Luca Mazzone

David Deutsch (@DavidDeutschOxf) has a nice post today explaining how he fixed his dishwasher with the help of ChatGPT. We have all been there over the last couple of years. In my case, from fixing a light fixture in my kitchen to repairing a leak in my irrigation system. Deutsch and many readers point out something that has been a staple of my talks for a decade. GDP was designed to measure an economy that produced coal and steel, easily measurable quantities. And GDP did its job quite well for decades. IT, first, and later the internet and AI, changed the landscape. My favorite example is books. Even as late as 2010 or so, getting the most recent books in Spanish on, let’s say, Spanish economic history was hard in the U.S.: expensive and time-consuming. Every time I went to Madrid, I carried two bags, one of them empty because it would come back filled with books. Then Kindle arrived, and now I can buy nearly every single Spanish book I want in seconds and at a lower price than the physical copy. This was an enormous increase in my welfare that never got reflected in GDP. The literature is divided on how big this effect is. I tend to side with those who think it is a big deal. Therefore, many of the gains in GDP growth announced by the strongest defenders of AI might not materialize: they will go instead into higher welfare. But the issue goes beyond getting GDP wrong. What Deutsch perhaps did not notice is that he did not pay VAT on the service of the repair person he did not hire, and that such a repair person did not pay income taxes on the service he did not render. Taxing AI-based economies might thus become much harder, from a purely technical perspective. One solution would be to tax the profits of OpenAI (or Deutsch’s subscription), but I am among those who think those profits are not going to be nearly as large as anticipated. Competition among labs will drive the subscription prices of models down (unless labs can cartelize, for example, by appealing to “AI security”). Over 95%, and perhaps as much as 99%, of the gains from AI will pass to the final user, whether another business or an individual. Now, we could tax the final user, for instance, at a fixed rate per token used. But that implies we are taxing the high-return activity (how to fix the dishwasher) at the same rate as the low-return activity (Claude: “tell me a joke about my cat jumping”). And taxing per token might hurt those final users who use more tokens because they are more productive, something we might not want to do (yes, there is something called the uniform commodity taxation theorem, but it often breaks down). Let me give you an extreme example: imagine that tomorrow the new OpenAI model cures all cancers, forever. Just a vaccine, $10, once in your life, and you never get cancer again. The increase in human welfare from such an invention would be staggering. But how do you measure it in GDP? Yes, people will live longer, perhaps work longer. A second-order effect on GDP. And more importantly: how do you tax the vaccine? Do you even want to tax the vaccine? I would argue we want to subsidize it, and generously. When I was still an undergrad, my first RA job was helping to construct GDP and other national aggregate statistics in Spain. It was a most valuable experience, because it made me aware of what GDP means, its strengths (and it has many more than its critics concede), and its limitations. But it also taught me that what you can tax out of GDP is far more limited than you would think at first sight. There are real upper bounds on taxation, and I am afraid the bound is tighter now than it used to be.

Oh, I don't know. So many!!!!!! A few favorite of mines that any student can read and get 95% out of them: George Akerlof (1970), "The Market for 'Lemons': Quality Uncertainty and the Market Mechanism," QJE Michael Spence (1973), "Job Market Signaling," QJE Gary Becker (1973), "A Theory of Marriage: Part I," JPE Robert Lucas (1978), "On the Size Distribution of Business Firms," Bell Journal of Economics Sherwin Rosen (1981), "The Economics of Superstars," AER Douglas Diamond and Philip Dybvig (1983), "Bank Runs, Deposit Insurance, and Liquidity," JPE Thomas Schelling (1971), "Dynamic Models of Segregation," Journal of Mathematical Sociology Martin Weitzman (1974), "Prices vs. Quantities," Review of Economic Studies William Baumol (1967), "Macroeconomics of Unbalanced Growth: The Anatomy of Urban Crisis," AER Kevin Murphy, Andrei Shleifer and Robert Vishny (1989), "Industrialization and the Big Push," JPE Michael Kremer (1993), "Population Growth and Technological Change: One Million B.C. to 1990," QJE