This week in research #144

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

• Tompsett (open access) finds that the opening of new bridges over major rivers increase per capita economic activity

Also new from the Waikato working papers series:

• Luengo et al. investigate the causal impact of AI advice on price discovery in a controlled asset-market experiment, and find that access to AI advice significantly reduces mispricing relative to the baseline, regardless of whether the AI advice was aligned with long-term fundamentals, or myopic and based on current prices

Try this! Pull incentive sizing tool

My ECONS102 class covered intellectual property rights this week. As part of that topic, we discuss how governments might incentivise the development of new intellectual property without necessarily relying on strong intellectual property rights. One of the potential alternatives is pull funding - where the government funds successful research and development efforts once they have been developed.

In class, I focus on particular examples of advance market commitments and rewards or prizes. Advance market commitments involve governments making a commitment to buying the goods and services from intellectual property, after the IP is developed. Rewards or prizes involve the government offering to pay the reward or prize to whoever successfully develops some particular intellectual property.

That discussion leaves an important question unanswered. Pull funding creates an incentive for firms (or individuals) to develop some particular intellectual property. But how effective is that incentive? Or, turning that question around, how big does pull funding have to be to incentivise firms (or individual) to work on solving a particular problem?

The Market Shaping Accelerator team (a collaboration between researchers at Dartmouth College, the University of Chicago, and the Center for Global Development has provided a tool that gives us some idea of the answer to that question. You can find the tool here (and associated blog post here). Choose whether you want to use a prize, an AMC, or an AMC with milestones. Then decide on the number of stages in the development process (as well as how long each stage is, the cost, the probability of success of each stage, and how much cost can be covered from other sources). Then provide a discount rate for firms, and the firms' target probability of success. And then hit calculate!

The tool reports the number of firms that would be incentivised by your pull funding, the overall chance that at least one firm succeeds, and the size of the prize required. The tool also provides a comparison with push funding - where the government pays for research and development up-front, regardless of whether it will be successful or not. And the tool also allows you to compare different scenarios.

There is far more to this tool than I can do justice to with a short blog post. There are a lot of models running behind the scenes in this tool, and a lot of assumptions. Fortunately, the documentation gives you all the detail.

If you are interested in push funding, and how it can provide incentives for firms to develop new ideas, I recommend that you try the tool out for yourself. Enjoy!

The Commerce Commission goes rafting

Back in June, the Commerce Commission ruled on the case of a proposed merger between three commercial rafting operators in Rotorua. As the New Zealand Herald reported (in August):

The Commerce Commission has approved the merger of Rotorua’s three commercial rafting operators, much to the pleasant surprise of those behind the bid.

The ruling, finalised in June, came after months of investigation, during which Rotorua Rafting director Sam Sutton became so resigned to defeat that he and his fellow applicants came close to ditching the proposal.

After two decision extensions amid the commission’s concerns that the merger might lessen competition, Sutton was prepared for bad news.

I briefly covered the economics of antitrust law in my ECONS102 class today. My view still remains that the Commerce Commission's criterion for determining merger applications is deeply flawed. As I noted in this 2021 post, the Commerce Commission exists to enforce the Commerce Act, and section 47 of the Act says prohibits acquiring "assets of a business or shares" if that acquisition would have the effect of "substantially lessening competition".

Now, any merger between competing firms by its very nature removes some direct competition between them. So, the Commerce Commission's decision always hinges on whether a proposed merger meets the threshold of 'substantially' lessening competition. The Commerce Act defines 'substantial' only as "real or of substance", and the case law on this makes it clear that whether competition is substantially lessened is ultimately a matter of degree. So the exercise is inherently imprecise and subjective.

The US Federal Trade Commission (FTC) has a more objective approach, which is to compute the Herfindahl-Hirschman Index (HHI) before and after the proposed merger, and to presume that any merger that increases the HHI by 100 points in an industry that is already classed as 'concentrated' or 'highly concentrated' is substantially lessening competition.[*] The FTC may then choose to contest the proposed merger (in court). That at least provides a much transparent threshold against which mergers can initially be assessed. In my view, a more economically coherent approach would be for antitrust authorities to decide on the basis of economic welfare, as I discussed in this 2021 post.

Interestingly, the Commerce Commission's decision itself illustrates the difficulty of applying the test. Only two of the three Commissioners were satisfied that the merger was unlikely to substantially lessen competition, and all three agreed that it was a "finely balanced decision". Seven months after lodging their application, though, the rafting operators finally have their answer. And now they can get on with their business, safe in the knowledge that they are not 'substantially lessening competition'.

Read more:

• The Commerce Commission, competition and total welfare

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[*] The Herfindahl-Hirschman Index can be calculated by squaring the market share of each firm in the market, and adding up the resulting numbers. An industry with an HHI of under 1000 is classed as 'competitive', an industry with an HHI of between 1000 and 1800 is classed as 'concentrated', and an industry with an HHI of over 1800 is classed as 'highly concentrated'. For example, an industry with just four firms, with market shares of 40 percent, 27 percent, 19 percent, and 14 percent, would have an HHI of 40^2+27^2+19^2+14^2 = 2886, and would be classed as 'highly concentrated'.

Manufacturers' response to 'supercycles' in the market for computer memory

Back in May, David Oks wrote a fascinating Substack article about the economics of dynamic random access memory (DRAM) - the memory that is used in computers, smartphones, and gaming consoles, but also importantly in servers and data centres, such as those used to train generative AI models. I'm not going to focus on the effect of generative AI in this post, but instead on this particular part of Oks's article, which caught my attention:

And that combination—capital-intensive manufacturing plus fungibility—is a punishing combination. Because memory is fungible, the industry is intensely cyclical: the entire history of the DRAM industry is a history of boom-and-bust supercycles. First, strong demand from one sector or another—like Windows PC adoption in the 1990s—drives surging prices and a wave of investment from every player; cumulative overinvestment in an undifferentiated good produces oversupply; and then oversupply leads to collapsing prices.

And because production is so expensive, those down-cycles turn out to be existential: the memory industry is marked by constant wreckage. Intel dominated the memory game in the early 1970s but left in the 1980s, opting to focus on processors. Texas Instruments and IBM, also once major players, left in the 1990s. Germany’s Qimonda collapsed in 2009; Japan’s Elpida, once the world’s third-largest DRAM manufacturer, declared bankruptcy in 2012.

In my ECONS101 class, we teach a model of dynamic supply and demand that can be used to explain the boom-and-bust 'supercycles' that Oks describes. Consider the market for memory, and assume that it is perfectly competitive - most importantly, there are no barriers to entry into the market or barriers to exit from the market.[*] The market for memory is shown in the diagram on the left below. The diagram on the right will track changes in memory manufacturers' profits over time. Initially (at Time 0) the market is at equilibrium (where demand D0 meets supply S0) with price P0, and memory manufacturers are making profits π0. Now say there is a permanent increase in demand at Time 1, to D1. This increase in demand may be because of Windows PC adoption, or some other positive demand shock. Prices increase to P1, and memory manufacturers' profits also increase (to π1). There are no barriers to entry (this is a perfectly competitive market), so the higher profits encourage new manufacturers to enter this market (or more realistically, they encourage the existing manufacturers to increase capacity). However, new manufacturing capacity takes time to bring online, and firms make their investment decisions independently. By the time all of that new capacity becomes available, supply may have overshot the level required to simply meet the higher demand. Supply increases to S2 (more producers) at Time 2. Price falls to P2, and memory manufacturers' profits also fall (to π2).

Next, at Time 2 profits are low and some memory manufacturers will choose to exit the market (no barriers to exit because this is a perfectly competitive market), or more realistically it encourages the manufacturers to reduce their capacity. This helps explain the pattern that Oks describes, with Intel, Texas Instruments, IBM, and others exiting the market. Supply will decrease to S3 (fewer producers) at Time 3. Price will increase to P3, and memory manufacturers' profits will increase to π3. So, these 'supercycles' arise as memory manufacturers enter and exit the market in response to an initial increase in demand.

Now, memory manufacturers are not stupid. The manufacturers that remained after previous busts realised that they needed to change their approach in order to avoid these problems. Oks notes that:

And decades of collapse and consolidation left only a few players standing. In the 1990s, there were perhaps 20 meaningful producers of DRAM around the world; today there are three that account for more than 90 percent of global production. South Korea has two, SK Hynix and Samsung; and the United States has one, Micron.

And these memory makers have learned a very particular lesson from the unforgiving history of their industry: always leave demand unmet.

So, rather than rapidly increasing production in response to higher demand, the memory manufacturers have instead become much more cautious about adding capacity, deliberately allowing some demand to remain unmet. That reduces the risk that increasing supply causes a decline in prices and profits. However, the downside is, as Oks notes, that we now have a global shortage of memory as current production levels (and manufacturing capacity) are unable to keep up. That may open opportunities for new manufacturers to enter the market, even if they are less efficient (higher cost) than the incumbents. And therein lies the problem - by deliberately restricting supply tight, the incumbent manufacturers keep prices and profits high and that may eventually set off the next supercycle.

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[*] The market for computer memory isn't actually perfectly competitive, as there are likely to be large economies of scale in memory manufacturing. That means that a small firm entering the market would be at a large cost disadvantage to the large incumbent firms, and so small firms would be deterred from entering the market. However, there is another way of looking at this situation. Instead of considering new firms entering and exiting this market, think about the incumbent firms adding and subtracting additional manufacturing capacity. This has the same effect of increasing and decreasing supply, and leads to the same dynamic pattern in prices and profits.