US Real Wage Growth — Daily CSV Download (Inflation-Adjusted Wages)

Real wage growth — nominal average hourly earnings minus CPI inflation — measures whether American workers’ purchasing power is actually improving. During 2021–2022, nominal wages grew 5%+ but real wages fell sharply as inflation outpaced earnings. Real wage growth is the ultimate test of whether economic expansion benefits workers or is consumed by price increases.

Dataset: US Real Wage Growth (1964–2026) · Updated —


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Source: FRED series CES0500000003 · BLS (CES0500000003 & 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 CPI inflation and the unemployment rate helps situate this indicator within the broader macro regime.

Dataset Overview

IndicatorUS Real Wage Growth (1964–2026)
GeographyUnited States
FrequencyMonthly
Period1964–2026
Variablesdate, nominal_earnings_yoy, cpi_yoy, real_wage_yoy
FormatCSV, Excel (XLSX)
SourcesBLS (CES0500000003 & CPIAUCSL) via FRED
Last updated—

Dataset Variables

The CSV and Excel files contain the following columns.

ColumnTypeDescription
dateDate (YYYY-MM-DD)Observation date
nominal_earnings_yoyFloatAverage hourly earnings YoY change (%)
cpi_yoyFloatCPI year-over-year inflation (%)
real_wage_yoyFloatReal wage growth: nominal earnings minus CPI (%)

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 CES0500000003:

https://fred.stlouisfed.org/graph/fredgraph.csv?id=CES0500000003

Direct CSV Access — Eco3min Structured Dataset

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

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

Using the Dataset in R

library(readr)

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

head(df)
summary(df$nominal_earnings_yoy)

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

Methodology

Nominal average hourly earnings for all private employees (FRED: CES0500000003) YoY growth minus CPI YoY inflation (FRED: CPIAUCSL). This captures the net purchasing power change for the median American worker.

This dataset is updated monthly (first Friday — BLS Employment Situation) 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

Real wages are the link between macro aggregates and lived experience. Positive real wage growth means workers are getting ahead; negative means inflation is winning. The 2021–2023 cycle saw the largest real wage decline since the 1970s, followed by a recovery as inflation decelerated.

Related Research

Real wage growth connects to the real interest rate story — both measure the same concept (nominal minus inflation) applied to different prices (labor vs capital).

Macroeconomic Dataset Hub

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

Explore the Eco3min Dataset Hub

Sources

  • BLS (CES0500000003 & CPIAUCSL) via FRED

Suggested Citation