New discussion paper reviews the twin challenges of measurement and aggregation in economics and the natural sciences, with climate risk as a guiding example.
Authors: Eddie Gerba and Gireesh Shrimali
This paper synthesises a broad range of theoretical and empirical perspectives, tracing ideas from early systems theory to modern macroeconomic debates, and compares the approaches of economics, complexity science, and climate science to the micro–macro aggregation problem.
Several key conceptual tensions are highlighted—most notably the “micro–macro gap”—and the limitations of traditional models when confronted with heterogeneity, deep uncertainty, and non-linear feedbacks are demonstrated, especially in the climate-risk context. It also reviews emerging methodologies and proposes integrated frameworks to combine micro-level detail with macro-level consistency. Finally, the paper outlines a roadmap for future research and policy, advocating interdisciplinary collaboration, improved data infrastructure, and adaptive modelling strategies to better capture climate change.