Measuring Improvements in the Movement of Highway and Intermodal Freight
The overall focus was productivity of transportation industries (including the trucking industry), not the performance of the highway system or of FHWA relative to freight productivity. It was noted, however, that transportation infrastructure investment has an effect on transportation productivity, which in turn can be a big contributor to the bottom line of U.S. industry and the economy.
The panelists generally agreed on the difficulties in measuring transportation industry performance. Randall Eberts, Assistant Vice President and Economist of the Cleveland Federal Reserve Bank maintained that several levels of economic performance must be considered in linking public capital infrastructure with overall economic productivity: 1) performance of the transportation facility (e.g., efficiency, condition); 2) performance of the transportation industry as a whole (e.g., how elements work together to provide productive service); and 3) aggregation from the local economy to the international economic picture.
Traditional industry measures of physical productivity and performance, such as route-miles, number of terminals, and percentage of empty vehicle-miles, were identified, as well as labor productivity and multifactor productivity measures (e.g., output per unit of combined labor, capital, and intermediate outputs). Firm-level measures were also identified, such as dock productivity, pickup and delivery productivity, freight bills handled per hour, and average load factors.
Difficulties in measuring productivity in the motor carrier industry were noted. In particular, Paul Roberts, President of Transmode Consultants, noted that the measure of productivity is complicated because of difficulties in measuring inputs and outputs, as well as the different outlooks of economists and engineers (e.g., economists measure productivity in dollars, while engineers use physical measures). Some of the presentations suggested that traditional measures in terms of ton-miles carried are deficient because they fail to account for the quality of service provided; that is, more ton-miles carried per unit of labor appears to be a productivity improvement, but it does not capture improvements in reliability and on-time delivery.
Bahar Norris, Senior Economist at the U.S. DOT Volpe Center noted that changes in price are not the same as changes in productivity and made a distinction between “performance” measures and “productivity” measures. For example, she suggested that price reductions that occurred in the 1980s were the result not of productivity factors but of declines in fuel prices and a reduction in excess profits due to increased competition. Norris also noted that single factor productivity measures, such as those considering only a change in labor units, are deficient because they fail to consider all factors in production. According to Thomas Corsi, Professor of Transportation, Business, and Public Policy at the University of Maryland, multifactor productivity measures are also suspect because they are highly sensitive to the specific inputs and outputs selected and to the weights given to each measure.
Instead of multifactor productivity measures, the motor carrier industry tends to use three indicators:
Annual miles per truck
Average load per truck