Measuring International Trade on U.S. Highways (2005) / Chapter Skim
Currently Skimming:
4 Data Sources, Models Used, and Emerging Technologies
4 Data Sources, Models Used, and Emerging Technologies
Pages 20-36
The Chapter Skim interface presents what we've algorithmically identified as the most significant single chunk of text within every page in the chapter.
Select key terms on the right to highlight them within pages of the chapter.
From page 20... ...
study implicitly recognized many of the difficulties that would be encountered in developing measures of ton-miles and value-miles of international trade traffic carried on highways in each state, and it directed BTS to identify long-term data improvements to provide accurate and reliable measures for use in highway apportionments. This section provides a few observations about the potential of various approaches to sufficiently improve data to enable its use in formula allocation.
|
From page 21... ...
truck traffic from imports arriving by air is ignored. Finally, the BTS report pointed out two problems in estimating transportation at the substate level: there is datedness and a lack of focus on foreign business in the County Business Patterns data, and there are missing values of various kinds in calculating the Oak Ridge National Laboratory's (ORNL)
|
From page 22... ...
. If the records in this database included a few additional key data elements, they could be used directly to report international trade volumes, values, destinations, and modes.
|
From page 23... ...
Integration is extremely desirable since there are more than 100 agencies and offices involved in trade, and as a result, some data collection has been redundant, and data collection currently makes use of some paper forms and incompatible automated systems. ITDS and ACE will also promote standardization of federal international trade and transportation requirements.
|
From page 24... ...
As noted in that report, in the mid-1970s the Census Bureau had access to all foreign trade paper documents collected by the Customs and Border Protection Agency, and those documents served as a universe from which a follow-up survey of shipper-based establishments was conducted. Today, an analogous survey would involve sampling international transactions filed with that agency through ACE.
|
From page 25... ...
. Although the gravity model could have been applied at the level of county centroids, it would have required that the factors related to the costs of transportation from one port or border crossing or county to another be used, which was computationally too demanding (involving a matrix of dimension of more than 3,000 by 3,000)
|
From page 26... ...
BTS used the Census Bureaus' County Business Patterns data to distribute the freight movements from the state to the county level. To do this, BTS used the ratio of each countys' total payroll to total state payroll to allocate that proportion of the state total shipments to the individual counties.
|
From page 27... ...
One important benefit of the ORNL highway network is that it is embedded within the ORNL intermodal network, which permits one to model the mode and route used to move freight from one node in the network to another on the basis of travel costs and time required. This assignment model, within the same general approach, sometimes makes use of a least impedance approach that deterministically selects a transportation option and sometimes uses a logit approach that weights various choices based on their estimated probabilities of selection.
|
From page 28... ...
In concluding this section, the panel notes one related point. Another approach to providing estimates of higher quality for states, other than additional data collection, would be to try to use combining-information models with variables that are collected more frequently than the current survey frequencies, possibly at lower levels of geographic aggregation.
|
From page 29... ...
The rest of this section briefly discusses eight emerging technologies: 4 The Canadian roadside sample program is an intercept survey of commercial trucks at U.S.-Canada border crossings.
|
From page 30... ...
. 6Recent experience by CalTrans suggests that the current cost estimates of WIM might be too low, since full-speed WIM sensors require a huge investment in high-quality pavement to ensure that the truck does not bounce over the sensors.
|
From page 31... ...
Virtual Weigh Station (VWS) Technology Virtual weigh station technology uses WIM, closed circuit television cameras, and, in some cases, optical character recognition technology (for license plate numbers)
|
From page 32... ...
Moreover, the various programs that do exist are not interoperable so a tag that can be identified in one state may not be recognized in another state, and the data are not a public record that can be used to track commodity flows by public agencies.
|
From page 33... ...
The unique bar code assigned to a package corresponds to information contained in a database that houses detailed information on the freight with which the tag is associated. 7See Terratracker (2004)
|
From page 34... ...
The advantage of using bar code technology is that it can provide detailed information for each parcel loaded on a truck and that data can follow the freight from pick-up to delivery. The disadvantage of this technology is that the information is not a public record that can be used to track commodity flows by public agencies.
|
From page 35... ...
However, in today's security environment, more deployments in the near term are likely. Archived Data User Service Archived data user service (ADUS)
|
From page 36... ...
36 MEASURING INTERNATIONAL TRADE ON U.S. HIGHWAYS require modifications to manage such large amounts of data -- including scrubbing the data and supplying notes on data gaps or documenting when data collection systems are out of calibration or offline due to maintenance, etc.
|
Key Terms
This material may be derived from roughly machine-read images, and so is provided only to facilitate research.
More
information on Chapter Skim is available.