The Legacy of the Interstate Commerce Act and Labor: Legislation, Unionization, and Labor Earnings in Surface Transportation Services

State regulatory agencies regulated rates and entry for for-hire transportation within a state.

The Civil Aeronautics Board regulated fare and route entry (and exit) of air transport service.

The 1973 Regional Rail Reorganization Act (3R) was actually the initial legislation that addressed the financial performance of the rail industry. However, this Act did not address rate-setting or route restrictions.

See Winston et al. (1990) for a comprehensive analysis of the economic effects of partial deregulation of surface freight transport services.

Legislation that removed impediments to incumbent bus and rail carriers’ ability to abandon low-density routes might further contribute to unions avoiding significant erosion of their ability to continue negotiating relatively high wages. Servicing the more lucrative routes enhances these carriers’ ability to meet union wage demands.

Drivers in the private-carriage sector provide in-house transport service for non-trucking companies.

Additional analysis of the labor market effect of the MCA suggests that unionized trucking firms are not at a competitive disadvantage despite past findings of an erosion of the union wage premium in the for-hire sector (McMullen and Lee 1999).

Concurrent with the passage of the ICC Termination Act Congress passed the 1995 Airport Improvement Act (AIA), which prohibited state and local authorities from the regulation of rates, routes, or services within the transportation industry. States were still permitted to continue to exercise regulatory authority over safety, financial fitness, insurance, vehicle size and weight, and highway route controls for hazardous materials after the passage of the 1995 AIA.

1983 is chosen as the initial observation year due to the relatively small annual sample of individuals reporting their union status in the CPS sample prior to that date. In addition, choosing 1983 as the initial observation year avoids the use of pre 1980 CPS data that assigns the earnings of drivers who don’t report his/her earnings if they were a non-union, non-driver employed in a different industry (Henrickson and Wilson 2008; Hirsch and Schumacher 2004).

To account for individuals who do not report their earnings the CPS imputes earnings using an approach such that non-respondents are assigned ‘allocated’ reported earnings of a matched reporting ‘donor’, who has an identical mix of observable attributes (Hirsch and Schumacher 2004). However, rather than matching individuals by their exact age, or level of educational attainment, individuals are grouped into six categories. Hirsch and Schumacher show that when researchers include these regressors in a wage equation containing greater regressor detail than the matched categories, match bias leads to highly misleading results.

Information on rail switchmen and brakemen are generally included in the labor market analysis of previous work. Employment and wage findings for these occupations are excluded from the current analysis due to their extremely small sample sizes in the late 1990s and thereafter.

Further weakening union control over the labor supply of the for-hire driver work force following the ICC Termination Act created a challenge for the IBT to maintain standardized wages such that differences in returns to human capital investment should be minimized.

Data are stacked over time rather than reported as a true panel data set because each observation denotes information for a unique individual operative for each observation year.

Hourly wage rates are calculated by taking the ratio of individual workers’ weekly earnings and weekly hours worked.

Tables including estimation results on the control variables are available from the author on request.

In general statistical significance is achieved for these control variables when estimating Eq. (3). Smaller sample population makes achieving statistical significance more difficult when estimating the other wage equations. Nonetheless, F-scores are statistically significant for all estimations. Notable findings for the control variables include increased significance for returns to college education for truck drivers over time. The 1983 results on the college education wage differential derived when estimating Eq. (1) for this group of operatives is only 0.9 percent compared to a statistically significant differential of 7.4 percent by 2011. Given declining union density over the same time frame, this wage pattern is consistent with the notion that differences in returns to human capital investment are smaller when unions possess greater control over the labor supply. The negotiation advantage that is associated with such control allows unions to enforce wage standardization that minimizes wage differences that are attributable to differences in worker characteristics.

A shortcoming that is associated with the use of the CPS to estimate wages over time is the absence of measures that identify worker tenure on the job. Hence, the possibility of high turnover for low tenure transportation operatives following deregulation suggests that the wage erosion depicted in Fig. 4 may actually understate the true erosion of union wage premiums in trucking and busing services.

The extended period of increasing for-hire wage premiums for non-union drivers is consistent with the union threat effect concept, which argues that non-union employers increase wages to avoid the threat of unionization. Findings in Fig. 1 reveal that union density remained historically low for for-hire drivers during this period of increasing for-hire wage premiums for non-union drivers.

Note that the 1994 and 1995 sample observation years are excluded from the data set. Hence, the calculation of the industry premium erosion for conductors is made for an 11-year period rather than for 13 years.