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Commuting time stability: A test of a co-location hypothesis

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  • Kim, Chansung

Abstract

During the past few decades, the populations of many US and European cities have shown the same residence and workplace mobility patterns: Annually, approximately 10% of the population changed residences and approximately 20% of employed workers changed workplaces within the same metropolitan area. Even though the Seattle metropolitan region experienced a substantial amount of residential and workplace mobility and a boom in employment and population in the 1990s, the morning commute time and distance was roughly constant. To explain this situation, researchers have proposed a co-location hypothesis, that is, residents and workers will change their residence or workplace or both adapt to worsening congestion. This research attempted to shed light on the mechanism of the co-location hypothesis using the Puget Sound Transportation Panel data consisting of seven waves of two consecutive years between 1989 and 1997 conducted by the Puget Sound Regional Council. Because most studies used cross-sectional work trip data to study location and commuting, the underlying relationship between location and commuting was limited. This study attempted to understand commuting patterns by residential and workplace changers. The study found that the commuting patterns of residence and workplace location changers were the same and this was reinforced by existing gravity model. Particularly, when workers change their locations, they prefer similar commuting zone (i.e., time and distance) compared to their previous commuting zone. These behaviors caused the average commute time and distance to be stable, regardless of high residence and workplace mobility, and the rapid growth of employment and population.

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Bibliographic Info

Article provided by Elsevier in its journal Transportation Research Part A: Policy and Practice.

Volume (Year): 42 (2008)
Issue (Month): 3 (March)
Pages: 524-544

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Handle: RePEc:eee:transa:v:42:y:2008:i:3:p:524-544

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Citations

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Cited by:
  1. Sevcíková, Hana & Raftery, Adrian E. & Waddell, Paul A., 2011. "Uncertain benefits: Application of Bayesian melding to the Alaskan Way Viaduct in Seattle," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(6), pages 540-553, July.
  2. Tillema, Taede & van Wee, Bert & Ettema, Dick, 2010. "The influence of (toll-related) travel costs in residential location decisions of households: A stated choice approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(10), pages 785-796, December.
  3. Parent, Olivier & LeSage, James P., 2010. "A spatial dynamic panel model with random effects applied to commuting times," Transportation Research Part B: Methodological, Elsevier, vol. 44(5), pages 633-645, June.
  4. Gershenson, Seth, 2013. "The causal effect of commute time on labor supply: Evidence from a natural experiment involving substitute teachers," Transportation Research Part A: Policy and Practice, Elsevier, vol. 54(C), pages 127-140.
  5. Joly, I., 2011. "Test of the relation between travel and activities times : different representations of a demand derived from activity participation," Working Papers 201103, Grenoble Applied Economics Laboratory (GAEL).
  6. David Levinson & Ahmed El-Geneidy, 2007. "The Minimum Circuity Frontier and the Journey to Work," Working Papers 200905, University of Minnesota: Nexus Research Group.
  7. Rafael Henrique Moraes Pereira & Tim Schwanen, 2013. "Commute Time in Brazil (1992-2009): Differences Between Metropolitan Areas, by Income Levels and Gender," Discussion Papers 1813a, Instituto de Pesquisa Econômica Aplicada - IPEA.

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