Download Real 10-Year Treasury Yield CSV (1962–2026) — Free Monthly Data

The real 10-year Treasury yield — nominal 10Y yield minus CPI inflation — is arguably the single most important variable in macro-finance. It determines the true cost of long-term capital, the discount rate for equity valuations, and the boundary between inflationary and deflationary monetary regimes. From +9.4% under Volcker (1982) to −6.4% during the 2022 inflation shock, this series spans the full spectrum of monetary history. FRED series GS10 minus CPIAUCSL since 1962.

Dataset: Real 10-Year Treasury Yield — US Real Interest Rates (1962–2026) · Updated —



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Source: FRED series GS10 · US Treasury (GS10) & BLS (CPIAUCSL) 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 10-year Treasury yield and the CPI inflation helps situate this indicator within the broader macro regime.


Dataset Overview

IndicatorReal 10-Year Treasury Yield — US Real Interest Rates (1962–2026)
GeographyUnited States
FrequencyMonthly
Period1962–2026
Variablesdate, gs10, cpi_yoy, real_10y_yield, regime
FormatCSV, Excel (XLSX)
SourcesUS Treasury (GS10) & BLS (CPIAUCSL) via FRED
Last updated

Dataset Variables

The CSV and Excel files contain the following columns.

ColumnTypeDescription
dateDate (YYYY-MM-DD)Observation date
gs10FloatNominal 10-year Treasury yield (%)
cpi_yoyFloatCPI year-over-year inflation (%)
real_10y_yieldFloatReal 10Y yield: GS10 minus CPI YoY (%)
regimeCategoricalMonetary regime classification

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 GS10:

https://fred.stlouisfed.org/graph/fredgraph.csv?id=GS10

Direct CSV Access — Eco3min Structured Dataset

https://eco3min.fr/dataset/real-10y-treasury-yield.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/real-10y-treasury-yield.csv"
df = pd.read_csv(url, parse_dates=["date"])

print(df.head())
print(df["gs10"].describe())

Using the Dataset in R

library(readr)

url <- "https://eco3min.fr/dataset/real-10y-treasury-yield.csv"
df <- read_csv(url)

head(df)
summary(df$gs10)

Both examples load the dataset directly from the URL — no download or API key required.


Methodology

Nominal 10-year Treasury yield (FRED: GS10, monthly average) minus CPI YoY inflation (FRED: CPIAUCSL). Regime classification follows five periods: Great Inflation, Volcker Shock, Great Moderation, ZIRP/QE, and Post-COVID normalization.

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

The real 10Y yield is the gravity of asset pricing. When real rates are deeply negative, every asset class is repriced upward; when they normalize, the entire valuation structure adjusts. This series is the foundation for regime-based analysis across equities, bonds, real estate, and commodities.

Related Research

This dataset is the foundation of two Eco3min research studies: the complete 770-observation real rates history with five regime classifications, and the tent-shaped relationship between real rates and the CAPE ratio.


Macroeconomic Dataset Hub

This dataset is part of the Eco3min macro-financial data repository.

Explore the Eco3min Dataset Hub


Sources

  • US Treasury (GS10) & BLS (CPIAUCSL) via FRED

Suggested Citation

Last updated — 4 April 2026