CPIAUCSL: US Consumer Price Index All Urban Consumers — Monthly Headline Series Since 1947

CPIAUCSL is the Federal Reserve Bank of St. Louis identifier for the seasonally adjusted Consumer Price Index for All Urban Consumers (CPI-U) — the foundational US inflation series and the most widely referenced inflation measure in economic analysis, Fed communications, and financial contracts. Published monthly by the Bureau of Labor Statistics, CPIAUCSL covers approximately 93% of the US population and serves as the deflator behind countless real-return calculations, TIPS coupon adjustments (via its unadjusted counterpart), and Social Security cost-of-living adjustments.

Dataset: US CPI Inflation Rate · Updated 2026-06-01

Source: FRED series CPIAUCSL · Bureau of Labor Statistics

Macro Takeaway

Dataset Overview

Dataset Variables

The CSV and Excel files contain the following columns. Each row represents one month.

Column names match the CSV headers exactly.

Download the Complete Dataset

The full dataset spans over a century of US consumer price data — from World War I through the post-COVID inflation episode. Each figure can be reproduced interactively through the precise-amount conversion front end for this series.

FRED Direct CSV Access

The CPI index is available from FRED under series code CPIAUCSL:

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

The raw FRED CPIAUCSL series provides only the index level. The Eco3min dataset adds the pre-calculated year-over-year inflation rate, saving the additional step of computing percentage changes — a common source of errors when researchers handle seasonal adjustments and base effects.

Direct CSV Access — Eco3min Structured Dataset

https://eco3min.fr/dataset/us-cpi-inflation.csv

This URL returns the complete dataset in CSV format.

Using the Dataset in Python

import pandas as pd

url = "https://eco3min.fr/dataset/us-cpi-inflation.csv"
df = pd.read_csv(url, parse_dates=["date"])

# Latest inflation reading
latest = df.dropna().iloc[-1]
print(f"Latest CPI YoY: {latest['cpi_yoy']:.1f}%")
print(f"Date: {latest['date'].strftime('%B %Y')}")

Using the Dataset in R

library(readr)

url <- "https://eco3min.fr/dataset/us-cpi-inflation.csv"
df <- read_csv(url)

head(df)
summary(df$cpi_yoy)

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

Methodology

CPIAUCSL is the seasonally adjusted Consumer Price Index for All Urban Consumers, compiled by the Bureau of Labor Statistics from monthly price surveys covering approximately 80,000 items across 75 urban areas. The index measures the average change in prices paid by urban consumers for a representative basket of goods and services. It covers roughly 93% of the US population.

The series CPIAUCSL is seasonally adjusted (the “S” suffix stands for “Seasonally Adjusted”) and uses a reference base period of 1982–1984 = 100. The basket weights are updated biennially based on the Consumer Expenditure Survey. As of the most recent weight update, housing (shelter) accounts for approximately 36% of the headline index weight, making it the single largest component and a key driver of the post-2021 inflation persistence.

The year-over-year inflation rate in this dataset is calculated as cpi_yoy = (CPIAUCSL[t] / CPIAUCSL[t-12] − 1) × 100, where t is the current month and t-12 is the same month one year prior. This methodology eliminates seasonal effects (already removed in CPIAUCSL itself) and provides a clean annualized inflation rate.

This dataset is updated monthly via automated pull from the FRED API, typically within 24 hours of the BLS CPI release.

Data Quality & Provider Notes

CPIAUCSL is one of the most observed economic series in the world, with a precise release calendar and decades of methodological documentation. The series is among the most reliable in FRED, but a small number of release-mechanic and revision details matter for serious users.

• Release latency. The BLS publishes the CPI report at 08:30 ET, typically between the 10th and 14th of the month for the prior month’s data. CPIAUCSL is updated on FRED within minutes of the release.
• Revisions policy. The CPI index level is not revised after initial publication. However, BLS revises seasonal adjustment factors once per year (typically February), which can modify the entire historical CPIAUCSL series back to 2020 at each annual revision. The non-seasonally adjusted counterpart (CPIAUCNS) is never revised after release and is the legally referenced series for TIPS, Social Security COLA, and most inflation-linked contracts.
• Alternative sources. The same data is available directly from BLS (Series CUSR0000SA0 for seasonally adjusted, CUUR0000SA0 for unadjusted) and through Bloomberg, Refinitiv, and Haver Analytics. ALFRED provides vintage CPIAUCSL data, which is essential when reproducing historical real-time decisions because of the annual seasonal revision.
• Known gaps. Monthly series with no gaps since January 1947. Pre-1947 splices using BLS historical CPI-U data are available but methodologically heterogeneous and are not part of CPIAUCSL itself.

For real-return calculations and financial contracts, the choice between CPIAUCSL (seasonally adjusted) and CPIAUCNS (unadjusted) is non-trivial: contracts indexed to CPI use the unadjusted series, while macroeconomic analyses typically use the seasonally adjusted version.

Common Pitfalls When Using CPIAUCSL

CPIAUCSL is the most cited inflation series in the world, but its very ubiquity creates several recurring interpretation errors that distort analysis.

1. Confusing the CPIAUCSL index level with the YoY inflation rate. The FRED series CPIAUCSL is the price index (1982–84 = 100), not the year-over-year change. The Eco3min dataset adds the precomputed YoY rate (the cpi_yoy column). Plotting the CPIAUCSL level and labeling it “inflation” is a frequent error in commentary — the level shows cumulative price growth since 1982, not the current inflation rate.
2. Confusing CPIAUCSL (headline) with CPILFESL (core). Headline includes food and energy; core excludes them. The Fed tends to “look through” headline volatility — but headline is the politically and economically operative measure for households and indexed contracts. Using headline where core is analytically appropriate (or vice versa) is a routine source of confusion. Our review of core CPI vs headline CPI details when each is the right reference.
3. Mixing CPIAUCSL (seasonally adjusted) with CPIAUCNS (unadjusted). TIPS coupons, Social Security COLA, and most inflation-linked contracts reference the unadjusted series CPIAUCNS. Pulling CPIAUCSL into a TIPS-linked calculation introduces systematic seasonal bias because the seasonal adjustment is itself revised every year.
4. Treating the Fed’s target as a CPIAUCSL target. The Fed’s 2% target is on core PCE, not CPI. The CPI-PCE gap (typically 30–50 bps with CPI higher) means a 2.5% CPIAUCSL print is consistent with a 2% core PCE — but commentary that reads CPIAUCSL directly against the 2% target systematically misjudges Fed reaction. See the PCE vs CPI gap study.

Historical Regimes

1947–1965 — Post-war stability. CPIAUCSL inflation averaged 2–3% as the Bretton Woods system provided a nominal anchor through dollar-gold convertibility. This period is sometimes cited as the “golden age” of price stability, though it was underpinned by structural conditions (demographics, productivity growth, fixed exchange rates) that no longer exist. The earlier 1914–1946 era — captured by BLS CPI-U historical splices rather than CPIAUCSL itself — included WWI inflation above 20% and Depression deflation of −10% in 1932.

1966–1982 — The Great Inflation. CPIAUCSL inflation accelerated from 3% to a peak of 14.8% in March 1980, driven by fiscal expansion (Vietnam War, Great Society), two oil shocks, and a Federal Reserve that consistently underestimated inflation persistence. The Volcker tightening (Fed Funds above 20%) ultimately broke the cycle at the cost of two recessions, an episode documented in our 110-year inflation history study. This remains the reference case for how entrenched inflation expectations can become self-reinforcing.

1983–2020 — The Great Moderation. CPIAUCSL averaged roughly 2.5% over nearly four decades, the longest period of sustained low inflation in US history. The decline was driven by Fed credibility (anchored expectations), globalization (cheap imports), and technology-driven productivity gains. By 2020, the consensus concern had shifted to structurally too-low inflation, with the Fed adopting its Average Inflation Targeting framework. The divergence between headline and core remained relatively stable through this period.

2021–2023 — Post-pandemic inflation shock. CPIAUCSL surged to 9.1% in June 2022 (BLS data), the highest since 1981, driven by pandemic-era fiscal stimulus, supply chain disruptions, and energy price spikes. The subsequent disinflation path proved uneven — core services inflation (particularly shelter) remained more persistent than goods inflation. The role of M2 money supply growth in this episode reopened a long-dormant debate about the monetarist transmission channel.

2024–2026 — Disinflation and stabilization. CPIAUCSL declined from above 9% toward the 2–3% range, with the relationship to WTI crude and shelter-component lags driving most of the residual volatility. Whether CPIAUCSL durably returns to the pre-2020 2–2.5% range or settles at a structurally higher level remains the central macro question, with implications for core PCE, real rates, and asset valuations alike.

Related Macroeconomic Datasets

CPIAUCSL is the deflator behind real returns, the input to TIPS pricing, and the politically operative measure of household inflation. The following datasets contextualize headline CPI against the policy rate, the core measures the Fed actually targets, and the structural drivers (M2, oil) that have shaped each historical regime. The same regimes, re-read as a sequence of waves, are the subject of the takedown of the viral 1970s-versus-2026 overlay.

Macroeconomic Dataset Hub

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

Explore the Eco3min Dataset Hub

Sources

• U.S. Bureau of Labor Statistics — Consumer Price Index for All Urban Consumers: All Items in U.S. City Average
• Federal Reserve Bank of St. Louis — FRED series CPIAUCSL

Dataset Reference

Eco3min Research. (2026). CPIAUCSL: US CPI Inflation Rate History (1947–2026).<br> https://eco3min.fr/en/us-inflation-history-dataset/