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Simulating Histories within Dynamic Microsimulation Models

Author

Listed:
  • Jinjing Li

    (Maastricht University / UNU-MERIT, Keizer Karelplein 19, Maastricht, the Netherlands)

  • Cathal O'Donoghue

    (Rural Economy and Development Programme, Teagasc, Teagasc Rural Economy Research Centre, Athenry, Co. Galway, Ireland;)

Abstract

Constructing a base dataset is one of the most important elements in the dynamic microsimulation modelling. However, the access to a long historical panel is usually restricted for many reasons. This paper aims to develop a back simulation method that has the potential to generate a consistent synthetic history panel based on a typical household survey dataset with some complementary statistics. The model uses Living in Ireland (LII) household survey as an example to reconstruct the individual labour market trajectory since 1939. The overall results of the simulated panel have been proven sensible and consistent based on several validation tests. This method opens the possibility to further investigate into several fields of application such as life-cycle income analysis and pension reform evaluation, which typically requires the historical profile of individuals and has traditionally been difficult to perform.

Suggested Citation

  • Jinjing Li & Cathal O'Donoghue, 2012. "Simulating Histories within Dynamic Microsimulation Models," International Journal of Microsimulation, International Microsimulation Association, vol. 5(1), pages 52-76.
    • Handle: RePEc:ijm:journl:v:5:y:2012:i:1:p:52-76
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    References listed on IDEAS

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    1. Emmanuelle Walraet & Béatrice Sédillot & José Bardaji, 2003. "Un outil de prospective des retraites : le modèle de microsimulation Destinie," Économie et Prévision, Programme National Persée, vol. 160(4), pages 193-213.
    2. Mitton,Lavinia & Sutherland,Holly & Weeks,Melvyn (ed.), 2000. "Microsimulation Modelling for Policy Analysis," Cambridge Books, Cambridge University Press, number 9780521790062, June.
    3. Carl Emmerson & Howard Reed & Andrew Shephard, 2004. "An assessment of PenSim2," IFS Working Papers W04/21, Institute for Fiscal Studies.
    4. Rebecca Cassells & Ann Harding & Simon Kelly, 2006. "Problems and Prospects for Dynamic Microsimulation: A review and lessons for APPSIM," NATSEM Working Paper Series 63, University of Canberra, National Centre for Social and Economic Modelling.
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    Cited by:

    1. Richiardi Matteo & Poggi Ambra, 2012. "Imputing Individual Effects in Dynamic Microsimulation Models. An application of the Rank Method," Department of Economics and Statistics Cognetti de Martiis. Working Papers 201213, University of Turin.
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    3. Leonardo Eric CALCAGNO, 2017. "Does the introduction of non-contributory social benefits discourage registered labour? Testing the impact of pension moratoriums on unregistered employment in Argentina (2003-2015)," LEO Working Papers / DR LEO 2526, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    4. Li, Jinjing & O'Donoghue, Cathal, 2012. "A methodological survey of dynamic microsimulation models," MERIT Working Papers 2012-002, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    5. Leonardo Eric Calcagno, 2017. "Does the introduction of non-contributory social benefits discourage registered labour? Testing the impact of pension moratoriums on unregistered employment in Argentina (2003-2015)," Working Papers hal-01611132, HAL.
    6. 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.

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