Method: The data used is the 2018 National Financial Capability Study (NFCS) by Financial Investor Regulatory Authority. We used Latent Class Analysis (LCA) to identify financial access profiles and examined logistic regression to assess sociodemographic factors and financial knowledge associated with financial access profiles. For financial access, items include checking and savings account, using alternative financial services (i.e., pawnshop, auto loans), having credit cards (CC), CC payment, CC interests, retirement account through and not through an employer, investments, and emergency savings. The grouping variable was created using the birth year: silent, boomers, GenXers, and millennials. Other variables include objective knowledge (Lusardi-Mitchel score), subjective knowledge. Household income, race, education, gender, employment status, marital status, age, and financially supporting children.
Results: The LCA results showed four latent classes (entropy=0.86), named as (1) Financially vulnerable (33%), (2) CC-relying (28%), (3) AFS user (7%), and (4) Well-off (33%). The composition of the classes in each generation differs, especially for Millennials. For example, the Silent Generation and Boomers showed overall financially well-off (66%, 50%, respectively). However, those who are well-off among Millennials are only 16%. Further, Millennials took up most of the AFS users (16%), while other generations showed nearly no AFS users (<3%). Those who rely on credit-card to cover expenses varied by generation, but the highest among GenXers (37%). Logistic regression showed white, more educated, male, working, married or living with partners, older, and low number of supporting children were more likely to be in financially well-off group, compared to non-white, low education, female, not-working, living alone, younger or having more children.
Conclusion: Heterogeneity exists in financial access among generations. Clearly older generations (Silent and Boomers) are most likely to be financially well-off, while younger generations more likely to exhibit somewhat risky financial behaviors. This shows that age-graded approach with life-course perspective in building policies and the program is critical. Also, race, gender, and socioeconomic disparities manifest in FC, which in turn may lead to disparities in financial outcomes. Thus, programs and policies on FC should target filling the gaps created from these disparities.