Spatial distributions of job accessibility, housing rents, and poverty: The case of Nairobi
Shohei Nakamura and
Paolo Avner
Journal of Housing Economics, 2021, vol. 51, issue C
Abstract:
The inter-connectedness of workers’ residential locations and job opportunities is a key determinant of labor market outcomes. This study provides an analysis of the spatial distributions of job accessibility, housing rents, and poverty in a large African city. In Nairobi, Kenya, workers and jobs are not well connected: On average, residents can access fewer than 10 percent of existing jobs by foot within an hour. Even using a minibus, they can reach only about a quarter of jobs. This study further demonstrates that poorer households and residents living in informal settlements are even more limited. Living closer to job opportunities is costly in Nairobi. Not only are housing quality and living conditions frequently better in such areas, but the high value placed on job accessibility also makes these areas more expensive. This severely affects the residential location choices of low-income households.
Keywords: Job accessibility; Urban poverty; Slums; Urban planning; Housing rent (search for similar items in EconPapers)
JEL-codes: O18 R14 R21 R31 R41 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S1051137720300796
Full text for ScienceDirect subscribers only
Related works:
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:eee:jhouse:v:51:y:2021:i:c:s1051137720300796
DOI: 10.1016/j.jhe.2020.101743
Access Statistics for this article
Journal of Housing Economics is currently edited by H. O. Pollakowski
More articles in Journal of Housing Economics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().