Evaluating binary alignment methods in microsimulation models

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.