FRED UMCSENT — Daily CSV Download (US Consumer Sentiment)

The University of Michigan Consumer Sentiment Index is the longest-running survey of American consumer confidence. It captures how households perceive current conditions and future expectations. Extreme lows have coincided with recessions (2008: 55, COVID: 71, 2022 inflation shock: 50 — a record low). The index is both a psychological indicator and a leading signal of consumption decisions.

Dataset: US Consumer Sentiment — University of Michigan (1952–2026) · Updated —


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Source: FRED series UMCSENT · University of Michigan 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 unemployment rate and the CPI inflation helps situate this indicator within the broader macro regime.

Dataset Overview

IndicatorUS Consumer Sentiment — University of Michigan (1952–2026)
GeographyUnited States
FrequencyMonthly
Period1952–2026
Variablesdate, umcsent
FormatCSV, Excel (XLSX)
SourcesUniversity of Michigan via FRED
Last updated—

Dataset Variables

The CSV and Excel files contain the following columns.

ColumnTypeDescription
dateDate (YYYY-MM-DD)Observation date
umcsentFloatUniversity of Michigan Consumer Sentiment Index

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 UMCSENT:

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

Direct CSV Access — Eco3min Structured Dataset

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

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

Using the Dataset in R

library(readr)

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

head(df)
summary(df$umcsent)

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

Methodology

FRED series UMCSENT. The index is based on monthly telephone surveys of ~500 households covering personal finances, business conditions, and buying conditions. The final index combines current conditions and expectations sub-indices.

This dataset is updated monthly (preliminary mid-month, final end-of-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

Consumer sentiment is the behavioral layer of macro analysis. It captures the psychological impact of inflation, unemployment, and financial conditions before they show up in hard spending data. The 2022 record low — driven by inflation rather than unemployment — was a novel regime.

Related Research

Sentiment collapses have historically accompanied or anticipated yield curve inversions and credit stress. Cross-referencing sentiment with financial conditions provides a dual real-economy/financial-market warning system.

Macroeconomic Dataset Hub

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

Explore the Eco3min Dataset Hub

Sources

  • University of Michigan via FRED

Suggested Citation