A Taxonomy of Inference in Simulation Models

Simulation models have become increasingly popular in economics in the last two decades, because they can deal with a wide range of research questions. The set-up and analysis of simulation models can range from very specific to very general and can be underpinned by different combinations of theoretical considerations and empirical data. We offer a taxonomy of existing simulation approaches and show how their results can be used to explain observed economic features, examine economic systems and predict future economic processes. Moreover, we offer a new type of method that helps to better exploit empirical findings in simulation models.