Fed's Credit Card Data Reveals Income-Based Consumption Shifts

A More Timely Gauge of the American Consumer

The Federal Reserve’s newly detailed methodology for tracking consumption via credit card data represents a significant step toward real-time economic assessment. According to the paper released October 30, 2026, data pulled from over 350 million credit cards, covering more than 3,000 U.S. counties since 2014, closely mirrors established measures of personal consumption expenditures (PCE), explaining 92 percent of the variation in monthly PCE growth at the national level. This high correlation suggests the potential to use credit card data as an early indicator of economic trends, supplementing—and potentially, eventually, accelerating the timeline of—insights drawn from the traditional PCE data relied upon by economists and market participants.

Heterogeneous Responses to Monetary Policy

The power of this new data set, however, extends beyond simply replicating existing metrics. The granularity of the data – specifically, the county-month panel structure – allows for analysis previously impossible with traditional consumption data. The research focuses on identifying how consumption responds to monetary policy shocks across different income levels. The findings indicate that low-income counties exhibit larger spending declines in response to such shocks than high-income counties. This observation aligns with theoretical models that predict heterogeneous responses to monetary policy, where lower-income households are disproportionately affected by changes in interest rates and credit availability.

Implications for Fed Policy and Economic Modeling

The finding of income-based divergence in consumption response has important implications for the Federal Reserve's policy decisions. If lower-income households are more sensitive to monetary policy, it suggests that tightening policies could have a more pronounced impact on vulnerable populations. This necessitates a more nuanced approach to monetary policy, potentially requiring consideration of distributional effects alongside aggregate economic objectives. Furthermore, the data provides a valuable testbed for heterogeneous-agent New Keynesian models, allowing researchers to refine and validate these models against real-world consumption patterns.

Data Accessibility and Future Research

The paper also addresses practical considerations for researchers seeking to utilize similar data, offering guidance on coverage, sample composition, and the approximation of credit card spending from credit bureau data. This commitment to transparency and methodological rigor enhances the usability and reliability of the data for academic and policy-oriented research. The availability of county-level data, stretching back to 2014, provides a rich historical record for analyzing consumption trends and their relationship to various economic factors. The researchers have effectively laid the groundwork for a more detailed and responsive understanding of the American consumer.

A Challenge for Traditional Benchmarks

While the new data closely tracks PCE growth nationally, the demonstrated ability to disaggregate consumption patterns by income level presents a challenge to the traditional, aggregate benchmarks used to assess the health of the U.S. economy. The 92% correlation provides a strong validation of the methodology, but the added dimension of income-based analysis creates a new standard for evaluating the impact of Fed policy over time.