Evaluating binary alignment methods in microsimulation models
Jinjing Li and
Cathal O'Donoghue
No 2012-003, MERIT Working Papers from United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT)
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.
Keywords: alignment; microsimulation; algorithm evaluation (search for similar items in EconPapers)
JEL-codes: C15 C18 C50 (search for similar items in EconPapers)
Date: 2012
References: Add references at CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
https://unu-merit.nl/publications/wppdf/2012/wp2012-003.pdf (application/pdf)
Related works:
Journal Article: Evaluating Binary Alignment Methods in Microsimulation Models (2014) 
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:unm:unumer:2012003
Access Statistics for this paper
More papers in MERIT Working Papers from United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT) Contact information at EDIRC.
Bibliographic data for series maintained by Ad Notten ( this e-mail address is bad, please contact ).