Part 4: Discussion
As the research has shown, sprawl, or urban-rural migration, is not just a result of a behavior change but also more significantly a result of changes in the age structure of the population. Given age-specific migratory patterns driven by residential preference, coupled with age specific behavior patterns and a changing age structure, growth in sprawl indicators will occur seemingly unrelated to the overall growth of the contemporary population. Therefore it is necessary to compare the growth of sprawl indicators not to the growth of the total population at the time in question but to the growth of a subset of the population (a specific age group for instance) most likely to engage in the behavior associated with that indicator. Using age structure deviation analysis and a decomposition of changes in population by age group, it has been concluded that a significant portion of Rhode Island's problems with high levels of development is due to these demographic effects. This study suggests programs designed to stop sprawl should focus on specific age groups in a population to create more tailored programs. It was also determined that suburban sprawl is intimately linked to population growth displaced in time by about 30-40 years. As a result of not accounting for these demographic dynamics, the measure of success or failure of policy decisions currently risks being over or under stated if the policies are designed to decrease certain indicators of sprawl that appear may not be tied directly to sprawl. Also the research suggests that other indicators of sprawl may be susceptible to the age structure effects detailed here.
One possible problem with the approach taken in the above analysis is that municipalities evolve and change in character as time moves on. This is perhaps one of the greatest sources of error on the analysis as all classifications were done during the 1990's and don't actually reflect what these areas may have been classified as in earlier times. The reason why this may be important is as people "sprawl" into a municipality they are changing that area. First increased housing construction brings new roads, more people and a larger market. Businesses are created or expanded to service this larger market and more infrastructure is needed to service all of this development. If there is enough of this development than that area may begin to qualify as the next higher classification type. This is clearly an issue that may be affecting the accuracy of the study.
Some of the insights of this study will have direct application to other areas of the US, as Rhode Island's age structure is similar to that of the US as a whole. However zoning, migration and other factors make this a limited comparison. Many of the other areas experiencing large volumes of development seen as sprawl have had large influxes of population as people migrate from one region of the country to another for economic reasons. The age structure effect may be exacerbating the larger issue of migration into the receiving region but it is by no means the only cause. However, the idea of residential preference can help explain the choice of housing location once the decision to move to a region, such as Atlanta, is made based on economic factors. Zoning is also an issue along with whether or not the area in question has fixed borders, such as the North Eastern US. One last issue with this analysis is that since it is on a statewide basis, it may be hiding more localized behavior patterns. The conclusions drawn are on aggregate regions (e.g. urban and non-urban) within one state and may not hold for particular subgroups, including individual towns, populations categorized by race or ethnicity, or socio-economic class.
The above research raises questions regarding some of the metrics currently being used to measure sprawl, as it appears some may not be directly tied by causation to sprawl. One example of this is the aggregate increase in housing starts or construction. As the above has shown, the housing demand has changed significantly over time but the underlying age specific behavior patterns have had very little change over the same period of time. One issue arising from this that needs to be more closely looked at is the idea that sprawl is a behavior that, as it has changed through time, has done increasing harm to the environment. Better definition as to exactly what the behavior component is and how it manifests itself is needed.
Using the indicator of open space as an example of something needing further research, the above research may have implications with regards to how much land a person aged 20 uses for residential purposes and a person aged 45 uses. If there is a difference then does one adjust for that, as this research suggests the implications of not doing so could be significant, thus measuring the change in age specific rates of land use to determine if behavior has changed? Getting around this by simply measuring the amount of land dedicated to each housing unit is a possible issue as, given unchanged age specific demand but an uneven age structure, there may be more people needing the living arrangement of a 20 year old over that of a 45 year old. Therefore a different overall amount of land per person will be picked up by such a measure but will most likely not truly reflect any change in behavior.
Another example is the VMT per person and any increases in this measure. Since two year olds do not drive, is it a valid argument to assess vehicle miles traveled to said two year old? Logic would say that a two year old does require specific trips by a licensed adult for the purpose of doctor's visits, day care, etc; However is it important to try and separate that or, assuming a relationship with fertility rates and child rearing, is age specific VMT for 30-35 year olds (the most likely to have a 2 year old) adequate since it is change in behavior that seems to be more important? This system of focusing in on drivers only is methodologically similar to how headship rates function.
Given possible issues with some of the common sprawl indicators, there may be issues with measurements of policy effectiveness. For instance, if a Transfer of Development Rights (TDR) program is placed into effect to limit housing construction and development during a period of high housing demand and then ten years later housing demand is markedly lower due to purely demographic effects, the program may appear to be effective at curbing development when in reality it may have had little or no impact on the levels of development.
There have been studies (Burnley, Murphy et al. 1997) that seek to determine if people who are looking to live in suburban environments are aware of the costs associated. The results show that most know that suburban living is more costly, economically and socially, than urban living but were willing to sacrifice significantly for suburban life. What this study did not do is try to ascertain what benefit these people felt was derived from a life in the suburbs. This is where age-specific residential preference may have something to offer. There is correlation as to what may in fact be the reason for the sacrifice of these people. That is the presence of children under the age of twenty and the likelihood of living in a suburban environment. Although there is no direct evidence, this follows a logical framework most would relate to.
What this suggests needs to happen is the traditional economic decision model for migration should be viewed in a different light. This decision model looks at the benefit of staying in the city, the benefit of leaving the city for a new area and the cost associated with moving. What many claim needs to happen is a punishment model whereas the costs associated with moving are jacked up to prevent migration out of the urban areas. However, if children and family environment are the primary source of utility for moving then a more rewarding system can be implemented which allows for programs that enhance the utility of staying in the city by creating a more family friendly urban environment.
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