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VII. Conclusions

Our evidence supports the argument that suburbanized employment -- or sprawl -- is associated with shorter distance commutes on average. This is not to say that commutes are shortening as cities expand their footprint; indeed, they seem to be slowly lengthening (Kahn, 2000). Other factors, such as rising incomes, are apparently generating more and longer trips to work. Contrary to much conventional folklore, however, the marginal effect of job suburbanization appears to be to bring jobs and workers closer. Put another way, the average commute would be longer still if jobs were not suburbanizing.

A closer look reveals that this is not a transparent outcome. There are strong differences by industry, for example. The suburbanization of construction, wholesale, and service employment is associated with shorter commutes, while manufacturing and finance deconcentration (weakly) explain longer commutes. These results may reflect a combination of industry agglomeration effects, differential job location stability by industry, and historical transitions.

What does this mean? First, our study is exploratory and thus preliminary. Many loose ends remain, suggesting numerous ways to refine and extend our understanding of these relationships. On the one hand, the AHS data do not allow U.S. to test how commute duration has changed. This ignores the substantial role of congestion in urban form and behavior debates (Solow, 1973; Wheaton, 1998). Other evidence suggests that congestion may be lower in outlying areas, so the dispersal of employment to outlying counties within metropolitan areas may actually reduce commute duration more than it does commute distance. Alternatively, if job dispersal to outlying counties is associated with a higher amount of non-work travel by affluent households living in those areas, commute duration could increase despite a slight decline in commute distance. This is because peak period travel duration is only partially accounted for by work trips; non-work trips make up a growing majority of trips made during peak periods (Giuliano, 1991).

In addition, while these results partially support the Crane (1996) hypothesis that commutes are longer for individuals with greater uncertainty about their future job locations and higher moving costs, our data do not permit us to explore that conjecture in detail.

Finally, even if further study provides consistent support for the "sprawl shortens commutes" story, the public policy implications require more discussion. On the one hand, there is the issue of whether, on net, jobs follow workers to the suburbs or vice versa. The evidence is mixed on either count, suggesting the simultaneity of this process is challenging to nail down empirically. If jobs returned to the city, is it possible that workers would follow suit? On the other hand, neither the influence of urban form on travel behavior nor the merits of concentrated versus dispersed urban growth are well understood. The former is yet another complex set of nuanced behaviors awaiting better data and empirical strategies (Boarnet and Crane, 2001). Regarding the latter, we do not know how the social and economic costs of sprawl, however measured, compare with their benefits (Crane and Greenstein, 2002). A key purpose of our study is to explore the underlying behaviors needed for both kinds of evaluations.

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