FEDS Paper: Measuring Consumption with Credit Card Data: Benchmarking and Beyond — QuantCalc Tools Rate & Fee Analysis

FEDS Paper: Measuring Consumption with Credit Card Data: Benchmarking and Beyond — QuantCalc Tools Rate & Fee Analysis (QuantCalc Tools Desk Note, 2026-10-30) — This briefing summarizes the supplied source material at https://www.federalreserve.gov/econres/feds/measuring-consumption-with-credit-card-data-benchmarking-and-beyond.htm. Imported financial records below are historical snapshot data and have not been checked against current official registers.

Answer-First Summary: Aditya Aladangady , Ricardo Duque Gabriel , and Carlo Wix

We introduce a novel monthly county-level consumption dataset constructed from spending data on over 350 million credit cards in the Federal Reserve’s Y-14M reports, covering over 3,000 U.S. counties since 2014. We first show that the data closely track traditional consumption measures, explaining 92 percent of the variation in monthly adjusted personal consumption expenditures (PCE) growth at the national level, capturing meaningful cross-sectional variation in annual adjusted PCE growth at the state level, and reproducing the impulse response of official consumption measures to identified monetary policy shocks. We then use the county-month panel to estimate heterogeneous consumption responses to monetary policy shocks across the county-level income distribution, an analysis infeasible with traditional consumption data. We find suggestive evidence that low-income counties exhibit larger spending declines than high-income counties, consistent with heterogeneous-agent New Keynesian models. Finally, we provide practical guidance for researchers working with similar data, discussing coverage, sample composition, and the approximation of credit card spending from credit bureau data.

Core Analysis (QuantCalc Tools Rate & Fee Analysis)#

Aditya Aladangady , Ricardo Duque Gabriel , and Carlo Wix

We introduce a novel monthly county-level consumption dataset constructed from spending data on over 350 million credit cards in the Federal Reserve’s Y-14M reports, covering over 3,000 U.S. counties since 2014. We first show that the data closely track traditional consumption measures, explaining 92 percent of the variation in monthly adjusted personal consumption expenditures (PCE) growth at the national level, capturing meaningful cross-sectional variation in annual adjusted PCE growth at the state level, and reproducing the impulse response of official consumption measures to identified monetary policy shocks. We then use the county-month panel to estimate heterogeneous consumption responses to monetary policy shocks across the county-level income distribution, an analysis infeasible with traditional consumption data. We find suggestive evidence that low-income counties exhibit larger spending declines than high-income counties, consistent with heterogeneous-agent New Keynesian models. Finally, we provide practical guidance for researchers working with similar data, discussing coverage, sample composition, and the approximation of credit card spending from credit bureau data.

Key Quantitative & Regulatory Takeaways#

• Primary Subject: FEDS Paper: Measuring Consumption with Credit Card Data: Benchmarking and Beyond
• Figures & Entities in Supplied Text: 2014
• Provided Source: Source link

Structured Fact & Metric Comparison Table#

Frequently Asked Questions (FAQ)#

What are the exact figures and regulatory details reported in FEDS Paper: Measuring Consumption with Credit Card Data: Benchmarking and Beyond?#

The supplied text states: Aditya Aladangady , Ricardo Duque Gabriel , and Carlo Wix

We introduce a novel monthly county-level consumption dataset constructed from spending data on over 350 million credit cards in the Federal Reserve’s Y-14M reports, covering over 3,000 U.S. counties since 2014. We first show that the data closely track traditional consumption measures, explaining 92 percent of the variation in monthly adjusted personal consumption expenditures (PCE) growth at the national level, capturing meaningful cross-sectional variation in annual adjusted PCE growth at the state level, and reproducing the impulse response of official consumption measures to identified monetary policy shocks. We then use the county-month panel to estimate heterogeneous consumption responses to monetary policy shocks across the county-level income distribution, an analysis infeasible with traditional consumption data. We find suggestive evidence that low-income counties exhibit larger spending declines than high-income counties, consistent with heterogeneous-agent New Keynesian models. Finally, we provide practical guidance for researchers working with similar data, discussing coverage, sample composition, and the approximation of credit card spending from credit bureau data.

Has QuantCalc Tools independently verified this tools data?#

No independent verification was performed by this rewrite step. The supplied source link is https://www.federalreserve.gov/econres/feds/measuring-consumption-with-credit-card-data-benchmarking-and-beyond.htm.

Quantitative Verification & Analytical Model#