dynamic Microsimulation Model of the Millennium Birth Cohort in England," International Journal of Microsimulation, International Microsimulation Association, vol. 14(1), pages 2-42.
    13. Maria Luisa Maitino & Letizia Ravagli & Nicola Sciclone, 2020. "IrpetDin. A Dynamic Microsimulation Model for Italy and the Region of Tuscany," International Journal of Microsimulation, International Microsimulation Association, vol. 13(3), pages 27-53.
    14. van de Ven, Justin, 2017. "SIDD: An adaptable framework for analysing the distributional implications of policy alternatives where savings and employment decisions matter," Economic Modelling, Elsevier, vol. 63(C), pages 161-174.
    15. Stern, Steven, 1997. "Approximate Solutions to Stochastic Dynamic Programs," Econometric Theory, Cambridge University Press, vol. 13(3), pages 392-405, June.
    16. Gourieroux, C & Monfort, A & Renault, E, 1993. "Indirect Inference," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(S), pages 85-118, Suppl. De.
    17. Giuseppe Carone, 2005. "Long-Term Labour Force Projections for the 25 EU Member States:A set of data for assessing the economic impact of ageing," Labor and Demography 0512006, University Library of Munich, Germany.
    18. John Creedy & Guyonne Kalb & Hsein Kew, 2007. "Confidence Intervals For Policy Reforms In Behavioural Tax Microsimulation Modelling," Bulletin of Economic Research, Wiley Blackwell, vol. 59(1), pages 37-65, January.
    19. Jinjing Li & Cathal O'Donoghue, 2013. "A survey of dynamic microsimulation models: uses, model structure and methodology," International Journal of Microsimulation, International Microsimulation Association, vol. 6(2), pages 3-55.
    20. Miroslav Štefánik & Tomáš Miklošovič, 2020. "Modelling foreign labour inflows using a dynamic microsimulation model of an ageing country - Slovakia," International Journal of Microsimulation, International Microsimulation Association, vol. 13(2), pages 102-113.
    21. Gaëtan de Menten & Gijs Dekkers & Geert Bryon & Philippe Liégeois & Cathal O'Donoghue, 2014. "LIAM2: a New Open Source Development Tool for Discrete-Time Dynamic Microsimulation Models," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 17(3), pages 1-9.
    22. Pierre-Olivier Gourinchas & Jonathan A. Parker, 2002. "Consumption Over the Life Cycle," Econometrica, Econometric Society, vol. 70(1), pages 47-89, January.
    23. Deborah J Schofield & Melanie J B Zeppel & Owen Tan & Sharyn Lymer & Michelle M Cunich & Rupendra N Shrestha, 2018. "A Brief, Global History of Microsimulation Models in Health: Past Applications, Lessons Learned and Future Directions," International Journal of Microsimulation, International Microsimulation Association, vol. 11(1), pages 97-142.
    24. Cathal O'Donoghue & Gijs Dekkers, 2018. "Increasing the Impact of Dynamic Microsimulation Modelling," International Journal of Microsimulation, International Microsimulation Association, vol. 11(1), pages 61-96.
    25. Christopher D. Carroll, 1992. "The Buffer-Stock Theory of Saving: Some Macroeconomic Evidence," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 23(2), pages 61-156.
    26. Holly Sutherland & Francesco Figari, 2013. "EUROMOD: the European Union tax-benefit microsimulation model," International Journal of Microsimulation, International Microsimulation Association, vol. 1(6), pages 4-26.
    27. Richiardi, Matteo & Bronka, Patryk & van de Ven, Justin, 2022. "Dynamic simulation of taxes and welfare benefits by database imputation," Centre for Microsimulation and Policy Analysis Working Paper Series CEMPA3/22, Centre for Microsimulation and Policy Analysis at the Institute for Social and Economic Research.
    28. Leif Andreassen & Dennis Fredriksen & Hege M Gjefsen & Elin Halvorsen & Nils M Stølen, 2020. "The dynamic cross-sectional microsimulation model MOSART," International Journal of Microsimulation, International Microsimulation Association, vol. 13(1), pages 92-113.
    29. Tim Goedemé & Karel Van den Bosch & Lina Salanauskaite & Gerlinde Verbist, 2013. "Testing the Statistical Significance of Microsimulation Results: A Plea," International Journal of Microsimulation, International Microsimulation Association, vol. 6(3), pages 50-77.
    30. repec:ijm:journl:v109:y:2017:i:1:p:106-134 is not listed on IDEAS
    31. Mitton,Lavinia & Sutherland,Holly & Weeks,Melvyn (ed.), 2000. "Microsimulation Modelling for Policy Analysis," Cambridge Books, Cambridge University Press, number 9780521790062.
    32. Campbell, Donald T., 1979. "Assessing the impact of planned social change," Evaluation and Program Planning, Elsevier, vol. 2(1), pages 67-90, January.
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