Honors Projects

Abstract

This study examines overconsumption in the United States by analyzing how socioeconomic factors influence household spending relative to income. Overconsumption is defined as elevated discretionary spending relative to income, with a focus on categories such as apparel, entertainment, and food away from home. Using 2024 Consumer Expenditure Survey (CEX) data, three multiple linear regression models were created to evaluate predictors of overall consumption, discretionary consumption, and apparel spending as proportions of income.

Results show that income is the most significant predictor across all models, with higher-income households consistently spending a smaller share of their income. Age and household size also demonstrate negative relationships with the three spending ratios, suggesting more conservative spending patterns among older individuals and larger households. Education and urban status show limited and inconsistent effects. Model explanatory power declines for more specific categories, with apparel spending exhibiting the weakest fit, indicating that discretionary and apparel consumption behaviors are less driven by the socioeconomic factors included in the models.

Overall, the findings suggest that while demographic and economic variables help explain broad consumption trends, they fall short in capturing more nuanced forms of overconsumption. This emphasizes the importance of behavioral, cultural, and technological influences in shaping modern spending patterns and highlights the need for future research that takes these factors into account.

Department

Honors Program

Major

Business Analytics and Intelligence

First Advisor

Diane Conway

First Advisor Department

Applied Statistics and Operations Research

Second Advisor

Kathryn Phillips

Second Advisor Department

Marketing

Publication Date

Spring 4-27-2026

Download

Share

COinS