Freight Forecasts: Check Editions and Assumptions

“Keep the model edition and assumption date beside the planning decision, so reviewers can see which part still needs a current buyer record.”
How far apart are FAF5’s growth cases for each commodity?
In FHWA’s FAF5 forecast study, the high- and low-growth cases for domestic freight from 2017 to 2050 sit 0.5 points a year apart or less for 29 of the 42 commodity groups, so a claim far outside its group’s band needs evidence of its own. Zinit Research charts the three cases for every group, and the check under the chart places a supplier’s or analyst’s growth claim against them.
Zinit Research · FHWA FAF5 forecast study, November 2022
The gap between FAF5’s high- and low-growth cases to 2050 runs from 0.1 points a year for electronics, machinery and three other groups to 1.5 points for crude petroleum
Average annual change in domestic freight tonnage from 2017 to 2050, by commodity group (SCTG, the Standard Classification of Transported Goods). Dots are FAF5’s baseline, bars run from its low-growth to its high-growth case, and the diamond is the claim entered in the check below. FHWA built the cases on data available through April 2021 and gives them no probabilities. Select a row, or a group below, to place a growth claim against it.
Place a growth claim against FAF5’s cases
A claim of +3.5% a year sits 1.5 points above FAF5’s high-growth case for mixed freight (1.8% to 2.0% a year from 2017 to 2050, baseline 2.0%). FAF5’s cases are 33-year averages for national domestic tonnage, built on data available through April 2021, so ask which edition, scenario and years the claim comes from, and set it beside your own shipment history before it shapes a lane plan.
FAF5 rate: (2050 tons ÷ 2017 tons)^(1/33) − 1, as printed in Table 10 of the report. The all-commodities row is computed by Zinit Research from the sum of the 42 rows.
Source: Federal Highway Administration, FAF Version 5 Commodity Flow Forecast Study: Final Forecasting Results, November 2022, Table 10 (domestic flows). Coal falls outside the scale and is labelled instead. SCTG 19 appears under its current FAF name; the report calls it “Coal, n.e.c.”. Chart: Zinit Research. Data and method
Evaluating Macroeconomic Scenario Assumptions and Model Editions
The November 2022 FAF Version 5 forecast study describes FAF5.2 projections built from a 2017 data base year, with forecasts for 2020, 2022, 2023, 2025 and later horizons through 2050. Its macroeconomic assumptions were developed in April 2021, incorporating the recession and recovery information available at that time. The publication date, base year and assumption date describe different parts of the model. A buyer reviewing this historical edition should retain all of them in the planning record, because an updated presentation date would not update those underlying assumptions.
The baseline assumptions in that report describe an economy without a major mishap through 2050 and identify examples of disruptions outside that baseline path, including large oil-price shocks and unforeseen macroeconomic policy changes. This is the stated boundary of that particular case. Before adopting it, ask which risks the buyer’s planning case addresses separately and who owns the corresponding response. Keep the high- and low-growth cases under their stated assumptions; attach no probability to either case without a separately supported probability model.
The FAF5 file posted today still carries the 2021 forecast for domestic freight
BTS released FAF5’s forecast scenarios in version 5.2 on November 22, 2021. None of the nine releases since then announces new forecasts in its notes, and seven of them revise foreign trade flows, among them version 5.4’s update to the 2017–2050 foreign trade flows. The file posted now, version 5.7.1 of August 15, 2025, shows the result: its 2050 baseline for domestic tonnage is 24.91 billion tons, 3.8 million tons from the report’s Table 10 and within the rounding of its 42 rows, while its 2050 export forecast sits 8.2% above the report’s Table 12. A deck that cites “the latest FAF” for domestic freight in 2050 is still citing assumptions from April 2021, and that is the date the register’s assumption field should carry.
| Report | File | Change | |
|---|---|---|---|
| Domestic | 24.91 | 24.91 | 0.0% |
| Imports | 1.81 | 1.82 | +0.4% |
| Exports | 1.99 | 2.16 | +8.2% |
Report: FHWA’s FAF5 forecast study (November 2022), the sum of the commodity rows in Tables 10, 11 and 12, each rounded in the report. FAF5.7.1: the BTS state summary workbook for 2050, domestic, import and export flows summed over every state by Zinit Research.
The Scenario-Assumption Diagnostic Register
To prevent teams from confusing long-term public scenario benchmarks with immediate procurement realities, category managers should maintain an explicit scenario-assumption register before presenting lane projections to executive stakeholders or carrier partners. Establishing structured governance over macroeconomic vintages clarifies model boundaries, which aligns with broader organizational practices in supplier risk assessment methodologies.
| Register field | What the buyer records | Review action |
|---|---|---|
| Edition and document | Exact dataset/release and the method document used; preserve the retrieved files. | Confirm that the selected forecast belongs to the named edition. |
| Data base year | Observation period used to construct the underlying dataset. | Keep it distinct from the publication and retrieval dates. |
| Assumption date | Date of the economic inputs and any later documented revisions. | Ask the planning owner which later developments require a separate adjustment. |
| Scenario | Named baseline, high-growth or low-growth case and its stated premises. | Record the reason for selection; do not invent a likelihood. |
| Units and geography | Weight/value units, price basis, commodity definitions and geographic boundaries. | Reconcile these with the buyer’s lane, product and load definitions before arithmetic. |
| Horizon | Period represented by the selected model output and the buyer’s planning decision. | Check that the planning use fits the output’s time scale. |
| Shock assumptions | Disruptions included or omitted in the named case, with the source passage. | Compare them with the buyer’s risk register and unresolved dependencies. |
| Private buyer forecast | Shipment demand, load characteristics, operating schedules and relevant carrier terms. | Identify the internal owner and evidence needed for the procurement decision. |
| Refresh owner and trigger | Named reviewer, the input being monitored, and a condition that reopens the decision. | Document the next action when that condition occurs; choose the timing for this decision. |
Authored review aid, with fields awaiting the buyer’s actual records. It supplies no benchmark values, universal review frequency, current forecast or carrier commitment.
Understanding Document Scopes and Conversion Methodologies
Procurement teams frequently combine different federal freight publications without accounting for differences in scope and methodology. Agency presentations like the FAF5 data overview webinar highlight that while public models provide valuable multi-scale multimodal perspectives across 42 commodity groups, they are not tailored to specific local operating regions and may lack granularity for local-scale operational decisions. Furthermore, planners looking to translate annual freight weights into operational vehicle counts must examine historical technical documentation, such as the truck payload factor methodology, which developed procedures to convert annual tonnage flows into daily truck movements across network segments.
The July 2026 FAF Version 6 user’s guide defines a Zone of Entry as the entire FAF region or state where an import enters the United States, rather than a single location. It also describes updated historical state-level base-year products as planned under the newer methodology and data sources. Retain the date of that statement when reviewing the guide; it does not establish the availability of those products today. Before joining an older forecast to a later dataset, obtain the relevant definitions and any documented crosswalk, and identify which comparison remains unresolved.
| Document Title & Citation | Publication Vintage | Primary Scope & Subject Focus |
|---|---|---|
| FAF5 Final Forecasting Results | November 2022 | Long-term commodity flow projections from 2017 base through 2050 across macroeconomic scenarios |
| FAF6 User Guide | July 2026 | Data dictionary, geographic zone definitions, and access conventions for regional datasets |
| FAF5 Overview Webinar | July 2022 | Base year data overview, web tool demonstration, and analytical strengths and limitations |
| Payload Factors Report | April 2020 | Methodologies for out-of-scope commodity flows and converting annual tons to daily trucks |
Compares publication vintages and structural focus across official freight analysis reference documents.
FAF6.0 and FAF5.7.1 publish different 2022 tonnages for most commodity groups
Both editions now describe 2022. FAF5.7.1 carries an annual estimate built forward from its 2017 base, and FAF6.0 a new base year built on the 2022 Commodity Flow Survey. Their national totals sit 1.0% apart, 19.83 and 19.63 billion tons, while 28 of the 42 commodity groups differ by more than 10%, from −41.9% for nonmetallic minerals to +52.6% for furniture. FAF6.0 covers the 2022 base year only, and BTS’s numbering puts forecast years in a later release, so a growth rate computed from an FAF5 forecast to an FAF6 base year would mostly measure the change of edition.
2022 tonnage in FAF6.0 against FAF5.7.1: the eight largest rises and the eight largest falls
Source: BTS and Oak Ridge National Laboratory, FAF5.7.1 and FAF6.0 state summary tables by commodity, 2022, summed over every state’s within-state and outbound flows by Zinit Research. Domestic, import and export flows are included. Chart: Zinit Research. Data and method
How should teams govern an automated scenario review?
Operational Safeguards and Implementation Boundaries
Prepare the private records before bringing the planning case to a carrier discussion. Assign an owner for the shipment-demand file, another for operational constraints where those responsibilities differ, and a reviewer for the carrier terms. Include the required service window, load characteristics, equipment requirements and any known acceptance conditions. Ask which fields are verified, which are estimates and which still need an answer. The supplier relationship management guide provides related context for keeping responsibilities and agreements visible. When discussing an offered service, record the carrier’s actual response and its scope alongside the planning assumptions. Keep an unresolved commercial requirement visible until its owner has obtained the necessary evidence.
For a proposed warehouse lane, walk through the register with the planning owner before inviting a carrier to respond. Start with the document and the selected scenario, then reconcile the commodity, geography, unit and horizon with the lane being discussed. Have the operations owner explain the proposed loading calendar and the assumptions behind the company’s shipment forecast. Where a field is unresolved, name the evidence needed and the person who will obtain it. The next review can then revisit that field directly instead of treating an unchanged macroeconomic chart as confirmation that the operating requirement has been met.
Frequently asked questions
What macroeconomic cutoff date drives FAF5 forecasting scenarios?
Projections in the FAF Version 5 forecast study are based on macroeconomic trends and data available through April 2021, incorporating recovery assumptions from that period.
Can freight buyers treat FAF baseline scenarios as predictive probability distributions?
The FAF5 report describes the baseline’s assumptions and alternative growth cases. Use those named cases as documented scenarios. A buyer should not assign a probability to a case unless separate evidence supports that probability.
How do FAF models convert annual commodity tonnage into vehicle volumes?
The historical truck payload factors report describes methods for converting annual origin-destination commodity weight into truck flows. A buyer considering that conversion must review the method and payload assumptions for the specific use, then obtain the private operating records needed for a service decision.
Where does this data come from?
- What the numbers are
- Domestic, import and export tonnage for 2017 and for 2050 under FAF5’s baseline, high-growth and low-growth scenarios for the 42 SCTG commodity groups, with the growth rates as printed in Tables 10 to 12 of FHWA’s November 2022 forecast study (million tons), and national tonnage by commodity and by trade type from the FAF5.7.1 and FAF6.0 state summary workbooks, summed by Zinit Research over every state’s within-state and outbound flows (thousand tons). FAF figures are modeled estimates of freight moving among U.S. regions; none of them describes a buyer’s lanes, a carrier’s capacity or a contract.
- Source files
- Freight Analysis Framework Commodity Flow Forecast Study (FAF Version 5): Final Forecasting Results, Tables 10 to 12, Federal Highway Administration. Retrieved October 22, 2026. Direct download of the published PDF; tables read from its text layer. SHA-256 09f6d2beffd0…
- FAF5.7.1 state summary by domestic mode and trade type, 2017, Bureau of Transportation Statistics and Oak Ridge National Laboratory. Retrieved October 22, 2026. Workbook extracted unchanged from the published 1997 to 2050 summary-table archive. SHA-256 437418178e07…
- FAF5.7.1 state summary by domestic mode and trade type, 2050, Bureau of Transportation Statistics and Oak Ridge National Laboratory. Retrieved October 22, 2026. Workbook extracted unchanged from the published 1997 to 2050 summary-table archive. SHA-256 c314590cda5f…
- FAF5.7.1 state summary by commodity, 2022, Bureau of Transportation Statistics and Oak Ridge National Laboratory. Retrieved October 22, 2026. Workbook extracted unchanged from the published 1997 to 2050 summary-table archive. SHA-256 2d829ccb3ddc…
- FAF6.0 state summary by commodity, 2022, Bureau of Transportation Statistics and Oak Ridge National Laboratory. Retrieved October 22, 2026. Workbook extracted unchanged from the published summary-table archive. SHA-256 ff5e6b0a5345…
- FAF6 metadata, commodity codes, Bureau of Transportation Statistics and Oak Ridge National Laboratory. Retrieved October 22, 2026. Direct download. SHA-256 8c555ebfbd03…
- Freight Analysis Framework (FAF) Versions, Bureau of Transportation Statistics. Retrieved October 22, 2026. Read from the Internet Archive capture of July 10, 2026, because bts.gov refuses automated requests. SHA-256 d2b8974346a4…
- Freight Analysis Framework Version 6 (FAF6), Oak Ridge National Laboratory for the Bureau of Transportation Statistics. Retrieved October 22, 2026. Page as served. SHA-256 74b9be2ac52f…
- Editions used
- FAF5 forecasts: released in version 5.2 on November 22, 2021; FHWA’s report on them is dated November 2022 and uses data available through April 2021.
- FAF5.7.1: posted August 15, 2025; 2017 base year, annual estimates to 2024 and forecasts to 2050.
- FAF6.0: ORNL’s FAF6 page says “The current version of FAF6 (FAF6.0) provides estimates for tonnage (unit: thousand tons) and value (unit: million dollars) by origin-destination pair of FAF regions, commodity type, and mode for the base year (2022).” The page was last modified August 5, 2026.
- How the page stays current
- The forecast study does not change. The FAF5 figures change when BTS posts a new FAF5 version, and FAF6 forecasts are expected in a later FAF6 release; the page is rebuilt from whichever files are retained, with each edition named.
- Download the data
One ZIP holds the 3 CSV files below and a README that lists the sources and the citation.
- faf5-editions-2050-by-trade-type.csv
- faf5-scenarios-by-commodity-2017-2050.csv
- faf5-vs-faf6-2022-by-commodity.csv
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The download should start on its own. If it doesn’t, use the link below.
Download the data (ZIP, 15 KB)- Related Zinit Research
- Cite this page
Zinit Research. “Freight Forecasts: Check Editions and Assumptions.” Data: Federal Highway Administration, FAF5 forecast study (2022); Bureau of Transportation Statistics, FAF5.7.1 and FAF6.0. https://zinit.com/journal/research/freight-forecast-assumption-vintages, data retrieved October 22, 2026.
- How this page is produced
- Zinit Research downloads the source files listed above, keeps the originals, and computes every chart, table and figure in the data sections from them; an automated check rebuilds each number from the files before the page is published. The article text follows the Editorial Policy.
Sources
- Freight Analysis Framework Commodity Flow Forecast Study (FAF Version 5): Final Forecasting Results — Paul Bingham; Aleksandra Maguire; Larry O’Rourke; Birat Pandey, Federal Highway Administration, 2022. Historical evidence (official report): Version/assumption register, source applicability, units and private buyer-record boundaries.
- Freight Analysis Framework Version 6 User’s Guide — Bureau of Transportation Statistics; Hyeonsup Lim; Majbah Uddin, Bureau of Transportation Statistics, 2026. Current empirical evidence (official report): Version/assumption register, source applicability, units and private buyer-record boundaries.
- Freight Analysis Framework (FAF5): Overview of Base Year/Forecasted Data and Tools — Federal Highway Administration, 2022. Historical evidence (official report): Version/assumption register, source applicability, units and private buyer-record boundaries.
- Research, Development, and Application of Methods to Update Freight Analysis Framework Out-of-Scope Commodity Flow Data and Truck Payload Factors — Christopher Lindsey; Daniel Beagan; Krishnan Viswanathan, Federal Highway Administration, 2020. Foundational evidence (official report): Version/assumption register, source applicability, units and private buyer-record boundaries.