Analyzing Generational Consumption Shifts through DID Model: Evidence from the U.S. Consumer Expenditure Survey
DOI:
https://doi.org/10.61173/wjywq832Keywords:
Generation Z, Consumer Expenditure Survey, DID, Entertainment Spending, Digital ConsumptionAbstract
Young people often behave differently from older groups when it comes to how they spend money, especially in uncertain times. This paper focuses on Generation Z (ages 18–24) and examines how their entertainment and digital expenditures changed before and after recent disruptions between 2019 and 2023. The analysis uses microdata from the Consumer Expenditure Survey (CE), which is conducted by the U.S. Bureau of Labor Statistics and offers detailed household spending and demographic information. To explore this issue, the study combines Ordinary Least Squares regression with a Difference-in-Differences (DID) approach, allowing both descriptive and causal insights. The research results indicate three main points. First, Gen Z consistently spent less on entertainment compared with young Millennials (ages 25–35). Second, during the disruptive years, overall entertainment spending declined across groups, reflecting precautionary saving behavior. Third, although descriptive trends suggest Gen Z may have shifted more quickly toward digital substitutes such as streaming and gaming, the regression evidence does not show a statistically significant difference compared to Millennials. Overall, the findings underline both the structural limits faced by Gen Z and the tentative signs of adaptability visible in descriptive data, though these patterns are not statistically significant. The study contributes to understanding how younger consumers react to shocks, and its findings are relevant for firms designing digital strategies as well as for policymakers concerned with digital equity and financial literacy.
References
that younger cohorts typically spend a larger share of their [1] Twenge, J. M. (2017). iGen: Why today’s super-connected disposable income on immediate consumption rather than kids are growing up less rebellious, more tolerant, less happy— long-term savings. This framework helps explain why and completely unprepared for adulthood. New York, NY: Atria Gen Z may appear more responsive in descriptive data, Books.
even though the DID estimates do not show statistical [2] Belk, R. (2013). Extended self in a digital world. Journal of significance. Millennials, by contrast, face heavier obli- Consumer Research, 40(3), 477–500. gations like rent, childcare, and debt repayments, which [3] Baker, S. R., Farrokhnia, R. A., Meyer, S., Pagel, M., &
limit flexibility. In other words, structural position within Yannelis, C. (2020). How does household spending respond to an the life cycle is a crucial lens for interpreting generational epidemic? Consumption during the 2020 COVID-19 pandemic. differences in spending. The Review of Asset Pricing Studies, 10(4), 834–862. [4] Deursen, A. J. A. M., & van Dijk, J. A. G. M. (2014). The 5. Conclusion digital divide shifts to differences in usage. New Media & Society, 16(3), 507–526. This paper examined how Generation Z and young Mil- [5] Hargittai, E. (2010). Digital natives? Variation in Internet lennials adjusted their entertainment spending during skills and uses among members of the “Net Generation”. 2019–2023 using Consumer Expenditure Survey microda- Sociological Inquiry, 80(1), 92–113. ta. Three main findings emerged. First, Gen Z consistently [6] U.S. Bureau of Labor Statistics. (2025). Consumer spent less on entertainment than Millennials at baseline. Second, overall spending declined for both groups after Expenditure Surveys, Public Use Microdata (PUMD). U.S. 2020, reflecting precautionary saving during uncertainty. Department of Labor. Retrieved from https://www.bls.gov/cex/ Third, while Gen Z appeared to shift toward digital for- pumd.htm
mats, the DID regression shows no statistically signifi- [7] Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless cant difference compared to Millennials. These findings Econometrics: An Empiricist’s Companion. Princeton, NJ: contribute to the literature on generational consumption Princeton University Press.
by showing how descriptive and causal approaches can [8] U.S. Bureau of Labor Statistics. (2024). Consumer Price yield different insights, and by highlighting the limitations Index: All Urban Consumers (CPI-U). U.S. Department of of identifying statistically significant differences with Labor. Retrieved from https://www.bls.gov/cpi/ current data. For policymakers, the results emphasize the [9] Bleemer, Z., Brown, M., Lee, D., Strair, K., & van der
importance of supporting digital inclusion and monitoring Klaauw, W. (2021). Echoes of rising tuition in students’ platform concentration. For researchers, they point to the borrowing, educational attainment, and homeownership in postvalue of combining expenditure data with qualitative ap- recession America. Journal of Urban Economics, 122, 103298.
proaches to better understand how cultural and economic [10] Zuboff, S. (2019). The Age of Surveillance Capitalism. New pressures shape generational consumption. York, NY: PublicAffairs. At the same time, this study has some limitations. The data
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