| Reading: Finegan, J., “Pipe Dreams” Inc.com Magazine, August 1994 |
| Instructor’s resource: MBM Dimensions |
Further activity:
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Additional resources:
| Learning Objectives: Understand and apply Market-Based Management |
| Case: Weston, Hilary A., 2000, “Automation Consulting Services”, Harvard Business School Case No. 9-190-053 |
The following discussion questions can be used:
Instructor’s resource:
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| Learning Objectives: Understand organisational control mechanisms.
Focus on diversity: Hilary A. Weston was one of the co-authors of the ACS case. |
| Case: Coles, Peter, Lakhani, Karim and McAfee, Andrew, “Prediction Markets at Google” Harvard Business School Case No. 9-607-088, August 20, 2007
Case preparation: “Prediction Markets”, February 2016 |
Textbook Reading: Chapter 4 (Section 4.5; pp. 127-134)
I am Facebook friends with someone who used to work at Google – here’s a photo of one of the T-shirts:
The Google case was published in 2007 and was accompanied by a lot of interest in prediction markets. In 2021 they launched a new internal prediction market because of two main reasons:
I am an academic not an entrepreneur, but if there’s one area that I think is ripe for a successful venture it’s creating the go to prediction market. By the early 2000s we had established that prediction markets were an effective tool for corporate management, and we also learnt how useful they could be for a broad range of policy issues. It’s a scandal that governments – and the US in particular – have been so opposed to their use. (The reason is that they’re treated either as gambling firms or futures traders which are two of the most targeted and heavily regulated and industries). According to Scott Alexander:
There ought to be a billion dollar prediction market, maybe a ten billion dollar one. Smart VCs clearly believe something like this, or Kalshi wouldn’t have gotten $30 million+ in investment. Sometimes people who incorrectly believe I know things about prediction markets ask me if know the missing secret sauce. I don’t think there’s any secret. A prediction market will strike it big when it gets three things right at the same time:
It’s a dream of mine that I may have students who manage to put those things together, solve the regulatory issues, and launch a killer app. So far the closest is probably Polymarket but also see Kalshi and Prediki. Here is a website that aggregates prediction market data:
That said, Michael Story is a superforecaster and has made some important criticisms of prediction markets. See here. In his thoughts on the 2024 US Presidential election, Martin Sandbu argues that:
“A nearly 50-50 “prediction” says nothing at all — or nothing more than “we don’t know anything” about who will win in language pretending to say the opposite.”
The following seems to be a really important point:
“For something to count as a prediction, it has to be falsifiable, and probability distributions can’t be falsified by a single event.”
Perhaps the best attempt to explain the failure of predictions markets to gain traction is here:
They define prediction markets as “contracts that trade on the outcome of future events” and split traders into three types:
They argue that “most things we might want to know about the future aren’t much fun to bet on”, and this results in a lack of demand: “without savers or gamblers to add volume to the market, the market cannot attract enough sharps to create the liquidity to drive prices toward accuracy.” I am not so pessimistic about the potential for prediction markets, but recognise that in order to work they must:
Here are a couple of op-eds on the benefits of insider trading:
Here is a New York Post article explaining how Nancy Pelosi (and her husband) have benefitted from trading off the stocks of companies that she regulates, and why she is resisting efforts to stop Congressional lawmakers from being able to continue to do so. You can track her trades here. Here is a funny halloween costume.
To read more about the “Policy Analysis Market” (PAM) which was designed by Robin Hanson as a tool for the US Department of Defense, but got cancelled in July 29th 2003 having been described as a “terrorism futures market” by the Washington Post, see:
The Climate Risk and Uncertainty Collective Intelligence Aggregation Laboratory (CRUCIAL) uses prediction markets to learn more about future climate related challenges. See:
Or this video:
Finally, for more about the management failure that led to the Challenger disaster, see:
“Why There Aren’t So Many Hotel Fires Anymore” Stuff You Should Know.
Points to consider:
| Learning Objectives: Understand how to operate a prediction market. |
| Case: Wessen, R.R. and Porter, D., “The Cassini Resource Exchange” Ask Magazine 16, Fall 2007, p. 14-18 |
Textbook Reading: Chapter 4 (Section 4.5; pp. 127-134)
For more on the Cassini mission, see here: https://science.nasa.gov/mission/cassini/
Watch Cassini’s grand finale:
I find it a real shame that for many years I’ve been opening students eyes to the economic benefits of utilising internal pricing between different business units, but almost all attention to “transfer pricing” in the last 10 years or so is in terms of tax avoidance (and therefore something to be discouraged). In terms of useful cases, the most relevant ones from HBR are all pretty old, although Knowledge at Wharton have an interview that covers IBM’s utilisation of transfer pricing.
In terms of metrics, I like this warning from Jeff Bezos:
“Somebody a long time ago invented that metric… [and] they had a reason why they chose that… but that metric is the proxy… And then fast forward 5 years… and a kind of inertia can set in, and you forget the truth behind why you were watching that metric in the first place, and the world shifts a little, and now that proxy isn’t as valuable as it used to be, or it’s missing something, and you have to be on alert for that and know ‘I don’t really care about this metric.. and this metric is only worth putting energy into, and following and improving and scrutinizing only in so much as it actually affects [what I care about]’. [You have to be on guard against] managing metrics that you don’t really understand, you don’t know why they exist, and the world may have shifted out from under them a little and the metrics are no longer as relevant as they were.”
| Learning Objectives: Think creatively about how to use markets within organisations |
| Reading: Spence, M., 1973, “Job Market Signaling”. Quarterly Journal of Economics 87(3):355–374 |
| Lecture handout: Signalling* |
Textbook Reading: Chapter 3 (Section 3.4; pp. 90-96)
Here’s a lecture video providing an example of the model.
Here’s my treatment of signalling and countersignalling:
And here is a great twitter thread on why you should always wear a tie with a formal suit:
https://twitter.com/dieworkwear/status/1776148941278781833
In “What toffs and plebs share“, Ed West uses the signalling vs. counter signalling distinction to argue that institutions such as horse racing or the army demonstrate a unity of peasant culture and aristocracy. He identifies a U-curve of social patterns, with those in the middle trying hard to distinguish themselves from those below, even though this reduces their ability to mix with those at the top.
A good book (that I haven’t read yet) that uncovers how deeply social status affects human action, see:
Recommended audio:
Recommended video:
This debate considers the extent to which higher education is merely signalling:
| Learning Objectives: Understand the returns to education
Focus on diversity: Claudia Goldin is a world leading labour economist, a former president of the American Economic Association, and co-author of a highly influential book on the earnings gap between high skilled and low skilled workers. She is also a pioneer for studying the role of women in the economy and won the Nobel Prize in 2023. See here for a video profile. |
| Reading: Akerlof, G.A., 1970, “The Market for ‘Lemons’: Quality Uncertainty and the Market Mechanism“. Quarterly Journal of Economics 84(3):488–500 (£) |
Textbook Reading: Chapter 3 (Section 3.4; pp. 90-96)
Instructor resource:
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Here’s a good video explaining the lemons problem:
Here is an excellent 3 minute video with advice on buying a used car:
| Learning Objectives: Think critically about the role of asymmetric information on market performance
Cutting edge theory: Product heterogeneity and customisation Focus on diversity: Amy Finkelstein, of MIT, was featured by The Economists 2008 list of emerging economists for her work on asymmetric information in health insurance. She won the John Bates Clark medal in 2012. Spotlight on sustainability: Importance of long term reputational effects of short term strategic choices |
| Lecture handout: Capital theory* |
Textbook Reading: Chapter 6 (pp.165-197)
There is still a website containing the “Millennium Dome Collection”, but this Guardian article provides a thorough retrospective. Here is a lovely list of repurposed American gas stations.
Here is the video of the Sinclair C5 Infomercial:
For more on business plan ecology, see
For a book length treatment of the concept of intangible capital see:
The lesson for economic policy in a world of intangibles is to invest in “knowledge infrastructure”, i.e.
For a nice attempt to avoid treating intangibles as a residual, or less clear category and a meaningful attempt to conceptualise and study them see:
They argue that intangibles require a storage medium, where “The medium can be a piece of physical capital, like a computer (for software), or a document (for a patent or a design), or a person (for a method or an innovation).” This need for a storage medium implies two things:
They argue that, “the extent to which these properties generate a valuable intangible asset— which motivates investment—depends on the properties of the storage technology, and the resulting non-rivalry and excludability, and the institutions that enforce property rights.”
Some people, such as Mariana Mazzacuto, argue that states should be bolder about their role in technological innovation, and that ‘directed planning’ can improve on market outcomes. Here key work is:
Mark Pennington has provided a good critique of this view, however. For example:
In conclusion, “the Mazzucato case for state-based experimentation… is the suggestion that if governments commit to spending enough public money on their favoured projects it would be remarkable if none of this expenditure did any good. Yet, this position hardly amounts to an endorsement of the transformational potential of the state.”
When talking about macroeconomics I think it’s important to distinguish between the overall economy and the circumstances of an individual firm. We can’t always assume that macro conditions are felt the same by each company within it. I explain more in this video:
This article from the New York Times has a great visualisation of how unemployment is measured.
The most striking fact about labour markets over recent years is the decline in labour force participation across the developed world:
By contrast, labour force participation of women has increased:
Martin Wolf believes this is due to the following main factors:
But notice how, in the US, the prime-age female participation rate has in fact fallen from 2000 to 2019. These images are from: Wolf, M., 2023, The crisis of democratic capitalism, Allen Lane, p. 96.
| Learning Objectives: To understand what capital goods are
Spotlight on sustainability: Look at instances where resources have been reconfigured for alternate uses |
| Case: Hild, M., Dwidevy, A., and Raj, A., 2004, “The Biggest Auction Ever: 3G Licensing in Western Europe”, Darden Business Publishing
Discussion question: What are the alternatives to auctions? |
Textbook Reading: Chapter 3 (Intro and Section 3.3; pp. 65-67 and pp.83-89) and Chapter 12 (Section 12.4; pp. 434-437
In this lecture video Tim Roughgarden “provides a detailed case study of the 2016-2017 Federal Communications Commission incentive auction for repurposing wireless spectrum”. It demonstrates how economics, computer science and business can coincide to solve complete real world problems. For a short overview of the success of spectrum auctions, see here:
| Instructor resource: The Biggest Auction Ever: What Happened Next?, February 2019 + |
You can test you knowledge of this session with this quiz.
This video introduces two key concepts: the Coase theorem, and the transitional gains trap.
In the past I have used an assignment where I asked students to link together the concepts from the video with the 3G license auction. Here is a great example of their work:
Extra activity: The Dutch flower auction
| Learning Objectives: To consider how auctions compare to other allocation mechanisms. To understand different types of auction and apply them to real examples.
Cutting edge theory: Auctions are used in e-commerce Focus on diversity: An expert on applied auction formats, Susan Athey was the first female winner of the John Bates Clark medal. She has been an advisor to Microsoft and you can follow her on Twitter here. Spotlight on sustainability: How governments can use beauty contests to mitigate the environmental impact of infrastructure spending |
| Group activity: Cournot and Bertrand Games, December 2018
The activity is based on Beckman, S. R., 2003, “Cournot and Bertrand games” Journal of Economic Education, Vol.34, No.1, pp.27-35 |
Textbook Reading: Chapter 5 (Section 5.2; pp. 139-145)
Here is a good example of (potential) tacit collusion
In this Lex Fridman interview with FBI hostage negotiator Chris Voss, Voss calls the word “fair” the f bomb. In his experience,
Nobody uses the word fair when they have got criteria to back them up
Here’s Bart Wilson on the meaning of the word “fair”:
| Learning Objectives: Gain experience of iterated prisoner’s dilemmas |
| Reading: “I’ve got debts, please buy my kidneys” The Times September 27th 2009
Discussion question: What are some different ways in which we could allocate kidneys? |
In April 2021 a New Jersey man sued the federal government for the right to sell his own kidneys:
“If the opportunity existed so that I could help out someone in need while helping myself, I might do it,” Bellocchio said.
Bellocchio argues that kidney transplants are low-risk procedures, and notes that you can donate an organ — even though you can’t sell one.
“Altruistic donors are lauded for their selflessness. Their vital role in saving lives is undeniable,” the court papers say.
“However, demand outstrips supply, and there is no valid constitutional or public policy rationale why one should not be able to receive a profit from such a transaction.”
Further reading: Postrel, V., “Here’s Looking at You, Kidney” Texas Monthly, June 2006
The issue of repugnance rests on the claim that the moral status of an activity shouldn’t hinge on whether money changes hands. If something is morally permissible to exchange for free, then people should be allowed to trade. Another way of thinking about this is that the reason slavery was wrong was because of the slavery, not the profits. If someone “donated” a slave, that wouldn’t be ok.
Common rejoinders to markets include things like:
Consider the case of sulphur dioxide emissions (via McMillan, J., (2002) Reinventing the Bazaar, W.W. Norton & Co. (p.182-187) link), and notice how for many environmental activists the moral objections to trading rights to pollute seemingly outweighed the dramatic progress on reducing harmful pollution. This implies that switching people’s mindset to tolerate market mechanisms could be an incredibly powerful tool to improve the world around us.
The Story of Vaccine CA is a really good example of an urgent allocation problem that cannot be solved by markets or by central planning. It’s an ethnographic and anecdotal account of a 200 day period where tech volunteers got together to alert American’s on where covid shots were available.
Listen:
| Learning Objectives: Understand the scope and ethical boundaries of markets
Focus on diversity: Virginia Postrel’s decision to donate a kidney, and write about it, provides a personal and inspirational view of the topic. |
