The Royal Swedish Academy of Sciences, on October 13, 2025, announced that the Nobel Prize in Economics would be awarded to Joel Mokyr, Philippe Aghion, and Peter Howitt for explaining how innovation drives sustained economic expansion. Their work answers questions about the world's explosive growth, spread over the last two centuries, that follows a whole millennia of stagnation.
About the Winners
Joel Mokyr, born in 1946 in Leiden, Netherlands, is a professor at Northwestern University. After earning his PhD from Yale University in 1974, he became a leading economic historian specializing in technological change and the Industrial Revolution. Philippe Aghion, born in 1956 in Paris, France, completed his PhD at Harvard University in 1987. He currently holds professorships at Collège de France, INSEAD in Paris, and the London School of Economics. Peter Howitt, born in 1946 in Canada, earned his PhD from Northwestern University in 1973 and is now a professor at Brown University. Together with Aghion, he developed groundbreaking mathematical models of economic growth.
The Components of Useful Knowledge
Mokyr's research revealed that sustained growth requires a continuous flow of 'useful knowledge.' But, what makes knowledge useful? He identified two essential components that must work together.
First is propositional knowledge. This is understanding why things work based on observing the natural world, almost like the theory behind a technology.
The second is prescriptive knowledge. These are the practical institutions and blueprints that show how to actually make something work—the manual.
Before the Industrial Revolution, innovators had theories about why things worked, but lacked the practical knowledge to build upon them reliably. This changed in the 16th and 17th centuries when scientists began using precise measurements, controlled experiments, and insisting on reproducible results. This created a powerful feedback loop between theory and practice.
The steam engine exemplifies this transformation. It improved rapidly thanks to new understanding of atmospheric pressure and vacuums. Similarly, steel production advanced through better comprehension of how oxygen reduces carbon content in molten iron. Ideas that previously remained on drawing boards—like Leonardo da Vinci's helicopter designs—could finally become reality when both types of knowledge were abundant.
Mokyr argued that Britain led the Industrial Revolution not just because of ideas, but because it had skilled artisans and engineers who could transform concepts into commercial products. The policy implication is clear: governments must invest heavily in technical education and skills training for sustained growth.
He also emphasized that societies must remain open to change. Innovation creates winners and losers as new technologies replace old ones, and resistance from established interests can stifle progress.
Creative Destruction
While Mokyr explained innovation's historical role, Aghion and Howitt created a mathematical framework to understand how technological advancement generates sustained growth. Their model captures the concept of "creative destruction"—the idea that innovation simultaneously creates value while destroying incumbent businesses.
This is how the theory works. Companies invest in R&D to create patented products, giving them temporary monopolies and profits. However, competitors can also invest in R&D to develop better products. When superior innovations emerge, they replace existing technologies, and profits shift to the new innovators. This continuous cycle drives economic growth.
Their model addresses a critical policy question concerning whether governments should subsidise R&D, and if yes, how much. According to these economists, to answer this question, one must take two competing forces into account.
On one hand, when new technology replaces old, society continues benefiting from the displaced technology even after the original company stops profiting. This suggests R&D deserves subsidies to encourage continued innovation.
On the other hand, companies capturing most profits from incremental improvements over existing technologies may receive rewards disproportionate to society's actual gains. From this perspective, R&D investment might already be excessive from society's viewpoint.
The optimal level of R&D varies by country and economic context, but Aghion and Howitt's framework helps policymakers identify which measures will most effectively achieve sustained growth.
The Way Ahead
The three economists have made significant contributions to our understanding of innovation-driven growth, providing both historical insights and analytical frameworks that have shaped modern economic policy. Their work helps explain one of humanity's most important economic transformations and offers guidance for fostering prosperity in an era of accelerating technological change.
However, like all economic models, these theories have limitations worth acknowledging. Mokyr's explanation, while rich in historical detail, is heavily rooted in the European experience during the Scientific Revolution. His framework effectively explains Britain's Industrial Revolution, but questions remain about its universal applicability. Does it fully account for South Korea's rapid growth in the 1970s or China's economic transformation in the 1990s? These cases suggest that while Mokyr's insights are valuable, they may need adaptation to explain growth patterns across different cultural and institutional contexts.
The Aghion-Howitt model, meanwhile, offers important theoretical insights but faces practical challenges. On questions like R&D subsidies, the model reveals competing forces without providing definitive answers, thus limiting its immediate policy utility. The model also treats innovation somewhat mechanistically—and with linearity—as though more R&D investment reliably produces more breakthroughs. In reality, major innovations often emerge unpredictably, through serendipity, individual genius, or unexpected connections that resist systematic modeling.
Additionally, these models operate within certain assumptions—such as relatively efficient markets and fair competition—that don't always hold in practice. Real-world markets involve monopolistic behavior, regulatory capture, information asymmetries, and other imperfections that complicate the neat theoretical predictions.
The concept of "creative destruction," while analytically useful, also deserves careful consideration. The theory rightly identifies how innovation drives progress through the replacement of old technologies with new ones. Yet this process has real human costs—job losses, displaced communities, and economic disruption—that merit serious policy attention. Recognizing innovation's role in growth doesn't mean dismissing the need for robust social safety nets, retraining programs, and policies that help workers and communities adapt to technological change.
These limitations don't diminish the laureates' fundamental contributions. All economic models simplify reality to make it comprehensible. That's what makes them useful tools for understanding complex phenomena. The question isn't whether these models are perfect, but whether they advance our understanding and provide useful frameworks for thinking about policy.
The challenge now is to build on their work, refining these models to better capture the full complexity of innovation, extending them to diverse economic contexts, and ensuring that the growth they help generate is both sustainable and broadly shared.
Understanding the mechanisms of innovation-driven growth is essential, but so is ensuring that growth translates into genuine improvements in human welfare across society.
