M2 Money Supply-to-GDP Ratio — Daily CSV Download (Monetary Expansion Ratio)
The M2-to-GDP ratio — sometimes called the “monetization ratio” — measures how much money is circulating relative to the size of the economy. Sharp increases suggest monetary accommodation is outpacing real growth (inflationary); declines suggest money is being withdrawn faster than the economy is shrinking (deflationary). The ratio surged from ~70% to ~90% during 2020–2021 and has since partially normalized.
Dataset: M2 Money Supply-to-GDP Ratio (1959–2026) · Updated —
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Source: FRED series M2SL · Federal Reserve (M2SL) & BEA (GDP) 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 M2 money supply and the CPI inflation helps situate this indicator within the broader macro regime.
Dataset Overview
| Indicator | M2 Money Supply-to-GDP Ratio (1959–2026) |
|---|---|
| Geography | United States |
| Frequency | Quarterly |
| Period | 1959–2026 |
| Variables | date, m2_gdp_pct |
| Format | CSV, Excel (XLSX) |
| Sources | Federal Reserve (M2SL) & BEA (GDP) 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 |
m2_gdp_pct | Float | M2 money supply as % of GDP |
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-gdp-ratio.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-gdp-ratio.csv" df = pd.read_csv(url, parse_dates=["date"]) print(df.head()) print(df["m2_gdp_pct"].describe())
Using the Dataset in R
library(readr) url <- "https://eco3min.fr/dataset/m2-gdp-ratio.csv" df <- read_csv(url) head(df) summary(df$m2_gdp_pct)
Both examples load the dataset directly from the URL — no download or API key required.
Methodology
M2 money supply (FRED: M2SL, monthly, averaged to quarterly) divided by nominal GDP (FRED: GDP). The ratio captures the monetization of the economy — how many dollars of money supply exist per dollar of output.
This dataset is updated quarterly 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
The M2/GDP ratio provides a structural view of monetary conditions. Combined with M2 growth rates and the Fed balance sheet ratio, it reveals whether money creation is inflationary (outpacing GDP), neutral, or deflationary (GDP growing faster than money).
- M2 Money Supply — The numerator — absolute M2 level
- M2 Growth Rate — YoY change — the rate of money creation
- US GDP Growth Rate — The denominator’s growth rate
- US CPI Inflation History — M2/GDP surges tend to precede inflation
- Fed Balance Sheet-to-GDP Ratio — Central bank footprint normalized by output
Related Research
The 2020–2021 M2/GDP surge — the largest since WWII — preceded the 2022 inflation episode. The partial normalization since then raises the question: has the excess money been absorbed, or is it still embedded in asset prices?
Macroeconomic Dataset Hub
This dataset is part of the Eco3min macro-financial data repository.
Explore the Eco3min Dataset Hub
Sources
- Federal Reserve (M2SL) & BEA (GDP) via FRED