City By Combo Auction

I recently heard talks by Ryan Avent, author of “The Gated City”; and Matt Yglesias, author of “The Rent Is Too Damn High.” Both agreed that the inefficiency of urban land use has increased greatly in the last few decades, at least in the biggest US cities like New York. Most of the infrastructure that makes such cities great was made during the era of political machines, when a dominant party had great power to coordinate activities city wide.

We dismantled political machines out of revulsion for unchecked power. But now our cities fail to coordinate. Local zoning boards may often coordination to benefit local interests, but they also often fail to coordinate with distant boards to achieve city-wide gains. For example, when each area limits density to keep out poor folks, such as via lot size and height rules, the city fails to provide a place for needed poor workers. How can cities better coordinate, without the vast corruptible discretion of political machines?

Imagine for simplicity that we are starting a new city, or at least a new city area, from scratch. Some developers are thinking about building various types of housing, targeted at various types of residents. National chains are considering locating stores and food outlets. Employers and private schools are thinking of locating there as well. The question is: who will build where, and what utilities such as roads, power, water, sewer, internet will be built where to supply this new area?

One solution is to have a single developer initially own the entire area, and negotiate directly with all these parties. Political machines once filled a similar role. Today politicians and boards for zoning and utilities try to fill such roles. But there are other options. Yesterday I explained the concept of a combinatorial auction, using the example of assigning offices when moving to a new office building. Today I’d like to elaborate on how such a mechanism could be used to coordinate urban land use and utilities.

It would look a lot like the scenario I outlined yesterday for allocating offices. Just on a bigger scale. Each party would submit bids describing their willingness to pay for various combinations of land features. Bids could specify:

  1. Land area, soil type, topography.
  2. Views (or not) of mountains, ocean, factories, etc.
  3. Distance (meters or road time) from residents, shopping, jobs, schools, parks.
  4. Local limits on ambient sound, smells, light, etc.
  5. Limits on nearby resident demographics, and the “class” of shops.
  6. Limits you are willing to supply for own sound, smell, demographics, class.
  7. Utility services (e.g., power, water, internet, trash) required, at what prices.

A computer could then search for a max value set of mutually compatible bids. The winning assignment might specify:

  1. Which parties get what land for which uses.
  2. Local limits on building heights and appearances.
  3. What land is used for utilities such as roads, power generation, etc.
  4. What utility capacity is supplied at each place, and related price limits.
  5. Local policies limiting local behavior making sound, smell, light, etc.

Revenue from winning bids could help pay for city services. The cost of utility services could be included either via a cost model, or via bids from competing service suppliers. Adjustments might be made for an expected underbidding for shared resources. Bidding assistants and iterative bidding might keep bid elaboration efforts manageable. Calculation of max value bid sets might even be farmed out to competing calculators (who keep bids secret).

Now of course real cities are not usually built all at once, so we’d need to adapt the above process to incremental city change. Bids for each new time period could request options for similar future use at the same price, and specify a compensation due if that option is revoked. Futures markets estimating future winning bids might help determine the opportunity cost of awarding such commitments.

Yes there might still be opportunities for corruption and favoritism in this system, such as by leaking secret bids, and biasing the auction rules. But this still seems far less corruptible than today’s system. And we might use futarchy to take away even more opportunities for corruption.

Yes, it would be very hard to get agreement to change to this system from today’s system of property rights and regulatory restrictions. I despair of it happening in our comfortable and change-averse cities. So we might have to wait until a big disruption creates lots of other change. More about that tomorrow.

GD Star Rating
Tagged as: , ,
Trackback URL:
  • That’s a rather ominous way to end your post. How can I sleep tonight not knowing what big disruption to my comfortable change-averse lifestyle Robin Hanson was alluding to?

    • Probably global warming and the melting of Greenland. That will add 7 meters to sea level which puts much of NYC under water. The cheapest thing to so would be to abandon it and build something new elsewhere.

    • Wonks Anonymous

      Robin has already stated what he believes the next big change to be.

      daedalus2u, relevant books would be “Climatopolis” and “The World in 2050”.

  • nazgulnarsil

    with my libertarian hat on methinks the elimination of zoning would result in greater productivity than more efficient coordination between zoning powers.

    Of course now that i’ve had that thought I must seek out the strongest possible critique of it. Looks like I have a long read ahead of me.

    • Preferred Anonymous

      Hear hear, you have a commendable attitude towards your opinions. 🙂

  • Douglas Knight

    “For example, when each area limits density to keep out poor folks, such as via lot size and height rules, the city fails to provide a place for needed poor workers.”

    I don’t believe that example. Cities have centralized zoning.

    Political machines may explain why infrastructure is built more slowly, but how does it address the inability to increase density? There’s no city-wide coordination needed for a particular building. Maybe the developer has to bribe too many people now, but why are they dispersed?

    Part of the problem is uncertain property rights: lots of people might be granted veto rights by a court. Making the property rights explicit is probably more important than mechanisms for aggregating preferences in their deployment. This also addresses much corruption.

    But most of the problems seem to me to come from people not wanting to admit their preferences, because they are unfashionable or contradict the rules of other levels of government. eg, people make complicated rules to keep out poor people, rather than just keeping them out, while the state may require that the city try to bring them in.

  • Ari T

    Fascinating. Apparently this problem is NP-complete, which makes it even more fascinating. Apparently there are heuristics available.

    If cities were more autonomous and competing with each other (instead of countries or states), do you think it would be likely for some city to come up with this kind of solution?

  • Doc Merlin

    Or better yet do away with zoning altogether!

  • arch1

    I’m not enough of an economic thinker to easily articulate my reasons for believing this, but in this scenario, it seems to me that optimal solutions (in the sense of a maximal-sum set of compatible bids) are particularly likely to be hugely suboptimal in a separate and arguably more important sense (that of maximizing any reasonable measure of aggregate human utility).

    This is mitigated by the fact that the winning bid set can be used to fund city services. That said, my gut feel is that the proposed approach, unless carefully constrained, would put the utility of the many at the mercy of the dollars of a few to a much greater degree than is typical with most current approaches to city planning.

    That said, I do have a sense that city planning is fertile ground for the application of optimization technologies.

  • Pingback: Overcoming Bias : Em City By Combo Auction()

  • dugancm

    In response to your despair, perhaps this near project might be worth some of your time?

    City 2.0:

  • Instead of bidding on outcome packages, I think you’ll get a better solution if people bid price-per-unit, or something so that you can optimize via e.g. the simplex method, rather than choose winning bids.

  • Pingback: Overcoming Bias : MRE Futures, To Not Starve()

  • Pingback: Overcoming Bias : For Stability Rents()