"Wasteful" Commuting: A Resolution
AbstractA debate over the empirical underpinnings of urban economic models is emerging under the unlikely rubric of "wasteful commuting." Hamilton (1982) shows that a commonly used monocentric model, in which employment and population densities decline exponentially from a center, greatly underpredicts actual commuting distances in typical U.S. and Japanese metropolitan areas. He concludes that the monocentric model is fundamentally flawed. This conclusion is challenged by White (1988b), who examines the cost-minimizing assignment of households to residential locations, taking density patterns as they are and measuring cost by travel time. White finds that for a sample of U.S. metropolitan areas, only 11 percent of actual commuting cost is in excess of the cost-minimizing amount, rather than the 87 percent found by Hamilton. Hamilton (1989) and Cropper and Gordon (1991), using variations of White's technique, obtain results intermediate between these extremes.
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Bibliographic InfoArticle provided by University of Chicago Press in its journal Journal of Political Economy.
Volume (Year): 100 (1992)
Issue (Month): 4 (August)
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Other versions of this item:
- Small, Kenneth A. & Song, Shunfeng, 1992. ""Wasteful" Commuting: A Resolution," University of California Transportation Center, Working Papers qt5142n2ts, University of California Transportation Center.
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- Hamilton, Bruce W, 1982. "Wasteful Commuting," Journal of Political Economy, University of Chicago Press, vol. 90(5), pages 1035-51, October.
- Wheaton, William C., 1974. "Linear programming and locational equilibrium : The Herbert-Stevens model revisited," Journal of Urban Economics, Elsevier, vol. 1(3), pages 278-287, July.
- Griffith, Daniel A., 1981. "Modelling urban population density in a multi-centered city," Journal of Urban Economics, Elsevier, vol. 9(3), pages 298-310, May.
- Cropper, Maureen L. & Gordon, Patrice L., 1991. "Wasteful commuting: A re-examination," Journal of Urban Economics, Elsevier, vol. 29(1), pages 2-13, January.
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