Introduction

In general terms, structural life-cycle models provide general-purpose frameworks for linking the causes and effects of events and decisions across the life course. Contrasting the statistical character of the models estimated in WP1, the basic idea of a structural model is that individuals maximize a lifetime utility functions subject to constraints (budget or time constraint) by making decisions, say with respect to labour supply and consumption. In this framework, an individual’s utility tomorrow will depend on the decision taken today, and today’s action is decided upon given the individual’s expectation of future outcomes and events. Public policies alter the economic environment, changing the individuals’ constraints, and thus decisions and lifetime utility (Low and Meghir, 2017).

The focus of our model on the risk factor health, and how this interacts dynamically with labour supply and retirement decisions. This is for two reasons: First, structural lifecycle models embodying health are rare, especially for Germany. We are aware of one model that draws on data from the SOEP to model a binary health status and focuses on the individual level (Haan et al., 2017). Second, SOEP-RV provides a unique comparative advantage for the estimation: Its administrative part provides periods of disability, severity of disability, and replacement rate. These disability periods must be attested by physicians. The SOEP survey data, contains a health module on self-reported health items.2 Further, the German transfer system is highly complex: in case of a severe health shock several transfer schemes may provide the individual with support in cash and in-kind (disability pension, sick pay, care insurance, etc.). Modelling this complex and interdependent web of transfer schemes implies a stark data requirement. As detailed above, SOEP-RV is able to meet this requirement through the linkage of insurance records and survey data. Having formulated the dynamic model, we proceed to model estimation. Having estimated the dynamic model, we can then quantify the life-cycle effects of counterfactual policies designed to reduce inequality. Interventions include changes to the tax- and transfer-system and the health insurance system.

Tasks

1. Health shocks, Employment and Retirement (HER) over the life cycle: model building
2. HER-model estimation
3. HER-model estimation semi-structurally