JAMSIM: a Microsimulation Modelling Policy Tool

Abstract

JAMSIM (JAva MicroSIMulation) is an innovative synthesis of open source packages that provides an environment and set of features for the creation of dynamic discrete-time microsimulation models that are to be executed, manipulated and interrogated by non-technical, policy-oriented users. Combining the leading open source statistical package R and one of the foremost agent-based modelling (ABM) graphical tools Ascape, JAMSIM is available as an open source tool, for public reuse and modification. Here we describe microsimulation, our functional requirements, a review of tools used by other micro-simulators and an evaluation of existing software, followed by the architecture, features and use of JAMSIM.

Determinants and disparities: A simulation approach to the case of child health care

“…Data manipulation and analysis were carried out using SAS (SAS Institute, 2013) and R (R Development Core Team, 2013). Model implementation used JAVA and R (Mannion et al, 2012).…”

A survey of dynamic microsimulation models: uses, model structure and methodology

“…Whilst agent based simulation modellers use more generic purpose packages, microsimulation modellers tend to use more specific software. (Wolfson and Rowe, 1998) o LIAM2, developed by the Belgium Federal Planning Bureau (Bryon et al, 2011) o UMDBS, developed by Sauerbier (2002) o GENESIS, developed by UK Department for Work and Pensions (Edwards, 2004) o JAMSIM, developed by Centre of Methods and Policy Application in the Social Science (COMPASS), University of Auckland (Mannion et al, 2012) o LIAM, developed by O'Donoghue et al 2009Modgen provides a C++ library for developers to incorporate required common actions and modules. It is often used to develop continuous microsimulation models, such as LifePath.…”

Simulation of Synthetic Complex Data: The R Package simPop

“…Such datasets are particularly appealing for policymakers and development practitioners, who use them as input into simulation models for assessing the ex-ante distributional impact of policies and programs. Examples are found in multiple sectors, including health (Barrett, Eubank, Marathe, Marathe, Pan, and Swarup 2011;Brown and Harding 2002;Tomintz, Clarke, and Rigby 2008;Smith, Pearce, andHarland 2011), transportation (Beckman, Baggerly, andMcKay 1996;Barthelemy and Toint 2013), environment (Williamson, Mitchell, and McDonald 2002), and others.…”