A July 9 webinar presented by experts from the Texas A&M Texas Transportation Institute unveiled a new, free online modeling tool allowing shippers and others to calculate the total costs of grain transportation using a wide range of variables.

The webinar, entitled “Impacts of the Transportation System on Agricultural Products,” showcased a model that made use of a 2019 study by TTI on the advantages of barge transportation undertaken for the U.S. Department of Agriculture’s Agricultural Marketing Service.

David Ellis, senior research scientist at TTI, said the model’s data is from 2018 and 2019, but still valid even though “a lot has happened since then.” Research scientists Max Steadman and Brianne Glover were co-presenters.

One of the main goals of the study and model, Ellis said, is to help advocates for infrastructure improvements make their case to public officials and decision-makers. Increased transportation costs reduce producers’ revenues, increase export prices and make United States products less competitive in the world market.

“Historically, there’s been a need to better communicate that there’s not only a cost to making infrastructure improvements through higher taxes; there are also costs to doing nothing,” he said. The new model helps quantify those costs.

    One chart showed averages of total transportation expenses for different soybean products. For raw soybeans with a domestic destination, the average low and high transportation cost was the same: $5.80 per ton. For export soymeal, the total cost differential can range from $11.90 to $51.65. For biodiesel, the cost difference can vary between $7.30 to $101.17 per ton.

That’s because those products can have different routes, said Ellis, with different numbers of processing steps. Also factored in are the various types of delays the products might encounter among the various transportation modes—such as lock and dam delays, wait times on railroads, or traffic congestion in major urban areas. Delays can be caused by both private and public causes, but most delays area caused by public underinvestment in infrastructure, he said.

The model can split movement of cargoes by mode. It can also calculate transportation costs for a variety of agricultural products, not just corn and soybeans. That came about because Ellis was challenged by a Texas legislator at a public hearing to show how transportation costs could affect the price of a can of soup. The model may soon be extended to include data from other cargo corridors such as the Pacific Northwest.

This particular model is too new to have been used to advocate to public officials, Ellis said. But he said that when TTI is able to argue the costs of doing nothing, and to back up its arguments with data, the results are encouraging. He said that during the past 4 years, the state of Texas has spent $5 billion more on transportation infrastructure projects than it originally planned to, thanks in part to presentations by TTI used by infrastructure advocates.

The webinar is available on YouTube at https://www.youtube.com/watch?v=86J92U4mRKg.

David Murray can be reached at journal@hpj.com.

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