Stuck in the Slow Lane: Undoing Traffic Composition Biases in the Measurement of Trucking Productivity
AbstractIt is easy to confuse true productivity advances in transportation industries with changes in tonmiles per unit of input that are the result of changes in the composition of traffic, as initially happened with the mid-20th century U.S. railroads. Transportation productivity varies enormously by traffic type, for example, with long-haul versus short-haul traffic. Measurements of changes in physical productivity can easily be biased by modest changes in the traffic mix. We control for endogenous changes in the composition of truck traffic and find that trucking has in fact lagged the U.S. economy as a whole in productivity growth over the period of our data, 1982–1997. Loosening of weight, length, and speed limits is the likely explanation for the growth we do observe. Improvements in information technology have brought real improvements in the quality of trucking services (in reliability, predictability, speed, order tracking, etc.), but as in other service industries, true physical productivity improvements in trucking are limited.
Download InfoTo our knowledge, this item is not available for download. To find whether it is available, there are three options:
1. Check below under "Related research" whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a search for a similarly titled item that would be available.
Bibliographic InfoArticle provided by Southern Economic Association in its journal Southern Economic Journal.
Volume (Year): 75 (2009)
Issue (Month): 4 (April)
Find related papers by JEL classification:
- L92 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Railroads and Other Surface Transportation
- D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
- C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
You can help add them by filling out this form.
reading list or among the top items on IDEAS.Access and download statisticsgeneral information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Laura Razzolini).
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.