ISPRS, Vol.34, Part 2W2, “Dynamic and Multi-Dimensional GIS”, Bangkok, May 23-25, 2001 
PROXIMITY AND ACCESSIBILITY TO SUITABLE JOBS 
AMONG WORKERS OF VARIOUS WAGE GROUPS 
Fahui WANG 
Department of Geography, Northern Illinois University 
DeKalb, IL 60115-2854, U.S.A. 
Fax: 815-753-6842, E-mail: wang@geog.niu.edu 
Keywords: job proximity, job accessibility, GIS, suitable jobs. 
Abstract 
This research proposes two indexes, job proximity and accessibility, to measure resident workers’ locational advantage with respect 
to their suitable job markets. Job proximity is designed to capture the spatial separation between residents and jobs. Job 
accessibility measures one’s ability to overcome such separation that may be affected by transportation means, road network, 
congestion, and intensity of competition for jobs among workers. The research suggests that in Cleveland in 1990 the mean wage 
rate of $30,000 is a critical turning point: below this level, the higher the mean wage rate in a residential area, the farther the area is 
away from the jobs; above the level, the trend is reversed. In other words, below a wage threshold, workers tend to trade better and 
more spacious housing (usually farther away from jobs) for more commuting; but above the threshold, workers retreat for saving in 
commuting (pertaining to their high opportunity cost of commuting). Although low-wage workers enjoy better job proximity, many of 
them (particularly some inner-city residents) have the worst job accessibility because of their limited mobility. Job proximity declines 
with distance from the CBD and conforms to the monocentric model, so does job accessibility but to a less degree. Since workers 
with various wages respond differently to job access, the distribution of mean wage rates in the metropolitan area is hardly 
monocentric. 
INTRODUCTION 
Many urban policy researchers recognize the profound 
impacts of lack of employment opportunities in some areas 
in a city ranging from social disorders (Wilson, 1996) to 
criminal behavior (Freeman, 1996; Wang and Minor, 2000), 
but disagree on its causes. Some attribute to, at least 
partially, the spatial separation between residence and 
employment such as employment decentralization and 
residential segregation (Kain, 1968; Ihlanfeldt and Sjoquist, 
1990; Immergluck, 1998). Others suggest that it is caused by 
socioeconomic factors including vehicle ownership (Taylor 
and Ong, 1995) and racial discrimination (Ellwood, 1986). 
Whether it is a spatial or nonspatial problem leads to 
different policy remedies. 
This research uses two indexes, job proximity and job 
accessibility, to distinguish clearly spatial factors from other 
factors. Job proximity is designed to capture the spatial 
separation between residents and jobs. Job accessibility 
measures one’s ability to overcome such a separation that 
may be affected by transportation means, routes, 
congestion, and intensity of competition for jobs among 
workers. The research compares the two measures among 
resident workers of various wage groups in attempt to reveal 
who have the true advantage with respect to job access. 
Although the purpose of this paper is not to explain commute 
patterns or residential search behavior, findings from the 
research shed light on such issues. 
The development of job proximity index follows Wang (2000) 
with one important improvement. Wang (2000) does not 
consider the segmented labor markets, and assumes all jobs 
are equally feasible for resident workers regardless 
occupations or wage rates. This research considers only 
those jobs within the same wage group of resident workers 
as their suitable jobs. The job accessibility index is based on 
Shen (1998) with one remedy—accounting for the 
congestion effect in areas with higher-density jobs or 
residents. Shen (1998) limits his analysis of job accessibility 
to low-wage workers in the inner city. This research 
evaluates job proximity and accessibility among workers of 
all wage groups at all locations in a metropolitan area. By 
doing so, the research is interested in the comparison 
among workers of various wage groups and their possible 
different responses to job access in terms of residential 
choice and commute behavior. 
While many socioeconomic characteristics may play a role 
affecting workers’ job access (Shen, 2000; Wang, 2001), the 
research focuses on the wage rates. There are several 
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reasons for this strategy. First, the classic urban economic 
theory considers income (wage as a surrogate) as the most 
important factor in determining the residential location. In 
order to test the theory, this research analyzes how workers 
in various wage groups desire and respond to job access. 
Second, wage serves as an indicator to segment the job 
markets and identify suitable jobs for workers (Immergluck, 
1998; Shen, 1998). Such information (jobs by wage rates) is 
available the Census for Transportation Planning Package 
(CTPP) data used for this research. Third, wage is perhaps 
the most important determinant for vehicle ownership and 
thus affects job accessibility. 
After a brief discussion of data sources and the study area, 
the paper explains the measures of job proximity and 
accessibility in separate sections. Then findings are 
summarized using the two measures across all locations in 
the study area. The paper is concluded with a summary and 
discussion of policy implications. 
DATA SOURCES AND STUDY AREA 
This research uses the 1990 Census for Transportation 
Planning Package (CTPP) Urban Element provided by the 
Bureau of Transportation Statistics (1996). The Urban 
Element of CTPP is aggregated at the level of Traffic 
Analysis Zone (TAZ) in Cleveland, Ohio. The CTPP is 
composed of three parts. Part 1 is similar to traditional 
census data by area of residence, and has information such 
as number of resident workers and breakdowns to various 
wage groups, mean wage rate, mean commute time, and 
household vehicle availability. Part 2 is by area of work 
(unique among all census products), and has number of jobs 
and breakdowns to wage groups. Part 3 provides very 
detailed journey-to-work information, such as number of 
commuters from a TAZ to another TAZ by a specific mode 
(e.g., drive-alone, car-pool, public bus) and average 
commute time between them. The spatial GIS data of the 
study area (often referred to as coverage) are from the 
Environmental Systems Research Institute, Inc. (2000) web 
site, including: (1) the TAZ coverage, (2) the coverage of 
urbanized areas, and (3) the road network coverage. 
The study area is Cleveland of Ohio, a site selected by the 
author for a research project funded by the National Institute 
of Justice. The 1990 CTPP data in the Cleveland region are 
compiled by the Northeast Ohio Areawide Coordinating 
Agency (NOACA) and include five counties: Cuyahoga, 
Geauga, Lake, Lorain and Medina (see Figure 1). As the 
research focuses on the nonagricultural jobs, the job market