Dynamic microsimulation models are ex-ante policy evaluation tools, based on real or artificial data, used to produce realistic future projections of “status quo” trends and to test “what if” scenarios related to potential policy and program interventions. The main advantages offered by these kind of models are: i) the ability to account for population heterogeneity allowing the identification of the distributional impacts of a reform; ii) the ability to assess both short- and long-run effects of a reform. Despite the first pioneering models date back to 50 years ago, these tools have gained popularity only recently, mainly thanks to an increasing computing power and to the availability of micro-data. A limited but growing number of dynamic microsimulation models are focused on health.
Among these models, the aspects of health considered and the methods used vary widely, ranging from the attempt to project and estimate long-term health care costs, assessing the future costs of disability, analyzing the distributional effects of different pharmaceutical access policies or projecting the chronic disease burden. Models like the Future Elderly Model (FEM), the Population Health Model (POHEM) or the Australian Dynamic
Population and Policy Microsimulation Model (APPSIM) represent leading examples of dynamic microsimulation models dedicated to health and health care expenditure
For more information about our models at CEIS Tor Vergata, click the links below.