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On weights in dynamic-ageing microsimulation models


  • Gijs Dekkers

    () (Federal Planning Bureau, CeSO University of Leuven, and CEPS/INSTEAD)

  • Richard Cumpston

    () (Research School of Finance, Actuarial Studies & Applied Statistics Australian National University)


A dynamic model with cross-sectional dynamic ageing builds up complete synthetic life histories for each individual, starting from a survey dataset or an administrative dataset. Many of these datasets include weights. This is a problem for dynamic microsimulation models, since the most obvious solution, expanding the dataset, is not always advisable or even possible. This short paper presents an alternative method to use weights in dynamic microsimulation models with dynamic ageing. This approach treats the weighting variable as just another variable in the model, and the weights are only used after simulation to derive weighted simulation results. Tests using Australian data confirm that weighted variables give sensible results, with reductions in runtimes and memory requirements.

Suggested Citation

  • Gijs Dekkers & Richard Cumpston, 2012. "On weights in dynamic-ageing microsimulation models," International Journal of Microsimulation, International Microsimulation Association, vol. 5(2), pages 59-65.
  • Handle: RePEc:ijm:journl:v:5:y:2012:i:2:p:59-65

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    References listed on IDEAS

    1. Jinjing Li & Cathal O'Donoghue, 2014. "Evaluating Binary Alignment Methods in Microsimulation Models," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 17(1), pages 1-15.
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    Cited by:

    1. Alessandra Caretta & Sara Flisi & Cecilia Frale & Michele Raitano & Simone Tedeschi, 2013. "T-DYMM : the treasury dynamic microsimulation model of the Italian pension system," Working Papers 11, Department of the Treasury, Ministry of the Economy and of Finance.

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    sample weights; dynamic microsimulation;


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