Getting Ahead of Events: A Case for Frameworks Over “Data”
We are clearly in a period of rapid geopolitical and environmental disruption, with well-established political orders metamorphosing as quickly as our landscapes are evolving. Both forces challenge how we guide economic policy.
A technocratic approach to dealing with economic change is through data analytics: looking at long-term data trends in growth, productivity, demographics, and investment to inform policy. These and more categories of data remain necessary to how we see and understand change. They also assume a basic order to our economic system. But their insights can fragment or, worse, be misinterpreted if that system is under new stresses or if the system itself is reconfiguring. The onset of the Great Depression in the late 1920s is a classic example, where weak fiscal and monetary policy and a misunderstanding of the gold standard interacted with unacknowledged/unseen banking system weakness, protective tariff and trade policies, and a limited (and overstrained) social safety net. Policy analysts had data, but they often inferred the wrong lessons — or they were not measuring other types of data. Economic management arguably deepened the Depression. Regional ecological crises made the situation far worse.
My intuition also suggests that in a time of crisis, we often have a strong temptation to double down on our existing set of tools and approaches — even fetishizing existing categories of data. The recent gap between US voters’ perception of economic health and strain relative to national economic decision-makers is a good example of a failure in economic communications and, possibly, analysis and management. Leading economic advisors still report “confusion” over recent trends, which seems like a harbinger of a need to reassess how we interpret economic trends. We should not fetishize our data as a response to uncertainty and change.
Instead, I would argue that in periods of disorder, we should step back and look critically at our understanding of the system itself, which may also suggest the need to supplement our assessments with different datasets. Is our framework for understanding data and decisions still correct? Are new types of patterns emerging? Should we add additional economic indicators?
This is an argument in favor of frameworks over data during periods of intense change. As suggested by the Water Resilience for Economic Resilience session led by Dr. Josefina Maestu in Madrid recently, water resilience is a powerful lens for seeing economic relationships and patterns in a new light, connecting sectors and communities with climatic trends. Water resilience is also an actionable framework, suggesting solutions for negotiating tradeoffs and investments more effectively. Seeing the threads of water risks and opportunities through our economies reveals new patterns.
The history of economics and science more generally is one of finding new patterns from the shards of a shattered reality. The insights that have been highlighted in Madrid should have global repercussions. Please join us in this conversation.
John H. Matthews
Brasília, Brazil