Open AccessThe Role of Microsimulation in Longitudinal Data Analysis
Author(s) -
Douglas A. Wolf
Publication year - 2001
Publication title -
canadian studies in population
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.157
H-Index - 8
eISSN - 1927-629X
pISSN - 0380-1489
DOI - 10.25336/p67k5x
Subject(s) - microsimulation , imputation (statistics) , econometrics , longitudinal data , computer science , range (aeronautics) , missing data , economics , data mining , transport engineering , engineering , machine learning , aerospace engineering
Microsimulation is well known as a tool for static analysis of tax and transferpolicies, for the generation of programmatic cost estimates, and dynamicanalyses of socio-economic and demographic systems. However,microsimulation also has the potential to contribute to longitudinal data analysis in several ways, including extending the range of outputs generated by a model, addressing several defective-data problems, and serving as a vehicle for missing-data imputation. This paper discusses microsimulation procedures suitable for several commonly-used statistical models applied to longitudinal data. It also addresses the unique role that can be played by microsimulation in longitudinal data analysis, and the problem of accounting for the several sources of variability associated with microsimulation procedures.