Proceedings of the 2014 Winter Simulation Conference A. Tolk, S. Y. Diallo, I. O. Ryzhov, L. Yilmaz, S. Buckley, and J. A. Miller, eds. The Role of Languages for Modeling and Simulating Continuous-Time Multi-Level Models in Demography Alexander Steiniger Adelinde M. Uhrmacher University of Rostock Albert-Einstein-Str. 22 D-18059 Rostock, GERMANY Sabine Zinn Jutta Gampe Frans Willekens Max Planck Institute for Demographic Research Konrad-Zuse-Str. 1 D-18057 Rostock, GERMANY ABSTRACT Demographic microsimulation often focuses on effects of stable macro constraints on isolated individual life course decisions rather than on effects of inter-individual interaction or macro-micro links. To change this, modeling and simulation have to face various challenges. A modeling language is required allowing a compact, succinct, and declarative description of demographic multi-level models. To clarify how such a modeling language could look like and to reveal essential features, an existing demographic multi-level model, i.e., the linked life model, will be realized in three different modeling approaches, i.e., ML-DEVS, ML-Rules, and attributed pi. The pros and cons of these approaches will be discussed and further requirements for the envisioned language identified. Not only for modeling but also for experimenting languages can play an important role in facilitating the specification, generation, and reproduction of experiments, which will be illuminated by defining experiments in the experiment specification language SESSL. 1 INTRODUCTION In demography, in addition to macro-projection (Bohk et al. 2009), microsimulation plays an important role (Willekens 2005, Willekens 2009, van der Gaag 2009). Its essence is the individual’s life-course, which is defined by the sequence of states that the individual visits over time and the waiting times between state transitions. The time-scales can either be discrete (usually in units of years) or continuous. In discrete-time models, time advances in discrete, equidistant steps. In contrast, a continuous-time microsimulation has a continuous time scale along which events can occur. In general, continuous-time models are the optimal theoretical choice for a precise description of population dynamics, as they mirror life-course developments most closely (Willekens 2005). The underlying stochastic model of continuous-time microsimulation is a continuous-time Markov model parameterized with transition rates. Accordingly, a continuous-time microsimulation model is also a competing risks model (cf. Zinn (2011)). Currently, demographic microsimulation focuses often on effects of stable macro constraints on isolated individual life course decisions rather than on effects of inter-individual interaction (Jager and Janssen 2003) or the macro-micro link (Ewert et al. 2007, Gilbert and Troitzsch 2008). To change this, we have to face various challenges. Two issues seem to refer to modeling: (a) how to model inter-individual interactions and dynamic binding/grouping (e.g., household formation and dissolution) in continuous space and time and (b) how to integrate dynamics at different levels. Another challenge refers to validation, as with more expressive models, demography has started to move from data- to hypotheses-driven development of individual-based, mechanistic models. This has an impact on validation processes and methods used. The question how far already existing approaches address requirements of multi-level modeling and simulation in demography, we will explore based on the linked lives model of Noble et al. (2012). 2978 978-1-4799-7486-3/14/$31.00 ©2014 IEEE