Tag Archives: Tax

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 contributions, 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. 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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All Pay Liability

We could raise government revenue much more efficiently than we now do, with less damage to the economy for any given amount of revenue raised. For example, we could tax fixed characteristics like height instead of income, we could tax traffic congestion a lot more, and we could do better at taxing pollution, including carbon. Recently I posted on a more efficient system of property taxes, that allows more revenue to be raised at a lower cost. Today, I’ll post on a more efficient system of accident liability, which similarly raises more revenue at a lower cost.

Some don’t want me to talk about these things. They hope to “starve the beast” by drying up government revenue sources. That seems to me a lost cause, the sort of logic that pushed radicals toward generic destruction, hoping that eventually the masses would get fed up and revolt. I instead expect a better world overall if governments adopt more efficient policies, including more efficient tax policies.

Regarding accident liability, we want a system that will encourage good levels of care and activity by all who can influence accident rates. For example, regarding car accidents we want drivers to pick good car models, speeds, sleep, and maintenance frequencies. We also want them to take into account the possibility of hurting others via accidents when they choose how often they drive. In addition, we want a system that induces fewer actual court cases, which are expensive, and that asks courts to make fewer judgements, in which they might err.

The simplest system is no liability. Courts just don’t get involved. This has the lowest possible rate of court cases, namely zero. It creates good incentives for accident victims to set their care and activity levels well, but gives rather poor incentives for others to set such things well.

The next simplest system is strict liability. This induces good care and activity by potential injurers, but not from potential victims. It also induces a high rate of court cases; nearly every accident results in a lawsuit. While the parties might settle out of court, if a case goes to trial the court must determine responsibility, i.e., who caused the accident, and how much damages the victim suffered as a result.

Relative to strict liability, systems of negligence cut the rate of court cases, but at the cost of asking courts to make more judgements. As with strict liability, courts must judge who is responsible and victim damage levels. But in addition, courts must also ask themselves if that injurer took enough care to prevent the accident. For each of visible parameter, the courts must judge both the actual level of care taken, and the optimal level of care.If the injurer took enough care overall, that injurer does not owe damages. And if that no damages situation is the usual case, there are fewer court cases, as there are fewer lawsuits.

In practice, however, courts can only look at a small number of injurer choice parameters visible enough to them, such as driving speed. Far more parameters, including all injurer activity level parameters, remain invisible, and so are not considered. Negligence doesn’t create good incentives to set all those less visible parameters.

There are standard variations on these systems, such as allowing contributory negligence on the part of the victim. But all of these systems fail to induce optimal levels of care and activity in someone. We have long known, however, of a simple system that gets pretty much all of these things right, and in addition only asks courts to judge who is responsible for an accident and victim damage levels. (I didn’t invent this system; it is mentioned in many law & econ texts.) In this simple system, courts do not need to consider anyone’s actual or ideal levels of care or activity.

This simple system is to make all responsible parties pay the damage levels of all other parties hurt by the accident. The trick is that they pay all of these amounts to the government, instead of to each other. As each party now internalizes all of the damage suffered by all of the parties, they should choose all their private care and activity levels well. And the government gets more revenue to boot.

The big problem with this all-pay liability system is that none of these responsible parties, including the victims, want to report this accident to the government. They’d all rather pretend it didn’t happen. So the government needs some other way to find out about accidents. In dense areas where they government already has access to mass surveillance systems, they can just use those systems. In other areas, governments might offer bounties to third parties who report accidents, and put strong penalties on those who fail to report their own accidents. Or the system might revert to other liability rules in contexts where governments might otherwise detect accidents too infrequently.

With all-pay liability, we expect a lawsuit for every accident. But in that suit the courts only need to judge who is responsible and victim damage levels. No other judgements need be made. So if we could find simple streamlined ways to make these judgements, this system might not be that expensive to administer. And then we’d have both better accident prevention and more available government revenue.

(Yes, people might want to buy insurance against the risk of making these payments. Yes, if multiple parties could coordinate to prevent accidents together, this system might induce them to spend too much on prevention. Hopefully we could identify such efforts and treat them differently.)

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