STB Docket No. EP 385 (Sub-No. 8) 

Waybill Sample Reporting 

Comments of the 

U.S. Depattment of Agriculture 

Greg Ibach 

Under Secretary 

Marketing and Regulatory Programs 

U.S. Depattment of Agriculture 

Washington, D.C. 20250 

Date: January 28, 2020 
Introduction 

The Carload Waybill Sample (CWS) is an extremely impmiant dataset within the rail industry, 

and USDA applauds the Board' s efforts to improve it. Even though the sample size is limited, 

there is no parallel to the CWS in terms of its breadth of application, scope, and coverage. It is 

the most detailed and comprehensive data the federal government currently has on rail freight 

movements, making it instrumental in identifying trends and issues in the industry. In addition, 

as acknowledged in the Notice of Proposed Rulemaking (NPRM), waybill data are also a key 

component in rate and service cases before the Board, such as in the Three Benchmark (3B) 

methodology. These data are needed to inform a variety of rail-related decisions and research. 

Fmihermore, for any conclusions or determinations derived from it to be sound, the underlying 

data must be an accurate representation ofrail traffic. Therefore, USDA appreciates the Board 

issuing this NPRM to make waybill data more useful to all without creating an undue burden on 

railroads. 

The following discusses USDA's recommendations to the Board. In general, USDA believes the 

Board should collect the population waybill data or at least fmiher increase the sample size from 

the proposal and take this oppmiunity to add additional data to the CWS. 

Discussion and Recommendations 

The Board rightly recognizes a bigger sample size enables a higher degree of precision in 

estimates and opens the door to new questions and analyses that are not possible with a smaller 

sample size. However, while the proposal is a step in the right direction, USDA encourages the 

Board to significantly increase data collection beyond what has been proposed. 

The Full Population is the First-Best Option 

USDA postulates that if the Interstate Commerce Commission had the technology at its disposal 

that the Board does now, it would not have needed to unde1iake the statistical design process that 

led to the creation of today's CWS. USDA believes this proceeding is an opportunity to take a 

step back from the mechanics, look at what purpose CWS was created to serve, look at what 

issues are relevant now, and ask if continuing to tweak guidelines set in motion within the 

technological limitations and regulatory concerns of the 1950's is still the best answer for today. 

Based on the NPRM, it is unclear why the Board does not simply collect the whole population of 

carload waybill data. According to the Board, "all reporting caniers submit waybill data in 

computerized form today." Moreover, caniers must already have access to the population data in order to generate a sample from it. Therefore, submitting the entire population would not likely 

be a significant additional burden. To the contrary, it may even reduce the burden on railroads, as 

they would no longer have to stratify the population. The Board's "computerized and automated" 

CWS processing and the modern fact of inexpensive data storage mean collecting the population 

2 
simplifies matters for the data providers by avoiding the complex determination of which records 

to pull out and which ones to exclude. Moreover, just like with US.ACE data, the Board going to 

a full population would not enlarge the burden requirement (only the size of the submission) 

because the repo1iing frequency would not be changed. Just as over 50 barge companies submit 

monthly data on their movements to US.ACE, railroads would continue to provide data at 

established intervals-either monthly or quaiierly. 

A Stratified Sample is a Second-Best Option 

Ifthe population data cannot be collected, USDA believes the Board should both significantly 

increase the sample size more than proposed and stratify by the categories that are most 

imp01iant for coverage. For example, distance, railroad, and commodity are clearly imp01iant 

variables to the Board. Adding a regional or spatial variable to the stratification design would 

enable better geographic analysis with the CWS. 

According to the analysis in the NPRM, only 20 percent of the Board's selected traffic categories 

would have 25 or greater observations after the proposed sample increase. While that would 

cover 93 percent of revenue, it is unclear why the Board accepts a level of coverage that does not 

include all categories. In fact, one advantage of stratification is to ensure coverage across all 

categories that are deemed impmiant. In other words, it is unclear why the Board continues to 

stratify by number of carloads per waybill alone, given the stated imp01iance of coverage across 

other categories. If commodity, mileage range, and railroad are imp01iant categories to have 

coverage of in a rate case, why not also explicitly stratify the sample by some of those categories 

as well? 1 

However, from USDA's perspective, a bigger issue is the value of the CWS should go well 

beyond rate cases and the paiiicular stratification analyzed. Stratification is a great option to 

ensure coverage in a limited sample geared towards targeted questions. However, there are many 

questions for which the CWS is the only source of answers. For these reasons, USDA believes 

the Board's primary focus should be to significantly increase the overall sample size as a 

propmiion of the population; adjusting the sample size within particular strata should only be a 

secondary consideration. 

Significantly increasing the overall sample size will provide increased coverage across a wide 

variety of strata, almost regardless of the actual stratification strategy chosen, assuming one is 

needed at all. The Board demonstrated this fact in its cuiTent proposal where the explicit 

1 As a side note on stratification, the Procedure for Sampling Waybill Records by Computer document states, 

"waybills in the file to be used as a frame for this study may be in any order." Under systematic sampling, order is 

an imp011ant consideration to account for patterns in the frame that may correspond to the skip interval. It seems it 

would be better to either specify an order, use a random ordering, or even use a simple random sample rather than 

"any order," in order to avoid potential sampling bias. 

3 
recommended in the 2015 Transpmiation Research Board (TRB) study for example, would be an 

extremely valuable addition to the CWS, it being the only source of railroad shipment-level 

data. 2 In addition, in various recent proceedings, the Board has recognized the need for 

additional data reporting on service metrics and demunage and accessorial charges, yet these 

data are currently collected piecemeal. 3 A comprehensive and standardized collection of these 

railroad metrics by shipment, as could be accomplished in the CWS, would be far more valuable 

for more in-depth analysis. Fmihermore, this is an oppmiunity to look ahead and anticipate what additional data would be valuable to have in the CWS for purposes of better understanding the 

railroad industry and supporting the needs of shippers. 

With any of the proposed sampling changes there will be some transitional burden on railroads 

and STB in terms of coding and quality control. If railroads and STB are already modifying their 

CWS processes as a result of this proceeding, adding additional variables to this modification 

would be less costly now than at a separate time. 

Summary 

USDA supports the Board's proposal and appreciates the Board's intention to improve the CWS. 

It is an irreplaceable dataset, containing a wide range of valuable information. The Board is 

moving in the right direction in proposing to increase the sample size, but USDA encourages the 

Board to go even further. The Board should consider removing the stratification process 

altogether and collect the population data. In lieu of the population data, the Board should still 

collect a significantly larger sample and modify the stratification to reflect additional impmiant 

variables. Finally, the Board should use this opportunity to add new variables to the waybill in 

order to collect additional information that could provide insight into a wider range of the complex issues facing railroads and shippers. 

2 Among its recommendations, TRB wrote, "STB should appraise the data needed to fulfill its role in supervising the 

supply of common carrier service. For example, consideration should be given to collecting information that permits 

the h·acking of the time elapsed from a shipper request for service to rail car placement, removal, and all'ival at the 

destination, perhaps in conjunction with information on the scheduled delivery time. The appropriate platform for 

such data collection may be the CWS, because shipment-level h·acking of service is essential for understanding 

trends in service levels and patterns across time, regions, and traffic segments. STB should explore options for 

collecting shipment-level data, including additions to and enhancements of the CWS itself. STB should examine all 

data elements in the standard railroad freight waybill that could be useful for monitoring service performance and 

consider adding such elements to the CWS. STB should also examine opp01tunities for collecting new data, which 

would either be added to the waybill reporting or subsequently linked to CWS records." (Emphasis added. Source: 

Transpo1iation Research Board, Modernizing Freight Rail Regulation, Special Rep01i 318, p. 217.) 

3 See for instance, Ex Paiie No. 724 (Sub-No. 4), United States Rail Service Issues-Performance Data Rep01iing; 

Ex Parte No. 742, Public Listening Session on CSX Transportation Inc. 's Rail Service Issues; Ex Paiie 754, 

Oversight Hearing on Demmnge and Accessorial Charges; and the Board's December 2018 letters to the Class I 

railroads on demurrage and accessorial charges. 

4 
G· g lb h 

Under Secretary 

Marketing and Regulatory Programs 

U.S. Department of Agriculture 

Washington, D.C. 20250 

5