Method. The study used data from FINRA’s 2018 National Financial Capability Study. Panel respondents (N = 27,091) had a mean age of 48 (SD = 17) years and reported a normal distribution of income; 26% identified with a marginalized racial/ethnic identity. Reported financial anxiety levels were M = 4.51 (SD = 2.02; on a scale of 1 to 7, with higher as worse anxiety). For the FP measure, 11 objectively oriented items (e.g., having unpaid medical bills) and five subjectively oriented items (e.g., having too much debt) were selected for analysis. Employing exploratory (EFA) and confirmatory factor analyses (CFA), a piecewise modeling approach was used to construct two correlated latent variables that comprise the FP measure. The project was carried out with the lavaan package for R, using oblimin rotation and the WLSMV estimator.
Results. Preliminary factor adequacy was ascertained (KMO = 0.92). The final EFA model showed reasonable fit (χ2 = 4879.999, df = 76, p < .001; SRMR = 0.059; CFI = 0.995; TLI = 0.994; RMSEA = 0.055, 90% CI [0.054, 0.057]). Items were rearranged or excluded according to both theoretical and statistical threshold benchmark levels (excluding those with factor loadings < |.40|). After correlating errors according to the modification indices that were theoretically supportable, the final CFA model achieved reasonable fit (χ2 = 4083.276, df = 49, p < .001; SRMR = 0.048; CFI = 0.996; TLI = 0.995; RMSEA = 0.061, 90% CI [0.059, 0.062]). Standardized CFA factor loadings ranged from 0.669 to 0.906 for objective FP and 0.592 to 0.875 for subjective FP. The objective and subjective latent variables provided a better fitting model on their own as correlated constructs (β = 0.872, p < .001), than modeling them as primaries to a second-order latent variable for financial precarity. As such, they are referred together as the measure of financial precarity, albeit being distinct.
Conclusions. The project contributes a new measure of FP that is more holistic than measures which focus exclusively on either material or psychological domains. The measure supports deeper research into scarcity and can help policymakers and practitioners better understand the experiences of those struggling with financial difficulties. Next steps include incorporating questions on sharing financial resources, assessing measurement invariance across marginalized populations, and testing the validity and reliability of the measure.