- API
Coal Unit Train Loadings
internal.agtransport.usda.gov | Last Updated 2024-05-24T12:53:50.000ZWeekly actual and planned coal loadings from the Surface Transportation Board's (STB) Rail Service Metrics. Railroads provide the average daily count (per week) of unit train coal traffic from major coal producing regions. They have the option of providing this metric on a train- or carload basis. For example, BNSF reports the average daily loadings for the week of coal unit trains. CSX, on the other hand, reports on a carload basis. Data are broken out by coal production region.
- API
Mexico Transportation Costs
internal.agtransport.usda.gov | Last Updated 2022-07-14T15:55:07.000ZThis data contains the costs of transporting grain to Mexico by truck, barge or rail, and ocean vessels to Mexico by water route, and by truck and rail by the land route. It includes the total transportation and landed costs.
- API
Transportation and Landed Costs of Brazilian Soybeans to China and Germany
internal.agtransport.usda.gov | Last Updated 2024-05-13T14:46:10.000ZThis dataset contains transportation and landed costs of Brazilian soybeans to Shanghai, China and Hamburg, Germany. Transportation costs are broken out by mode and vary by route. The data also contains Brazil farm values to compute total landed costs.
- API
Grain Prices
internal.agtransport.usda.gov | Last Updated 2024-05-23T17:06:53.000ZPrices are a fundamental component of exchange and have long been important to the functioning of agricultural markets. Grain prices are closely related to grain transportation, where the supply and demand for grain simultaneously determines both the price of grain, as well as the demand for grain transportation. This data has corn, soybean, and wheat prices for a variety of locations. These include origins—such as Iowa, Minnesota, Nebraska, and many others—and destinations, such as the Pacific Northwest, Louisiana Gulf, Texas Gulf, and Atlantic Coast. The data come from three sources: USDA-AMS Market News price reports, GeoGrain, and U.S. Wheat Associates. Links are included below. GeoGrain offers granular data for purchase. The GeoGrain data here is an average of those granular prices for a given state (and the "Southeast" region, which combines Arkansas, Mississippi, and Alabama). This is one of three companion datasets. The other two are grain basis (https://agtransport.usda.gov/d/v85y-3hep) and grain price spreads (https://agtransport.usda.gov/d/an4w-mnp7). These datasets are separate, because the coverage lengths differ and missing values are removed (e.g., there needs to be a cash price and a futures price to have a basis price).
- API
Commodity Price Spreads
internal.agtransport.usda.gov | Last Updated 2024-05-23T16:30:32.000ZThe data shows grain prices at select inland origin points and export destination ports and the price spread between them. More specifically, this dataset compares interior prices of corn in Illinois and Nebraska with the Gulf; Iowa and Gulf soybean prices; Kansas and Gulf hard red winter wheat; and North Dakota and Portland hard red spring wheat.
- API
Latest Week of Grain Basis Data
internal.agtransport.usda.gov | Last Updated 2024-05-23T17:06:50.000ZThis filtered view pulls the latest week of data from the Grain Basis dataset.
- API
Grain Basis
internal.agtransport.usda.gov | Last Updated 2024-05-23T17:06:50.000ZBasis reflects both local and global supply and demand forces. It is calculated as the difference between the local cash price and the futures price. It affects when and where many grain producers and shippers buy and sell grain. Many factors affect basis—such as local supplies, storage and transportation availability, and global demand—and they interact in complex ways. How changes in basis manifest in transportation is likewise complex and not always direct. For instance, an increase in current demand will drive cash prices up relative to future prices, and increase basis. At the same time, grain will enter the transportation system to fulfill that demand. However, grain supplies also affect basis, but will have the opposite effect on transportation. During harvest, the increase in the supply of grain pushes down cash prices relative to futures prices, and basis weakens, but the demand for transportation increases to move the supplies. For more information on how basis is linked to transportation, see the story, "Grain Prices, Basis, and Transportation" (https://agtransport.usda.gov/stories/s/sjmk-tkh6), and links below for research on the topic. This data has corn, soybean, and wheat basis for a variety of locations. These include origins—such as Iowa, Minnesota, Nebraska, and many others—and destinations, such as the Pacific Northwest, Louisiana Gulf, Texas Gulf, and Atlantic Coast. This is one of three companion datasets. The other two are grain prices (https://agtransport.usda.gov/d/g92w-8cn7) and grain price spreads (https://agtransport.usda.gov/d/an4w-mnp7). These datasets are separate, because the coverage lengths differ and missing values are removed (e.g., there needs to be a cash price and a futures price to have a basis price). The cash price comes from the grain prices dataset and the futures price comes from the appropriate futures market, which is Chicago Board of Trade (CME Group) for corn, soybeans, and soft red winter wheat; Kansas City Board of Trade (CME Group) for hard red winter wheat; and the Minneapolis Grain Exchange for hard red spring wheat.
- API
U.S. vs Brazil Soybean Transportation Costs
internal.agtransport.usda.gov | Last Updated 2024-04-11T14:05:50.000ZThe data shows the transportation cost of shipping soybeans from select U.S. and Brazil origins to China
- API
Grain Price Spreads
internal.agtransport.usda.gov | Last Updated 2024-05-23T17:06:53.000ZA "spread" can have multiple meanings, but it generally implies a difference between two comparable measures. These can be differences across space, across time, or across anything with a similar attribute. For example, in the stock market, there is a spread between the highest price a buyer is willing to pay and the lowest price a seller is willing to accept. In this dataset, spread refers to differences in prices between two locations, an origin (e.g., Illinois, Iowa, etc.) and a destination (e.g., Louisiana Gulf, Pacific Northwest, etc.). Mathematically, it is the destination price minus the origin price. Price spreads are closely linked to transportation. They tend to reflect the costs of moving goods from one point to another, all else constant. Fluctuations in spreads can change the flow of goods (where it may be more profitable to ship to a different location), as well as indicate changes in transportation availability (e.g., disruptions). For more information on how price spreads are linked to transportation, see the story, "Grain Prices, Basis, and Transportation" (https://agtransport.usda.gov/stories/s/sjmk-tkh6). This is one of three companion datasets. The other two are grain prices (https://agtransport.usda.gov/d/g92w-8cn7) and grain basis (https://agtransport.usda.gov/d/v85y-3hep). These datasets are separate, because the coverage lengths differ and missing values are removed (e.g., there needs to be a cash price and a futures price to have a basis price, and there needs to be both an origin and a destination to have a price spread). The origin and destination prices come from the grain prices dataset.
- API
Public Use Carload Waybill Sample
internal.agtransport.usda.gov | Last Updated 2024-05-22T16:17:22.000ZThe Surface Transportation Board's Carload Waybill Sample is perhaps the most comprehensive dataset available on railroad movements and trends. More technically, it is a stratified sample of carload waybills for all U.S. rail traffic submitted by those rail carriers terminating 4,500 or more revenue carloads annually. See 49 C.F.R. §§ 1244.1 to 1244.5. Waybill data have broad applications and usage in national railroad policy and regulations, such as rate cases, costing systems, productivity studies, exemption decisions, and analyses supporting regulations. Waybill data are used by transportation practitioners, consultants, and law firms in preparing verified statements to be submitted in formal proceedings before the Board or other public agencies. Various federal agencies use the Waybill Sample as part of their informational and decision-making framework, and many states use it as a source of information for developing state transportation plans. STB creates the Public Use Waybill file from the confidential Waybill Sample file. See the attached documents for more information. The "Reference Guide" document contains additional details on the variables and Standard Transportation Commodity Codes (STCC). In the "Creation of the Public Use Waybill Sample" document, STB provides more detail on the public use sample and how it is created. There is also a map of Bureau of Economic Analysis (BEA) Areas and a document describing the Waybill sampling instructions.