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Alignment is a technique widely used in (dynamic) microsimulation modeling to ensure that the simulated totals conform to some exogenously specified targets, or aggregate projections (Baekgaard, 2002; Klevmarken, 2002, Li and O'Donoghue, 2014). Alignment is a way to incorporate additional information which is not available in the estimation data. The underlying assumption is that the microsimulation model is a poor(er) model of the aggregate, but a good model of individual heterogeneity: by forcing the microsimulation outcomes to match the targets in a way that is as least distortive as possible, the microsimulation model is left with the task of distributing the totals in the population. In general, the above assumption is very dangerous and unwarranted, and alignment should be looked at with great suspicion. 


Baekgaard H (2002). “Micro-macro linkage and the alignment of transition processes: some issues, techniques and examples”. National Centre for Social and Economic Modelling (NATSEM) Technical paper No. 25.

Klevmarken A (2002). “Statistical inference in micro-simulation models: incorporating external information”. Mathematics and Computers in Simulation,  59: 255-265.

Li J, O'Donoghue C (2014). “Evaluating Binary Alignment Methods in Microsimulation Models”. Journal of Artificial Societies and Social Simulation, 17(1): art. 15.