Tag Archives: Regulation

Regulating Infinity

As a professor of economics in the GMU Center for the Study of Public Choice, I and my colleagues are well aware of the many long detailed disputes on the proper scope of regulation.

One the one hand, the last few centuries has seen increasing demands for and expectations of government regulation. A wider range of things that might happen without regulation are seen as intolerable, and our increasing ability to manage large organizations and systems of surveillance is seen as making us increasingly capable of discerning relevant problems and managing regulatory solutions.

On the other hand, some don’t see many of the “problems” regulations are set up to address as legitimate ones for governments to tackle. And others see and fear regulatory overreach, wherein perhaps well-intentioned regulatory systems actually make most of us worse off, via capture, corruption, added costs, and slowed innovation.

The poster-children of regulatory overreach are 20th century totalitarian nations. Around 1900, many were told that the efficient scale of organization, coordination, and control was rapidly increasing, and nations who did not follow suit would be left behind. Many were also told that regulatory solutions were finally available for key problems of inequality and inefficient resource allocation. So many accepted and even encouraged their nations to create vast intrusive organizations and regulatory systems. These are now largely seen to have gone too far.

Or course there have no doubt been other cases of regulatory under-reach; I don’t presume to settle this debate here. In this post I instead want to introduce jaded students of regulatory debates to something a bit new under the sun, namely a newly-prominent rationale and goal for regulation that has recently arisen in a part of the futurist community: stopping preference change.

In history we have seen change not only in technology and environments, but also in habits, cultures, attitudes, and preferences. New generations often act not just like the same people thrust into new situations, but like new kinds of people with new attitudes and preferences. This has often intensified intergenerational conflicts; generations have argued not only about who should consume and control what, but also about which generational values should dominate.

So far, this sort of intergenerational value conflict has been limited due to the relatively mild value changes that have so far appeared within individual lifetimes. But at least two robust trends suggest the future will have more value change, and thus more conflict:

  1. Longer lifespans – Holding other things constant, the longer people live the more generations will overlap at any one time, and the more different will be their values.
  2. Faster change – Holding other things constant, a faster rate of economic and social change will likely induce values to change faster as people adapt to these social changes.
  3. Value plasticity – It may become easier for our descendants to change their values, all else equal. This might be via stronger ads and schools, or direct brain rewiring. (This trend seems less robust.)

These trends robustly suggest that toward the end of their lives future folk will more often look with disapproval at the attitudes and behaviors of younger generations, even as these older generations have a smaller proportional influence on the world. There will be more “Get off my lawn! Damn kids got no respect.”

The futurists who most worry about this problem tend to assume a worst possible case. (Supporting quotes below.) That is, without a regulatory solution we face the prospect of quickly sharing the world with daemon spawn of titanic power who share almost none of our values. Not only might they not like our kind of music, they might not like music. They might not even be conscious. One standard example is that they might want only to fill the universe with paperclips, and rip us apart to make more paperclip materials. Futurists’ key argument: the space of possible values is vast, with most points far from us.

This increased intergenerational conflict is the new problem that tempts some futurists today to consider a new regulatory solution. And their preferred solution: a complete totalitarian takeover of the world, and maybe the universe, by a new super-intelligent computer.

You heard that right. Now to most of my social scientist colleagues, this will sound bonkers. But like totalitarian advocates of a century ago, these new futurists have a two-pronged argument. In addition to suggesting we’d be better off ruled by a super-intelligence, they say that a sudden takeover by such a computer will probably happen no matter what. So as long as we have to figure out how to control it, we might as well use it to solve the intergenerational conflict problem.

Now I’ve already discussed at some length why I don’t think a sudden (“foom”) takeover by a super intelligent computer is likely (see here, here, here). Nor do I think it obvious that value change will generically put us face-to-face with worst case daemon spawn. But I do grant that increasing lifespans and faster change are likely to result in more intergenerational conflict. And I can also believe that as we continue to learn just how strange the future could be, many will be disturbed enough to seek regulation to prevent value change.

Thus I accept that our literatures on regulation should be expanded to add one more entry, on the problem of intergenerational value conflict and related regulatory solutions. Some will want to regulate infinity, to prevent the values of our descendants from eventually drifting away from our values to parts unknown.

I’m much more interested here in identifying this issue than in solving it. But if you want my current opinion it is that today we are just not up to the level of coordination required to usefully control value changes across generations. And even if we were up to the task I’m not at all sure gains would be worth the quite substantial costs.

Added 8a: Some think I’m unfair to the fear-AI position to call AIs our descendants and to describe them in terms of lifespan, growth rates and value plasticity. But surely AIs being made of metal or made in factories aren’t directly what causes concern. I’ve tried to identify the relevant factors but if you think I’ve missed the key factors do tell me what I’ve missed.

Added 4p: To try to be even clearer, the standard worrisome foom scenario has a single AI that grows in power very rapidly and whose effective values drift rapidly away from ones that initially seemed friendly to humans. I see this as a combination of such AI descendants having faster growth rates and more value plasticity, which are two of the three key features I listed.

Those promised supporting quotes: Continue reading "Regulating Infinity" »

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Firm Inefficiency

Economists are often stereotyped as claiming that firms are very economically efficient, i.e., that they very effectively minimize costs and maximize profits. This is a common source of derision of economists by other social scientists. And it is true that efficiency is the standard assumption made in textbooks and in math models. But over time I’ve been persuaded that it is often far from an accurate assumption. (And I doubt that most older economists believe it.)

I’ve been persuaded by a steady accumulation of plausible examples of widespread persistent inefficiencies. No one example is overwhelmingly obvious – all have stories for why they are only apparent inefficiencies. But added all together, they persuade me. Some examples:

  1. Threats Help Productivity – When firms face more competition, they often have big bursts of productivity. But if increases were possible, why not do them before?
  2. Long-Lasting Deadwood – Firms often keep employees who are widely known within the firm to not be pulling their weight relative to other employees. They tend to be fired during a downturn, or after a takeover.
  3. Not Invented Here – Firms are famously reluctant to adopt changes that appear to have been developed elsewhere, preferring instead changes for which someone internal can take credit.
  4. Shooting Messengers – Many firms greatly discourage passing bad news up to bosses. GM was just exposed as such a firm via a safety issue. Those who do pass bad news up are punished as if they were personally a big cause of the bad news.
  5. Yes Men – If bosses keep quiet about their opinion, they can evaluate subordinates via comparing employee opinions with boss opinion. But bosses consistently forgo this by telling subordinates lots of opinions and punishing those who question such opinions.
  6. Mergers & Acquisitions – Firms that buy and merge with other firms seem to consistently lose money.
  7. Poison Pills – Rules that discourage takeover attempts by financially penalizing such attempts prevent investors from getting more for their shares.
  8. Overpaid CEOs – It is far from clear that firms actually earn more when they hire more expensive CEOs.
  9. Too Many Meetings – It is widely believed that most firms hold too many meetings that go on too long with too many people.
  10. Too Many Interviews – It is hard to find much evidence that interviews add info on job performance. So why do candidates go through so many interviews?
  11. Biased Evaluations – Bosses consistently give lower evaluations to people they didn’t hire, relative to people they did hire. Yet official evaluations don’t correct for this.
  12. Excess Credentials – People consistently feel pressure to hire people whose credentials make them look good on paper, relative to people they believe would do a better job.
  13. Few Experiments – Firms tend to be reluctant to do experiments, such as to find preferred product variations. Experiments would force them to admit they don’t yet know.
  14. Few Track Records – Meetings are full of people making predictions on decision consequences, but firms almost never keep formal track records to rate accuracy.
  15. Reward Braggarts – Firms consistently neglect people who don’t toot their own horn, even when their superior features are widely known.
  16. Allow Info Silos – Groups and divisions with a firm are allowed to keep a lot of info secret within their group. Yet if the firm works together toward a common goal, what can be the benefit of keeping such secrets?
  17. Predictable Consultants – Management consultants are often hired at great expense to give advice that is quite predictable given the opinions of those who hired them.
  18. Little Telecommuting – Telecommuting seems to save big on costs, yet is not adopted much.
  19. I’ll add more here in response to suggestions.

My working hypothesis to explain these inefficiencies is that the people and supporting coalitions closest to them tend to gain from them, and that selection pressures on political coalitions are often much stronger than selection pressures on firms.

If many of these inefficiencies are real, then yes government regulators can also see them, and yes it might not be that hard for smart sincere people to design regulations to increase welfare by correcting for them. However, government regulatory agencies are also “inefficient” in many ways, leading them to choose and enforce regulations which differ from those that would most increase welfare. To judge if we are better off giving regulators more powers over firms, we must judge the relative magnitudes of these two types of inefficiencies.

Note that firm efficiency may still be a reasonable assumption to make in models, even if it is not an accurate assumption. Modeling is always a tradeoff between realism and understanding.

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Auto-Auto Deadline Looms

It is well-known that while electricity led to big gains in factory productivity, few gains were realized until factories were reorganized to take full advantage of the new possibilities which electric motors allowed. Similarly, computers didn’t create big productivity gains in offices until work flow and tasks were reorganized to take full advantage.

Auto autos, i.e., self-driving cars, seem similar: while there could be modest immediate gains from reducing accident rates and lost productive time commuting, the biggest gains should come from reorganizing our cities to match them. Self-driving cars could drive fast close together to increase road throughput, and be shared to eliminate the need for parking. This should allow for larger higher-density cities. For example, four times bigger cities could plausibly be twenty-five percent more productive.

But to achieve most of these gain, we must make new buildings with matching heights and locations. And this requires that self-driving cars make their appearance before we stop making so many new buildings. Let me explain.

Since buildings tend to last for many decades, one of the main reasons that cities have been adding many new buildings is that they have had more people who need buildings in which to live and work. But world population growth is slowing down, and may peak around 2055. It should peak earlier in rich nations, and later in poor nations.

Cities with stable or declining population build a lot fewer buildings; it would take them a lot longer to change city organization to take advantage of self-driving cars. So the main hope for rapidly achieving big gains would be in rapidly growing cities. What we need is for self-driving cars to become available and cheap enough in cities that are still growing fast enough, and which have legal and political support for driving such cars fast close together, so they can achieve high throughput. That is, people need to be sufficiently rewarded for using cars in ways that allow more road throughput. And then economic activity needs to move from old cities to the new more efficient cities.

This actually seems like a pretty challenging goal. China and India are making lots of buildings today, but those buildings are not well-matched to self-driving cars. Self-driving cars aren’t about to explode there, and by the time they are cheap the building boom may be over. Google announced its self-driving car program almost four years ago, and that hasn’t exactly sparked a tidal wave of change. Furthermore, even if self-driving cars arrive soon enough, city-region politics may well not be up to the task of coordinating to encourage such cars to drive fast close together. And national borders, regulation, etc. may not let larger economies be flexible enough to move much activity to the new cities who manage to support auto autos well.

Alas, overall it is hard to be very optimistic here. I have hopes, but only weak hopes.

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Hidden Asset Taxes Must Be Huge

Paul Krugman:

Piketty’s big idea is that we are in the early stages of returning to a society dominated by great dynastic fortunes, by inherited wealth. … Imagine a wealthy family that has managed, somehow or other, to guarantee that a large fraction of its income is used to accumulate more wealth. Can this family thereby acquire a dominant position in society?

The answer depends on the relationship between r, the rate of return on assets, and g, the overall rate of economic growth. If r is less than g, dynasties are doomed to erode: even if all income from a very large fortune is devoted to accumulation, the family’s wealth will grow more slowly than the economy, and it will slowly slide into obscurity. But if r is greater than g, dynastic wealth can indeed grow to gigantic size. …

Piketty tells us something remarkable: historically, r has almost always exceeded g – but there was an exceptional period in the 20th century, a period of rapid labor force growth and technological progress, when r was less than g. And he asserts that the kind of society we consider normal, in which high incomes reflect personal achievement rather than inherited wealth, is in fact an aberration driven by this exceptional period. … A couple of questions:

1. How much of the decline in r relative to g in the 20th century reflected fast growth, and how much reflected policies that either taxed or in effect confiscated inherited wealth? In other words, how much was destiny, how much wars and political upheaval? Piketty stresses both factors, but never gives us a relative quantitative assessment. (more from Piketty here, here)

This rate of return on assets r that Krugman and Piketty discuss is something like the ratio of rental to purchase price of land. I don’t have access to Piketty’s book, but I’ve been pondering this question for a few months, and I’ve concluded that the usual estimates of asset returns r must fail to include many taxes that in practice reduce the actual rate of return r that growing dynasties can achieve. And I think that once we include all hidden taxes, the actual rate of return r that dynasties could achieve in practice must have usually be no more than the economic growth rate g. Let me explain.

Some taxes are explicit, like property taxes. Other taxes are implicit in the property destruction and transfer that result from wars, political upheavals, and legal corruption, and in the costs of reasonable efforts to prevent such losses. Finally, there are implicit taxes resulting from local legal limits on who one may use to manage a dynastic fund. For example, if a dynasty must give its eldest living male wide discretion over spending and investment choices, and if such males often turn out to be spent-thrift fools, this will greatly limit this dynasty’s ability to grow over the long run. An ideal might be to delegate dynasty management to a reputed professional trust that is legally obligated to follow explicit instructions to grow the fund as fast as possible over the long run. But, as I’ve discussed before, most societies have put substantial legal obstacles before solutions like this.

I argue that the net effect of all these hidden taxes on dynastic funds must have been to usually reduce asset returns to below growth rates. My argument is simple: If asset returns had typically been above growth rates, then if any dynastic funds had chosen to grow at the maximum possible rate, then even if those funds had started small they would have come to dominate investments worldwide. And they would have done so on a timescale short compared to the time period over which historical records suggest that asset returns have exceeded growth rates. By competing with each other, such dominating dynastic funds would then have increased the supply of investment so much as to drive down asset returns to or below the sustainable level, which is the economic growth rate.

I conclude that consistently across space and time, the net effects of all forms of taxes on dynastic investment funds, including taxes implicit in limiting who one may trust not to pilfer those funds, has been to reduce real assets returns to below growth rates. Perhaps well below.

Of course, if the main hidden tax in history has been pilfering by dynasty managers, that can result in a world where such pilferers spend a large fraction of world income, without much social value to show for it. One might easily dislike such a scenario, and want to prevent it. But instead of adding more explicit taxes to prevent the growth of dynastic funds, it seems to me better to cut the pilfering tax. Because this should encourage much more investment overall, which seems a good thing. This includes investment in helping and protecting the future, including protection from disasters, including existential risks. Which also seem like good things.

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Trends Rarely Inform Policy

I’d like to try to make a point here that I’ve made before, but hopefully make it more clearly this time. My point is: trend tracking and policy analysis have little relevance for each other.

You can discuss education policy, or you can discuss education trends. You can discuss medical policy or you can discuss medical trends. You can discuss immigration policy, or you can discuss immigration trends. And you can discuss redistribution and inequality trends, or you can discuss redistribution and inequality policy. But in all of these cases, and many more, the trend and policy topics have little relevance for each other.

On trends, we collect a lot of data, usually on parameters that are relatively close to what we can easily measure, and also close to summary outcomes that we care about, like income, mortality, or employment. Many are interested in explaining past trends, and in forecasting future trends. Such trend tracking supports the familiar human need for news to discuss and fret about. And when a trend looks worrisome, that naturally leads people to want to discuss what oh what we might do about it.

On policy, we have lots of thoughtful theoretical analysis of policies, which try to judge which policies are better. And we have lots of relevant data analysis, that tries to distinguish relevant theories. Such analysis usually ends up identifying a few key parameters on which policy decisions should depend. But those tend to be abstract parameters, close to theoretical fundamentals. They usually have only a distant relation to the parameters which are tracked so eagerly as trends.

To repeat for emphasis: the easy to measure parameters where trends are most eagerly tracked are rarely close to the key theoretical parameters that determine which policies are best. They are in fact usually so far away that it is hard to judge the sign of the relation between them. This makes it unlikely that a change in one of these policies is a reasonable response to noticing some tracked-parameter trend.

For example which policies are best in medicine depends on key theoretical parameters like risk-aversion, asymmetric info on risks, meddling preferences, market power of hospitals, customer irrationality, and where learning happens, etc. But the trends we usually track are things like mortality, rates of new drug introduction, and amounts, fractions, and variance of spending. These later parameters are just not very relevant for inferring the former. People may find it fascinating to track trends in doctor salaries, cancer deaths, or how many are signed up for Obamacare. But those are pretty irrelevant to which policies are best.

As another example, debates on immigration refer to many relevant theoretical parameters, including meddling preferences, demand elasticity for low wage workers, and the intelligence, cultural norms, and cultural plasticity of immigrants. In contrast, trend trackers talk about trends in immigration, low-skill wages, wage inequality, labor share of income, voter participation, etc. Which might be fascinating topics, but they are just not very relevant for whether immigration is a good or bad idea. So it just doesn’t make sense to suggest changing immigration policy in response to noticing particular trends in these tracked parameters.

Alas, most people are a lot more interested in tracking trends than in analyzing policies. So well meaning people with smart things to say about policy often try to make their points seem more newsworthy by suggesting those policies as answers to the problems posed by troublesome trends. But, in doing so they usually mislead their audiences, and often themselves. Trends just aren’t very relevant for policy. If you want to talk policy, talk policy, and skip the trends.

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Tech Regs Are Coming

Over world history, we have seen a lot of things regulated. We can see patterns in these regulations, and we understand many of them – it isn’t all a mystery.

As far as I can tell, these patterns suggest that recent tech like operating systems, search engines, social networks, and IM systems are likely to be substantially regulated. For example, these systems have large network effects and economies of scale and scope. Yet they are now almost entirely unregulated. Why?

Some obvious explanations, fitting with previous patterns of regulation, are that these techs are high status, new, and changing fast. But these explanations suggest that low regulation is temporary. As they age, these systems will change less, eroding their high status derived from being fashionable. They will become stable utilities that we all use, like the many other stable utilities we use without much thought. And that we regulate, often heavily.

You’d think that if we all know regulation is coming, that we’d be starting to argue about how and how much to regulate these things. Yet I hear little of this. Those who want little regulation might keep quiet, hoping the rest will just forget. But silence is more puzzling for those who want more regulation. Are they afraid to seem low status by proposing to regulate things that are still high status?

Similarly puzzling to me are all these internet businesses built on the idea that ordinary regulations don’t apply to stuff bought on the internet. They think that if you buy them on the internet, hired cars and drivers don’t have to follow cab regulations, rooms for a night don’t have to follow hotel regulations, ventures soliciting investors don’t have to follow securities regulations, and so on. Yes, regulators are slow and reluctant to regulate high status things, but can they really expect to evade regulation long enough to pay off their investors?

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Why Aren’t Cities Taller?

Urban economics studies the spatial distribution of activity. In most urban econ models, the reason that cities aren’t taller is that, per square meter of useable space, taller buildings cost more to physically make. (Supporting quotes below.) According to this usual theory, buildings only get taller when something else compensates for these costs, like a scarce ocean view, or higher status or land prices.

Knowing this, and wondering how tall future cities might get, I went looking for data on just how fast building cost rises with height. And I was surprised to learn: within most of the usual range, taller buildings cost less per square meter to build. For example, for office buildings across 26 US cities, 11-20 stories tend to be cheaper than 5-10 stories, which are cheaper than 2-4 stories (quote below). I also found data on two sets of Chinese residential buildings. Here is cost to build per square meter (on Y axis) vs. height in meters (on X axis) for 24 buildings 3 to 39 stories tall, built in Hong Kong in the early 1990s:


Here are 36 buildings 2 to 37 stories tall, built in Shanghai between 2000 and 2007:


The Shanghai buildings don’t get more expensive till after about 20 stories, while Hong Kong buildings are still cheap at 40 stories.

Now I have no doubt that some elements of cost, like structural mass, rise with height, and that there is some height where such costs dominate. But since there are scale economies in making bigger buildings, it isn’t obvious theoretically where rising structure costs overwhelm scale economies.

Perhaps the above figures are misleading somehow. But we know that taking land prices, higher status, and better views into account would push for even taller buildings. And a big part of higher costs for heights that are rarely used could just be from less local experience with such heights. So why aren’t most buildings at least 20 stories tall?

Perhaps tall buildings have only been cheaper recently. But the Hong Kong data is from twenty years ago, and most buildings made in the last years are not at least 20 stories tall. In fact, in Manhattan new residential buildings have actually gotten shorter. Perhaps capital markets fail to concentrate enough capital in builders’ hands to enable big buildings. But this seems hard to believe.

Perhaps trying to build high makes you a magnet for litigation, envy, and corrupt regulators. Your ambition suggests that you have deeper pockets to tax, and other tall buildings nearby that would lose status and local market share have many ways to veto you. Maybe since most tall buildings are prevented local builders have less experience with them, and thus have higher costs to make them. And many few local builders are up to the task, so they have market power to demand higher prices.

Maybe local governments usually can’t coordinate well to build supporting infrastructure, like roads, schools, power, sewers, etc., to match taller buildings. So they veto them instead. Or maybe local non-property-owning voters believe that more tall buildings will hurt them personally. (The big city nearest me actually has a law against buildings over 40 meters tall.)

Note that most of these explanations are variations on the same theme: local governments fail to coordinate to enable tall buildings. Which is in fact my favored explanation. City density, and hence city size, is mainly limited by the abilities of the conflicting elements that influence local governments to coordinate to enable taller buildings.

Remember those futurist images of dense tall cities scraping the skies? The engineers have done their job to make it possible. It is politics that isn’t yet up to the task.

Those promised quotes: Continue reading "Why Aren’t Cities Taller?" »

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Random Rights Are Bad

Food truck and fast food meals can be pretty skimpy. So wouldn’t it be great if we passed a diner’s bill of rights law, requiring all prepared food to come with free unlimited drinks, a fast human waiter, cloth napkins and tablecloths, and a seat by a window? Well no, that wouldn’t be great. All those food trucks and fast food places would go out of business, leaving diners only with the option to eat at expensive fancy restaurants.

It might feel good to play Santa for free, handing out stuff that costs you little yet appears to benefit others lots. But something-for-nothings are usually illusions. Rights limit options, and that is generally bad.

Yes, sometimes we can benefit strategically from having our options limited, but such situations are rare. Random limits on options are usually bad. So if you propose limiting options, you should be prepared to offer particular arguments for why your particular cases are in fact strategic exceptions.

George Dvorsky says we should give lots of rights to ems:

If we’re going to be making minds, we sure as hell need to do it responsibly. … This was the topic of Anders Sandberg’s talk … about the harm that could be inflicted on software capable of experiencing thoughts, emotions, and sensations. … Sandberg proposed that virtual [lab] mice be given virtual painkillers. Another issue is time-rate rights. Does a human emulation have the right to live in real-time, so that it can interact properly with non-digital society? …

Back in 2010, … I proposed that the following rights be afforded to fully conscious human and human-like emulations:

  • The right to not be shut down against one’s will
  • The right to not be experimented upon
  • The right to have full and unhindered access to one’s own source code
  • The right to not have one’s source code manipulated against their will
  • The right to copy (or not copy) oneself
  • The right to privacy (namely the right to conceal one’s own internal mental states)
  • The right of self-determination

… I’d like to include Sandberg’s idea of time-rate rights.

In the comments Dvorsky also likes a “right to have a body and senses.”

But just as with a diner’s bill of rights, limiting options is in general bad. Ems would usually choose each new life, by negotiating with employers, landlords, etc. for a job, place, etc. for a new copy to live. So just as requiring free drinks with a meal can take away that meal as an option, requiring an em life to come with “a right to live in real time” may take away that life as an option. Since the cost to run an em is roughly linear in speed, prohibiting ems that can’t run faster than a thousand times slower than human speeds can in effect raise the cost of such ems by a factor of a thousand. That might greatly reduce the demand for such ems, and hence their number.

Yes, there may be particular situations where limiting options helps ems, but we should expect to hear arguments for why particular cases are exceptions to the usual rule. Dvorsky offers no such arguments, and given how little we know about the em world it is hard to believe he’s worked out detailed arguments that he forgot to mention. Maybe Dvorsky just likes to play Santa for free?

Btw, here’s a post where I criticize a similar effort by Greg Egan to give ems rights. See also Alex on harmful rights.

Added: Just as we have good reasons to stop people from being forced to eat meals that they didn’t choose, we also have good reasons to stop ems from being forced to live lives they didn’t choose. We know lots about why property rights are often useful. More examples of bad random rights:

  • The right to a bookstore that has certain random books.
  • The right to a kitchen holding certain random spices and utensils.
  • The right to a home with certain random furniture items.
  • The right to a movie with certain random plot elements.
  • The right to a laptop with certain random features and accessories.

Added 10a: Anders’ talk is based on this paper; key quote: Continue reading "Random Rights Are Bad" »

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Is Govt Over-Regulated?

I heard a talk recently by Jal Mehta on his new book Allure of Order, where he says how he’d reform US (pre-college) schools. He wants the US to do like Finland where schools are great: select smarter folks as teachers, train them more, and give them more respect, time to prepare, and freedom to structure classes. When I asked him directly how he would pay for all this, he said to cut administration.

It seemed to me that Mehtra’s main complaint is that US teachers are over-regulated. And it occurs to me that this is a common complaint about US government. For example, we hear that US police are over-constrained by rules. And a similar problem would befall US single player health plans — while the UK National Health Service has lots of discretion that is mostly accepted by the UK public, US versions would instead be regulated in great detail.

If you think that private actors in the US tend to be over-regulated, you should wonder why. Perhaps it is because government regulators just act spitefully toward non-government actors, but more plausible are over-confidence and do-something biases. When problems occur, people want something done, and more regulations are something to do. Voters and regulators both overestimate their ability to anticipate future problems and what would help them.

But if this is why US private actors are over-regulated, then US government actors should be over-regulated too. For example, people should see things go wrong in schools, and so add more rules to “do something,” rules that assume too much about what rules can do, and that require too many administrators to implement.

This view suggests that being pro- or anti-regulation isn’t the same as being pro- or anti-government, and it suggests a possible left-right deal: reduce regulation in both private and public sectors. Have more trust in private competition to deal with the problems we leave to the private sphere, and in smart well-trained civil servants to deal with the problems we leave to the public sphere. And have less trust in lawyers, judges and rule-specialists of all sorts to fix our problems with more rules.

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Tax Old Firms More?

It is widely believed that free markets tend to undersupply innovation, and that new firms tend to be more innovative. Here is yet another compatible academic analysis:

A subsidy to incumbent R&D equivalent to 5% of GDP reduces welfare by about 1.5% because it deters entry of new high-[quality] firms. On the contrary, substantial improvements (of the order of 5% improvement in welfare) are possible if the continued operation of incumbents is taxed while at the same time R&D by incumbents and new entrants is subsidized. This is because of a strong selection effect: R&D resources (skilled labor) are inefficiently used by low-[quality] incumbent firms. Subsidies to incumbents encourage the survival and expansion of these firms at the expense of potential high-[quality] entrants. (more)

Many have suggested that we subsidize firm research, though it still seems puzzling that we don’t do more of this. Yes it can be hard to measure research spending, but that probably isn’t the whole issue. However, one rarely hears serious proposals to tax old firms more relative to young firms. (Exception here.) And the age of a firm seems even easier to measure.

Why not tax old firms more, or young firms less? This doesn’t seem to be a left vs. right issue, or to favor any other side of a familiar political divide. Is this another example of our pretending to oppose dominance by big powers, but really accept it?

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