* We would like to thank K. E. McConnell, Paul Gottlieb, Arthur O’Sullivan, Marlon Boarnet, and anonymous referees for valuable comments.
URBAN GROWTH EXTERNALITIES AND NEIGHBORHOOD INCENTIVES: ANOTHER CAUSE OF URBAN SPRAWL?*
Article first published online: 20 MAR 2013
© 2013, Wiley Periodicals, Inc.
Journal of Regional Science
Volume 53, Issue 2, pages 332–348, May 2013
How to Cite
Cinyabuguma, M. and McConnell, V. (2013), URBAN GROWTH EXTERNALITIES AND NEIGHBORHOOD INCENTIVES: ANOTHER CAUSE OF URBAN SPRAWL?. Journal of Regional Science, 53: 332–348. doi: 10.1111/jors.12008
- Issue published online: 26 APR 2013
- Article first published online: 20 MAR 2013
- Received: September 2011; revised: March 2012; accepted: May 2012.
ABSTRACT This paper suggests a cause of low density urban development or urban sprawl that has not been given much attention in the literature. There have been a number of arguments put forward for market failures that may account for urban sprawl, including incomplete pricing of infrastructure, environmental externalities, and unpriced congestion. The problem analyzed here is that urban growth creates benefits for an entire urban area, but the costs of growth are borne by individual neighborhoods. An externality problem arises because existing residents perceive the costs associated with the new residents locating in their neighborhoods, but not the full benefits of new entrants which accrue to the city as a whole. The result is that existing residents have an incentive to block new residents to their neighborhoods, resulting in cities that are less dense than is optimal, or too spread out. The paper models several different types of urban growth, and examines the optimal and local choice outcomes under each type. In the first model, population growth is endogenous and the physical limits of the city are fixed. The second model examines the case in which population growth in the region is given, but the city boundary is allowed to vary. We show that in both cases the city will tend to be larger and less dense than is optimal. In each, we examine the sensitivity of the model to the number of neighborhoods and to the size of infrastructure and transportation costs. Finally, we examine optimal subsidies and see how they compare to current policies such as impact fees on new development.