From tulip bulbs to sub‐prime mortgages examining the sub‐prime crisis : The case for a systemic approach

Purpose – The collapse of the sub‐prime mortgage market parallels several earlier failures within the financial services sector, begging the question why the lessons of past failures were not learned. Throughout history from the tulip bulb crisis of the 1600s to the most recent economic crisis, decision‐makers keep making the same mistakes. This occurs in part because of a failure to recognize similarities between past and current events. This conceptual paper aims to use systems dynamics tools to examine the crisis and illustrate how seemingly independent events are linked. Design/methodology/approach – The paper provides a fundamental review of systems thinking concepts and uses a tool of systems dynamics, causal loop diagrams (CLD), to provide a visualization of the dynamics of the sub‐prime market collapse over time. This approach provides insights that traditional analytic methods do not, which should be beneficial in understanding future cases where speculative demand drives behavior. Findings – The paper uses the CLD tool to understand the evolution of the recent financial crisis. It finds that the dynamics of the collapse closely mirror many historic financial disasters (the paper cites several) and proposes the fundamental CLD of this phenomenon be elevated to a special category of the “limits to growth” archetype model. The paper makes this recommendation in the hope it will allow investors and policy makers to quickly recognize future speculative events when they happen again. Originality/value – This paper argues that, despite the surface level uniqueness and complexity of the recent economic collapse, there is an underlying simplicity that links the recent collapse with speculative boom/busts going back over 400 years. The representation that the paper develops applies the language of systems thinking to the most recent financial crisis. A mental model of this system and the corresponding systems structure can be used to not only understand what happened, but also inform decision‐makers when similar speculative behavior occurs in the future.