USDA-ERS Macroeconomic Forecasts & ERS Farm Income Data

The Department of Agriculture Agricultural Research Service seeks macroeconomic forecasts and farm income data under a firm-fixed-price requirements contract, with quotations due June 24, 2026 at 3:00 PM Eastern Time and questions due June 22 at 12:00 PM Eastern Time. The procurement is unrestricted with no small business set-aside; all responsible sources may quote.

Place of performance is virtual with no travel required. The contractor must deliver a Windows-compatible global macroeconomic model covering 81 economies across four regional blocs plus the Eurozone and six trading blocs, estimated using quarterly data and updated monthly. The theoretical framework must be Keynesian in the short-run and Monetarist in the long-run, with endogenized monetary policy, adaptive expectations, and full global linkages. The model must provide 5-year forecasts monthly and 10-year to 25-year forecasts at least four times annually, with historical data back to 1980 for all covered economies. The contractor must deliver monthly economic condition reports, provide sitewide or defined user access to ERS/MTED, furnish technical support 9 am–5 pm EST via telephone or email, conduct training webinars and in-person training upon request, and supply comprehensive documentation including user guides and country-specific equation files. The contractor must demonstrate at least 10 years of track record. Contractor personnel may require suitability determinations and must complete mandatory USDA security and privacy training.

The base period runs July 1, 2026 through June 30, 2027, with four optional one-year renewal periods. NAICS code is 541690. Evaluation criteria are technical approach (capability to meet SOW requirements), price (fair and reasonableness), and past performance (acceptable, neutral, or unacceptable). Award goes to the highest technically-rated offeror with fair and reasonable pricing and acceptable or neutral past performance. The contracting officer is Jacob Toft.