Real-Time Estimates of Differences in Real Expenditure Growth and Inflation across Households

Abstract

This article presents a framework to monitor differences in real expenditure growth and inflation in real time, focusing on variations across the expenditure distribution. High-frequency tracking of heterogeneity in real expenditure growth and inflation holds particular value for policymakers. The newly constructed time series reveals three key findings. First, households with lower expenditure levels have faced higher inflation since 2000 than those with higher expenditure levels, with significant disparities in the range of 0.57 and 1.23 percentage-point differences between 2005–2008 and 2011, respectively. Second, volatility in real expenditure growth is higher for lower-expenditure households than for higher-expenditure ones. Third, there was significant heterogeneity in the recovery of real expenditure in the two years following the outbreak of COVID-19.

Introduction

Tracking real-time differences in real expenditure growth and inflation across households at a high frequency is valuable for understanding current economic situations and informing the policymaking process. The Bureau of Economic Analysis (BEA) releases the personal consumption expenditures (PCE) price index as a monthly measure of inflation and consumer spending on goods and services by U.S. households. However, these published figures lack details about which groups of households experience different rates of real expenditure growth.

This article presents a framework for estimating real expenditure growth and inflation across households along the expenditure distribution. The idea behind this methodology is to use an estimate of the by-category expenditure share for each household group (split by the level of expenditures). With the shares, the framework estimates the total expenditure of each household group every month at the PCE release, which provides total expenditure by category every month. Thus, this approach relies on two key facts: (i) Households at different expenditure levels buy distinct baskets of goods and services, and (ii) these baskets remain relatively stable over time.

Using the Consumer Expenditure Survey (CE), Garner et al. (2024) divide households into five expenditure-based quintiles and identify their spending shares across 16 categories that align with the PCE classification. Expenditures and income are highly correlated, suggesting that fluctuations in consumption by expenditure quintiles likely provide a reliable approximation for consumption patterns by income quintiles, as argued in Appendix 1. Estimating each quintile’s share within PCE categories enables the computation of cross-household differences in expenditure growth based on PCE data.