Jay Forrester, Urban Dynamics, and unacknowledged tradeoffs between economic stability and social justice
Jay W. Forrester Dies at 98; a Pioneer in Computer Models," New York Times), I didn't know that he published a text, Urban Dynamics, applying system dynamics to cities, the focus being on complex systems being immune to simplistic approaches ("The beginnings of system dynamics," McKinsey Quarterly, 1995).
In Forrester's speech, he has this to say about what we now call affordable housing:
Urban Dynamics was the first of my modeling work to produce strong emotional reactions. It suggested that all of the major urban policies being pursued by the United States lay somewhere between neutral and highly detrimental in their impact, whether from the viewpoint of the city as an institution or from the perspective of unemployed, low-income residents. More, it argued that the most damaging policy of all was to build low-cost housing. At that time, this policy was thought essential to reviving the inner cities.That is very controversial, but there is no question that there is a lot of truth to it from a strict economic standpoint.
The conclusions of our work were not easily accepted. It took people several hours to come to an understanding of what urban dynamics was about. City officials and members of local communities would become more and more negative and emotional until they could see and accept the way in which low-cost housing was a double-edged sword for making urban conditions worse. Such housing used up space where jobs could have been created, while drawing in people who needed jobs. Building low-cost housing was a powerful process for producing poverty, not alleviating it.
I am not saying don't build affordable housing, but if you want affordable housing to not overly impact negatively a community's revenue stream and costs, then you have to recognize the opportunity costs involved with affordable housing need to be countered with other actions that smooth over the economic impacts.
That's "development," and development that generates greater revenue than costs. In most communities, residents believe that single family housing generates more net revenue when it actually costs money, while multiunit housing generates more net revenue than costs. In DC, which collects income taxes, the average household without children generates net revenue for the city while households with children attending public schools are money sinks.
To deal with such costs, be it for affordable housing, great schools, or other public facilities and parks and transit that make the city livable, it means that the opportunity costs of "lopping a floor or two from a building, not having reasonable density bonuses near Metrorail stations, and not taking full advantage of the full capacity of build out in redevelopment opportunities have serious, persistent, and long term economic consequences that are not favorable.
Interestingly, a paper ("Urban Dynamics: the first fifty years,"System Dynamics Review, 1995) on five examples of application of the Urban Dynamics model has some model assumptions that don't necessarily pertain today, such as that all old housing becomes undesirable over time or that buildings as they age aren't able to be reused for higher value applications (Jane Jacobs' point that cities need a large stock of old buildings to seed innovation).
I found this discussion interesting, about a project in Concord, Massachusetts, because it is exactly the issue faced by the City of Washington today, in terms of the failure to acknowledge complex tradeoffs are required to fund the city and to pay for things people say they want, such as "affordable housing." In this particular case, people were concerned about Concord "becoming too popular," and losing the characteristics that made the community special and desirable.
Town goals and tradeoffsSounds like DC in a nutshell.
The first models exhibited S-shaped growth patterns, with population equilibrium reached after exhausting whatever resource fueled community attractiveness. Instead of the “Land Fraction Occupied” hypothesis, we substituted housing costs, open space, schools, commuter access, town services and utility use as potential resource constraints. All proved initially attractive, only to ultimately turn negative when population grew to high levels. Little by little, the participants in the “Concord Project” recognized that they faced a very difficult choice: what to sacrifice and what to preserve?
In most communities, such tradeoffs go unrecognized, much less openly debated. Although the simple models did not pretend to forecast future growth, they did get across the point that growth was not inevitable. The town could control its own destiny. It had only to agree which problems to live with, which counterpressures to inflate, and it could lower its attractiveness as a target for developers and a magnet for regional population growth.
In a pluralistic society, such choices are virtually impossible to make. Each group, in seeking its own goals, unwittingly blocks others from achieving theirs. ... After mastering the dynamics of the simpler models, we plunged ahead with several larger models. One combined all of the attractiveness factors in order to examine their interrelationships. Another sought to disaggregate the single population level by age and income.
The models suggested that the tradeoffs would not be enough. The town could not supply affordable housing without fueling rapid growth. Nor could the town purchase sufficient open land for conservation without driving up the price of remaining land. High land prices coupled with restrictive zoning guaranteed high housing costs. Every option led back to the same conclusion: limiting the amount of housing effectively stopped further growth. Yet limiting the housing supply would drive prices sky-high.
I guess I need to track down that book.
Labels: change-innovation-transformation, planned change, provision of public services, public finance and spending, real estate development, systems engineering, urban revitalization, urban vs. suburban