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Groups of firms often achieve a competitive advantage through the formation of geo-industrial clusters. Although many exemplary clusters are the subjects of case studies, systematic approaches to identify and analyze the hierarchical structure of geo-industrial clusters at the global scale are scarce. In this work, we use LinkedIn's employment history data from more than 500 million users over 25 years to construct a labor flow network of over 4 million firms across the world, from which we reveal hierarchical structure by applying network community detection. We show that the resulting geo-industrial clusters exhibit a stronger association between the influx of educated workers and financial performance, compared to traditional aggregation units. Furthermore, our analysis of the skills of educated workers reveals richer insights into the relationship between the labor flow of educated workers and productivity growth. We argue that geo-industrial clusters defined by labor flow provide useful insights into the growth of the economy.

There is a parallel between today's stock market and Fischer random chess. The last time we faced a global pandemic was in 1918, and this might as well have been in the BC era. Few of us were alive then, but even the history books are not that useful, as the structure of the US and global economy, the central bank system, the diversity and dynamism of society, and the state of technological progress are nothing like the world knew then. Most of the mental models we as investors rely on are based on an environment that no longer exists. The only common denominator between now and then is that humans have not really changed that much - it takes a few millennia to rewire our DNA and thus our fundamental behavior.

Beginning in the late 1970s, China's economy delivered the largest growth spurt in recorded history. Striking discontinuity between recent outcomes and the economic experience of the prior 200 years invites portrayal of recent events as a "China miracle" that requires neither economic nor historical analysis. This overlooks deep institutional constraints arising from authoritarian rule and its supporting elite networks and fails to recognize the link between central government weakness and the origins of the recent boom. In both the pre-1949 treaty ports and in the aftermath of the Cultural Revolution, the retreat of central control enabled episodes of economic openness and dynamism built upon 'bottom up' initiative and decentralized innovation. Historic legacies that shape political structures and individual behavior will continue to influence China's economic trajectory.

In a collaboration with Italian scientists as part of the European project Ecopotential, EPFL scientists built a model to predict the dynamics of two carabid species across the landscape of Gran Paradiso National Park in the Graian Alps, in Northern Italy, now combining field measurement with advanced remote sensing. The results are published in PNAS and the open-model is available on GitHub. "The main result of this work, which I deem important, is to suggest that an integrated ecohydrological framework blending field evidence, both theoretical and remotely acquired, has contributed substantially to our understanding of key indicators of ecological well-being, carabid beetles, in complex environments like iconic mountains," explains Andrea Rinaldo, who leads the Laboratory of Ecohydrology.

The complexity of an ecological community can be distilled into a network, where diverse interactions connect species in a web of dependencies. Species interact directly with each other and indirectly through environmental effects, however to our knowledge the role of these ecosystem engineers has not been considered in ecological network models. Here we explore the dynamics of ecosystem assembly, where species colonization and extinction depends on the constraints imposed by trophic, service, and engineering dependencies. We show that our assembly model reproduces many key features of ecological systems, such as the role of generalists during assembly, realistic maximum trophic levels, and increased nestedness with mutualistic interactions. We find that ecosystem engineering has large and nonlinear effects on extinction rates. While small numbers of engineers reduce stability by increasing primary extinctions, larger numbers of engineers increase stability by reducing primary extinctions and extinction cascade magnitude. Our results suggest that ecological engineers may enhance community diversity while increasing persistence by facilitating colonization and limiting competitive exclusion.