M2 Growth Rate — Daily CSV Download (Money Supply YoY Change)
The year-over-year growth rate of M2 money supply is one of the most powerful leading indicators of inflation. M2 growth historically leads CPI inflation by 12–18 months. The unprecedented +27% YoY growth in February 2021 preceded 9.1% CPI inflation in June 2022. The subsequent contraction to −4.7% in late 2023 — the first sustained M2 decline since the 1930s — foreshadowed the inflation deceleration.
Dataset: US M2 Money Supply Growth Rate (1960–2026) · Updated —
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Source: FRED series M2SL · Federal Reserve Bank of St. Louis — FRED (M2SL)
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 CPI inflation and the M2 level helps situate this indicator within the broader macro regime.
Dataset Overview
| Indicator | US M2 Money Supply Growth Rate (1960–2026) |
|---|---|
| Geography | United States |
| Frequency | Monthly |
| Period | 1960–2026 |
| Variables | date, m2_yoy_pct |
| Format | CSV, Excel (XLSX) |
| Sources | Federal Reserve Bank of St. Louis — FRED (M2SL) |
| Last updated | — |
Dataset Variables
The CSV and Excel files contain the following columns.
| Column | Type | Description |
|---|---|---|
date | Date (YYYY-MM-DD) | Observation date |
m2_yoy_pct | Float | M2 year-over-year growth rate (%) |
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 M2SL:
https://fred.stlouisfed.org/graph/fredgraph.csv?id=M2SL
Direct CSV Access — Eco3min Structured Dataset
https://eco3min.fr/dataset/m2-growth-rate.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/m2-growth-rate.csv" df = pd.read_csv(url, parse_dates=["date"]) print(df.head()) print(df["m2_yoy_pct"].describe())
Using the Dataset in R
library(readr) url <- "https://eco3min.fr/dataset/m2-growth-rate.csv" df <- read_csv(url) head(df) summary(df$m2_yoy_pct)
Both examples load the dataset directly from the URL — no download or API key required.
Methodology
Year-over-year percentage change of FRED series M2SL. Computed as (M2_t / M2_{t-12} − 1) × 100. M2 includes cash, checking deposits, savings, money market funds, and small CDs.
This dataset is updated monthly (15th of each month) 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
M2 growth is the bridge between monetary policy and inflation. The Fed creates reserves (balance sheet) → banks create deposits (M2) → excess money chases goods (CPI). The 12–18 month lag is one of the most consistent relationships in macro.
- M2 Money Supply — The absolute level from which growth is computed
- M2-to-GDP Ratio — Money growth normalized by economic size
- US CPI Inflation — The variable that M2 growth leads by 12–18 months
- Core PCE Inflation — The Fed’s preferred inflation measure — also led by M2
- Fed Balance Sheet (WALCL) — QE drives M2 growth through reserve creation
Related Research
The 2020–2023 M2 cycle was the most extreme since the 1940s: +27% growth followed by −4.7% contraction. The inflation and disinflation that followed confirmed the monetary transmission channel remains alive.
Macroeconomic Dataset Hub
This dataset is part of the Eco3min macro-financial data repository.
Explore the Eco3min Dataset Hub
Sources
- Federal Reserve Bank of St. Louis — FRED (M2SL)