#14 – Eric Beinhocker: “New Economics” Is Coming For You
Jan 13, 2025
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In this engaging discussion, Eric Beinhocker, a Professor at the University of Oxford, contrasts traditional neoclassical economics with the emerging field of complexity economics. They delve into how these theories shape growth strategies and influence policy, especially in our tech-driven world. Topics like the evolution of markets, the divergence of technology progress, and the crucial role of trust in economic collaboration are highlighted. Eric advocates for a nuanced approach to navigate the complexities of modern economies and enhance public policy.
The contrast between neoclassical and complexity economics reveals differing views on economic dynamics, with the latter focusing on continuous innovation and emergent interactions.
Policymakers should adopt adaptive, experimental approaches to effectively respond to the complexities of modern economic systems and challenges.
Deep dives
The Divide Between Economic Theories
The distinction between neoclassical economics and complexity economics highlights the differences in how these theories view the economy. Neoclassical economics is characterized as an equilibrium system that assumes a stable state, whereas complexity economics views the economy as a dynamic, evolving system driven by constant innovations in technology and institutions. This latter approach emphasizes the role of human behavior, integrating modern behavioral science to provide a more realistic depiction of how the economy functions through the emergent interactions of individuals and networks. The theory suggests that understanding these dynamics leads to better predictions and policy recommendations, as evidenced by cases like the 2008 financial crisis, where complexity economics provided more effective explanations and solutions.
Learning from Historical Economic Models
Historical economic models have consistently struggled to provide accurate predictions, particularly in complex situations like financial crises, pandemics, and climate change. Complexity economics has emerged as a more effective alternative, utilizing agent-based models and empirical data to analyze interactions within networks and industries. For instance, during the COVID-19 pandemic, models developed by researchers outperformed traditional economic forecasts by accurately predicting sector-specific impacts and labor market dynamics. Additionally, climate change models grounded in complexity economics have provided insights into the technology evolution around clean energy, surpassing traditional predictions that often fall short.
Implications of Technological Evolution
Technological evolution plays a significant role in shaping economic structures, as both physical and social technologies evolve in tandem. Markets foster an environment that encourages experimentation and diversity, driving innovation and adaptation within companies. However, rapid scaling can lead to rigidity and complexity catastrophes, where systems become too intertwined to adapt efficiently. As markets and technologies continue to evolve, the balance between leveraging these advancements for cooperation and managing the decline of trust and fairness becomes a central challenge for both companies and policymakers.
The Need for Adaptive Policymaking
Policymakers must adopt an adaptive approach in the face of complex, reflexive economic systems where traditional predictions often fail. Emphasizing experimentation and learning from both successes and failures can result in more effective policies that better respond to dynamic market conditions. For instance, instead of solely relying on carbon pricing, a broader array of policy tools that have demonstrated effectiveness should be prioritized to combat climate change. Ultimately, this requires fostering a culture within political systems that values innovation and flexibility, allowing for continuous re-evaluation of policies to ensure they are achieving their intended goals.
My guest today is Eric Beinhocker, Professor of Practice in Public Policy at the Blavatnik School of Government, University of Oxford, and the founder and Executive Director of the Institute for New Economic Thinking at the University’s Oxford Martin School. Eric is the author of numerous academic articles and books, including The Origin of Wealth: Evolution, Complexity, and the Radical Remaking of Economics (2007).
In our conversation, Eric and I contrast traditional economics (neoclassical theory) with new economics (complexity economics). We also explore the policy implications of these differing economic theories, discussing topics ranging from aggressive growth strategies to complexity catastrophes in digital economies. I hope you enjoy our conversation.
References:
The origin of wealth: Evolution, complexity, and the radical remaking of economics (2007) https://moldham74.github.io/AussieCAS/papers/Origins of Wealth.pdf
Getting Big Too Fast: Strategic Dynamics with Increasing Returns and Bounded Rationality (2007) https://pubsonline.informs.org/doi/pdf/10.1287/mnsc.1060.0673
Fair Social Contracts and the Foundations of Large-Scale Collaboration (2022) https://oms-inet.files.svdcdn.com/staging/files/Fair-Social-Contracts-Beinhocker-v8-22-22.pdf
Reflexivity, complexity, and the nature of social science (2013) https://www.tandfonline.com/doi/full/10.1080/1350178X.2013.859403
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