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Evaluating binary alignment methods in microsimulation models

Author

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  • Li, Jinjing

    () (UNU-MERIT/MGSoG, Maastricht University)

  • O'Donoghue, Cathal

    (Teagasc, NUI, Ireland)

Abstract

Alignment is a widely adopted technique in the field of microsimulation for social and economic policy research. However, limited research has been devoted to the understanding of their simulation properties. This paper discusses and evaluates six common alignment algorithms used in the dynamic microsimulation through a set of theoretical and statistical criteria proposed in the earlier literature (e.g. Morrison 2006; O'Donoghue 2010). This paper presents and compares the alignment processes, probability transformations, and the statistical properties of alignment outputs in transparent and controlled setups with both synthetic and real life dataset (LII). The result suggests that there is no single best method for all simulation scenarios. Instead, the choice of alignment method might need to be adapted to the assumptions and requirements in a specific project.

Suggested Citation

  • Li, Jinjing & O'Donoghue, Cathal, 2012. "Evaluating binary alignment methods in microsimulation models," MERIT Working Papers 003, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
  • Handle: RePEc:unm:unumer:2012003
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    File URL: https://www.merit.unu.edu/publications/wppdf/2012/wp2012-003.pdf
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    Cited by:

    1. repec:ijm:journl:v10:y:2017:i:1:p:106-134 is not listed on IDEAS
    2. 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.
    3. Barry J. Milne & Roy Lay-Yee & Jessica M. Mc Lay & Janet Pearson & Martin von Randow & Peter Davis, 2015. "Modelling the Early life-course (MELC): A Microsimulation Model of Child Development in New Zealand," International Journal of Microsimulation, International Microsimulation Association, vol. 8(2), pages 28-60.
    4. Matteo Richiardi, 2016. "Editorial," International Journal of Microsimulation, International Microsimulation Association, vol. 9(3), pages 1-4.
    5. repec:ijm:journl:v109:y:2017:i:1:p:106-134 is not listed on IDEAS
    6. 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.

    More about this item

    Keywords

    alignment; microsimulation; algorithm evaluation;

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General

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