A Lifecycle Consumption and Portfolio Choice Model with Uncertain Family Dynamics for German Households

• Applicant: Professor Dr. Raimond Maurer
• Subject Area: Operations Management and Computer Science for Business Administration
• Term: since 2024
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 536564474

Households make financial decisions and face the question of optimal consumption and investment strategies over the lifecycle, under various sources of uncertainties like labor market risk, capital market risk, mortality risk and uncertain family transitions. Family transitions can result important changes in a household’s financial position: wealth can rise due to a bequest, or it can fall in the event of a divorce. When one partner dies or a child arrives, new expectations are formed for future income and consumption. While most of current portfolio choice models assume a constant marital status over the lifecycle, real-world transitions between different family states can have significant implications for individuals’ financial positions and decisions. Previous research have integrated marital uncertainty into consumption and portfolio choice models for U.S. households. These studies demonstrate the importance of considering marital risk as an additional source of demographic shocks to better explain households’ financial choices: Yet we lack such a model for households in Germany. The objective is to develop and calibrate a dynamic stochastic consumption and portfolio choice lifecycle model that incorporates marital uncertainty and analyzes its impact on consumption, saving, and investment decisions in heterogeneous German households. Integrating marital transition risk into a portfolio choice model for Germany poses two challenges: First, the modelling of uncertain family transitions with different family specific institutional rules (e.g. family law, tax law). Second, the need for empirical parameter estimation to calibrate family transition risk. Drawing upon the framework of the MINT model, this research will empirically estimate discrete hazards and risks associated with marital events (e.g., marriage, divorce, fertility, spouse death, and self-death) for heterogeneous individuals. Survival Analytical Framework in discrete time will be used to quantify the hazards of life processes, taking into account individuals’ family histories, including marital, fertility, and cohabitation histories. By realistically calibrating a stochastic dynamic lifecycle model, this research will enhance our understanding of consumption and savings choices across different life stages and family circumstances. The contribution to the existing literature is twofold: first, the development of the first stochastic dynamic lifecycle model for Germany that incorporates marital uncertainties alongside other well-studied risks, and second, empirical estimations of family events using event history analysis, capturing households’ behavioural elements based on their experiences.

• DFG Programme: Research Grants