FRED GDP — Daily CSV Download (US GDP Growth Rate)
US real GDP growth is the headline measure of economic expansion and contraction. The NBER business cycle — the official recession dating — tracks GDP alongside other indicators. Two consecutive quarters of negative real GDP growth is the common (though not official) definition of recession. This dataset provides both annualized quarterly growth and year-over-year change.
Dataset: US GDP Growth Rate (1947–2026) · Updated —
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Source: FRED series GDP · Bureau of Economic Analysis (BEA) via FRED
Macro Takeaway
This indicator is a key component of the macro-financial monitoring framework. Its current level relative to its historical distribution — captured in the percentile and z-score above — provides immediate context for whether conditions are historically normal, stretched, or compressed.
Cross-referencing with the unemployment rate and the yield curve spread helps situate this indicator within the broader macro regime.
Dataset Overview
| Indicator | US GDP Growth Rate (1947–2026) |
|---|---|
| Geography | United States |
| Frequency | Quarterly |
| Period | 1947–2026 |
| Variables | date, gdp_billions, gdp_qoq_annualized, gdp_yoy |
| Format | CSV, Excel (XLSX) |
| Sources | Bureau of Economic Analysis (BEA) via FRED |
| Last updated | — |
Dataset Variables
The CSV and Excel files contain the following columns.
| Column | Type | Description |
|---|---|---|
date | Date (YYYY-MM-DD) | Observation date (quarterly) |
gdp_billions | Float | Nominal GDP in billions USD |
gdp_qoq_annualized | Float | Real GDP quarter-over-quarter growth, annualized (%) |
gdp_yoy | Float | Real GDP year-over-year growth (%) |
Column names match the CSV headers exactly.
Download the Complete Dataset
The full dataset is available in CSV and Excel formats.
FRED Direct CSV Access
The underlying data is available from FRED under series code GDP:
https://fred.stlouisfed.org/graph/fredgraph.csv?id=GDP
Direct CSV Access — Eco3min Structured Dataset
https://eco3min.fr/dataset/us-gdp-growth.csv
This URL returns the complete dataset in CSV format. It can be used directly in pandas, R, curl, or any data tool.
Using the Dataset in Python
import pandas as pd url = "https://eco3min.fr/dataset/us-gdp-growth.csv" df = pd.read_csv(url, parse_dates=["date"]) print(df.head()) print(df["gdp_billions"].describe())
Using the Dataset in R
library(readr) url <- "https://eco3min.fr/dataset/us-gdp-growth.csv" df <- read_csv(url) head(df) summary(df$gdp_billions)
Both examples load the dataset directly from the URL — no download or API key required.
Methodology
Real GDP from BEA (FRED: GDPC1 for real, GDP for nominal). Quarterly, seasonally adjusted at annual rates (SAAR). Growth computed as annualized QoQ and YoY percentage change.
This dataset is updated quarterly (advance, second, third estimates) via automated pull from the FRED API.
Historical Regimes
Historical regime analysis for this dataset will be added in a future update. The key stats block above provides immediate context for the current reading relative to the full historical distribution.
Related Macroeconomic Datasets
GDP is the ultimate outcome variable — but it is published with a lag and revised repeatedly. Leading indicators like the yield curve, PMIs, and credit spreads often signal GDP turning points quarters in advance.
- US Unemployment Rate — Okun’s law: GDP and unemployment are inversely related
- ISM Manufacturing PMI — Leading indicator that anticipates GDP turns
- US Industrial Production — Hard output data that drives GDP manufacturing component
- Nonfarm Payrolls — Employment — the other side of output
- US Consumer Sentiment — Behavioral leading indicator of consumption
Related Research
Every yield curve inversion has preceded a GDP contraction. The research studies on yield curve inversions and credit spreads provide the early warning framework for GDP downturns.
Macroeconomic Dataset Hub
This dataset is part of the Eco3min macro-financial data repository.
Explore the Eco3min Dataset Hub
Sources
- Bureau of Economic Analysis (BEA) via FRED