Abstract
More than 10 years ago O'Donoghue (2001a) surveyed the dynamic microsimulation models that had been developed up to that point. However many of the barriers mentioned have been gradually overcome in the last decade. This paper surveys the development and practices in dynamic microsimulation over the past decade, and discusses the methodological challenges today. It provides an overview of the methodological choices made in more than 60 known dynamic microsimulation models and examines the advantages and disadvantages of different practices. In addition, this paper reviews the main progress made in the field and explores how future microsimulation models could evolve potentially.
Highlights
A dynamic microsimulation model is a model that simulates the behaviour of micro-units over time
In order to evaluate certain impacts of public policies, e.g. the redistributive impact over the course of a lifetime, it is necessary to utilise a long panel dataset. Such datasets are not available, either because the analysis relates to the future, as in the case of pension forecasts, or because collected datasets do not cover sufficiently long time periods; analysts use dynamic microsimulation models to assist in their analysis, a concept which was initially suggested by Orcutt in 1957
This study mostly focuses on the development of dynamic microsimulation models, it is worth to note that microsimulation is closely related to two other individual level modelling approaches, cellular automata and agent based models (Williamson, 2007)
Summary
A dynamic microsimulation model is a model that simulates the behaviour of micro-units over time. In order to evaluate certain impacts of public policies, e.g. the redistributive impact over the course of a lifetime, it is necessary to utilise a long panel dataset Such datasets are not available, either because the analysis relates to the future, as in the case of pension forecasts, or because collected datasets do not cover sufficiently long time periods; analysts use dynamic microsimulation models to assist in their analysis, a concept which was initially suggested by Orcutt in 1957. A few generic software programmes have emerged, such as ModGen (Wolfson and Rowe, 1998), UMDBS (Sauerbier, 2002), GENESIS (Edwards, 2004) and LIAM (O’Donoghue et al, 2009), eliminating the need to create a model from scratch It has allowed an internationalisation of the models with developments in Belgium (Dekkers and Belloni, 2009), Italy (Dekkers et al, 2010), Canada (Spielauer, 2009), UK (Emmerson et al, 2004) etc. We review the progress made by the discipline since the earliest models and suggest some directions for future development
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