US international trade balance intelligence, monthly
Monthly US international trade-balance intelligence, 1992-01 onward: the U.S. Census Bureau / BEA headline goods-and-services trade balance (FRED BOPGSTB, millions of USD, seasonally adjusted) with goods export and import levels (BOPGEXP/BOPGIMP), the goods balance, the implied services-balance residual, MoM/YoY momentum, a trailing-12-month trend anchor, deficit tiers (surplus/narrow/moderate/deep on fixed cut points), deficit-widening and record-deficit flags. All three series redistributed keyless via FRED fredgraph.csv. Method caveats: BEA revises history with each release (revisions mint new snapshots); latest rows are most revision-prone; values are nominal dollars; the services leg is an implied residual, not a published series; national grain only. One row per month x USA; in-window nulls fail loudly, never imputed. Who joins this: demand forecasters join trade_balance_m / balance_12m_avg_m on month + country_code as the net-external-demand regime; retail planners read goods import levels as the inbound-supply pulse; sales teams use deficit_widening_flag as a macro headwind input.
- Rows
- 415
- Columns
- 19
- Source cadence
- Monthly
- Last refreshed
- Oct 1, 2026
- Theme
- economy
| Column | Type | Description |
|---|---|---|
| month_start | date | First day of the calendar month (ISO date join key). (unit: date) |
| month | string | Calendar month as YYYY-MM (panel label). (unit: string) |
| year | integer | Calendar year (panel join key). (unit: integer) |
| country | string | Country name (shared normalization layer). (unit: string) |
| country_code | string | ISO 3166-1 alpha-3 country code (USA). (unit: string) |
| trade_balance_m | float | Headline US trade balance: goods and services, balance-of-payments basis (FRED BOPGSTB; U.S. Census Bureau / BEA). Negative = deficit. (unit: millions of USD, seasonally adjusted) |
| goods_exports_m | float | US exports of goods, balance-of-payments basis (FRED BOPGEXP). (unit: millions of USD, seasonally adjusted) |
| goods_imports_m | float | US imports of goods, balance-of-payments basis (FRED BOPGIMP). (unit: millions of USD, seasonally adjusted) |
| goods_balance_m | float | Goods trade balance = goods_exports_m - goods_imports_m (derived, $M). (unit: millions of USD) |
| services_balance_m | float | Implied services balance = trade_balance_m - goods_balance_m (derived residual, $M). Labelled implied: small BOP conceptual differences can move the residual; the published series themselves are verbatim upstream. (unit: millions of USD) |
| exports_mom_pct | float | Month-over-month change in goods exports, percent (null for the first panel month). (unit: percent) |
| imports_mom_pct | float | Month-over-month change in goods imports, percent (null for the first panel month). (unit: percent) |
| balance_mom_m | float | Month-over-month change in the trade balance, millions of USD (null for the first panel month). (unit: millions of USD) |
| balance_yoy_m | float | Year-over-year change in the trade balance, millions of USD (null for the first 12 panel months). (unit: millions of USD) |
| balance_12m_avg_m | float | Trailing 12-month mean of the trade balance — the trend anchor (null for the first 11 panel months). (unit: millions of USD) |
| deficit_tier | string | Deficit regime on fixed cut points: surplus (balance >= 0), narrow (0..-25B), moderate (-25B..-75B), deep (< -75B). (unit: string) |
| deficit_widening_flag | integer | 1 when the deficit is $5B+ wider than 12 months ago (balance_yoy_m < -5000); null for the first 12 panel months. (unit: flag) |
| record_deficit_flag | integer | 1 on the panel row(s) with the largest deficit in the series' history, else 0. (unit: flag) |
| row_hash | string | Deterministic 16-hex sha256 of month + balance + exports + imports (idempotency key). (unit: string) |
First 10 sample rows — a preview, not the complete dataset.
| month_start | month | year | country | country_code | trade_balance_m | goods_exports_m | goods_imports_m | goods_balance_m | services_balance_m | exports_mom_pct | imports_mom_pct | balance_mom_m | balance_yoy_m | balance_12m_avg_m | deficit_tier | deficit_widening_flag | record_deficit_flag | row_hash |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1992-01-01 | 1992-01 | 1,992 | United States | USA | -2,026 | 35,498 | 42,450 | -6,952 | 4,926 | — | — | — | — | — | narrow | — | 0 | e5dd717ceb74052f |
| 1992-02-01 | 1992-02 | 1,992 | United States | USA | -831 | 36,854 | 42,447 | -5,593 | 4,762 | 3.82 | -0.007 | 1,195 | — | — | narrow | — | 0 | aa02e5ec46e81da7 |
| 1992-03-01 | 1992-03 | 1,992 | United States | USA | -2,641 | 35,711 | 43,066 | -7,355 | 4,714 | -3.101 | 1.458 | -1,810 | — | — | narrow | — | 0 | d72bd7f32c28fe6d |
| 1992-04-01 | 1992-04 | 1,992 | United States | USA | -3,109 | 35,439 | 43,723 | -8,284 | 5,175 | -0.762 | 1.526 | -468 | — | — | narrow | — | 0 | aa71cd7bb9b1566f |
| 1992-05-01 | 1992-05 | 1,992 | United States | USA | -3,919 | 35,403 | 44,123 | -8,720 | 4,801 | -0.102 | 0.915 | -810 | — | — | narrow | — | 0 | 62c5e74b7a0920d8 |
| 1992-06-01 | 1992-06 | 1,992 | United States | USA | -2,824 | 37,099 | 44,637 | -7,538 | 4,714 | 4.791 | 1.165 | 1,095 | — | — | narrow | — | 0 | a0e4ec8a2abcbda0 |
| 1992-07-01 | 1992-07 | 1,992 | United States | USA | -2,781 | 37,753 | 45,185 | -7,432 | 4,651 | 1.763 | 1.228 | 43 | — | — | narrow | — | 0 | decb6538633033df |
| 1992-08-01 | 1992-08 | 1,992 | United States | USA | -4,455 | 36,051 | 45,368 | -9,317 | 4,862 | -4.508 | 0.405 | -1,674 | — | — | narrow | — | 0 | ff21168809008f8e |
| 1992-09-01 | 1992-09 | 1,992 | United States | USA | -3,530 | 37,043 | 45,495 | -8,452 | 4,922 | 2.752 | 0.28 | 925 | — | — | narrow | — | 0 | 1573d7c8d8bc601a |
| 1992-10-01 | 1992-10 | 1,992 | United States | USA | -3,520 | 37,997 | 46,352 | -8,355 | 4,835 | 2.575 | 1.884 | 10 | — | — | narrow | — | 0 | 8cb970699fead314 |
Profiled Oct 1, 2026 from snapshot 20261001T205313Z-6520e21afb72
Measured- Completeness
- 99.5%
- Rows
- 415
- Columns
- 19
- Columns with gaps
- 6
| Column | Missing | Distinct | Range | Distribution |
|---|---|---|---|---|
| month_startdate | 0% | 385 | Jan 1, 1992 → Jul 1, 2026 | — |
| monthvarchar | 0% | 408 | — |
|
| yearbigint | 0% | 34 | 1,992 → 2,026median 2,009 | |
| countryvarchar | 0% | 1 | — |
|
| country_codevarchar | 0% | 1 | — |
|
| trade_balance_mdouble | 0% | 427 | -132,983 → -831median -40,160 | 10 outside 1st–99th percentile |
| goods_exports_mdouble | 0% | 402 | 35,403 → 222,014median 101,170 | 10 outside 1st–99th percentile |
| goods_imports_mdouble | 0% | 511 | 42,447 → 342,316median 165,910 | 10 outside 1st–99th percentile |
| goods_balance_mdouble | 0% | 396 | -159,452 → -5,593median -60,867 | 10 outside 1st–99th percentile |
| services_balance_mdouble | 0% | 457 | 4,298 → 32,455median 12,070 | 10 outside 1st–99th percentile |
| exports_mom_pctdouble | 0.24% | 442 | -25.41 → 15.04median 0.5853 | 10 outside 1st–99th percentile |
| imports_mom_pctdouble | 0.24% | 358 | -19.23 → 11.74median 0.5062 | 10 outside 1st–99th percentile |
| balance_mom_mdouble | 0.24% | 396 | -27,855 → 72,642median -239.5 | 10 outside 1st–99th percentile |
| balance_yoy_mdouble | 2.9% | 394 | -71,058 → 79,326median -2,737 | 10 outside 1st–99th percentile |
| balance_12m_avg_mdouble | 2.7% | 371 | -89,260 → -3,267median -40,294 | 10 outside 1st–99th percentile |
| deficit_tiervarchar | 0% | 3 | — |
|
| deficit_widening_flagbigint | 2.9% | 2 | 0 → 1median 0 | |
| record_deficit_flagbigint | 0% | 2 | 0 → 1median 0 | |
| row_hashvarchar | 0% | 355 | — |
|
- Current
20261001T205313Z-6520e21afb72 · sha256 6520e21afb72…
415 rows · first snapshot
Point any LLM at the metadata endpoint — the documentation above is machine-readable too (JSON-LD + Croissant).
curl "https://datazimuts.com/v1/datasets/fred_trade_balance_intel/us_trade_balance_monthly" | jq '{title, rows, columns_count, license}'import requests
ds = requests.get("https://datazimuts.com/v1/datasets/fred_trade_balance_intel/us_trade_balance_monthly").json()
print(ds["title"], ds["rows"], "rows")
# Sample rows for an LLM context window
for row in ds.get("sample_rows", [])[:5]:
print(row)API endpoint: https://datazimuts.com/v1/datasets/fred_trade_balance_intel/us_trade_balance_monthly
Tip: fetch /llms.txt for the full machine-readable catalog.
Where this data comes from and what was made from it. Other people's work shows as counts; only shared projects are named.
Cite this snapshot
Pinned to snapshot 20261001T205313Z-6520e21afb72 and its content hash, so readers get exactly the data you used.
US International Trade Balance Intelligence (FRED, keyless). (2026). US international trade balance intelligence, monthly [Data set, snapshot 20261001T205313Z-6520e21afb72, sha256 6520e21afb72]. Datazimuts. Retrieved 2026-10-02, from https://datazimuts.com/en/datasets/fred_trade_balance_intel/us_trade_balance_monthly?snapshot=20261001T205313Z-6520e21afb72
@misc{dz_fred_trade_balance_intel_us_trade_balanc_6520e21a,
title = {{US international trade balance intelligence, monthly}},
author = {{US International Trade Balance Intelligence (FRED, keyless)}},
year = {2026},
publisher = {Datazimuts},
howpublished = {\url{https://datazimuts.com/en/datasets/fred_trade_balance_intel/us_trade_balance_monthly?snapshot=20261001T205313Z-6520e21afb72}},
note = {Snapshot 20261001T205313Z-6520e21afb72, sha256 6520e21afb7206629b82b4bcb7e2d4cc1ee3ad645683ade780f906a757074b89; accessed 2026-10-02}
}Embed a table or a chart
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