Modeling the relation between income and commuting distance

Giulia Carra, Ismir Mulalic (), Mogens Fosgerau and Marc Barthelemy
Additional contact information
Giulia Carra: IPHT - Institut de Physique Théorique - UMR CNRS 3681 - Université Paris-Saclay - CNRS - Centre National de la Recherche Scientifique - DRF (CEA) - Direction de Recherche Fondamentale (CEA) - CEA - Commissariat à l'énergie atomique et aux énergies alternatives
Marc Barthelemy: CAMS - Centre d'Analyse et de Mathématique sociales - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique, IPHT - Institut de Physique Théorique - UMR CNRS 3681 - Université Paris-Saclay - CNRS - Centre National de la Recherche Scientifique - DRF (CEA) - Direction de Recherche Fondamentale (CEA) - CEA - Commissariat à l'énergie atomique et aux énergies alternatives

Post-Print from HAL

Abstract: We discuss the distribution of commuting distances and its relation to income. Using data from Denmark, the UK, and the US, we show that the commuting distance is (i) broadly distributed with a slow decaying tail that can be fitted by a power law with exponent $\gamma \approx 3$ and (ii) an average growing slowly as a power law with an exponent less than one that depends on the country considered. The classical theory for job search is based on the idea that workers evaluate the wage of potential jobs as they arrive sequentially through time, and extending this model with space, we obtain predictions that are strongly contradicted by our empirical findings. We propose an alternative model that is based on the idea that workers evaluate potential jobs based on a quality aspect and that workers search for jobs sequentially across space. We also assume that the density of potential jobs depends on the skills of the worker and decreases with the wage. The predicted distribution of commuting distances decays as $1/r^{3}$ and is independent of the distribution of the quality of jobs. We find our alternative model to be in agreement with our data. This type of approach opens new perspectives for the modeling of mobility.

Date: 2017-06-08
New Economics Papers: this item is included in nep-ure
Note: View the original document on HAL open archive server: https://cea.hal.science/cea-01568435v1
References: Add references at CitEc
Citations:

Published in Journal of the Royal Society Interface, 2017, 13 (119), pp.20160306. ⟨10.1098/rsif.2016.0306⟩

Downloads: (external link)
https://cea.hal.science/cea-01568435v1/document (application/pdf)

Related works:
Working Paper: Modeling the relation between income and commuting distance (2016)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:cea-01568435

DOI: 10.1098/rsif.2016.0306

Access Statistics for this paper

More papers in Post-Print from HAL
Bibliographic data for series maintained by CCSD ().