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
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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 ‘underpaid’given 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 driver’s 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 individual’s 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 protected] on deregulation’s 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 1350–4851 print/ISSN 1466–4291 online # 2005 Taylor & Francis Group Ltd 13
http://www.tandf.co.uk/journalsDOI: 10.1080/1350485042000291411
Applied Economics Letters, 2005, 12, 13–18
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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.
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Table 1. Comparing hourly earnings across occupations
Adjusted for human capital
Populationoccupationcode
Hourly earnings(unadjusted)
Predictedearnings
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).
Are
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Table 2. Comparing weekly earnings across occupations
–Weekly Earnings
–Adjusted for Human Capital
Populationoccupationcode
Weekly earnings(unadjusted)
Predictedearnings
Difference fromtruck drivers
t-stat. fordifference
Number ofobservations
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 oper 706 $496.27 $468.49 $134.52 3.793 118Grinding & polishing machine oper 709 $541.34 $501.46 $101.55 2.749 116Printing machine operators 734 $617.18 $536.87 $66.14 2.234 370Textile sewing machine operators 744 $334.91 $418.27 $184.74 7.455 528Painting and spraying machine oper 759 $557.36 $525.21 $77.80 2.390 220
Material Moving OperatorsOperating engineers 844 $709.83 $635.73 �$32.72 �0.962 289Crane and tower operators 849 $701.10 $557.97 $45.05 1.081 90Excavating & loading machine oper 853 $645.86 $618.52 �$15.51 �0.383 151Industrial truck/tractor equip oper 856 $519.41 $471.80 $131.21 5.093 642
LabourersStock handlers and baggers 877 $346.87 $377.27 $225.74 9.947 1555Freight & material handler, nec 883 $454.71 $445.31 $157.71 6.306 856Labourers, ex construction (8769) 889 $442.60 $424.82 $178.19 7.724 1637
Precision ProductionAutomobile mechanics 505 $634.97 $552.78 $50.24 1.849 1104Bus, truck, and engine mechanics 507 $685.64 $601.36 $1.65 0.054 431Aircraft engine mechanics 508 $806.37 $610.29 �$7.28 �0.188 130Heavy equipment mechanics 516 $710.87 $618.19 �$15.18 �0.435 206HVAC mech 534 $693.86 $594.45 $8.56 0.274 424Carpenters 567 $634.02 $563.90 $39.11 1.470 1890Electricians 575 $815.32 $645.98 �$42.97 �1.476 987Plumbers, pipefitters & steamfitters 585 $732.71 $622.91 �$19.90 �0.665 690Roofers 595 $557.59 $558.77 $44.24 1.269 254Machinists 637 $680.48 $577.62 $25.39 0.893 599Butchers and meat cutters 686 $508.31 $511.01 $92.00 3.179 370Bakers 687 $437.58 $419.44 $183.57 6.176 227
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).
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of freight drivers. Average hourly earnings for these
drivers are $13.11, while the predicted hourly earn-ings are $12.06, $1.57 less per hour than drivers inmotor freight. Motor freight drivers earn a premiumof 13.1% over employees with similar skills doing
similar work, but who may be less likely to workextended hours or be away from home for extendedperiods.
Comparing the earnings of drivers in motor freightwith those of other motor vehicle operatives againindicates that motor freight drivers earn a premium
over other drivers. Drivers in motor freight earn$1.40 (11.4%) more than driver sales workers, $2.27(20.1%) per hour more than bus drivers, and $3.70
(37.2%) more than taxi drivers; each difference issignificant at the 5% or better level.6
The balance of Table 1 compares drivers in motorfreight with non-transportation blue-collar occupa-
tions. Individuals in the first group, productionoperatives, are engaged in repetitive operations, typi-cally in a factory or other production facility. Similar
to truck driving, these jobs normally require nomore than a high-school degree and no more thana few months of occupation-specific training and
on-the-job experience. They provide better workingconditions than truck driving, at least with respect tohours of work and rest and time spent at home. Thewages predicted by our regression model indicate
that the hourly earnings of truck drivers in motorfreight are similar to those of painting and printingmachine operators but significantly greater than
that of sewing machine, punch press and grindingmachine operators.
The educational and training requirements for
labourers, manual workers involved in operationssuch as stock and freight handling, are similar tothose of truck drivers but labourers are less likely
to control expensive or powerful machinery.Although labourers’ duties often involve extendedperiods of heavy work, they are not characterizedby the extended working time and time away from
home issues that characterize the work of truckdrivers. Consistent with the lesser requirements ofthe labourers’ position, most labourers are paid
considerably less, between $2.34 and $4.03, thantruck drivers, and these differences are statisticallysignificant.
Material moving occupations involve the operationof heavy equipment. Proficiency in these occupationsmay require extended formal and on-the-job training;
they also involve exposure to weather and hazardous
conditions and may involve periods of time awayfrom home. Our estimates suggest that two of thethree construction occupations are paid more thandrivers (operating engineers and excavating machine
operators), while tower and crane operators havesimilar hourly earnings (crane and tower operators).Industrial truck and tractor equipment operators,
individuals who operate trucks and other movingequipment on factory premises and whose jobsinvolved skills similar to those of truck drivers, are
paid $1.70 per hour less than drivers. The lower payis consistent with a downward adjustment in compen-sation for the better conditions of industrial truck
operators.Finally, precision production occupations are blue-
collar jobs that require advanced vocational training,often three or four year apprenticeships. Some
of these occupations involve exposure to weather,various hazards in construction sites, and may alsorequire that workers spend part of the year away
from home. The predicted earnings of most of theseoccupations are $1.00 to $2.00 per hour more thanthose of truck drivers, and most of these differences
are statistically significant. The occupations for whichearnings are not significantly higher than those ofdrivers are those that do not involve extendedadvanced vocational training (auto mechanics and
roofers) or trades that formerly involved advancedskills but that have evolved into production jobs infactories (butchers, bakers and some machinists).
The pattern that emerges from the hourly wagedata indicates that truck drivers earn more thanworkers in manual occupations with similar training
requirements that do not entail the hours or workingconditions associated with truck driving. In contrast,drivers often earn considerably less than manual
occupations that involve advanced vocational train-ing and that may involve less favourable workingconditions.
The favourable position of truck drivers relative to
occupations with similar training requirementsbecomes more pronounced when weekly earningsare considered (Table 2). Drivers in motor freight
earn considerably more per week than drivers outsideof motor freight, transportation operatives, andlabourers. Drivers’ weekly pay is similar to that of
material moving operatives, including operatingengineers and excavating machine operators, andof precision production workers including aircraft
6A driver sales worker is typically a truck driver who delivers and positions goods. Soft drink and bakery drivers, who unloadtheir trucks and place the goods on store shelves are driver sales workers.
Are truck drivers underpaid? 17
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engine mechanics, plumbers and carpenters. On a
weekly basis, the earnings of drivers closely approach
those of electricians.
In combination, these results imply that truck
drivers are paid somewhat more per hour than
those employed in occupations with similar skill
requirements but better working conditions.
However, the longer weekly work hours of truck
drivers allow them to earn as much per week as
blue-collar workers in occupations requiring consid-
erably more skills and occupational training. An
interpretation of these results is that truck drivers
engage in a Faustian bargain in which they accept
long hours of work in return for earning as much
as workers engaged in manual occupations that
require more training and skills.
Nevertheless, it is possible that markets do not
compensate drivers for the full value of the disutility
associated with their working conditions. Economic
theory proposes that compensating differentials are
driven by the movement of marginal workers out of
employment with worse conditions and into employ-
ment with better conditions. Firms seeking to staunch
the flow of workers away from worse conditions,
must increase their pay, thereby generating a suffi-
cient compensating differential. This mechanism
relies on ease of movement between markets. Differ-
ences in the hours of work regulations between truck-
ing and the balance of the economy can impede such
movement. Movement from a 60-hour week in truck-
ing to a job with similar pay and somewhat better
conditions outside of trucking would be accompanied
by a one-third reduction in weekly take home pay.
The reduction in income associated with migration
out of the industry serves to restrain the arbitraging
of pay and working conditions. Although the
results of this inquiry suggest that driver pay is not
greatly out of line with the nature of their job, the
impediments to the smooth functioning of the
market suggests that moderate underpay may exist
and persist.
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