The aim of this model is to provide a unified framework for studying and mitigating the economic and demographic consequences of increasing inequality. The MIWAG model is a rich life-cycle model that allows to trace out how initial heterogeneity is transmitted into unequal behaviours and outcomes over the lifecycle. It can be used for studying how different policies lead to different dynamics over the life-cycle and how this affects intra-generational inequality. Moreover, this life-cycle model can be implemented in an overlapping generations framework, which also allows studying how inequality evolves across cohorts (inter-generational inequality).

The figure below shows the main components of the life cycle model developed in Sanchez-Romero, Marsicano, Kuhn (2024). The color of the arrows depicts whether the impact
between two nodes is positive (green) or negative (red).

MIWAG Chart © Miguel Sanchez-Romero

Figure 1: Life-cycle model
Source: Sanchez-Romero, M., Marsicano, M., & Kuhn, M. (2024).

The set of initial characteristics -unobservable characteristics- (initial modal age at death, learning ability, and effort of schooling) for each individual has been calibrated using the Bayesian melding technique with the IMIS algorithm (Poole and Raftery, 2000). The Bayesian melding technique provides an inferential framework for deterministic models taking into account both model's inputs and outputs.