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Supply chains and production networks play a crucial role in economic growth and productivity. Specialization and interdependence among different industries enable the efficient exchange of goods and services. Countries with diverse and complex supply chains have the potential for faster growth and greater resilience. However, disruptions in supply chains, as seen during the COVID-19 pandemic, can reveal vulnerabilities. Understanding and mapping supply chains can help manage and mitigate risks, as well as optimize economic performance.
Inequality in productivity, rather than income distribution, is a significant driver of economic inequality. The distribution of productive capabilities among countries leads to varying outcomes in terms of economic growth and prosperity. Places with fewer productive capabilities tend to be trapped in a cycle of limited economic opportunities. Addressing inequality requires policies that focus on inclusion and connecting individuals to more complex production networks. This would provide the opportunity for individuals and regions to participate in higher-value economic activities.
Global value chains have allowed for the integration of economies and facilitated the entry of less-developed countries into the global market. These value chains enable countries to specialize in specific tasks or components, making participation in global trade more accessible. However, disruptions to global value chains, as observed during the pandemic, can have adverse effects. The resilience of economies depends on the diversity and flexibility of their supply chains. Understanding the dynamics of global value chains can help in managing risks and promoting sustainable economic growth.
Understanding and mapping supply chains at both the industry and firm level is essential for effective decision-making and risk management. Predictive models that incorporate the complexity of supply chains can provide valuable insights into the potential impact of disruptions, such as natural disasters or global crises. By analyzing the interdependencies within supply chains, policymakers can better identify vulnerabilities, support resilience, and make informed decisions to mitigate negative economic and social consequences.
Large cities allow for better complementarities among industries, leading to increased productivity and employment. Research shows that many wage and inequality puzzles can be explained by these complementarities. For example, the ability to implement technology and knowledge transfer relies on business travel, which has been shown to increase productivity, employment, and exports. The shutdown of business travel during the pandemic raised concerns about the impact on productivity and the need to efficiently move workers to adapt to changing occupational mobility networks.
The pandemic highlighted the trade-offs between lockdowns, transfers, and poverty in countries with limited fiscal space. Lockdowns reduce the spread of the virus but can lead to increased unemployment and poverty. Poorer individuals have a harder time working from home, exacerbating inequality. Models combining economic and epidemiological data can provide insights into the economic effects of different policies and the differential impact on different socioeconomic groups. Additionally, research on inequality and agent-based models can help policymakers understand forces generating inequality and develop effective policies that address the long-term effects on the workforce and education.
As our world knits together, economic interdependencies change in both shape and nature. Supply chains, finance, labor, technological innovation, and geography interact in puzzling nonlinear ways. Can we step back far enough and see clearly enough to make sense of these interactions? Can we map the landscape of capability across scales? And what insights emerge by layering networks of people, firms, states, markets, regions? We’re all riding a bucking horse; what questions can we ask to make sure that we can stay in the saddle?
Welcome to COMPLEXITY, the official podcast of the Santa Fe Institute. I’m your host, Michael Garfield, and every other week we’ll bring you with us for far-ranging conversations with our worldwide network of rigorous researchers developing new frameworks to explain the deepest mysteries of the universe.
This week on Complexity, we speak with two SFI External Professors helping to rethink political economy: newly-appointed Science Board Co-Chair Ricardo Hausmann (Website, Wikipedia, Twitter) is the Director of the Harvard Growth Lab and J. Doyne Farmer (Website, Wikipedia) is Director of the Complexity Economics program at the Institute for New Economic Thinking at the Oxford Martin School. In this episode we zoom wide to try and find a way to garden all together, learning limits that can help inform discussion and decisions on the shape of things to come…
If you value our research and communication efforts, please subscribe, rate and review us at Apple Podcasts, and consider making a donation — or finding other ways to engage with us — at santafe.edu/engage. You can find the complete show notes for every episode, with transcripts and links to cited works, at complexity.simplecast.com. Heads up that our online education platform Complexity Explorer’s Origins of Life Course is still open for enrollment until June 1st! We hope to see you in there…
Thank you for listening!
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Podcast theme music by Mitch Mignano.
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Mentions and additional resources:
The new paradigm of economic complexity
Pierre-Alexandre Balland, Tom Broekel, Dario Diodato, Elisa Giuliani, Ricardo Hausmann, Neave O’Clery, and David Rigby
in Research Policy
How production networks amplify economic growth
James McNerney, Charles Savoie, Francesco Caravelli, Vasco M. Carvalho, and J. Doyne Farmer
in PNAS
Productive Ecosystems and the arrow of development
by Neave O’Clery, Muhammed Ali Yıldırım, and Ricardo Hausmann
Horrible trade-offs in a pandemic: Poverty, fiscal space, policy, and welfare
Ricardo Hausmann and Ulrich Schetter
in ScienceDirect
Historical effects of shocks on inequality: the great leveler revisited
Bas van Bavel and Marten Scheffer
in Nature Humanities & Social Sciences Communications
(Twitter thread)
Complexity 56 - J. Doyne Farmer on The Complexity Economics Revolution
The Multiple Paths to Multiple Life
Christopher P. Kempes and David C. Krakauer
in Journal of Molecular Evolution
Scaling of urban income inequality in the USA
Elisa Heinrich Mora, Cate Heine, Jacob J. Jackson, Geoffrey B. West, Vicky Chuqiao Yang and Christopher P. Kempes
in Journal of The Royal Society Interface
Complexity 12 - Matthew Jackson on Social & Economic Networks
Complexity 81 - C. Brandon Ogbunu on Epistasis & The Primacy of Context in Complex Systems
Pitchfork Economics
by Nick Hanauer (podcast)
Complexity 15 - R. Maria del-Rio Chanona on Modeling Labor Markets & Tech Unemployment
Will a Large Complex System be Stable?
by Robert May
in Nature
Investigations
by Stuart Kauffman
The Collapse of Networks
by Raissa D’Souza (SFI Symposium Talk)
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