The economic welfare gains from the introduction of generic weight-loss drugs

The Financial Times reported this week (paywalled):

India’s powerful copycat pharmaceutical industry is set to roll out generic weight-loss drugs in the UK within weeks, with one leading producer forecasting a “huge price war” that could widen access to the popular medicines.

Bengaluru-based Biocon is the first company to win UK authorisation to offer a generic version of Novo Nordisk’s Saxenda weight treatment and is ready to launch sales by November.

Saxenda is an older drug of the same GLP-1 drug class as the Danish company’s popular Ozempic diabetes treatment and Wegovy weight-loss medication.

In an interview with the Financial Times, Biocon chief executive Siddharth Mittal declined to comment on his pricing strategy for generic Saxenda, but predicted his company’s sales of the drug would reach £18mn annually in the UK after the expiry of its patent protection there next month. Mittal said he expected Biocon’s generic version of Saxenda to be approved by the EU this year and in the US by 2025.

“When the generics come in there will be a huge price war,” he said. “There is a huge demand for these drugs at the right price.”

To see how the introduction of generic medicines affects the market, consider the diagram of the market for Saxenda below. When the active ingredient in Saxenda is protected by a patent, the market is effectively a natural monopoly. That means that the average cost curve (AC in the diagram) is downward sloping for all levels of output. This is because, as the quantity sold increases, the large up-front cost of developing Saxenda (see here for example) will be spread over more and more sales, lowering the cost on average. If Novo Nordisk (the producer of Saxenda) is maximising its profits, it will operate at the quantity where marginal revenue meets marginal cost, i.e. at QM, which it can obtain by setting a price of PM (this is because at the price PM, consumers will demand the profit-maximising quantity QM). Novo Nordisk makes a profit from Saxenda that is equal to the area PMBKL. [*]

Now consider what happens in this market when the patent expires and generic versions of Saxenda enter the market. We end up with a market that is more competitive, which would operate at the point where supply (MC) meets demand. This is at a price of PC, and the quantity of QC. Notice that the price of Saxenda falls dramatically - this is how the price war that Mittal mentions will play out.

Now consider what happens to the other areas of economic welfare. Before the patent expires, the consumer surplus is equal to the area GBPM. After the patent expires, the consumer surplus increases to the area GEPC. Consumers are made much better off by the patent expiry, because they can buy Saxenda at a much lower price, and they respond by buying much more of it. The producer surplus, which was PMBHPC, becomes zero. [**] The competition between the producers drives this producer surplus down. Total welfare (the sum of consumer and producer surplus) increases from GBHPC to GEPC. So, society is better off after the patent expiry.

Now, you could argue based on this that expiring the patent earlier would be even better, given the economic welfare gain that would result. And while I have some sympathy for that view, governments should be a little cautious here. The large producer surplus from having the patent in place creates an incentive for the big pharmaceutical firms to develop these pharmaceuticals in the first place. So, an appropriate balance between patent protection and incentives for pharmaceutical development needs to be found. Nevertheless, it is clear that once patents expire, there is a large welfare gain to society at that point.

*****

[*] This is different from the producer surplus, which is the area PMBHPC. The difference between producer surplus and profits arises because of the fixed cost - in this case, the cost of development of Saxenda.

[**] If we treat this as continuing to be a natural monopoly after the patent expiry, the market makes a negative profit of -JFEPC (because the price PC is less than the average cost of production ACC). However, you could argue that because the firms producing the generic version didn't face the up-front cost of development, this is no longer a natural monopoly once the patent has expired.

Nobel Prize for Daron Acemoglu, Simon Johnson, and James Robinson

Many economists had been picking this prize for a few years. Daron Acemoglu (MIT), Simon Johnson (MIT), and James Robinson (University of Chicago) were awarded the 2024 Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel (aka the Nobel Prize in Economics) yesterday, "for studies of how institutions are formed and affect prosperity".

While many, if not most, Nobel Prize winners in economics are largely unknown outside the discipline, having toiled away publishing papers only read by other economists, this award recognises three academics whose key contributions on which the award are based are contained within several best-selling books, including Why Nations Fail (by Acemoglu and Robinson, which I reviewed here), The Narrow Corridor (by Acemoglu and Robinson, which I reviewed here), and Power and Progress (by Acemoglu and Johnson, which I haven't read yet, but it is close to the top of my pile of books to-be-read). The Nobel Prize Committee's citation noted:

The laureates have shown that one explanation for differences in countries’ prosperity is the societal institutions that were introduced during colonisation. Inclusive institutions were often introduced in countries that were poor when they were colonised, over time resulting in a generally prosperous population. This is an important reason for why former colonies that were once rich are now poor, and vice versa.

Some countries become trapped in a situation with extractive institutions and low economic growth. The introduction of inclusive institutions would create long-term benefits for everyone, but extractive institutions provide short-term gains for the people in power. As long as the political system guarantees they will remain in control, no one will trust their promises of future economic reforms. According to the laureates, this is why no improvement occurs.

However, this inability to make credible promises of positive change can also explain why democratisation sometimes occurs. When there is a threat of revolution, the people in power face a dilemma. They would prefer to remain in power and try to placate the masses by promising economic reforms, but the population are unlikely to believe that they will not return to the old system as soon as the situation settles down. In the end, the only option may be to transfer power and establish democracy.

Notice that citation really is the theme across their three books. Of course, there is an academic base that those books are founded on as well, and which no doubt contributed to their prize. Alex Tabarrok at Marginal Revolution gives a good summary of their work, as does John Hawkins at The Conversation. As those two posts make clear, all three prize winners have made contributions beyond those in the citation.

However, Acemoglu is clearly a standout performer, and has been for a long time. He is one of the most cited economists in the world, with contributions across a number of areas. Tabarrok points to joint work between Acemoglu and pascual Restrepo on technological change. I have on my list of interesting ideas to go back and look at a different paper by Acemoglu and Restrepo, on the impacts of population ageing on economic growth, but using different measures of population ageing (as in my article here). I also pointed to Acemoglu's views on the impact of generative AI on inequality yesterday, which he has also researched recently.

In my ECONS102 class, I've been including more of a focus on economic and political institutions over time, and this prize may prompt me to even include a bit more (or at least, to point more explicitly to the work of Acemoglu, Johnson, and Robinson). And hopefully it will encourage even more people to read their books.

Generative AI and expectations about inequality

In the last week of my ECONS102 class, we covered inequality. In discussing the structural causes of inequality, I go through a whole bunch of causes grouped together under a heading of 'structural changes in the labour market', one of which is skills-biased technological change. The basic idea is that over time, some technology (like computers) has made people in professional, managerial, technical, and creative occupations more productive or allowed them to reach larger audiences at low cost. However, other technology (like robots) has tended to replace routine jobs in sectors like manufacturing. This has increased the premium for skilled labour, increasing the ‘gap’ between skilled and unskilled wages.

In discussing this idea of skills-biased technological change this year, I mused about the potential impact of generative artificial intelligence, and whether skills-biased technological change was about to reverse, leading to job losses in professional, managerial, technical, and creative occupations, while jobs in activities that might broadly be grouped into manual and dexterous labour (like plumbers, electricians, or baristas) would remain. A change like that would likely reduce inequality (but not necessarily in a good way!).

The truth is, I don't think that economists have a good handle on what the impacts of generative AI will be on the labour market. On the one hand, you have some economists like Stanford's Nick Bloom, claiming that a lot of jobs (in particular tasks or occupations or sectors) are at risk. The loss of low-productivity, low-wage jobs that Bloom considers at risk, like call centre workers, will likely increase inequality further. On the other hand, you have other economists like MIT's Daron Acemoglu, claiming that the impact of generative AI on inequality will be small.

Given that economists can't agree on this, it is interesting to know what the general public thinks. That's the question that this post on Liberty Street Economics by Natalia Emanuel and Emma Harrington addresses. Using data from the February 2024 Survey of Consumer Expectations, they report that:

In general, a substantial share of respondents did not anticipate that genAI tools would affect wages: 47 percent expected no wage changes. These beliefs did not differ significantly based on prior exposure to genAI tools.

However, respondents believed that genAI tools would reduce the number of jobs available. Forty-three percent of survey respondents overall thought that the tools would diminish jobs. This expectation was slightly more pronounced among those who had used genAI tools, a statistically significant difference.

And specifically in terms of inequality:

We find that those who have used genAI tools tend to be more pessimistic about future inequality. Specifically, we asked people whether they thought there would be more, less, or about the same amount of inequality as there is today for the next generation... while 33 percent of those who have not used genAI tools think there will be more inequality in the next generation, 53 percent of those who have used genAI tools think there will be more inequality. This gap persists and is statistically significant, even after controlling for other observable traits. 

So, a large minority of the general public seems to be concerned about generative AI's impact on inequality, and that concern is greater among those with experience (where a small majority believe inequality will increase). Now, it could be that those with greater experience are better able to accurately assess the risks to their own (and others') jobs from generative AI. Or maybe people who use generative AI are simply more likely to have read the AI doomers' predictions of an AI apocalypse (or equally, they could be more likely to read the bullish views of AI proponents). The general public may not know that they fear skills-biased technological change, but they may intuitively understand the potential risks. The real question, which we still cannot answer, is whether those risks are real or not.

This week in research #44

Here's what caught my eye in research over the past week:

• Hirschberg and Lye (open access) provide suggested guidelines for economists for writing computer code
• Allen (open access) investigates the causes and the consequences of the emergence of agriculture in the Middle East (and if you're into big questions, those are really big questions)
• Ferguson et al. (with ungated version here) provide a new meta-analysis of 46 studies on the correlation between time spent on social media and adolescent mental health, finding that there is little support for claims of harmful effects