Urban Sprawl as a Path Dependent Process
Atkinson, Glen, Oleson, Ted, Journal of Economic Issues
According to Michael Radzicki and John Sterman, "Path dependency is a characteristic of models that get locked into the particular dynamical path they initially 'choose' (usually by chance)" [Radzicki and Sterman 1994, 64]. When these models describe socioeconomic processes, the choosing is done by participants in the system rather than by natural forces. Models are a useful means of simulating dynamic change and presenting the logical consequences of remaining on a particular path. Path dependency is therefore another way of understanding economic change as a process of cumulative causation where the dominant feedback loops are self-reinforcing rather than self-correcting as they are in equilibrium models. Self-reinforcing feedback systems become evolutionary models because, if allowed to continue without some offsetting or opposing feedback, they will cause the underlying structure to change rather than re-establishing a new equilibrium within an unchanged structure as self-correcting systems do. Once the structure has changed, it is not possible to reverse the process and return to a previous equilibrium position because it has been eliminated as the structure changed. An existing path may have been determined by a chance event in the past or by the cumulative effects of past actions, and this means that the path we are on may or may not be desirable; more likely it will be desired by some and not by others.
Policy choices, then, are about actions to intervene in a system in order to alter the direction of a path. However, finding the correct policy choice may be difficult since these feedback loops (or cause-effect linkages) may not be linear and because there may be a lag between an action and its effect.
We will try to demonstrate in this paper that the concept of path dependency, and of structural change driven by self-reinforcing feedback loops leading to irreversible structural change, is a useful method to understand urban sprawl in metropolitan areas. Once urban sprawl is understood from the path dependency perspective, it is more likely that successful containment policies can be enacted since we will better understand the complications of cause-effect relationships in a nonlinear system. Instead of attempting to replace one urban spatial structure with another structure as master planning often does, we should seek to alter incentives and the dynamical path we are on.
The Dynamics of Urban Sprawl
At least since the end of World War II, our cities have been developing as low-density, land extensive settlements. This land use pattern has been encouraged by transportation and other technologies and by reinforcing public policies. The automobile has been designated as the major culprit in creating this pattern, but the automobile could not have had these effects without complementary public policies and subsidies. As the shopper began to travel to the downtown store by car, merchants wanted turnover at the curbside parking spaces, so they encouraged parking meters. Couple this shopper inconvenience with the development of suburban shopping centers and downtown shopping declined, leaving banks and offices serving municipal halls and court houses to occupy downtown. The centers became blighted and less attractive, which reinforced the move to the suburbs. Gradually the remaining professional offices found more suitable locations in or near the malls. Banks followed this trend, but their migration has accelerated recently due to deregulation and automated teller technology that reduced the need for the prestigious downtown locations. In fact, the banks lost most of their tenants in their high rise prestige locations (Number 1 Main Street was at one time a status symbol) as the professions moved to the suburbs.
Jobs moved to the edge of the city along with shopping and services, a trend exacerbated by the decline of manufacturing employment. Smokestack industry disappeared and was replaced by smaller facilities in industrial parks. …