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Does generalizing density functions better explain urban commuting? Some evidence from the Los Angeles region

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  • Shunfeng Song

Abstract

The assumption thaturban workers economize on commuting is implicit in urban economic theory. Yet it has been challenged by some recent studies. This study estimates commute flows implied by three urban density functions: monocentric, polycentric, and dispersive. A polycentric density function generalizes the standard monocentric model by assuming that employment and worker residences are distributed in a pattern consistent with several employment centres, not just one. A dispersive density function further generalizes the polycentric model by assuming that urban residents not only value access to employment centres but also value access to the overall job opportunities in their location choices. It is found that an urban density function better predicting the actual spatial patterns also better explains the actual commuting behaviour. This finding helps to preserve the assumption that urban workers make attempts to economize on commuting in their location choices.

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  • Shunfeng Song, 1995. "Does generalizing density functions better explain urban commuting? Some evidence from the Los Angeles region," Applied Economics Letters, Taylor & Francis Journals, vol. 2(5), pages 148-150.
  • Handle: RePEc:taf:apeclt:v:2:y:1995:i:5:p:148-150
    DOI: 10.1080/135048595357483
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    1. Small, Kenneth A & Song, Shunfeng, 1992. ""Wasteful" Commuting: A Resolution," Journal of Political Economy, University of Chicago Press, vol. 100(4), pages 888-898, August.
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    Cited by:

    1. Zhuo Chen & Seong-Hoon Cho & Neelam Poudyal & Roland K. Roberts, 2009. "Forecasting Housing Prices under Different Market Segmentation Assumptions," Urban Studies, Urban Studies Journal Limited, vol. 46(1), pages 167-187, January.
    2. Vincent Viguié, 2015. "Cross-commuting and housing prices in a polycentric modeling of cities," Policy Papers 2015.03, FAERE - French Association of Environmental and Resource Economists.

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