Tag Archives: Regulation

Fine Grain Futarchy Zoning Via Harberger Taxes

Futarchy” is my proposed system of governance which approves a policy change when conditional prediction markets give a higher expected outcome, conditional on that change. In a city setting, one might be tempted to use a futarchy where the promoted outcome is the total property value of all land in and near that city. After all, if people don’t like being in this city, and are free to move elsewhere, city land won’t be worth much; the more attractive a city is as a place to be, the more its property will be worth.

Yes, we have problems measuring property values. Property is only traded infrequently, sale prices show a marginal not a total value, much land is never offered for sale, sales prices are often obscured by non-cash terms of trade, and regulations and taxes change sales and use. (E.g., rent control.) In addition, we expect at least some trading noise in the prices of any financial market. As a result, simple futarchy isn’t much help for decisions whose expected consequences for outcomes are smaller than its price noise level. And yes, there are other things one might care about beside property values. But given how badly city governance often actually goes, we could do a lot worse than to just consistently choose policies that maximize a reasonable estimate of city property value. The more precise such property estimates can be, the more effective such a futarchy could be.

Zoning (and other policy that limits land use) is an area of city policy that seems especially well suited to a futarchy based on total property value. After all, the main reason people say that we need zoning is because using some land in some ways decreases how much people are willing to pay to use other land. For example, people might not want to live next to a bar, liquor store, or sex toy store, are so are willing to pay less to buy (or rent) next to such a place. So choosing zoning rules to maximize total property value seems especially promising.

I’ve also written before favorably on Harberger taxes (which I once called “stability rents”). In this system, owners of land (and property tied to that land) must set and may continuously adjust a declared property “value”; they are taxed per unit time as a percentage of momentary value, and must always agree to sell their property at their currently declared value. This system has great advantages in inducing property to be held by those who can gain the most value from it, including via greatly lowering the transaction costs of putting together big property packages. With this system, there’s no more need for eminent domain.

I’ve just noticed a big synergy between futarchy for zoning and Harberger taxes. The reason is that such taxes allow the creation of prices which support a much finer grain accounting of the net value of specific zoning changes. Let me explain.

First, Harberger taxes create a continuous declared value on each property all the time, not just a few infrequent sales prices. This creates a lot more useful data. Second, these declared values better approximate the value that people place on property; the higher an actual value, the higher an owner will declare his or her taxable value to be, to avoid the risk of someone taking it away. Third, these declared values are all relative to a standard terms of trade, not the varying terms of actual sales today. Thus the sum total of all declared property values can be a decent estimate of total city property value. Third, it is possible to generalize the Harberger tax system to create zoning-conditional property ownership and prices.

That is, relative to current zoning rules, one can define a particular alternative zoning scenario, wherein the zoning (or other property use limit) policies have changed. Such as changing the zoning of a particular area from residential to commercial on a particular date. Given such a defined scenario, one can create conditional ownership; I own this property if (and when) this zoning change is made, but not otherwise. The usual ownership then becomes conditional on no zoning changes soon.

With conditional ownership, conditional owners can make conditional offers to sell. That is, you can buy my property under this condition if you pay this declared amount of conditional cash. For example, I might offer to make a conditional sale of my property for $100,000, and you might agree to that sale, but this sale only happens if a particular zoning change is approved.

The whole Harberger tax system can be generalized to support such conditional trading and prices. In the simple system, each property has a declared value set by its owner, and anyone can pay that amount at any time to become the new owner. In the generalized system, each property has a declared value for each (combination of) approved alternative zoning scenario. By default, alternative declared values are equal to the ordinary no-zoning-change declared value, but property owners can set them differently if they want, to be either higher or lower. Anyone can make a scenario-conditional purchase of a property from its current (conditional) owner at its scenario-conditional declared value. To buy a property for sure, buy it conditional on all scenarios.

(For concreteness, assume that only one zoning change proposal is allowed per day per city region, that a decision is made on that proposal in that day, and that the proposal for each day is chosen via open public auction a month before. The auction fee can subsidize markets in bets on if this proposal will be approved and markets in tax-revenue asset conditional differences (explained below). A week before the decision day of a proposal, each right in a property is split into two conditional rights, one conditional on this change and one on not-this-change. At that point, owner declared values conditional on this change (or not) become active sale prices. Taxes are paid in conditional cash. Physical control of a property only transfers to conditional owners if and when a zoning scenario is actually approved.)

Having declared values for all properties under all scenarios gives us even more data with which to estimate total city property value, and in particular helps with estimating the difference in total city property value due to a zoning change. To a first approximation, we can just add up all the zoning-change-conditional declared values, and compare that sum to the sum from the no-change declared values. If the former sum is consistently and clearly higher than the latter sum over the proposal’s decision day, that seems a good argument for adopting this zoning proposal. (It seems safer to choose the higher value option with a chance increasing in value difference, and this all works even when other factors influence a decision.) At least if the news that this zoning proposal seems likely be approved gets spread wide and fast enough for owners to express their conditional declared values. (The bet markets on which properties will be effected helps to notify owners.)

Actually, to calculate the net property value difference that a zoning change makes, we need only sum over the properties that actually have a conditional declared value different from its no-change declared value. For small local zoning changes, this might only be a small number of properties within a short distance of the main changes. As a result, this system seems capable of giving useful advice on very small and local zoning changes, in dramatic contrast to a futarchy based on prices estimating total city property values. For example, it might even be able to say if a particular liquor store should be allowed at a particular location, or if the number of required parking spots at a particular shopping mall can be reduced. As promised, this new system offers much finer grain accounting of the net value of specific zoning changes.

Note that in this system as described, losers are not compensated by winners for zoning rule changes, even though we can roughly identify winners and losers. I’ve thought a bit about ways to add a extra process by which winners compensate losers, but haven’t been able to make that work. So the best I can think of is to have the system look at the distribution of wins and losses, and reject proposed changes where there are too many big losers relative to winners. That would force a search for variations which spread out the pain more evenly.

We are close to a workable proposal, but not quite there yet. This is because we face the problem of owners temporarily inflating their declared values conditional on a zoning change that they seek to promote. This might tip the balance to get a change approved, and then after approval such owners could cut their declared values back down to something reasonable, and only pay a small extra tax for that small decision period. Harberger taxes impose a stronger penalty for declaring overly-low values than overly-high values.

A solution to this problem is to use, instead of declared values, prices for the purely financial assets that represent claims on all future tax revenue from the Harberger tax on a particular property. That is, each property will pay a tax over time, we could divert that revenue into a particular account, and an asset holder could own the right to spend a fraction of the funds in that account. Such tax-revenue assets could be bought and sold in financial markets, and could also be made conditional on particular zoning scenarios. As such assets are easy to create and duplicate, the usual speculation pressures should make it hard to manipulate these prices much in any direction.

A plan to temporarily inflate the declared value of a property shouldn’t do much to the market price for a claim to part of all future tax revenue from that property. So instead of summing over conditional differences in declared-values to see if a zoning change is good, it is probably better to sum over conditional differences in tax revenue assets. Subsidized continuous market makers can give exact if noisy prices for all such differences, and for most property-scenario pairs this difference will be exactly zero.

So that’s the plan for using futarchy and Harberger taxes to pick zoning (and other land use limit policy) changes. Instead of just one declared value per property, we allow owners to specify declared values conditional on each approved zoning change (or not) scenario, and allow conditional purchases as well. By default, conditional values equal no-change values. We should tend more to adopt zoning proposals when, during its decision day, when the sum of its (tax-revenue-asset) conditional differences clearly and consistently exceeds zero.

Thanks to Alex Tabarrok & Keller Scholl for their feedback.

Added 11pm: One complaint people have about a Harberger tax is that owners would feel stressed to know that their property could be taken at any time. Here’s a simple fix. When someone takes your property at your declared value, you can pay 1% of that value to get it back, if you do so quickly. But then you’d better raise your declared value or someone else could do the same thing the next day or week. You pay 1% for a fair warning that your value is too low. Under this system, people only lose their property when someone else actually values it more highly, even after considering the transaction costs of switching property.

Added 2Feb: I edited this post a bit. Note that with severe enough property limits, negative declared property values can make sense. For example, if a property must be maintained so as to serve as a public park, the only people willing to become owners are those who get paid when they take the property, and then get paid per unit time for remanning owners. In this way, city services can be defined and provided via this same decision mechanism.

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Gender Is Big

Consider the possibility of discrimination against the left-handed. Such discrimination might make efficiency sense in contexts where expensive-to-change complementary equipment is designed for the right-handed. Such as pilots. In other contexts, one might justify mild discrimination based on weak correlations, such as between handedness and intelligence, gender, and health. But these other factors tend to be directly observable, and correlations are weak. So stronger correlations of handedness with success, especially where not explained by these other correlations, are suspicious.

What do we suspect? One possibility is political equilibria wherein an established group of insiders arbitrarily favor people like them against outsiders. We might especially suspect this if we saw people rewarding others for discriminating against the left-handed, as something like this would need to be part of an insiders-favoring political equilibria. It is plausible, though not obvious, that disrupting such an insider-favoring equilibria is good for the world. So we might consider prohibiting or at least hindering discrimination against left-handers. (One might also just think we are in a bad choice out of multiple equilibria, and not blame insiders so much.)

This all makes sense as a way to think about discrimination for what are arguably relatively minor, or small, features such as height or hair-length. But now consider gender. It seems to me that the above framework is far less useful for gender, as gender is not remotely a small feature.

For most people, their main long-term spouse is the most important relationship in their life. And most care greatly about the gender of that spouse. It isn’t just ordinary “straight cis” people who think this way. Gay/lesbians also mostly agree that the genders differ greatly in important features, and they have a strong preference for one end of the gender spectrum. In part because others care about gender, most people also care greatly about how others see their own gender. Most transgender people also care a lot (almost by definition) about how others see their gender; they just make unusual choices about that. So most everyone agrees that most everyone cares a lot about the genders of their associates, and the genders that others assign to them.

Some may postulate gender as an innate atomic feature of the universe of human concerns, so that when we desire that an associate have a certain gender that has nothing to do with their many other associated features. But that seems crazy to me. Much more plausibly, what we like about a gender is strongly tied to the set of associated features that tend to go along with that gender. That is, we like the package of features that “are” a gender. In this case, the fact that we strongly care about genders suggests that different genders differ greatly in many features that are important to us. These features probably include habits, attitudes, preferences, and abilities. Gender is big, and it matters a lot.

Because gender is big, we expect it to correlate substantially with many features that we care about when assigning people to roles. But this means that even strong correlations of gender with success in particular roles is at best only a weak cause for suspicion about insider-favoring or other bad equilibria. There are just too many other good reasons to expect to see large gender-role correlations.

Now you might argue that today’s large correlations between gender and important features are largely a legacy resulting from a bad past. And change takes time. So creating pressures for low gender-role correlations today will push us to move faster toward a better future, even if that costs us today in terms of matching people to roles well.

However, the prospects for a world anytime soon where different genders correlate little with other important features seems to me quite low. (As low as the chance that communist governments would rapidly “whither away” to produce “true” communism.) Yes, gender correlations have changed across societies and across time, but almost always there have been strong correlations between gender and important things. The fact that societies with weaker gender roles have more strongly gendered personalities also (weakly) suggests to me that we fundamentally want genders to differ, even if we aren’t that stuck on most particular differences. We want gender to be big; we want to love and be loved by people that differ from us in big known ways.

Thus I don’t see gender-success correlations as by themselves offering much of a justification for anti-discrimination efforts today to suppress such correlations. At least they don’t in terms of disrupting insider-favoring or other bad equilibria, or in terms of promoting a low-gender-differences future. But I do see some other justifications, which I may write about in future posts.

It seems to me that our public discussion about gender has for a while been somewhat in denial about the likely long continuation of strong gender correlations with important features. If the genders continue to act differently on average, then observers will naturally form gendered expectations based on such behavior. That is, there will be gender roles. We can and should talk about what we want those gender roles to be, but we can’t do that until we admit that such roles will exist.

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Umpires Shouldn’t Be On Teams

There are many complex issues to consider when choosing between public vs private provision of a good or service. But one issue seems to me to clearly favor the private option: rights. If you want to make rights-enforcing rules that are actually followed, you are better off having courts or regulators enforcing rules on a competitive private industry.

Consider this excellent 2015 AJPS paper:

Many regulatory policies—especially health, safety, and environmental regulations—apply to government agencies as well as private firms. … Unlike profit‐maximizing firms, government agencies face contested, ambiguous missions and are politically constrained from raising revenue to meet regulatory requirements. At the same time, agencies do not face direct competition from other firms, rarely face elimination, and may have sympathetic political allies. Consequently, the regulator’s usual array of enforcement instruments (e.g., fines, fees, and licensure) may be potent enough to alter behavior when the target is a private firm, but less effective when the regulated entity is a government agency. …

The ultimate effect of regulatory policy turns not on the regulator’s carrots and sticks, but rather on the regulated agency’s political costs of compliance with or appeal against the regulator, and the regulator’s political costs of penalizing another government. One implication of this theory is that public agencies are less likely than similarly situated private firms to comply with regulations. Another implication is that regulators are likely to enforce regulations less vigorously against public agencies than against private firms because such enforcement is both less effective and more costly to the regulator. …

We find that public agencies are more likely than private firms to violate the regulatory requirements of the [US] Clean Air Act and the Safe Drinking Water Act. Moreover, we find that regulators are less likely to impose severe punishment for noncompliance on public agencies than on private firms. (more)

See also:

There is evidence … that [public entities] are [better] able to delay or avoid paying fines when penalties are assessed. (more)

Public sector employees experienced a higher incidence rate of work-related injuries and illnesses than their private industry counterparts. (more)

I’ve tried but failed to find stats on public vs private relative rates of abuse, harassment, bribery, embezzlement, nepotism, and test cheating. (Can you find more?) But I’d bet they’d also show government agencies violating such rules at higher rates.

This perspective seems very relevant to criminal justice reform. Our status quo criminal justice system embodies enormous inefficiencies and injustices, but when I propose changes that involve larger roles for private actors, I keep hearing “yes that might be more efficient, but won’t private actors create more rights violations?” But the above analysis suggests that this gets the comparison exactly wrong!

Yes of course, if you compare a public org that has a rule with a private actor to whom no such rules applies, you may get more rule “violations” with the latter. And yes, enforcement of central rules can be expensive and limiting, so sometimes it makes sense to use private competition as a substitute for central rules, and so impose fewer rules on private actors. But once we allow ourselves to choose which rules to impose, private orgs seem just overall better for enforcing rules.

Note that when a government agency directly contracts with a specific private organization, using complex flexible terms and monitoring, as in military procurement, the above theory predicts that this contractor will look much more like an extension of the government agency for the purpose of rule enforcement. Rule enforcement gains come instead from private orgs that compete to be chosen by the public, or that compete to win simple public prizes where public orgs do not have so much discretion over terms that they can pick winners, but get blamed for rights violations of losers.

It is these independent private actors that I seek to recruit to reform criminal justice. We will get more, not less, enforcement of rules that protect rights, when the umpires who enforce rights are less affiliated with the teams who can violate them.

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Stubborn Attachments

Tyler Cowen’s new book, Stubborn Attachments, says many things. But his main claims are, roughly, 1) we should care much more about people who will live in the distant future, and 2) promoting long-run economic growth is a robust way to achieve that end. As a result, we should try much harder to promote long-run economic growth.

Now I don’t actually think his arguments are that persuasive to those inclined to disagree. On 1), the actions of most people suggest that they don’t actually care much about the distant future, and there exist quite consistent preferences (including moral preferences) to represent this position. (Also, I have to wonder how much Tyler cares, as in the 20 years I’ve known him I’ve often worked on distant future issues, and he’s shown almost no interest in such things.)

On 2), while Tyler mainly argues for econ growth by pointing to good trends over the last few centuries, many people see bad trends as outweighing the good, and many others see recent trends as temporary historical deviations. Tyler also doesn’t consider that future techs which speed population growth could cut the connection observed recently between total and per-capita growth; I describe such a scenario in my book Age of Em.

Tyler being Tyler, he is generally vague and gives himself many outs to avoid criticism. For example, he says that rights should take priority over growth, but he doesn’t specify those rights. He says he only advocates growing “wealth plus” which includes any good thing you could want, so don’t complain that growth will hurt a good thing. He notes that the priority on growth can justify the usual intuition excusing limited redistribution, but doesn’t mention that this won’t at all excuse not doing everything possible to promote growth. He says he isn’t committed to econ growth being possible forever, but only to a finite chance of eternal growth. Yet focusing all policy on trying to increase growth within some tiny-chance eternal growth scenario is overwhelmingly likely to seem a huge mistake later.

However, as I personally happen to agree with his main claims, at least the way I phrased them, I’d rather focus on their implications, which Tyler severely neglects. The following are the only “concrete” things he says about how exactly to promote long term econ growth:

For some more concrete recommendations, I’ll suggest the following: a) Policy should be more forward-looking and more concerned about the more distant future. b) Governments should place a much higher priority on investment than is currently the case, in both the private sector and the public sector. … c) Policy should be more concerned with economic growth, properly specified, and policy discussion should pay less heed to other values. … d) We should be more concerned with the fragility of our civilization. … e) We should be more charitable on the whole, but we are not obliged to give away all of our wealth. … f) We can embrace much of common sense morality with the knowledge that it is not inconsistent with a deeper ethical theory. … g) When it comes to most “small” policies affecting the present and the near-present only, we should be agnostic.

More “investment” and “growth”, that’s it?! We actually know of many more specific ways to encourage choices that promote long term growth, but they mostly come at substantial costs. I don’t how much you actually support faster long-term growth until I hear which such policies you’ll support. Continue reading "Stubborn Attachments" »

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Gossip Cabals

Four actresses relayed their suspicion that, after rejecting [Harvey] Weinstein’s advances and complaining about him, he had them removed from projects or persuaded others to remove them. A number of Farrow’s sources said Weinstein had referred to his success in planting stories in the media about individuals who had crossed him. … He told them that complying with his demands would help their careers, repeatedly mentioning Paltrow (without the actress’s knowledge) as someone he claimed to have had sex with. … these activities were enabled by employees, associates, and agents who set up these meetings, and lawyers and publicists who suppressed complaints with payments and threats. (more)

Ashley Judd … refused, and says he got revenge by seeking to damage her career. Director Peter Jackson has come forward to say he removed her from a casting list “as a direct result” of what he now thinks was “false information” provided by Weinstein. … Like with Ashley Judd, Peter Jackson said Weinstein warned him off casting [Mira Sorvino]. … Heather Graham … alleges he implied she had to sleep with him to get a film role, telling her that his wife would have been fine with it. … He insisted on listening to [Louisette Geiss] pitch in his hot tub, then asked her to watch him masturbate, she says – and told her he could green-light her script if she did so. … Daryl Hannah … suffered physical repercussions as her flights were cancelled and she was left stranded after she turned him down on one occasion, she adds. … Rosanna Arquette … says she rejected Weinstein’s advances and that she believes her acting career suffered as a result. (more)

What power exactly did Harvey Weinstein possess, to let him harass and rape with impunity for decades? He was an actor’s agent, who negotiated deals between actors and studios, but many agents do that. If one agent makes unreasonable demands, why not switch to another? How hard can it be anyway to evaluate an actor and suggest which projects they might be well suited for?

Well, okay, maybe it takes years to acquire good judgement, and some agents have much better judgment than others. Even so, if many agents are capable of evaluating and matching actors, how can one agent gain so much power over an actor who could easily switch to other agents?

Okay, yes, also, an actor-agent relation might develop slowly over a long time, and as with quitting a on marriage or a family, someone might put up with modest abuse before calling it quits. But Weinstein seems to have had far more power than most partners who increase in value over time.

Some say that wannabe actors are far more irrational and desperate than are most people in most relations. So they’ll do almost anything for a tiny increase of a chance for acting success. Maybe, but I want to explore other explanations, before I’m willing to conclude that.

One scenario is that corrupt agents offer to overestimate an actor’s suitability if they accept agent demands. But if the agent reneged on their promise, how would an actor enforce it? This strategy could result in studios giving them a try, seeing they are subpar, and then realizing that they are getting lower quality advice from that agent, reducing demand for that agent. And if there’s a limit to how much they could plausibly exaggerate quality, an agent could only plausibly use this strategy on the few best actors, as the rest will be rejected in any case.

Another scenario is that corrupt agents threaten to underestimate an actor’s suitability if they reject agent demands. Here enforcement is more reliably handled by the agent. If most actors give in to the threat, then most threats need not be carried out, and so the quality of signals sent to studios will be much less degraded. If the threat is carried out, studios will likely reject, and so not see that they got a bad signal. Also, this threat can be given to all types of actors, good and bad. So underestimation threats seems more effective overall than overestimation promises.

However, if an actor could easily switch to dozens of other agents, even this underestimation threat seems weak. I doubt such a threat would have moved me much when I was working with a book agent. But what if someone like Weinstein could credibly threaten, “If I give the word, you’ll never get another job in this town/industry again?”

This threat might be credible if the major acting powers formed a cabal where they agreed to believe their negative evaluations of others. Then Weinstein could tell other powers, like director Peter Jackson, that you are difficult, and none of them would audition you. If Jackson defied Weinstein and auditioned you anyway, then Weinstein could tell the other powers that Jackson is difficult. So an equilibrium could be formed where all the powers take each others’ strong negative evaluations of others at face value, for fear that otherwise they will become a target. And they could collectively benefit from this equilibrium, as they can each now make stronger credible threats to outsiders.

This sort of equilibrium seems to me very common part of human behavior. For example, academic elites in an area tend to all treat each other’s claims with respect, and endorse any of their dismissals of outsiders. In a social media mob pile on, where a big mob all says person X is bad, someone who speaks up saying X isn’t so bad should reasonably fear the mob would turn on them. And the set of top bosses in a firm typically shares an inclination to jointly reject any lower level person who challenges any one of those bosses. (“We can criticize each other privately, but we are unified in rejecting public criticism by outsiders.”)

In this sort of equilibrium, elites will in public usually say “We are the best people in this area, as proved by the fact that we all say we are best. If we all say someone else is bad, you can take that to the bank.” Sometimes they will say “George used to be good, but we all now agree that George has turned bad.” And in private each elite can say to wannabes, “Unless you do everything I demand, I’ll tell the other elites you are bad, and you’ll be out of this area for good.”

We economists tend to worry about firms colluding on prices, to keep them high, or colluding on entry, where I won’t enter your area if you don’t enter mine. But I suspect that gossip collusion like this is a far bigger problem. It happens not just in business, but in politics, arts, religion, sports, academia, journalism, law, etc.

While it would be hard, I could imagine attempts to more strong regulate and discourage this sort of behavior. But the striking thing is, we hardly even try.

Added 26Sep: Oops, seems Weinstein was a producer, not an agent. But producers serve a related role of evaluating and matching actors. A big part of the demand for him as a producer would be his ability to do those well.

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Compulsory Licensing Of Backroom IT?

We now understand one of the main reasons that many leading firms have been winning relative to others, resulting in higher markups, profits, and wage inequality:

The biggest companies in every field are pulling away from their peers faster than ever, sucking up the lion’s share of revenue, profits and productivity gains. Economists have proposed many possible explanations: top managers flocking to top firms, automation creating an imbalance in productivity, merger-and-acquisition mania, lack of antitrust regulation and more. But new data suggests that … IT spending that goes into hiring developers and creating software owned and used exclusively by a firm is the key competitive advantage. It’s different from our standard understanding of R&D in that this software is used solely by the company, and isn’t part of products developed for its customers.

Today’s big winners went all in. …Tech companies such as Google, Facebook, Amazon and Apple—as well as other giants including General Motors and Nissan in the automotive sector, and Pfizer and Roche in pharmaceuticals—built their own software and even their own hardware, inventing and perfecting their own processes instead of aligning their business model with some outside developer’s idea of it. … “IT intensity,” is relevant not just in the U.S. but across 25 other countries as well. …

When new technologies were developed in the past, they would diffuse to other firms fast enough so that productivity rose across entire industries. … But imagine instead of power looms, someone is trying to copy and reproduce Google’s cloud infrastructure itself. … Things have just gotten too complicated. The technologies we rely on now are massive and inextricably linked to the engineers, workers, systems and business models built around them. … While in the past it might have been possible to license, steal or copy someone else’s technology, these days that technology can’t be separated from the systems of which it’s a part. … Walmart built an elaborate logistics system around bar code scanners, which allowed it to beat out smaller retail rivals. Notably, it never sold this technology to any competitors. (more)

A policy paper goes into more detail. First, why is the IT of some firms so much better?

Proprietary IT thus provides a specific mechanism that can help explain the reallocation to more productive firms, rising industry concentration, also growing productivity dispersion between firms within industries, and growing profit margins. … There is a significant literature that identifies IT-related differences in productivity arising from complementary skills, managerial practices, and business models that are themselves unevenly distributed. Skills and managerial knowledge needed to use major new technologies have often been unevenly distributed initially because much must be learned through experience, which tends to differ substantially from firm to firm.

Yes, skills vary, but there are also just big random factors in the success of large IT systems, even for similar skills. What can we do about all this?

While there may be other reasons to question antitrust policies, the general rise in industry concentration does not appear to raise troubling issues for antitrust enforcement at this point by itself. …

Both IP law and antitrust law pay heed to … balancing innovation incentives against the need for disclosure and competition, balancing concerns about market power against considerations of efficiency. … This balance has been lost with regard to information technology … the policy challenge is to offset this trend. … This problem might require some lessening of innovation incentives. … The challenge both today and in the future for both IP and antitrust policy is to facilitate the diffusion of new technical knowledge and right now the trend seems to be in the wrong direction. …

To the extent that rising use of employee noncompete agreements limits the ability of technical employees to take their skills to new firms, diffusion is slowed. Similarly, for extensions of trade secrecy law to cover knowhow or the presumption of inevitable disclosure. Patents are required to disclose the technical information needed to “enable” the invention, but perhaps these requirements are ineffective, especially in IT fields. And if patents are not licensed, they become a barrier to diffusion. Perhaps some forms of compulsory licensing might overcome this problem. Moreover, machine learning technologies portend even greater difficulties encouraging diffusion in the future because use of these technologies requires not only skilled employees, but also access to critical large datasets.

It seems that making good backroom software, to use internally, has become something of a natural monopoly. Creating such IT has large fixed costs and big random factors. So an obvious question is whether we can usefully regulate this natural monopoly. And one standard approach to regulating monopolies is to force them to sell to everyone at regulated prices. Which in this context we call “compulsory licensing”; firms could be forced to lease their backroom IT to other firms in the same industry at regulated prices.

Note that while compulsory licensing of patents is rare in the US, it is common worldwide, and it one of the reasons that US drug firms get proportionally less of their revenue from outside the US; other nations force them to license their patents at particular low prices. So worldwide there is a lot of precedent for compulsory licensing.

The article above claimed that backroom IT is:

inextricably linked to the engineers, workers, systems and business models built around them. … While in the past it might have been possible to license, steal or copy someone else’s technology, these days that technology can’t be separated from the systems of which it’s a part.

I’m not yet convinced of this, and so I want to hear independent IT folks weigh in on this key question. I can see that different IT subsystems could be mixed up with each other, but I’m less convinced that the total set of backroom IT of a firm depends that much on its particular products and services. Maybe other firms in an industry would have to take the entire backroom IT bundle of the leading firm, rather than being able to pick and choose among subsystems. But when the leading IT bundle is so much better, I could see this option being attractive to the other firms.

The leading firm might incur some costs in making its IT package modular enough to separate it from its particular products and services. But such modularity is a good design discipline, and a compulsory licensing regime could compensate firms for such costs.

Note that I’m not saying that it is obvious that this is a good solution. I’m just saying that this is a standard obvious policy response to consider, so someone should be looking into it. At the moment I’m not seeing other good options, aside from just accepting the increased IT-induced firm inequality and its many consequences.

Added 12:30: Okay, so far the pretty consistent answer I’ve heard is that it is very hard to take software written for internal use and make it available for outside use. Even if you insist outsiders do things your way.

So assuming we are stuck with industry leaders winning big compared to others due to better IT, one worry for the future is what happens when leaders of different industries start to coordinate their IT with each other. Like phone firms are now coordinating with car firms. Such firms might merge to encourage their synergies. They we might have single firms as big winning leaders in larger economic sectors.

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Hazlett’s Political Spectrum

I just read The Political Spectrum by Tom Hazlett, which took me back to my roots. Well over three decades ago, I was inspired by Technologies of Freedom by Ithiel de Sola Pool. He made the case both that great things were possible with tech, and that the FCC has mismanaged the spectrum. In grad school twenty years ago, I worked on FCC auctions, and saw mismanagement behind the scenes.

When I don’t look much at the details of regulation, I can sort of think that some of it goes too far, and some not far enough; what else should you expect from a noisy process? But reading Hazlett I’m just overwhelmed by just how consistently terrible is spectrum regulation. Not only would everything have been much better without FCC regulation, it actually was much better before the FCC! Herbert Hoover, who was head of the US Commerce Department at the time, broke the spectrum in order to then “save” it, a move that probably helped him rise to the presidency:

“Before 1927,” wrote the U.S. Supreme Court, “the allocation of frequencies was left entirely to the private sector . . . and the result was chaos.” The physics of radio frequencies and the dire consequences of interference in early broadcasts made an ordinary marketplace impossible, and radio regulation under central administrative direction was the only feasible path. “Without government control, the medium would be of little use because of the cacaphony [sic] of competing voices.”

This narrative has enabled the state to pervasively manage wireless markets, directing not only technology choices and business decisions but licensees’ speech. Yet it is not just the spelling of cacophony that the Supreme Court got wrong. Each of its assertions about the origins of broadcast regulation is demonstrably false. ..

The chaos and confusion that supposedly made strict regulation necessary were limited to a specific interval—July 9, 1926, to February 23, 1927. They were triggered by Hoover’s own actions and formed a key part of his legislative quest. In effect, he created a problem in order to solve it. ..

Radio broadcasting began its meteoric rise in 1920–1926 under common-law property rules .. defined and enforced by the U.S. Department of Commerce, operating under the Radio Act of 1912. They supported the creation of hundreds of stations, encouraged millions of households to buy (or build) expensive radio receivers. .. The Commerce Department .. designated bands for radio broadcasting. .. In 1923, .. [it] expanded the number of frequencies to seventy, and in 1924, to eighty-nine channels .. [Its] second policy was a priority-in-use rule for license assignments. The Commerce Department gave preference to stations that had been broadcasting the longest. This reflected a well-established principle of common law. ..

Hoover sought to leverage the government’s traffic cop role to obtain political control. .. In July 1926, .. Hoover announced that he would .. abandon Commerce’s powers. .. Commerce issued a well-publicized statement that it could no longer police the airwaves. .. The roughly 550 stations on the air were soon joined by 200 more. Many jumped channels. Conflicts spread, annoying listeners. Meanwhile, Commerce did nothing. ..

Now Congress acted. An emergency measure .. mandated that all wireless operators immediately waive any vested rights in frequencies ..  the Radio Act … provided for allocation of wireless licenses according to “public interest”.  .. With the advent of the Federal Radio Commission in 1927, the growth of radio stations—otherwise accommodated by the rush of technology and the wild embrace of a receptive public—was halted. The official determination was that less broadcasting competition was demanded, not more.

That was just the beginning. The book documents so so much more that has gone very wrong. Even today, vast valuable spectrum is wasted broadcasting TV signals that almost no one uses, as most everyone gets cable TV. In addition,

The White House estimates that nearly 60 percent of prime spectrum is set aside for federal government use .. [this] substantially understates the amount of spectrum it consumes.

Sometimes people argue that we need an FCC to say who can use which spectrum because some public uses are needed. After all, not all land can be private, as we need public parks. Hazlett says we don’t use a federal agency to tell everyone who gets which land. Instead the public buys general land to create parks. Similarly, if the government needs spectrum, it can buy it just like everyone else. Then we’d know a lot better how much any given government action that uses spectrum is actually costing us.

Is the terrible regulation of spectrum an unusual case, or is most regulation that bad? One plausible theory is that we are more willing to believe that a strange complex tech needs regulating, and so such things tend to be regulated worse. This fits with nuclear power and genetically modified food, as far as I understand them. Social media has so far escaped regulation because it doesn’t seem strange – it seems simple and easy to understand. It has complexities of course, but behind the scenes.

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Power Corrupts, Slavery Edition

I’ve just finished reading a 1980 book Advice Among Masters: The Ideal in Slave Management in the Old South, which mostly quotes US slave owners from the mid 1800s writing on how to manage slaves. I really like reading ordinary people describe their to-me-strange worlds in their own words, and hope to do more of it. (Suggestions?)

This book has made me rethink where the main harms from slavery may lie. I said before that slaves were most harmed during and soon after capture, and that high interest rates could induce owners to work slaves to an early death. But neither of these apply in the US South, where the main harm had seemed to me to be from using threats of pain to induce more work on simple jobs.

However, this book gives the impression that most threats of pain were not actually directed at making slaves work harder. Slaves did work long hours, but then so did most poor European workers around that time. Slave owners didn’t actually demand that much more work from those capable of more work, instead tending to demand similar hours and effort from all slaves of a similar age, gender, and health.

What seems instead to have caused more pain to US south slaves was the vast number of rules that owners imposed, most of which had little direct connection to key problems like shirking at work, stealing, or running away. Rules varied quite a bit from owner to owner, but there were rules on where and when one could travel, times to rise and sleep, who could marry and live with who, who could talk to who when, when and how to wash bodies and houses, what clothes to wear when, who can cook, who can eat what foods, who goes to what sorts of churches when, and so on. Typical rules for slaves had much in common with typical “upstanding behavior” rules widely imposed by parents on their children, and by schools and armies on students and soldiers: eat well, rise early, keep clean, say your prayers, don’t drink, stay nearby, talk respectfully, don’t fraternize with the wrong people, etc.

With so many rules that varied so much, a standard argument against letting slaves visit neighboring plantations was that they’d less accept local rules if they learned of more lenient rules nearby. And while some owners emphasized enforcing rules via scoldings, fines, or reduction of privileges, most often violations were punished with beatings.

Another big cause of pain seems to have been agency failures with overseers, i.e., those who directly managed the slaves on behalf of the slave owners. Owners of just a few slaves oversaw them directly, and many other owners insisted on personally approving any punishments. However still others gave full discretion to overseers and refused to listen to slave complaints.

Few overseers had a direct financial stake in farm profitability, and many owners understood that such stakes would tempt overseers, who changed jobs often, to overwork slaves in the short run at the expense of long run profitability. Even so, short run harvest gains were usually easier for owners to see than long run harm to slaves, tempting overseers to sacrifice the former for the latter. And even if most overseers were kept well in line, a small fraction who used their discretion to beat and rape could impose high levels of net harm.

US south slave plantations were quite literally small totalitarian governments, and the main harms to such slaves seems to parallel the main libertarian complaints about all governments. A libertarian perspective sees the following pattern: once one group is empowered to run the lives of others, they tend to over-confidently over-manage them, adding too many rules that vary too much, rules enforced with expensive punishments. And such governments tend to give their agents too much discretion, which such agents use too often to indulge personal whims and biases. Think abusive police and an excess prison population today. Such patterns might be explained by an unconscious human habit of dominance via paternalism; while dominant groups tend to justify their rules in terms of helping, they are actually more trying to display their dominance.

Now one might instead argue that the usual “good behavior” rules imposed by parents, schools, militaries, and slave owners are actually helpful on average, turning lazy good-for-nothings into upright citizens. And in practice formal rule systems are so limited that agent discretion is needed to actually get good results. And strong punishments are needed to make it work. Spare the rod, and spoil the child, conscript, or slave. From this perspective, US south slave must have led decent lives overall, and we should be glad that improving tech is making it easier for modern governments to get involved in more details of our lives.

Looking to the future, if totalitarian management of individual lives is actually efficient, a more competitive future world would see more of it, leading widely to effective if not official slavery. Mostly for our own good. (This fear was common early in the industrial revolution.) But if the libertarians are right, and most dominant groups tend to make too many overly-harsh rules at the expense of efficiency, then a more competitive future world would see less such paternalism, including fewer slave-like lives.

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Regulating Self-Driving Cars

Warning: I’m sure there’s a literature on this, which I haven’t read. This post is instead based on a conversation with some folks who have read more of it. So I’m “shooting from the hip” here, as they say.

Like planes, boats, submarines, and other vehicles, self-driving cars can be used in several modes. The automation can be turned off. It can be turned on and advisory only. It can be driving, but with the human watching carefully and ready to take over at any time. Or it can be driving with the human not watching very carefully, so that the human would take a substantial delay before being able to take over. Or the human might not be capable of taking over at all; perhaps a remote driver would stand ready to take over via teleoperation.

While we might mostly trust vehicle owners or passengers to decide when to use which modes, existing practice suggest we won’t entirely trust them. Today, after a traffic accident, we let some parties sue others for damages. This can improves driver incentives to drive well. But we don’t trust this to fully correct incentives. So in addition, we regulate traffic. We don’t just suggest that you stop at a red light, keep in one lane, or stay below a speed limit. We require these things, and penalize detected violations. Similarly, we’ll probably want to regulate the choice of self-driving mode.

Consider a standard three-color traffic light. When the light is red, you are not allowed to go. When it is green you are allowed, but not required, to go; sometimes it is not safe to go even when a light is green. When the light is yellow, you are supposed to pay extra attention to a red light coming soon. We could similarly use a three color system as the basis of a three-mode system of regulating self-driving cars.

Imagine that inside each car is a very visible light, which regulators can set to be green, yellow or red. When your light is red you must drive your car yourself, even if you get advice from automation. When the light is yellow you can let the automation take over if you want, but you must watch carefully, ready to take over. When the light is green, you can usually ignore driving, such as by reading or sleeping, though you may watch or drive if you want.

(We might want a standard way to alert drivers when their color changed away from green. Of course we could imagine adding more colors, to distinguish more levels of attention and control. But a three level system seems a reasonable place to start.)

Under this system, the key regulatory choice is the choice of color. This choice could in principle be set different for each car at each moment. But early on the color would probably be set the same for all cars and drivers of a type, in a particular geographic area at a particular time. The color might come from in part a broadcasted signal, with the light perhaps defaulting to red if it can’t get a signal.

One can imagine a very bureaucratic system to set the color, with regulators sitting in a big room filled with monitors, like NASA mission control. That would probably be too conservative and fail to take local circumstances enough into account. Or one might imagine empowering fancy statistical or machine learning algorithms to make the choice. But most any algorithm would make a lot of mistakes, and the choice of algorithm might be politicized, leading to a poor choice.

Let me suggest using prediction markets for this choice. Regulators would have to choose a large set of situation buckets, such that the color must be the same for all situations in the same bucket. Then for each bucket we’d have three markets, estimating the accident rate conditional on a particular color. Assuming that drivers gain some direct benefit from paying less attention to driving, we’d set the color to green unless the expected difference between the green and yellow accident rate became high enough. Similarly for the choice between red and yellow.

Work on combinatorial prediction markets suggests that it is feasible to have billions or more such buckets at a time. We might use audit lotteries and only actually estimate accident rates for some small fraction of these buckets, using bets conditional on such auditing. But even with a much smaller number of buckets, our experience with prediction markets suggests that such a system would work better than either a bureaucratic or statistical system with a similar number of buckets.

Added 1p: My assumptions were influenced by the book Our Robots, Ourselves on the history of automation.

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Against DWIM Meta-Law

Smart capable personal assistants can be very useful. You give them vague and inconsistent instructions, and they “do what I mean” (DWIM), fixing your mistakes. If you empower them to control your interactions, you need less fear mistakes messing up your interactions.

But one thing a DWIM personal assistant can’t help you so much with is your choice of assistants. If assistants were empowered to use DWIM on your choice to fire them, they might tend to decide you didn’t really mean to fire them. So if you are to have an effective choice of assistants, and thus effective competition among potential assistants, then those same assistants can’t protect you much from possible mistakes in your meta-choices regarding assistants. They can protect you from other choices, but not that choice.

The same applies to letting people choose what city or nation to live in. When people live in a nation then that national government can use regulation to protect them from making many mistakes. For example, it can limit their legally available options of products, services, and contracts. But if people are to have an effective choice to change governments by changing regions, then such governments can’t use regulation much to protect people from mistakes regarding region choice. After all, a government authorized to declare your plan to move away from it to be a mistake can stop you from rejecting it.

Similarly we can elect politicians who pass laws to protect us from many mistakes. But if we are to have an effective choice of politicians to represent us, then they can’t protect us much from bad choices of politicians to represent us. We can’t let our current elected leaders much regulate who we can elect to replace them, if we are to be able to actually replace them.

I’ve long been intrigued by the idea of private law, wherein people can stay in the same place but contract with different legal systems, which then set the rules regarding their legal interactions with others. Such rules might in effect change the laws of tort, crime, marriage, etc. that people live under. And so such competition between private laws might push the law to evolve toward more efficient laws.

One of the things that legal systems tend to do is to protect people from mistakes. For example, contract law won’t enforce contracts it sees as mistakes, and it fills in contract holes it sees resulting from laziness. Law is often DWIM law. Which can be great when you trust your law to choose well. But if one is to have an effective choice of private law, and real competition for that role, then one’s current law shouldn’t be able to overrule one’s choice of a new law. Instead, one’s choice of a private legal system, like one’s choice of nation, needs to be a simple clear choice where one is not much protected from mistakes.

Today we don’t in fact have such private law, because our standard legal system won’t enforce contracts we sign that declare our intent to use different legal systems. To achieve private law, we’d need to change this key feature of our standard legal system.

Your choice to change nations, either for temporary travel or for permanent moves, can be a big mistake. It might result from temporary mood fluctuations, or from misunderstandings about the old nation or the new. Nevertheless we have little regulation of such choices. Instead individuals are mostly fully exposes to their possible mistakes. For example, while Europe is heavily regulated in general, European teens today can decide to go join ISIS, even when many others greatly regret such choices. We disapprove of nations that prevent people from leaving because that cuts competition between nations to serve people.

Similarly, if we want completion between legal systems without forcing people to move, we’ll have to change our law to accept our not protecting people from bad choices of legal systems. There will have to be a simple clear act by which one chooses a law, a choice not much subject to legal review and reversal. We’d want to encourage people to take such choices seriously, but then to accept the choices they make. Freedom of choice requires a freedom to make mistakes. For big choices, those can be big mistakes.

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