Are truck drivers underpaid?
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Are truck drivers underpaid?Dale Belman a & Kristen Monaco ba School of Labour and Industrial Relations , South Kedzie Hall, Michigan State University ,East Lansing, MI 48824-1032, USAb Department of Economics , California State University Long Beach , 1250 Bellflower Blvd,Long Beach, CA 90840, USAc Department of Economics , California State University Long Beach , 1250 Bellflower Blvd,Long Beach, CA 90840, USA E-mail:Published online: 16 Aug 2006.
To cite this article: Dale Belman & Kristen Monaco (2005) Are truck drivers underpaid?, Applied Economics Letters, 12:1,13-18, DOI: 10.1080/1350485042000291411
To link to this article: http://dx.doi.org/10.1080/1350485042000291411
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Are truck drivers underpaid?
Dale Belmana and Kristen Monacob*
aSchool of Labour and Industrial Relations, South Kedzie Hall,Michigan State University, East Lansing, MI 48824-1032, USAbDepartment of Economics, California State University Long Beach,1250 Bellflower Blvd, Long Beach, CA 90840, USA
There is an emerging debate over whether truck drivers are underpaidgiven their human capital and working conditions. Using data from the2000 Current Population Survey, the pay differentials between truckdrivers and other blue collar occupations are investigated. While truckdrivers appear to receive a small premium in their hourly wage comparedto workers with similar skill requirements, they receive substantial pre-mium in their weekly wage. This weekly wage differential is primarilythe result of a substantially longer work week.
It is well established in the literature that truckdriving became a less desirable occupation afterderegulation in the late 1970s, when wages plum-meted significantly.1 Average hourly wages foremployee truck drivers fell from $16.00 to $12.72over the period 1979 to 1993, a decrease of 20.5%.2
After bottoming out in 1993, hourly wagesrebounded somewhat and reached $13.70 in 2000, a
7.7% increase.Truck drivers face demanding working condi-
tions, especially long-haul truck drivers (Belzer,2000; Belman et al., forthcoming). Drivers hoursof work are governed by Federal Hours of ServiceRegulations which limit drivers to 60 hours of workin a seven day period. It is widely acknowledged inthe industry that long-haul drivers routinely violate
these regulations (Belman et al., 2004; Braver et al.,1992; Beilock, 1995) and often work considerablylonger than 60 hours per week.
In combination with the long hours of work,the post-deregulation decline in drivers real earningshas fuelled discussion over whether drivers are
adequately compensated for their work. The viewthat drivers pay is too low is common currencyamong those who drive, but such views are notlimited to drivers. Belzer (2000) argues that sincederegulation the non-union sector in trucking hastaken on many of the characteristics of sweatshops:below subsistence wages, overwork, and unpleasantand unhealthy working conditions. Others, such as
Corsi (2001) and Beilock (2001, 2003), argue againstsuch conclusions. In particular, Beilock notes thatdrivers earnings are closely aligned with those ofindividuals with similar education levels.
How might this issue be addressed? Economictheory suggests that wages are largely determinedby an individuals productivity, however, pay is notdetermined solely by productivity. The theory of
compensating differentials implies that pay is influ-enced by working conditions. Employers who pro-vide substandard working conditions will be unableto attract a sufficient supply of workers at the goingwage rate, which compels them to offer an incrementto pay to attract workers who would otherwise
*Corresponding author. E-mail: email@example.comResearch on deregulations impact on the trucking labour market includes Belzer (1995), Rose (1987), Hirsch (1988, 1993),Hirsch and Macpherson (1998), and Belman and Monaco (2001).2All figures are calculated in 2000 dollars using data from the Current Population Survey. Data from the May Survey is usedin 1979 and from the Outgoing Rotation Groups files after 1979.
Applied Economics Letters ISSN 13504851 print/ISSN 14664291 online # 2005 Taylor & Francis Group Ltd 13
Applied Economics Letters, 2005, 12, 1318
choose jobs with better conditions. As labour mar-
kets are characterized by a certain level of fluidity,
this compensating differential applies not only to
similar jobs within an industry but across industries
and occupations. Given the demanding nature of
truck drivers jobs, we would expect that if truck dri-
vers were underpaid their wages would resemble
those of workers with similar human capital working
under better conditions.
One way to determine whether the market is
compensating drivers for their working conditions
is to isolate the component of individuals wages
associated with their occupation and compare this
to that of similar occupations.3 This is done by
estimating a wage model with an indicator variable
for each occupation but no overall intercept. The
coefficient on the occupation indicator variable is
the occupational wage component, which reflects
the market valuation of the advantages and disadvan-
tages of that occupation. The estimated magnitudes
of the occupation components can be compared
between occupations and judgments made about the
appropriateness of the implied wage differentials.
This approach is necessarily somewhat judgmental
as there is seldom a perfect fit between occupations.
Nevertheless, it provides a workable means of explor-
ing the issue of driver underpay.4
We use data from the year 2000 Current
Population Survey Outgoing Rotation Groups files
to estimate a conventional human capital wage equa-
tion with controls for educational attainment, age,
gender, race and ethnicity, union membership, region
of residence and residence in a metropolitan area. We
limit our sample to those individuals employed in the
private sector only and exclude individuals who are
self-employed. The 99 821 individuals in the resulting
data were engaged in 484 different three-digit private
sector occupations according to the CPS definitions.
The model includes indicator variables for each of
these 484 occupations. To better understand the
occupational effects of employment in trucking, we
separate truck drivers employed in the trucking
industry from those employed in other industries.
We estimate this model using in turn log hourly
earnings and log weekly earnings as the dependent
variable, and report results for each of these respec-
tively in Tables 1 and 2.5 We use the log wage
estimates to construct predictions of the hourly
wage by occupation, and report these in the tables.
The predictions are standardized for human capital
by calculating the predicted wage at sample mean
human capital characteristics.
For each table, we display the occupational title in
column 1, followed by the occupation code used in
the CPS in column 2, the actual mean hourly earnings
by occupation (unadjusted for human capital or other
characteristics) in dollars in column 3, and by the
earnings predicted by the regression model (calcu-
lated at the mean human capital characteristics),
also in dollars, in column 4. In the next column, we
show the difference between the earnings of drivers in
the trucking industry and each of the other occupa-
tions, including truck driving outside of the trucking
industry, again in dollars. In the sixth column we
present the t-statistic that indicates whether the
difference is statistically significant. The last column
shows the sample size for the occupation, that is the
number of individuals in the sample in each occupa-
tion. In both tables, we restrict ourselves to occupa-
tions that have at least 80 observations to reduce the
effects of sampling variability. We believe that the
occupations in question are a representative subset
of the blue-collar occupations in our data and in
that sense the results in Tables 1 and 2 characterize
the patterns we found in the larger set of occupations.
Table 1 shows that the sample mean hourly
earnings for truck drivers employed in the trucking
industry is $15.67 while the earnings predicted at
sample mean human capital characteristics are
$13.64. A natural initial comparison is with truck
drivers employed outside of the trucking industry.
This occupation is comprised of drivers whose
work is similar to that of drivers within motor freight,
but it also includes local delivery drivers in light
trucks, construction drivers and others whose work
and working conditions are quite different from that
3An alternative would be to incorporate measures of working conditions into a conventional human capital model of wages.Although the numeric ratings for occupational characteristics are available from the Dictionary of Occupational Titles orfrom ONET, the incorporation of these measures into wage regressions has been problematic. Because of all these issues, fewarticles in the compensating differentials literature incorporate direct controls for occupational characteristics.4 Further explanation and an example of this approach is provided in Belman et al. (2002).5Hourly earnings are calculated as the ratio of average weekly earnings to actual hours last week. Actual rather than averagehours was used because employees who work irregular schedules report a value of variable hours for average hours and thisprecludes calculating an hourly wage. As many truck drivers work irregular schedules, use of average hours would excludelarge numbers of truck drivers. Although actual hours is a noisy representation of average weekly hours for an individual, theestimates of the hourly wage should be reasonably accurate given the size of the sample used in this study.
14 D. Belman and K. Monaco
Table 1. Comparing hourly earnings across occupations
Adjusted for human capital
Difference fromdrivers in trucking
t-stat. fordifference N
Motor Vehicle OperatorsTruck drivers-trucking industry 804 $15.67 $13.64 1308Truck drivers-other industries $13.11 $12.06 $1.57 2.910 1442
Transportation OperativesSupervisors, motor vehicle opers 803 $17.29 $13.98 $0.34 0.374 82Driver-sales workers 806 $14.35 $12.24 $1.40 1.948 155Bus drivers 808 $12.08 $11.36 $2.27 3.677 276Taxi cab drivers/chauffeurs 809 $11.21 $9.94 $3.70 6.063 215
OperativesPunching & stamping press oper 706 $12.33 $11.86 $1.78 2.200 90Grinding & polishing machine oper 709 $12.52 $12.31 $1.32 1.610 94Printing machine operators 734 $14.99 $13.42 $0.21 0.319 287Textile sewing machine operators 744 $8.56 $10.14 $3.49 6.400 423Painting and spraying machine oper 759 $13.78 $13.30 $0.34 0.464 168
Material Moving OperatorsOperating engineers 844 $17.53 $15.75 $2.11 2.778 215Crane and tower operators 849 $16.26 $13.62 $0.02 0.020 75Excavating & loading machine oper 853 $16.38 $15.50 $1.87 2.042 95Industrial truck/tractor equip oper 856 $12.58 $11.93 $1.70 2.927 485
LabourersStock handlers and baggers 877 $9.39 $9.61 $4.03 7.872 635Freight & material handler, nec 883 $11.81 $11.30 $2.34 4.157 522Labourers, ex construction (8769) 889 $11.65 $11.07 $2.56 4.876 1081
Precision ProductionAutomobile mechanics 505 $15.08 $13.77 $0.13 0.220 661Bus, truck, and engine mechanics 507 $16.15 $14.85 $1.22 1.797 341Aircraft engine mechanics 508 $18.74 $15.11 $1.47 1.716 108Heavy equipment mechanics 516 $16.29 $14.79 $1.16 1.511 174HVAC mech 534 $16.97 $14.91 $1.28 1.819 277Carpenters 567 $16.38 $14.85 $1.22 1.990 1021Electricians 575 $19.46 $16.42 $2.79 4.231 728Plumbers, pipefitters & steamfitters 585 $18.28 $15.78 $2.14 3.178 468Roofers 595 $15.89 $14.58 $0.94 1.172 150Machinists 637 $16.57 $14.53 $0.90 1.411 509Butchers and meat cutters 686 $12.38 $12.57 $1.07 1.658 275Bakers 687 $11.27 $11.19 $2.44 3.563 152
Earnings estimates constructed from a log wage equation estimated with the 2000 Outgoing Rotation of the Current Population Survey. The wagedifference is calculated as (estimated earnings of drivers estimated earnings of other occupation).
Table 2. Comparing weekly earnings across occupations
Adjusted for Human Capital
Difference fromtruck drivers
Motor Vehicle OperatorsTruck drivers-trucking industry 804 $708.54 $603.01 1986Truck drivers-other industries $554.77 $501.88 $101.13 4.105 2032
Transportation OperativesSupervisors, motor vehicle opers 803 $779.94 $615.26 $12.25 0.289 106Driver-sales workers 806 $614.17 $527.76 $75.25 2.245 206Bus drivers 808 $421.40 $457.35 $145.67 5.300 383Taxi cab drivers/chauffeurs 809 $484.80 $422.20 $180.82 6.438 362
OperativesPunching & stamping press o...