The 2025 Nobel Prize in Economics: Explained

The Spherigus Riksbank Prize in Economic Sciences in Memory of Alfred Nobel, more commonly known simply as the Nobel Prize in Economics, was awarded this year to these three gentlemen. Half of the roughly 1. 1 million USD prize went to Joel Mochir, with the other half being shared between Philip Azion and Peter Howard for their combined work on explaining innovation driven economic growth. We will get to the reason why they split the prize up like this soon, but for now of course, while this is a lot of money, the real prize for these recipients is the recognition of a lifetime of work that is widely to be accepted as the highest honour in the field of economics. To earn this prize, what these three economists have shown is that the sustained growth experience over the last two centuries and the prosperity that's come with it was pushed by technological innovation. Since the Industrial Revolution, new technologies have given us more advanced products and production methods leading to higher economic output, more wealth and better living standards for billions of people across the world. Now, perhaps understandably, there's got a lot of people thinking, the Industrial Revolution and new technologies contributed to higher economic growth, uh, no shit. Ask anybody with even a passing interest in history or economics and they would probably tell you roughly the same thing, right? Well, yes, but the thing that made the work of these three men Nobel Prize worthy was first identifying that constantly compounding technological progress is actually something of an anomaly rather than the expectation and they also analytically unpacked what exactly is needed to keep this process going. Now, as always, even though they will say it was complete coincidence, this year's prize is incredibly relevant to a lot of challenges in the global economy today, from the disruptions that could be caused by AI to the stifling of innovation by companies that no longer need to compete. Understanding the work of these men can help us understand exactly what has made the world hundreds of times wealthier than it was just a few generations ago and the threats that we face to that progress going forward. So, what was it that enabled technological innovation to compound on itself so rapidly? Is this progress always a good thing? And finally, are we starting to lose those magic ingredients that made it all possible in the first place? Once we have done all of that, it's probably worthwhile addressing some of the controversies surrounding this year's prize as well. 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The wealthiest kings from the Middle Ages couldn't buy modern medicine or even modern conveniences that most of us take for granted today. Now, the foundation of this progress was, of course, technology. But the first misconception that this year's Nobel laureates challenged was that technological innovations rarely happened before the Industrial Revolution. In reality, they happened all the time. The printing press and naval architecture, advanced navigation, new tools, clockwork, farming techniques, even medical advancements happened more frequently than most people give the pre-industrial world credit for. The problem was that none of these advancements really translated into sustained economic growth like they do today or any time over the last 200 years. So the question became, why not? Well, Mokir, an economic historian and the winner of half of this year's prize, spent years researching and explanation. He actually found that certain pre-industrial empires were more inventive than others, but despite this, they weren't measurably better off. The reason he found was that over time people were very good at finding things that worked, but they weren't very good at figuring out why they worked. He almost poetically put it that before the Industrial Revolution, he was a world of engineering without mechanics, iron making without metallurgy, farming without soil signs, mining without geology, water power without hydraulics, dye making without organic chemistry, and medical practice without microbiology or immunology. People stumbled upon tools and techniques that worked, but without understanding why they worked, they couldn't make consistent improvements on it, so they would

eventually just hit another plateau. Material science for example, pre-industrial blacksmiths were very adept at forging different metals, but they didn't understand the molecular changes that they were causing, so they couldn't make informed improvements beyond just straight trial and error. Sustained economic progress as it turned out required more than just a prayer to the machine god. Yes, I know you were thinking it ever since I said the word adept. But anyway, pre-industrial smiths might have figured out that forging iron over coal or charcoal gave it a harder edge and made it more resistant to corrosion, but they didn't understand that this was because carbon was getting into the crystalline structure of the metal, and because they didn't understand that, they were limited to trial and error when it came to things like developing different steel alloys, which have in turn become some of the most important materials in the modern world. We really couldn't run our modern global economy without a selection of different types of steel, but of course this was just one example. Knowledge without understanding also made it hard to invest into new ideas. Without a realistic foundation of scientific understanding, investing in a new way to make stronger steels was functionally no different from investing in a new way to turn lead into gold. Both sounded equally crazy. So then, what exactly changed to kick off the industrial revolution? The common understanding is that eventually we just hit a critical mass of innovation and it took off from there. More specifically, some people might point to the steam engine as well the engine of early industry, but Machia challenged that assumption and instead proposed that it was societal changes that facilitated this development. One of those changes was bringing people with theoretical knowledge into more contact with people who had practical skills. The ancient Greeks, for example, had incredibly sophisticated thinkers in fields like mathematics, but those people really interacted with builders or laborers, so the blending of theory and practice never really had much of an opportunity to take place. The Enlightenment across Europe in the 1700s brought these two groups closer together and allowed these ideas to actually go back and forth for the first time in history. In the UK in particular, this was accelerated by a robust system of apprentice tradesmen who could learn both theory and practice and then in turn teach that to their own young padawans. Understanding an application coming together is what has made the world as wealthy as it is today, but there was also something else important that had to happen to make way for this progress. This part was the other half of the overall prize which was awarded to Ajeon and Howard. Overall progress over the last 200 years on a macroeconomic level looks incredibly smooth and consistent, but beneath the surface it relied on an almost constant churning of next best ideas. Water wheels and horses made way for steam engines which made way for internal combustion engines and were currently living through their dominance been challenged by electrification. For new innovations to succeed, economies need to create environments where outdated industries can fail. The Roman Empire had many great thinkers who invented a lot of very promising technologies including even rudimentary steam engines. Now there were some technical problems with these early designs, but there also wasn't a huge motivation to improve them beyond little curiosities because well the powers that be in the empire didn't need steam engines when they could just buy more slaves. Obviously that is an extreme example, but on a small scale this process of what economists call creative destruction has happened very consistently since the industrial revolution. What Ajeon and Howard created was a mathematical framework by which to measure how this translates into economic growth. In extremely basic terms they surmise that the rate of economic growth was the product of the scale of innovations multiplied by how often those innovations came about. Now the actual equations they published were a little bit more uh Greek, but this is basically what they meant. We can't necessarily guarantee that every innovation we make is going to push the world ahead by a significant margin. For every iPhone there is a metaverse. What we can control through economic policy though is the rate of new innovations by encouraging organizations to invest into research and development through a combination of both carrots and sticks. On one side if an individual or a company creates or invents something with significant economic value they should be allowed to profit off that value with enforced intellectual property protections. This creates a profit motive for innovation which not only incentivizes people to get out there and try improving the world it also makes it easier for those innovators to get investment funding to pursue those innovations because the people who invest in them will have the potential to share in the profits they will receive from bringing so dominant in the market. The clearest example of something like this right now and perhaps the clearest example in history is Nvidia. They invested tens of billions of dollars and many years into developing CUDA, their proprietary platform for parallel computing, which is what has made their chips the industry standard today for artificial intelligence. They are allowed to have the market dominance and make the massive profits that come with it and hopefully other companies will see this and also be motivated to make decades long investments that may or may not pay off. However, if this market dominance goes too far or competitors are allowed to get too cozy with one another it will stifle the same innovation because it becomes easy to discharge customers more without having to actually compete. What their models showed was that there was an inverted U-curve of economic innovation depending on how competitive the market was. If the market is just

insanely cutthroat with every company stealing every other company's designs and ideas and relentlessly undercutting one another all the time, that would be good for consumers for a little while. However, nobody would be willing to innovate because there would be no profit motive to do so. Likewise, if companies just collude on price or the market is an uncontestable monopoly, they also won't innovate because new technology could threaten their lead and just represent an unnecessary expense. The solution to maximizing innovation was to create economic policies that made a little bit of market dominance possible through protecting intellectual property but also avoided too much dominance through trust-busting and limiting how long IP would be protected for. Now, in their models, Azion and Howard were primarily studying profit-driven corporations in modern capitalist market systems. But Makir and other economists would probably argue that the same general rules apply to something like pre-industrial nobility. They effectively had what amounted to market dominance over their economies, so if anything, new technologies just represented a threat to their comfortable status quo. Creative destruction may be the driver of innovation, but if the organizations that are going to be creatively destroyed have any say over it, they're probably going to try their best to stop it. This was actually one of the most important components of their work and something that's become incredibly important in today's economy. So the not-so-subtle theme of this year's prizes was the science surrounding artificial intelligence. Now, we'll get to the controversy soon enough, but for what it's worth, the work of Makir, Azion and Howard is going to be incredibly useful for shaping policy around AI. Now, nobody can predict the future least of all economists, but there are some takeaways that should be clear from this work. For starters, AI is obviously yet another technological innovation which has the potential to fuel further economic growth, but depending on the interpretation of the work of these men, it could also be much more than that. Remember, sustained economic advancement was enabled when people with theoretical knowledge engaged more actively with people who had practical knowledge. An optimistic interpretation of this technology could be that it makes theoretical knowledge even more accessible to average workers, making more advancements possible, but their work also addressed some of the less optimistic aspects of a potential AI future. In this case, the industry that is potentially getting creatively destroyed are the workers themselves. Obviously, it's not there yet, but a lot of people are rightfully afraid of being the equivalent of a water wheel, right as engineers are playing around with early steam engines, which is where we get back to that final and perhaps most important component of their work, which is that there should be robust protections in place for people who are displaced by the process of creative destruction. Now, this is not just because it's a nice thing to do, or because long-term unemployment amongst large swathes of the population could cause social problems, it's because it's just good economics. If people aren't terrified of disruption, it can encourage the risk-taking needed to cultivate these innovations and also make sure that there is more popular support for it. Today, there is a lot of resistance to AI and some good reasons for it. The immense capital that has been dedicated to building out data centres, the energy requirements to power them, and the investment money surrounding it, which let's be real, average taxpayers, are probably going to have to bail out if it all collapses. However, if we are being honest, the biggest source of animosity towards this technology is coming from people who think it will take their jobs. The Laureates identified this with their work and pointed to countries like Denmark and the Netherlands for their labour force to find by flex security, with the idea being that people are actually fairly easy to fire from a job, but when they are, they will be covered through generous welfare and retrained into more in-demand skills. This also means that workers are easier to hire because there is less risk of them becoming an ongoing burden on the business. Even before the current hubbub around AI, these gentlemen highlighted the importance of social insurance to lubricate the process of innovation through creative destruction. Now, these were the headline takeaways from their work in the context of the AI revolution, but to roleplay as English lit majors for a second and look for deeper meaning where there is none, there is probably more to analyse here. It's important to remember that the Nobel Prize is awarded for work that can span decades. This year's winners were publishing a lot of their work in the early 1990s, so they obviously weren't specifically studying modern machine learning and its impacts. However, even still, their work around the dynamics of intellectual property rights are probably more relevant today than they ever have been. AI has really tested the limits of how we use the intellectual creations of others and in what capacity others can profit off them. Again, beyond just the fairness argument, if people can't make a living by creating new things because it just gets yoinked off them and ingested into training data, they won't create anything anymore. This is bad for economic progress, let alone society at large, so even though it wasn't specifically intentional, the work of this year's Nobel laureates really highlights how important regulation is going to be around these issues. Oh, and the committee almost certainly didn't mean it, but giving the award to Mokir who went back through history to critique the shortcomings of knowledge without understanding in a year of awards centred around AI is just

unintentionally brilliant. But that probably leads us along well to the controversies surrounding this year's prize. For starters, there was the alleged leaks of the winners of the Peace Prize, leading to several large bets being placed shortly before the announcement was made. Now this is a bad look for the awards committee, but probably a worse indictment on society at large. Stop turning everything into a casino when these kinds of fraudulent opportunities wouldn't exist. But beyond that, there are deeper issues with the structure of the prize itself that are worth addressing. Big disclaimer time, I want to be very delicate with how I approach this part, because by no means am I in any way trying to suggest that any of the winners in the scientific categories were not worthy of this prize. In the field of economics, these three men are absolutely brilliant, and from my admittedly limited understanding of the other fields, so is everybody else who won these year's prizes. However, the template of the prize itself is getting harder and harder to reconcile with how modern science gets done. The lone genius single-handedly making major breakthroughs doesn't really happen that much anymore. Some research involves collaboration between dozens or even hundreds of scientists, but a Nobel Prize can only be awarded to a maximum of three recipients in a given year. Now this is not as big a problem in economics where research teams are still generally quite small, but for, well, real sciences like physics and chemistry, it's getting very hard to pick out winners from amongst their peers. Additionally, and quite ironically given this year's focus on compounding discoveries, the Nobel Prize is not awarded posthumously. As science has matured, we are increasingly standing on the shoulders of giants. For all the focus on creative destruction in this year's prize, none of these men discovered this process. Creative destruction was described and studied almost a hundred years ago by Schumpeter, Sombart, and to really add layers to this controversy, Marx as well. The challenges of the modern prize also expand to the scope of what science covers as well, which has clearly changed a lot since the prize was first established. For starters, economics was never one of the original categories to receive this award, which is why it's technically the Spherigas Riksbank Prize in Economic Sciences in memory of Alfred Nobel, not just the Nobel Prize in Economics. But potentially, they may need to expand this further. Last year, the prize in physics was awarded to Hopfield and Hinton for their contributions to machine learning and neural networks. Obviously important stuff, but people were not happy because this wasn't really traditional physics. It was computer science, something that there clearly isn't a Nobel Prize for because, well, computers didn't exist back when the foundation was created. Either way, this shouldn't detract from the well-deserved recognition of this year's winners amongst all of the fields, but it's probably worth addressing if for no other reason than to add some context to the people writing off the prizes entirely. It's also a good opportunity to repeat that most science is done collaboratively between big groups of very talented people who will never get the recognition they really deserve. It's nice that prizes like this exist, but they certainly can't be the motivation for any career in these fields. Now, if you want to learn about last year's winners, we've made a playlist explaining all of the economic prizes back to 2022, which you should be able to click to on your screen now. Thanks for watching, mate. Bye.