Are truck drivers underpaid?

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  • This article was downloaded by: [Lancaster University Library]On: 13 October 2014, At: 06:19Publisher: RoutledgeInforma Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House,37-41 Mortimer Street, London W1T 3JH, UK

    Applied Economics LettersPublication details, including instructions for authors and subscription information:http://www.tandfonline.com/loi/rael20

    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 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: kmonaco@csulb.edu1Research 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

    http://www.tandf.co.uk/journalsDOI: 10.1080/1350485042000291411

    Applied Economics Letters, 2005, 12, 1318

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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.

    14 D. Belman and K. Monaco

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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 o...