US GDPNow real-GDP growth nowcast, quarterly
Quarterly US GDPNow nowcast intelligence panel, 2011-Q3 onward: the Federal Reserve Bank of Atlanta's GDPNow nowcasting model for real-GDP growth (percent change at annual rate, SAAR; FRED GDPNOW, redistributed keyless via FRED fredgraph.csv). Carries the nowcast level, quarter-over-quarter revision, a 4-quarter trailing trend anchor, the acceleration read (nowcast minus trend), growth tiers and contraction/strong-growth flags, plus nowcast_live_flag marking the in-progress nowcast row. Method caveats: the latest row is a live model estimate revised multiple times within the quarter, not a realized outcome; it converges to the BEA advance estimate. One row per quarter x USA; in-window nulls fail loudly, never imputed. Who joins this: the catalog's only forward-looking macro signal — B2B sales teams join the nowcast on quarter + country_code to time outreach around growth turns; shops use vs_trend_pp and contraction_flag as demand-regime features.
Les titres et les descriptions proviennent des sources de données, en anglais.
- Lignes
- 61
- Colonnes
- 14
- Cadence de la source
- Trimestrielle
- Dernière actualisation
- 1 oct. 2026
- Thème
- economy
| Colonne | Type | Description |
|---|---|---|
| quarter_start | date | First day of the calendar quarter (ISO date join key). (unit: date) |
| quarter | string | Calendar quarter as YYYY-QN (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) |
| gdpnow_pct | float | GDPNow nowcast of real-GDP growth (FRED GDPNOW; Federal Reserve Bank of Atlanta). The latest row is the in-progress nowcast; earlier rows are finalized history converging to the BEA advance estimate. (unit: percent change at annual rate, SAAR) |
| nowcast_live_flag | integer | 1 on the latest row — the in-progress nowcast, still subject to revision; 0 on finalized quarters. (unit: flag) |
| nowcast_qoq_pp | float | Quarter-over-quarter change in the nowcast, percentage points (null for the first panel quarter). (unit: percentage points) |
| trailing_4q_avg_pct | float | 4-quarter trailing mean of the nowcast — the trend anchor (null for the first 3 panel quarters). (unit: percent change at annual rate, SAAR) |
| vs_trend_pp | float | Nowcast minus the 4-quarter trailing average — the acceleration read (null for the first 3 panel quarters). (unit: percentage points) |
| growth_tier | string | Growth regime on fixed cut points: contraction (< 0), slow (0–1.5), solid (1.5–3), strong (>= 3). (unit: string) |
| contraction_flag | integer | 1 when the nowcast prints below 0, else 0. (unit: flag) |
| strong_growth_flag | integer | 1 when the nowcast prints at or above 3.5, else 0. (unit: flag) |
| row_hash | string | Deterministic 16-hex sha256 of quarter + the nowcast level (idempotency key). (unit: string) |
10 premières lignes d’exemple — un aperçu, pas le jeu de données complet.
| quarter_start | quarter | year | country | country_code | gdpnow_pct | nowcast_live_flag | nowcast_qoq_pp | trailing_4q_avg_pct | vs_trend_pp | growth_tier | contraction_flag | strong_growth_flag | row_hash |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2011-07-01 | 2011-Q3 | 2 011 | United States | USA | 3,245 | 0 | — | — | — | strong | 0 | 0 | a243f5a99cda1ec5 |
| 2011-10-01 | 2011-Q4 | 2 011 | United States | USA | 5,168 | 0 | 1,924 | — | — | strong | 0 | 1 | e1f08ae254d0f4e9 |
| 2012-01-01 | 2012-Q1 | 2 012 | United States | USA | 3,015 | 0 | -2,153 | — | — | strong | 0 | 0 | f1207cb843757b4a |
| 2012-04-01 | 2012-Q2 | 2 012 | United States | USA | 0,224 | 0 | -2,791 | 2,913 | -2,689 | slow | 0 | 0 | 16d637b7f151130e |
| 2012-07-01 | 2012-Q3 | 2 012 | United States | USA | 1,849 | 0 | 1,625 | 2,564 | -0,715 | solid | 0 | 0 | 97c1c9328197ed5d |
| 2012-10-01 | 2012-Q4 | 2 012 | United States | USA | 0,078 | 0 | -1,771 | 1,291 | -1,214 | slow | 0 | 0 | 5c694f79ea42e020 |
| 2013-01-01 | 2013-Q1 | 2 013 | United States | USA | 2,872 | 0 | 2,794 | 1,256 | 1,616 | solid | 0 | 0 | 4733119053e49a63 |
| 2013-04-01 | 2013-Q2 | 2 013 | United States | USA | 1,3 | 0 | -1,572 | 1,525 | -0,225 | slow | 0 | 0 | bfaa38c4e48a99ec |
| 2013-07-01 | 2013-Q3 | 2 013 | United States | USA | 2,323 | 0 | 1,023 | 1,643 | 0,68 | solid | 0 | 0 | c7999c1069045c0c |
| 2013-10-01 | 2013-Q4 | 2 013 | United States | USA | 3,125 | 0 | 0,802 | 2,405 | 0,72 | strong | 0 | 0 | 47cb1a52b67e05a4 |
Profilé le 1 oct. 2026 à partir de l’instantané 20261001T173635Z-b49abe449e58
Mesuré- Complétude
- 99,2 %
- Lignes
- 61
- Colonnes
- 14
- Colonnes incomplètes
- 3
| Colonne | Manquant | Distinctes | Plage | Distribution |
|---|---|---|---|---|
| quarter_startdate | 0 % | 63 | 1 juill. 2011 → 1 juill. 2026 | — |
| quartervarchar | 0 % | 55 | — |
|
| yearbigint | 0 % | 19 | 2 011 → 2 026médiane 2 019 | |
| countryvarchar | 0 % | 1 | — |
|
| country_codevarchar | 0 % | 1 | — |
|
| gdpnow_pctdouble | 0 % | 69 | -32,08 → 36,97médiane 2,43 | 2 hors du 1er–99e centile |
| nowcast_live_flagbigint | 0 % | 2 | 0 → 1médiane 0 | 1 hors du 1er–99e centile |
| nowcast_qoq_ppdouble | 1,6 % | 60 | -31,12 → 69,06médiane 0,12 | 2 hors du 1er–99e centile |
| trailing_4q_avg_pctdouble | 4,9 % | 60 | -7,41 → 14,61médiane 2,2 | 2 hors du 1er–99e centile |
| vs_trend_ppdouble | 4,9 % | 65 | -24,67 → 35,56médiane -0,1318 | 2 hors du 1er–99e centile |
| growth_tiervarchar | 0 % | 4 | — |
|
| contraction_flagbigint | 0 % | 2 | 0 → 1médiane 0 | |
| strong_growth_flagbigint | 0 % | 2 | 0 → 1médiane 0 | |
| row_hashvarchar | 0 % | 57 | — |
|
- Actuelle
20261001T173635Z-b49abe449e58 · sha256 b49abe449e58…
61 lignes · premier instantané
Dirigez n’importe quel LLM vers le point d’accès des métadonnées — la documentation ci-dessus est aussi lisible par machine (JSON-LD + Croissant).
curl "https://datazimuts.com/v1/datasets/fred_gdpnow_intel/us_gdpnow_quarterly" | jq '{title, rows, columns_count, license}'import requests
ds = requests.get("https://datazimuts.com/v1/datasets/fred_gdpnow_intel/us_gdpnow_quarterly").json()
print(ds["title"], ds["rows"], "rows")
# Sample rows for an LLM context window
for row in ds.get("sample_rows", [])[:5]:
print(row)Point d’accès API : https://datazimuts.com/v1/datasets/fred_gdpnow_intel/us_gdpnow_quarterly
Astuce : récupérez /llms.txt pour le catalogue complet lisible par machine.
D’où viennent ces données et ce qui en a été fait. Le travail des autres apparaît sous forme de décomptes ; seuls les projets partagés sont nommés.
Citer cet instantané
Épinglé à l’instantané 20261001T173635Z-b49abe449e58 et à son empreinte, pour que vos lecteurs obtiennent exactement les données utilisées.
US GDPNow Nowcast Intelligence (FRED, keyless). (2026). US GDPNow real-GDP growth nowcast, quarterly [Data set, snapshot 20261001T173635Z-b49abe449e58, sha256 b49abe449e58]. Datazimuts. Retrieved 2026-10-02, from https://datazimuts.com/fr/datasets/fred_gdpnow_intel/us_gdpnow_quarterly?snapshot=20261001T173635Z-b49abe449e58
@misc{dz_fred_gdpnow_intel_us_gdpnow_quarterly_b49abe44,
title = {{US GDPNow real-GDP growth nowcast, quarterly}},
author = {{US GDPNow Nowcast Intelligence (FRED, keyless)}},
year = {2026},
publisher = {Datazimuts},
howpublished = {\url{https://datazimuts.com/fr/datasets/fred_gdpnow_intel/us_gdpnow_quarterly?snapshot=20261001T173635Z-b49abe449e58}},
note = {Snapshot 20261001T173635Z-b49abe449e58, sha256 b49abe449e58f89bd2abacc9c7747dd5ece0a6adae3927bac32a6c7d1a651fd3; accessed 2026-10-02}
}Intégrer un tableau ou un graphique
Collez ce code dans n’importe quelle page. L’intégration est épinglée au même instantané, suit le thème clair ou sombre du lecteur et affiche toujours la source, la licence et un lien de retour.
<iframe src="https://datazimuts.com/embed/chart?dataset=fred_gdpnow_intel%2Fus_gdpnow_quarterly&lang=fr&theme=auto&snapshot=20261001T173635Z-b49abe449e58&x=year&y=year&agg=avg" title="US GDPNow real-GDP growth nowcast, quarterly" width="100%" height="380" style="border:0" loading="lazy"></iframe>
Posez une question sur ce jeu de données. Les réponses viennent uniquement de sa fiche, de son profil mesuré et de son historique, et citent les faits utilisés.