Kumulative Dissertation, Otto-Friedrich-Universität Bamberg, 2026

Climate change, geopolitical tensions, and growing economic interconnectedness are increasing the vulnerability of economic and financial systems to shocks. Through feedback mechanisms and propagation effects, initially localized disruptions can generate system-wide consequences. This cumulative dissertation examines how methods from complexity economics can contribute to understanding these dynamics and strengthening the resilience and stability of economic networks. To this end, three complementary methods are applied to current economic policy challenges: an agent-based model to investigate short-selling restrictions during periods of financial stress, a global input-output analysis to assess the propagation of cost-push inflation across the European Union, and a Markov-switching vector autoregressive model to analyze the effects of climate-related risks on European bond markets and inflation expectations.

First, the findings show that temporary short-selling restrictions lead to positive price distortions but can simultaneously reduce negative deviations from fundamental values and mitigate the severity of market crashes. Second, the analysis of global production networks reveals substantial asymmetries in the transmission of price shocks. European peripheral economies are particularly exposed to externally originating shocks, indirect higher-order price effects, and limited substitution opportunities. Third, the effects of climate-related risks are found to depend on the prevailing market regime. While transition risks have limited disinflationary effects during periods of low volatility, physical risks exert destabilizing and inflationary effects, particularly in high-volatility regimes.

The concluding synthesis chapter situates the three approaches within the ISO 31000 risk governance process. Agent-based models facilitate the exploratory analysis of system dynamics and policy interventions; input-output analysis identifies structural dependencies and systemically significant exposures; and regime-dependent time-series models quantify empirical relationships and state-dependent risks. Overall, the dissertation demonstrates that these methods provide distinct yet complementary contributions to the identification, analysis, and evaluation of systemic risks. It thereby offers a methodologically pluralistic framework for evidence-based economic policy advice under conditions of growing uncertainty.