Digifesto

Tag: transaction cost economics

September 16, 2019

Bridging between transaction cost and traditional economics

Some time ago I was trying to get my head around transaction cost economics (TCE) because of its implications for the digital economy and cybersecurity. (1, 2, 3, 4, 5). I felt like I had a good grasp of the relevant theoretical claim of TCE which is the interaction between asset specificity and the make-or-buy decision. But I didn’t have a good sense of the mechanism that drove that claim.

I worked it out yesterday.

Recall that in the make or buy decision, a firm is determining whether or not to make some product in-house or to buy it from the market. This is a critical decision made by software and data companies, as often these businesses operate by assembling components and data streams into a new kind of service; these services often are the components and data streams used in other firms. And so on.

The most robust claim of TCE is that if the asset (component, service, data stream) is very specific to the application of the firm, then the firm will be more likely to make it. If the asset is more general-purpose, then it buy it as a commodity on the market.

Why is this? TCE does not attempt to describe this phenomenon in a mathematical model, at least as far as I have found. Nevertheless, this can be worked out with a much more general model of the economy.

Assume that for some technical component there are fix costs f and marginal costs $c$. Consider two extreme cases: in case A, the asset is so specific that only one firm will want to buy it. In case B, the asset is very general so there’s many firms that want to purchase it.

In case A, a vendor will have costs of f + c and so will only make the good if the buyer can compensate them at least that much. At the point where the buyer is paying for both the fixed and marginal costs of the product, they might as well own it! If there are other discovered downstream uses for the technology, that’s a revenue stream. Meanwhile, since the vendor in this case will have lock-in power over the buyer (because switching will mean paying the fixed cost to ramp up a new vendor), that gives the vendor market power. So, better to make the asset.

In case B, there’s broader market demand. It’s likely that there’s already multiple vendors in place who have made the fixed cost investment. The price to the buying firm is going to be closer to c, the market price that converges over time to the fixed cost, as opposed to c =+ f, which includes the fixed costs. Because there are multiple vendors, lock-in is not such an issue. Hence the good becomes a commodity.

A few notes on the implications of this for the informational economy:

  • Software libraries have high fixed cost and low marginal cost. The tendency of companies to tilt to open source cores with their products built on top is a natural result of the market. The modularity of open source software is in part explained by the ways “asset specificity” is shaped exogenously by the kinds of problems that need to be solved. The more general the problem, the more likely the solution has been made available open source. Note that there is still an important transaction cost at work here, the search cost. There’s just so many software libraries.
  • Data streams can vary a great deal as to whether and how they are asset specific. When data streams are highly customized to the downstream buyer, they are specific; the customization is both costly to the vendor and adding value to the buyer. However, it’s rarely possible to just “make” data: it needs to be sourced from somewhere. When firms buy data, it is normally in a subscription model that takes into account industrial organization issues (such as lock in) within the pricing.
  • Engineering talent, and related labor costs, are interesting in that for a proprietary system, engineering human capital gains tend to be asset specific, while for open technologies engineering skill is a commodity. The structure of the ‘tech business’, which requires mastery of open technology in order to build upon it a proprietary system, is a key dynamic that drives the software engineering practice.

There are a number of subtleties I’m missing in this account. I mentioned search costs in software libraries. There’s similar costs and concerns about the inherent riskiness of a data product: by definition, a data product is resolving some uncertainty with respect to some other goal or values. It must always be a kind of credence good. The engineering labor market is quite complex in no small part because it is exposed to the complexities of its products.

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December 30, 2018

State regulation and/or corporate self-regulation

The dust from the recent debates about whether regulation or industrial self-regulation in the data/tech/AI industry appears to be settling. The smart money is on regulation and self-regulation being complementary for attaining the goal of an industry dominated by responsible actors. This trajectory leads to centralized corporate power that is lead from the top; it is a Hamiltonian not Jeffersonian solution, in Pasquale’s terms.

I am personally not inclined towards this solution. But I have been convinced to see it differently after a conversation today about environmentally sustainable supply chains in food manufacturing. Nestle, for example, has been internally changing its sourcing practices to more sustainable chocolate. It’s able to finance this change from its profits, and when it does change its internal policy, it operates on a scale that’s meaningful. It is able to make this transition in part because non-profits, NGO’s, and farmers cooperatives lay through groundwork for sustainable sourcing external to the company. This lowers the barriers to having Nestle switch over to new sources–they have already been subsidized through philanthropy and international aid investments.

Supply chain decisions, ‘make-or-buy’ decisions, are the heart of transaction cost economics (TCE) and critical to the constitution of institutions in general. What this story about sustainable sourcing tells us is that the configuration of private, public, and civil society institutions is complex, and that there are prospects for agency and change in the reconfiguration of those relationships. This is no different in the ‘tech sector’.

However, this theory of economic and political change is not popular; it does not have broad intellectual or media appeal. Why?

One reason may be because while it is a critical part of social structure, much of the supply chain is in the private sector, and hence is opaque. This is not a matter of transparency or interpretability of algorithms. This is about the fact that private institutions, by virtue of being ‘private’, do not have to report everything that they do and, probably, shouldn’t. But since so much of what is done by the massive private sector is of public import, there’s a danger of the privatization of public functions.

Another reason why this view of political change through the internal policy-making of enormous private corporations is unpopular is because it leaves decision-making up to a very small number of people–the elite managers of those corporations. The real disparity of power involved in private corporate governance means that the popular attitude towards that governance is, more often than not, irrelevant. Even less so that political elites, corporate elites are not accountable to a constituency. They are accountable, I suppose, to their shareholders, which have material interests disconnected from political will.

This disconnected shareholder will is one of the main reasons why I’m skeptical about the idea that large corporations and their internal policies are where we should place our hopes for moral leadership. But perhaps what I’m missing is the appropriate intellectual framework for how this will is shaped and what drives these kinds of corporate decisions. I still think TCE might provide insights that I’ve been missing. But I am on the lookout for other sources.

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December 13, 2018

The secret to social forms has been in institutional economics all along?

A long-standing mystery for me has been about the ontology of social forms (1) (2): under what conditions is it right to call a particular assemblage of people a thing, and why? Most people don’t worry about this; in literatures I’m familiar with it’s easy to take a sociotechnical complex or assemblage, or a company, or whatever, as a basic unit of analysis.

A lot of the trickiness comes from thinking about this as a problem of identifying social structure (Sawyer, 200; Cederman, 2005). This implies that people are in some sense together and obeying shared norms, and raises questions about whether those norms exist in their own heads or not, and so on. So far I haven’t seen a lot that really nails it.

But what if the answer has been lurking in institutional economics all along? The “theory of the firm” is essentially a question of why a particular social form–the firm–exists as opposed to a bunch of disorganized transactions. The answers that have come up are quite good.

Take for example Holmstrom (1982), who argues that in a situation where collective outcomes depend on individual efforts, individuals will be tempted to free-ride. That makes it beneficial to have somebody monitor the activities of the other people and have their utility be tied to the net success of the organization. That person becomes the owner of the company, in a capitalist firm.

What’s nice about this example is that it explains social structure based on an efficiency argument; we would expect organizations shaped like this to be bigger and command more resources than others that are less well organized. And indeed, we have many enormous hierarchical organizations in the wild to observe!

Another theory of the firm is Williamson’s transaction cost economics (TCE) theory, which is largely about the make-or-buy decision. If the transaction between a business and its supplier has “asset specificity”, meaning that the asset being traded is specific to the two parties and their transaction, then any investment from either party will induce a kind of ‘lock-in’ or ‘switching cost’ or, in Williamson’s language, a ‘bilateral dependence’. The more of that dependence, the more a free market relationship between the two parties will expose them to opportunistic hazards. Hence, complex contracts, or in the extreme case outright ownership and internalization, tie the firms together.

I’d argue: bilateral dependence and the complex ‘contracts’ the connect entities are very much the stuff of “social forms”. Cooperation between people is valuable; the relation between people who cooperate is valuable as a consequence; and so both parties are ‘structurated’ (to mangle a Giddens term) individually into maintaining the reality of the relation!

References

Cederman, L.E., 2005. Computational models of social forms: Advancing generative process theory 1. American Journal of Sociology, 110(4), pp.864-893.

Holmstrom, Bengt. “Moral hazard in teams.” The Bell Journal of Economics (1982): 324-340.

Sawyer, R. Keith. “Simulating emergence and downward causation in small groups.” Multi-agent-based simulation. Springer Berlin Heidelberg, 2000. 49-67.

Williamson, Oliver E. “Transaction cost economics.” Handbook of new institutional economics. Springer, Berlin, Heidelberg, 2008. 41-65.

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December 9, 2018

Transaction cost economics and privacy: looking at Hoofnagle and Whittington’s “Free”

As I’ve been reading about transaction cost economics (TCE) and independently scrutinizing the business model of search engines, it stands to reason that I should look to the key paper holding down the connection between TCE and privacy, Hoofnagle and Whittinton’s “Free: Accounting for the Costs of the Internet’s Most Popular Price” (2014).

I want to preface the topic by saying I stand by what I wrote earlier: that at the heart of what’s going on with search engines, you have a trade of attention; it requires imagining the user has have attention-time as a scarce resource. The user has a query and has the option to find material relevant to the query in a variety of ways (like going to a library). Often (!) they will do so in a way that costs them as little attention as possible: they use a search engine, which gives an almost instant and often high-quality response; they are also shown advertisements which consume some small amount of their attention, but less than they would expend searching through other means. Advertisers pay the search engine for this exposure to the user’s attention, which funds the service that is “free”, in dollars (but not in attention) to the users.

Hoofnagle and Whittington make a very different argument about what’s going on with “free” web services, which includes free search engines. They argue that the claim that these web services are “free” is deceptive because the user may incur costs after the transaction on account of potential uses of their personal data. An example:

The freemium business model Anderson refers to is popular among industries online. Among them, online games provide examples of free services with hidden costs. By prefacing play with the disclosure of personal identification, the firms that own and operate games can contact and monitor each person in ways that are difficult for the consumer to realize or foresee. This is the case for many games, including Disney’s “Club Penguin,” an entertainment website for children. After providing personal information to the firm, consumers of Club Penguin receive limited exposure to basic game features and can see numerous opportunities to enrich their play with additional features. In order to enrich the free service, consumers must buy all sort of enhancements, such as an upgraded igloo or pets for one’s penguin. Disney, like others in the industry, places financial value on the number of consumers it identifies, the personal information they provide, and the extent to which Disney can track consumer activity in order to modify the game and thus increase the rate of conversion of consumers from free players to paying customers.

There are a number of claims here. Let’s enumerate them:

  1. This is an example of a ‘free’ service with hidden costs to users.
  2. The consumer doesn’t know what the game company will do with their personal information.
  3. In fact, the game will use the personal information to personalize pitches for in-game purchases that ‘enrich’ the free service.
  4. The goal of the company is to convert free players to paying customers.

Working backwards, claim (4) is totally true. The company wants to make money by getting their customers to pay, and they will use personal information to make paying attractive to the customers (3). But this does not mean that the customer is always unwitting. Maybe children don’t understand the business model when they begin playing Penguin Club, but especially today parents certainly do. App Stores, for example, now label apps when they have “in-app purchases”, which is a pretty strong signal. Perhaps this is a recent change due to some saber rattling by the FTC, which to be fair would be attributable as a triumph to the authors if this article had influence on getting that to happen. On the other hand, this is a very simple form of customer notice.

I am not totally confident that even if (2), (3), and (4) are true, that that entails (1), that there are “hidden costs” to free services. Elsewhere, Hoofnagle and Whittington raise more convincing examples of “costs” to release of PII, including being denied a job and resolving identity theft. But being convincingly sold an upgraded igloo for your digital penguin seems so trivial. Even if it’s personalized, how could it be a hidden cost? It’s a separate transaction, no? Do you or do you not buy the igloo?

Parsing this through requires, perhaps, a deeper look at TCE. According to TCE, agents are boundedly rational (they can’t know everything) and opportunistic (they will make an advantageous decision in the moment). Meanwhile, the world is complicated. These conditions imply that there’s a lot of uncertainty about future behavior, as agents will act strategically in ways that they can’t themselves predict. Nevertheless, agents engage in contracts with some kinds of obligations in them in the course of a transaction. TCE’s point is that these contracts are always incomplete, meaning that there are always uncertainties left unresolved in contracts that will need to be negotiated in certain contingent cases. All these costs of drafting, negotiating, and safeguarding the agreement are transaction costs.

Take an example of software contracting, which I happen to know about from personal experience. A software vendor gets a contract from a client to do some customization. The client and the vendor negotiated some sort of scope of work ex ante. But always(!), the client doesn’t actually know what they want, and if the vendor delivers on the specification literally the client doesn’t like it. Then begins the ex post negotiation as the client tries to get the vendor to tweak the system into something more usable.

Software contracting often resolves this by getting off the fixed cost contracting model and onto a cost-and-materials contact that allows billing by hours of developer time. Alternatively, the vendor can internalize the costs into the contract by inflating the cost “estimates” to cover for contingencies. In general, this all amounts to having more contract and a stronger relationship between the client and vendor, a “bilateral dependency” which TCE sees as a natural evolution of the incomplete contract under several common conditions, like “asset specificity”, which means that the asset is specialized to a particular transaction (or the two agents involved in it). Another term for this is lock-in, or the presence of high switching costs, though this way of thinking about it reintroduces the idea of a classical market for essentially comparable goods and services that TCE is designed to mitigate against. This explains how technical dependencies of an organization become baked in more or less constitutionally as part of the organization, leading to the robustness of installed base of a computing platform over time.

This ebb and flow of contract negotiation with software vendors was a bit unsettling to me when I first encountered it on the job, but I think it’s safe to say that most people working in the industry accept this as How Things Work. Perhaps it’s the continued influence of orthodox economics that makes this all seem inefficient somehow, and TCE is the right way to conceptualize things that makes better sense of reality.

But back to the Penguins…

Hoofnagle and Whittington make the case that sharing PII with a service that then personalizes its offerings to you creates a kind of bilateral dependence between service and user. They also argue that loss of privacy, due to the many possible uses of this personal information (some nefarious), is a hidden cost that can be thought of as an ex post transaction cost that is a hazard because it has not been factored into the price ex ante. The fact that this data is valuable to the platform/service for paying their production costs, which is not part of the “free” transaction, is an indication that this data is a lot more valuable than consumers think it is.

I am still on the fence about this.

I can’t get over the feeling that successfully selling a user a personalized, upgraded digital igloo is such an absurd example of a “hidden cost” that it belies the whole argument that these services have hidden costs.

Splitting hairs perhaps, it seems reasonable to say that Penguin Club has a free version, which is negotiated as one transaction. Then, conditional on the first transaction, it offers personalized igloos for real dollars. This purchase, if engaged in, would be another, different transaction, not an ex post renegotiation of the original contract with the Disney. This small difference changes the cost of the igloo from a hidden transaction cost into a normal, transparent cost. So it’s no big deal!

Does the use of PII create a bilateral dependence between Disney and the users of Penguin Club? Yes, in a sense. Any application of attention to an information service, learning how to use it and getting it to be part of your life, is in a sense a bilateral dependence with a switching cost. But there are so many other free games to play on the internet that these costs seem hardly hidden. They could just be understood as part of the game. Meanwhile, we are basically unconcerned with Disney’s “dependence” on the consumer data, because Disney can get new users easily (unless the user is a “whale”, who actual pays the company). And “dependence” Disney has on particular users is a hidden cost for Disney, not for the user, and who cares about Disney.

The cases of identity theft or job loss are strange cases that seem to have more to do with freaky data reuse than what’s going on with a particular transaction. Purpose binding notices and restrictions, which are being normed on through generalized GDPR compliance, seem adequate to deal with these cases.

So, I have two conclusions:

(1) Maybe TCE is the right lens for making an economic argument for why purpose binding restrictions are a good idea. They make transactions with platforms less incomplete, avoiding the moral hazard of ex post use of data in ways that incurs asymmetrically unknown effects on users.

(2) This TCE analysis of platforms doesn’t address the explanatorily powerful point that attention is part of the trade. In addition to being concretely what the user is “giving up” to the platform and directly explaining monetization in some circumstances, the fact that attention is “sticky” and creates some amount of asset-specific learning is a feature of the information economy more generally. Maybe it needs a closer look.

References

Hoofnagle, Chris Jay, and Jan Whittington. “Free: accounting for the costs of the internet’s most popular price.” UCLA L. Rev. 61 (2013): 606.

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December 4, 2018

the make or buy decision (TCE) in the software and cybersecurity

The paradigmatic case of transaction cost economics (TCE) is the make-or-buy decision. A firm, F, needs something, C. Do they make it in-house or do they buy it from somewhere else?

If the firm makes it in-house, they will incur some bureaucratic overhead costs in addition to the costs of production. But they will also be able to specialize C for their purposes. They can institute their own internal quality controls. And so on.

If the firm buys it on the open market from some other firm, say, G, they don’t pay the overhead costs. They do lose the benefits of specialization, and the quality controls are only those based on economic competitive pressure on suppliers.

There is an intermediate option, which is a contract between F and G which establishes an ongoing relationship between the two firms. This contract creates a field in which C can be specialized for F, and there can be assurances of quality, while the overhead is distributed efficiently between F and G.

This situation is both extremely common in business practice and not well handled by neoclassical, orthodox economics. It’s the case that TCE is tremendously preoccupied with.

My background and research is in the software industry, which is rife with cases like these.

Developers are constantly faced with a decision to make-or-buy software components. In principle, they can developer any component themselves. In practice, this is rarely cost-effective.

In software, open source software components are a prevalent solution to this problem. This can be thought of as a very strange market where all the prices are zero. The most popular open source libraries are very generic , having little “asset specificity” in TCE terms.

The lack of contract between developers and open source components/communities is sometimes seen as a source of hazard in using open source components. The recent event-stream hack, where an upstream component was injected with malicious code by a developer who had taken over maintaining the package, illustrates the problems of outsourcing technical dependencies without a contract. In this case, the quality problem is manifest as a supply chain cybersecurity problem.

In Williamson’s analysis, these kinds of hazards are what drive firms away from purchasing on spot markets and towards contracting or in-house development. In practice, the role of open source support companies fills the role of being a responsible entity G that firm F can build a relationship with.

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December 2, 2018

Discovering transaction cost economics (TCE)

I’m in the process of discovering transaction cost economics (TCE), the branch of economics devoted to the study of transaction costs, which include bargaining and search costs. Oliver Williamson, who is a professor at UC Berkeley, won the Nobel Prize for his work on TCE in 2009. I’m starting with the Williamson, 2008 article (in the References) which seems like a late-stage overview of what is a large body of work.

Personally, this is yet another time when I’ve discovered that the answers or proper theoretical language for understanding something I am struggling with has simply been Somewhere Else all alone. Delight and frustration are pretty much evening each other out at this point.

Why is TCE so critical (to me)?

  • I think the real story about how the Internet and AI have changed things, which is the topic constantly reiterated in so many policy and HCI studies about platforms, is that they reduced search costs. However, it’s hard to make the case for that without a respectable theorization of search costs and how they matter to the economy. This, I think, what transaction cost economics are about.
  • You may recall I wrote my doctoral dissertation about “data economics” on the presumption (which was, truly, presumptuous) that a proper treatment of the role of data in the economy had not yet been done. This was due mainly to the deficiencies of the discussion of information in neoclassical economic theory. But perhaps I was a fool, because it may be that this missing-link work on information economics has been in transaction cost economics all along! Interestingly, Pat Bajari, who is Chief Economist at Amazon, has done some TCE work, suggesting that like Hal Varian’s economics, this is stuff that actually works in a business context, which is more or less the epistemic standard you want economics to meet. (I would argue that economics should be seen, foremost, as a discipline of social engineering.)
  • A whole other line of research I’ve worked on over the years has been trying to understand the software supply chain, especially with respect to open source software (Benthall 2016; Benthall, 2017). That’s a tricky topic because the idea of “supply” and “chain” in that domain are both highly metaphorical and essentially inaccurate. Yet there are clearly profound questions about the relationships between sociotechnical organizations, their internal and external complexity, and so on to be found there, along with (and this is really what’s exciting about it) ample empirical basis to support arguments about it, just by the nature of it. Well, it turns out that the paradigmatic case for transaction cost economics is vertical integration, or the “make-or-buy” decision wherein a firm decides to (A) purchase it from an open market, (D) produce something in-house, or (C) (and this is the case that transaction cost economics really tries to develop) engage with the supplier in a contract which creates an ongoing and secure relationship between them. Labor contracts are all, for reasons that I may go into later, of this (C) kind.

So, here comes TCE, with its firm roots in organization theory, Hayekian theories of the market, Coase’s and other theories of the firm, and firm emphasis on the supply chain relation between sociotechnical organizations. And I HAVEN’T STUDIED IT. There is even solid work on its relation to privacy done by Whittington and Hoofnagle (2011; 2013). How did I not know about this? Again, if I were not so delighted, I would be livid.

Please expect a long series of posts as I read through the literature on TCE and try to apply it to various cases of interest.

References

Benthall, S. (2017) Assessing Software Supply Chain Risk Using Public Data. IEEE STC 2017 Software Technology Conference.

Benthall, S., Pinney, T., Herz, J., Plummer, K. (2016) An Ecological Approach to Software Supply Chain Risk Management. Proceedings of the 15th Python in Science Conference. p. 136-142. Ed. Sebastian Benthall and Scott Rostrup.

Hoofnagle, Chris Jay, and Jan Whittington. “Free: accounting for the costs of the internet’s most popular price.” UCLA L. Rev. 61 (2013): 606.

Whittington, Jan, and Chris Jay Hoofnagle. “Unpacking Privacy’s Price.” NCL Rev. 90 (2011): 1327.

Williamson, Oliver E. “Transaction cost economics.” Handbook of new institutional economics. Springer, Berlin, Heidelberg, 2008. 41-65.

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