A publication of the Indiana Business Research Center at IU's Kelley School of Business
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Taking the Hometown Discount: What is the Daily Commute Worth to You?

What is the cost of your daily work commute?  Most of us probably don’t think beyond the gas, but the true cost calculation of commuting goes beyond the physical cost of gasoline and automobile wear. True commuting costs should also include the lost productivity of idle time sitting in traffic and the emotional cost of the drive, sitting in traffic and for long commutes, being further removed from family and familiar surroundings. While traditional accounting methods can be used to calculate the monetary costs of commuting, the emotional costs are more difficult to quantify.

Rather than trying to determine the cost directly, this study utilized revealed preferences of job seekers in the reemployment market. The study examined unemployment insurance claims for a six-year period (2004-2009). Using data and methodology from previous research, the study developed a proximity variable based on ZIP codes of claimants and employment. The results show that while people would accept jobs closer to their home at a reduced wage, they would not wait longer for such a job to materialize.

This analysis concluded that the public valued commuting in Indiana, both in physical and emotional terms, to be $2,290 annually.

Research Method

This study is a continuation of a working paper examining the Indiana labor market. The Zimmer (2011) study focused on age using an Ordinary Least Squares (OLS) model to test for age bias while controlling for additional mitigating factors. The study found that businesses appreciate the experience and wisdom that comes with an aged workforce, but that beyond the age of approximately 50, age became a liability.

The test for hometown bias used the same data as the Zimmer analysis, which was based on 2004 to 2009 unemployment claims. The analysis focused on ZIP code information pertaining to the applicant’s home address and the employer after reintegration and tested for wage disparities. Controls were established for age, education, race and gender affects (Braun, 2011; Burr et al., 1996; Iversen and Rosenbluth, 2006; Moore, 2010; Niessen, 2006; Warr and Jackson, 1984). View more methodology»


Table 1 shows the influence of the variety of independent variables considered in determining wage differences for people moving through the unemployment insurance (UI) system between 2004 and 2009.

Table 1: Difference Between Wages Before Unemployment and After

Independent Variable Difference ($)
Total Weeks Claimed -$18
Same Industry $1,597
Wage Before Claim* -$1
Age $0**
Gender: Male $945
Proximity of Job to Home -$572
  Race:  White $357

*Second and third quarter average
** Not statistically significant at the 1 percent level.
Source: Indiana Department of Workforce Development

Each week of unemployment reduced an individual’s reemployment quarterly wages by $18 on average. The results indicated that the longer an individual waits to find reemployment, the more this negatively impacts the wage at which they will be hired back compared to their previous wage. The total weeks claimed variable was subject to selection bias. Better qualified individuals justifiably deserve higher compensation and would likely be removed quickly from the reemployment market. The inclusion of previous wages, demographic and educational variables should have largely captured the influence of employee qualification and helped control for selection bias.

The cost of switching industries grew as a person acquires skill and experience with a particular trade. The ability to leverage acquired skills and experience for higher wages was evident by the premium paid to those workers able to stay within a particular industry.

The most significant predictor of a person’s wages emerging from the reemployment market was the salary of the individual prior to entry. The results indicated that the potential of emerging from the reemployment market with wages equal to or higher than previous wages was unlikely.


Unlike the previous study, the age of unemployment was statistically insignificant. However, the previous study examined this variable by age cohort, and it was only at that time did it reveal its significance and switch from positive to negative in advancing years. The results would have likely repeated and been consistent if the data were completed by age cohort.

Race and Gender

Race and gender results were statistically significant. As previously noted, the data do not provide for the number of hours worked, which may have partially explained these results. The results generally indicated a difference observed in the gender and racial variables, favoring white and male claimants.


The link between wages and education within the reemployment market was positive and statistically significant. Outside of a doctorate, the results indicated that the more education a person obtains, the higher the premium in quarterly wage differential firms were willing to pay.

Table 2: The Link Between Wages and Education within the Reemployment Market

Education Post Unemployment Difference
Doctorate $1,014
Master's $1,519
Bachelor's $1,425
3 Years Technical/Vocational Education $485
2 Years Associate/ Vocational Education $908
1 Year Technical/Vocational Education $425
High School $160

Source: Indiana Department of Workforce Development


The occupation variable results were diverse. Some industries such as engineering and heavy construction did very well in reemployment, while others, such as the military and food service, did poorly.

Table 3: The Link Between Wages and Occupation within the Reemployment Market

Occupations Post Unemployment Difference
Management -$548
Business and Financial Operations -$437
Computer and Mathematical $275*
Architecture and Engineering $378
Life, Physical, and Social Science -$982
Community and Social Service -$1,035
Legal -$585*
Education, Training, and Library Occupations -$1,051
Arts, Design, Entertainment, Sports, and Media -$951
Health Care Practitioners and Technical -$146*
Health Care Support -$822
Protective Service -$1,323
Food Preparation and Serving Related Occupations -$1,441
Building and Grounds Cleaning and Maintenance -$1,355
Personal Care and Service -$1,287
Sales and Related -$1,000
Office and Administrative Support -$589
Farming, Fishing, and Forestry -$1,450
Construction and Extraction -$113*
Installation, Maintenance, and Repair $433
Production -$243
Transportation and Material Moving -$130*
Military Specific -$2,493

* Not statistically significant at the 1 percent level.
Source: Indiana Department of Workforce Development


The interesting aspect of this study was the proximity. Those finding work within the same ZIP code of residence generally accepted a discount in quarterly wage of $572. On an annual basis, people had a willingness to pay approximately $2,290 annually for the opportunity to work closer to home (as expressed by a hometown wage discount). Interestingly, when switching the dependent variable to total weeks, it was determined that individuals spend no additional time searching for employment in close proximity. While willing to take a lower salary for working closer to home, people did not delay taking a job for the sake of proximity.

The authors would like to thank Lori Wasson at the Indiana Department of Workforce Development for assistance in coding and extracting data from the Indiana Workforce Intelligence System (IWIS) data warehouse, a partnership of the Indiana Department of Workforce Development, Commission for Higher Education and Indiana Business Research Center.


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Timothy E. Zimmer, Ph.D.
Manager, Research and Analysis Division of the Indiana Department of Workforce Development

Sam Forrest
Economic Analyst, Research and Analysis Division of the Indiana Department of Workforce Development