Tag Archives: Allocative efficiency

The Impotence of AI for the Socialist Calculation Debate

05 Monday Jun 2023

Posted by in Artificial Intelligence, Central Planning, Markets

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Recent advances in artificial intelligence (AI) are giving hope to advocates of central economic planning. Perhaps, they think, the so-called “knowledge problem” (KP) can be overcome, making society’s reliance on decentralized market forces “unnecessary”. The KP is the barrier faced by planners in collecting and using information to direct resources to their most valued uses. KP is at the heart of the so-called “socialist calculation debate”, but it applies also to the failures of right-wing industrial policies and protectionism.

Apart from raw political motives, run-of-the-mill government incompetence, and poor incentives, the KP is an insurmountable obstacle to successful state planning, as emphasized by Friedrich Hayek and many others. In contrast, market forces are capable of spontaneously harnessing all sources of information on preferences, incentives, resources, as well as existing and emergent technologies in allocating resources efficiently. In addition, the positive sum nature of mutually beneficial exchange makes the market by far the greatest force for voluntary social cooperation known to mankind.

Nevertheless, the hope kindled by AI is that planners would be on an equal footing with markets and allow them to intervene in ways that would be “optimal” for society. This technocratic dream has been astir for years along with advances in computer technology and machine learning. I guess it’s nice that at least a few students of central planning understood the dilemma all along, but as explained below, their hopes for AI are terribly misplaced. AI will never allow planners to allocate resources in ways that exceed or even approximate the efficiency of the market mechanism’s “invisible hand”.

Michael Munger recently described the basic misunderstanding about the information or “data” that markets use to solve the KP. Markets do not rely on a given set of prices, quantities, and production relationships. They do not take any of those as givens with respect to the evolution of transactions, consumption, production, investment, or search activity. Instead, markets generate this data based on unobservable and co-evolving factors such as the shape of preferences across goods, services, and time; perceptions of risk and its cost; the full breadth of technologies; shifting resource availabilities; expectations; locations; perceived transaction costs; and entrepreneurial energy. Most of these factors are “tacit knowledge” that no central database will ever contain.

At each moment, dispersed forces are applied by individual actions in the marketplace. The market essentially solves for the optimal set of transactions subject to all of those factors. These continuously derived solutions are embodied in data on prices, quantities, and production relationships. Opportunity costs and incentives are both an outcome of market processes as well as driving forces, so that they shape the transactional footprint. And then those trades are complete. Attempts to impose the same set of data upon new transactions in some repeated fashion, freezing the observable components of incentives and other requirements, would prevent the market from responding to changing conditions.

Thus, the KP facing planners isn’t really about “calculating” anything. Rather, it’s the impossibility of matching or replicating the market’s capacity to generate these data and solutions. There will never be an AI with sufficient power to match the efficiency of the market mechanism because it’s not a matter of mere “calculation”. The necessary inputs are never fully unobservable and, in any case, are unknown until transactions actually take place such that prices and quantities can be recorded.

In my 2020 post “Central Planning With AI Will Still Suck”, I reviewed a paper by Jesús Fernández-Villaverde (JFV), who was skeptical of AI’s powers to achieve better outcomes via planning than under market forces. His critique of the “planner position” anticipated the distinction highlighted by Munger between “market data” and the market’s continuous generation of transactions and their observable footprints.

JFV emphasized three reasons for the ultimate failure of AI-enabled planning: impossible data requirements; the endogeneity of expectations and behavior; and the knowledge problem. Again, the discovery and collection of “data” is a major obstacle to effective planning. If that were the only difficulty, then planners would have a mere “calculation” problem. This shouldn’t be conflated with the broader KP. That is, observable “data” is a narrow category relative the arrays of unobservables and the simultaneous generation of inputs and outcomes that takes place in markets. And these solutions are found by market processes subject to an array of largely unobservable constraints.

An interesting obstacle to AI planning cited by JFV is the endogeneity of expectations. It too can be considered part of the KP. From my 2020 post:

“Policy Change Often Makes the Past Irrelevant: Planning algorithms are subject to the so-called Lucas Critique, a well known principle in macroeconomics named after Nobel Prize winner Robert Lucas. The idea is that policy decisions based on observed behavior will change expectations, prompting responses that differ from the earlier observations under the former policy regime. … If [machine learning] is used to “plan” certain outcomes desired by some authority, based on past relationships and transactions, the Lucas Critique implies that things are unlikely to go as planned.”

Again, note that central planning and attempts at “calculation” are not solely in the province of socialist governance. They are also required by protectionist or industrial policies supported at times by either end of the political spectrum. Don Boudreaux offers this wisdom on the point:

“People on the political right typically assume that support for socialist interventions comes uniquely from people on the political left, but this assumption is mistaken. While conservative interventionists don’t call themselves “socialists,” many of their proposed interventions – for example, industrial policy – are indeed socialist interventions. These interventions are socialist because, in their attempts to improve the overall performance of the economy, proponents of these interventions advocate that market-directed allocations of resources be replaced with allocations carried out by government diktat.”

The hope that non-market planning can be made highly efficient via AI is a fantasy. In addition to substituting the arbitrary preferences of planners and politicians for those of private agents, the multiplicity of forces bearing on individual decisions will always be inaccessible to AIs. Many of these factors are deeply embedded within individual minds, and often in varying ways. That is why the knowledge problem emphasized by Hayek is much deeper than any sort of “calculation problem” fit for exploitation via computer power.

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Note: The image at the top of this post is attributed by Bing to the CATO Institute-sponsored website Libertarianism.org and an article that appeared there in 2013, though that piece, by Jason Kuznicki, no longer seems to feature that image.

Sharing Apps and Market Benefits

24 Saturday Jun 2017

Posted by in Markets, Transaction Costs

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Transaction costs prevent lots of trades. So many that we often aren’t aware of their potentiality. Michael Munger asserts that transaction costs are so prohibitive that we tend to accumulate a lot of stuff that we could otherwise do without. That’s what he says in “Why we can’t break up with our stuff — yet“.

Transaction costs of all kinds have fallen dramatically over time. One of the greatest innovations in “transactions technology” was the avoidance of barter with the broad acceptance of a medium of exchange (money). Without a medium of exchange, trade requires a “double coincidence of wants”, which often makes the effort to engage in trade impractical. No less important was the establishment of secure property rights such that the integrity of a contract or transaction was protected, whether enforced by possible repercussions from other traders or through the police power of the state. Secure property rights and the use of money facilitated the development of markets and pricing that conveyed better information about scarcity. Other historical developments that reduced transaction costs include better transportation, communication, packaging, and more efficient distribution and supply chain management. In a variety of complex transactions, such as real estate, standardization of contracts has reduced transaction costs.

Those costs have been reduced dramatically of late by new communication and computing technologies. The size of these reductions is difficult to quantify in such prominent examples as Uber ride-sharing and Airbnb home-sharing, but there is no question that the new supplies of rides and accommodations would not have materialized absent the enabling on-line “apps”. The ease, low-cost and minimal risk of these transactions is incredible.

Suppose that hotels in Soho average $400 per night for a suite and that Airbnb rentals in Soho average $300. It’s fair to say that the average Airbnb host in Soho, without Airbnb, faced transaction costs in arranging for qualified occupants of at least $100 plus Airbnb’s fees. Probably much more. Now, it’s true that the hotel suites and the Airbnb rentals are fundamentally different “products”, but they are alternatives for meeting a particular need.

Similar reductions in transaction costs are occurring across a wide variety of sectors besides transportation and vacation rentals: trading in new and used goods, handymen, concierge services, snow plowing, home-sitting, food delivery, and hook-ups are but a few examples.

Munger’s twist on this story is that dramatically lower transaction costs will mean we’ll all need to own much less “stuff” on average, because we can “share”, or at least buy what we need at minimal transaction cost. Or, what we have will be used more intensively because we can share it profitably.

Munger mentions the high cost of owning an auto that he uses for about 5 out of 168 total hours in a week. The costs include dedicated “storage” space, both at home and at work, and sometimes the extra cost of “storing” it in airport parking. He could certainly afford to arrange alternative forms of transportation. Is owning the auto worthwhile because the transaction costs of the alternatives are too high? Well, Munger owns a nice car and he probably likes to drive it, so there is more to it than transaction costs. Still, if we mention the “convenience” of having a car at one’s disposal, that is really an expression of transaction costs avoided via ownership.

If the cost of arranging an acceptable and ready alternative is minimal, why own a car? This decision is very real in certain congested locales with costly real estate (e.g., parking New York City). In short, Munger believes even fewer individuals will bother to own personal autos, or that those cars will be less idle (rented to users), as technology reduces transaction costs:

“Why do I pay to store my car rather than let other people use it and collect rent? Transaction costs. …But we are living in the beginning of a pivotal era that will transform our relationship to ‘stuff’ (we’ll need less of it) and to each other (we’ll share more). For all of human history until about 1995, the desire to reduce transaction costs was tied to the desire to sell a particular product. Now, entrepreneurs are combining three things — mobile platforms, software apps, and internet connections — to sell reductions in transaction costs with no product attached. And that combination will change everything.“

Will that also mean fewer personally-owned kitchen appliances? Home furnishings? Clothing? Power tools? Stereo components? Probably not. Even if it’s easy to find a willing renter for my power tools or stereo components from time-to-time, I might not want to bother with the required exchanges (at pick-up and return). I use power tools from time-to-time, but I won’t want to shlep back and forth to rent them from someone when I could own them myself at relatively low cost. Perhaps I’ll rent a tiller or a power washer, but not a power drill. Maybe I could hire a gopher on the Air-gopher app to get the tools I need and return them when I’m done, but that adds back to my transaction costs. So there are certain limits to how far this can go in reducing our “stuff”.

Nevertheless, there is no question that there will be many new trades and competitive opportunities to exploit as transaction costs fall, and that implies more choice, lower prices, and less waste in the larger allocative sense. Those, I believe, are the major benefits of sharing technologies. For example, if you enjoy cooking but are the sole member of your household, imagine an app that allows you to sell your extra preparations to other individuals, or to give them away at a minimal transaction cost. Or, if you are able to perform odd jobs but prefer to take them at your convenience, you will likely be able to bid for projects of your choice. If you have a talent for teaching guitar, you could solicit business and even provide the lessons remotely through an on-line app. The major impediment to the development of such market innovations is potential interference by government or other entrenched interests who wish to prevent competition. Licensing laws and various forms of regulation and taxes could easily smother or eliminate the benefits of sharing technologies, and that would be a shame.

I’ll close with a digression on Munger’s hypothesis: why do I own or keep a lot of “stuff? It’s not all about transaction costs. Most people harbor nostalgic feelings for their “stuff”. I hate parting with my old shirts, old drivers licenses, theater programs, and ticket stubs. Most of those things have approximately zero market value. Some people believe it’s just plain wasteful to pitch something that can be put back into working order, like an old lawnmower. Transaction costs might be to blame, but the failure to junk the mower in the first place may be driven by a depression-era instinct for penny-pinching. The hoarder might simply underestimate the benefits of a new mower, or perhaps they deserve credit for undertaking a restoration project they enjoy.

I find myself hoarding all kinds of things that I think might be useful to me somehow, someday. Particularly things like miscellaneous nuts & bolts, sundry pieces of hardware, wire, old fixtures, pieces of lumber, and my late Dad’s old tools. I’m certain I won’t ever use 95%+ of these items, but it’s reassuring to have the inventory. Then again, every time I need an odd item, I find myself in my basement work room searching through all that stuff. Invariably, I end up on my way to the hardware store to get what I need. So much for minimizing transaction costs. What would it cost me to pitch all of it? An afternoon of painful evaluation… yet that too represents a transaction cost!

Scarcity Scarcity Everywhere, And Water Pricing Stinks

09 Monday Mar 2015

Posted by in Markets

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water

What weird irrationality compels water authorities to price “Adam’s Ale” so cheaply, then mercilessly harangue consumers to conserve? The enforcement of sometimes crazy rationing schemes, like watering lawns only on dates ending with the last digit of one’s street address, is but a symptom of this dysfunction. If water is scarce, then it should be priced accordingly. Only then will users voluntarily limit their use to quantities they value at no less than its real resource cost. This might involve changes in agricultural and industrial practices, landscaping and lifestyles. Perhaps there would be fewer lawns and swimming pools installed where water is most scarce. But these actions should be taken voluntarily in response to market incentives.

Water prices are generally regulated and administered, and only rarely established in an actual market. Pricing is usually based on the infrastructure costs of delivering water, as well as the costs of processing required to meet various standards. Again, these prices seldom reflect the real scarcity of water. This is partly due to populist distortions of the idea that water is basic to life, the perception that water is a public good, and the related political appeal of notions like “the water belongs to everyone”. There is also the admirable objective of keeping water affordable for the poor. But unit water prices faced by different users are not uniform: agricultural users sometimes pay as little as 90% less per unit than the generally cheap prices faced by urban consumers. Industrial users are also accorded favorable rates. Needless to say, incentives are way out of line!

When a resource is priced at levels that do not reflect its scarcity, something has to give. The resource will be overused, and overuse of water inflicts severe environmental damage. With water, that can mean draining lakes and killing springs and riverbeds along with the habitat they support, not to mention lower water quality. The waste doesn’t stop there: authorities are sometimes prone to propose costly infrastructure boondoggles to address water needs, such as dams and reservoirs in arid climates from which large quantities of stored water evaporate.

This episode of Econ Talk features a discussion of water mis-pricing and its consequences. (A hat tip on this to the estimable John Crawford). It covers issues in the management of water systems in the U.S. and under-developed countries. It is a very informative discussion, but it neglects one of the most promising methods of pricing, managing and conserving water supplies: marketable permits, or a secondary market in water rights.

Marketable permits involve the assignment of base usage rights using criteria such as estimates of total supplies and the customer’s past usage levels. This base allocation of rights can be dynamic, changing over time with drought conditions or improvements in conservation technology. Usage up to the permitted quantity is priced administratively, as usual, which keeps water affordable to individuals in lower economic strata. Beyond that base level, however, users must acquire additional permits from a willing seller at a mutually agreed-upon price. Trades can take place on a centralized water “exchange” so that prices are observable to all market participants. And trades may take various forms, such as short-term or long-term contracts which may involve prices that differ from “spot”.

How does this help solve the problem of scarcity? The price of water on the secondary market will rise to the point at which users no longer perceive a benefit to marginal flows of water above cost. A higher price encourages voluntary conservation in two ways: it is a direct cash cost of use above one’s base water rights, and it is an opportunity cost of foregoing the sale of permits on water use up to the base assignment. Those best-prepared to conserve can sell excess rights to those least prepared to conserve. The price established by the trade of permits will bear a strong relationship to the actual degree of scarcity.

A hallmark of allocative efficiency is when the marginal value of the resource is equalized across different uses. This condition implies that no gains from trade are left unexploited. But in the case of water, this means that gains in efficiency will be limited unless all users face the same “spot” price. To fully exploit the market’s potential for efficient allocation, large agricultural and industrial users must face a relatively low base price that differs from residential customers only in terms of infrastructural costs. Granted, voluntary trades between users can take place under specialized contracts as long as the terms are publicly available. This allows intensive users to hedge risks to assure that their needs can be met in the future. However, those users will still have to weigh the marginal benefits of certain crops or industrial processes against prices that more accurately reflect scarcity.

This discussion has ignored certain complexities. For example, assigning rights is complicated by the fact that there are almost always multiple sources of water, such as rivers, public and private wells, lakes and runoff capture. There are sometimes different classes of rights-holders on specific sources. Rights on some sources might not be subject to base pricing by a water authority, but water permits could still be sold by these rights-holders on the secondary market, providing an incentive for them to conserve.

There have been political and legal impediments to the development of water markets in the U.S., some of which are discussed here. A recent effort to promote a water market in the western U.S. has arisen in response to drought conditions. Here is a good article from the last link above, a lengthy abstract of a research paper proposing development of a water market in the American West. Of course, there are many academic papers on this topic, but they are mostly gated. I lived in San Antonio in the 1990s when a controversial proposal to build a large reservoir was under debate. This was intended to relieve demands on the Edwards Aquifer, upon which a large area of Texas depended for water. It was voted down by a coalition that included many libertarians and environmentalists. At about that time, I met a natural resource economist from the University of Texas system who proposed the establishment of a water market in south Texas. He had trouble getting local support for the idea; it was politically taboo due to superstitions about an effort to allocate rights (marketable permits) on what is often perceived as a “public good” (despite the exclusivity of its benefits to customers). Later, in 1998, the San Antonio branch of the Federal Reserve Bank of Dallas published this interesting article on the development of a water market in south Texas. To my knowledge, there is still no water market there, but battles over water use and conservation continue.