Psychological characteristics and household savings behavior: The importance of accounting for latent heterogeneity

Abstract

We employ a finite mixture model with maximum likelihood (ML) estimation to analyze latent heterogeneity in the relationship between psychological characteristics and household savings behavior. In a one-step ML estimation approach, we estimate a class membership model and a behavioral model of the classes jointly. Adopting this approach enables us to simultaneously assess how socio-demographic characteristics affect class membership probabilities and estimate class-specific regression coefficients, to test whether psychological characteristics predict savings behavior differently across latent classes. We apply this approach to a representative sample of UK households (n = 3,382) and identify two different latent classes: striving versus established households. We find that the relationship between psychological characteristics and savings behavior differs across these two classes, demonstrating the importance of accounting for latent heterogeneity when studying the drivers of savings behavior. Our results have implications for policymakers attempting to improve household savings behavior.

How Does Consumers' Financial Vulnerability Relate to Positive and Negative Financial Outcomes? The Mediating Role of Individual Psychological Characteristics

“…Second, participants indicated on average having $329,109 in total investments (SD = $1,607,991; Median = $3,500). To address the skewed distributions, we followed prior literature in consumer financial decision‐making (Gerhard, Gladstone, and Hoffmann ; Nyhus and Webley ) and took the natural log of total savings and investments for the purpose of our analyses. To accommodate for the fact that some participants had zero savings or investments, we added 1 to the value of each of these variables before taking the log.…”

A Behavioral Perspective on Saving Decisions. Empirical Evidence for Policymakers in the European Union

“…Finally, the literature has argued that the ability of individuals to save may be influenced by different socio-demographic variables (Abrahamse and Steg, 2009;Browning and Lusardi, 1996;Gerhard et al, 2018). In particular, empirical evidence shows that individuals' saving tends to increase with age and peaks around the age of 60 (Attanasio, 1998;Knoef et al, 2016).…”

“…An important way forward when trying to improve the quality of financial regulation is through using insights provided by BE. Indeed, BE insights have started to shape an emerging theoretical and empirical paradigm to understand circumstances in which individuals' behavior might prevent them from maximising their own welfare (Clifton et al, 2017b;Gerhard et al, 2018;Sunstein, 2018;Thaler and Benartzi, 2004). The provision of an appropiate institutional setting, such as access to well-functioning financial markets, may not be sufficient to improve individuals' decisions (World Bank, 2015).…”

Hand-to-mouth consumers, rule-of-thumb savers, and optimal control

“…More sophisticated patterns of eventual departure from optimal planning might be associated to the wide range of psychological factors influencing the savings behavior of individuals, factors that in no way can be associated with a plain optimal programming model. Gerhard et al (2018) investigate a large number of drivers of savings behavior, including financial literacy, the most relevant personality traits, self-control, optimism, attitudes toward savings, and regulatory focus. All these drivers contribute to shape decision rules that involve motivations that go beyond economic criteria.…”

“…Reasons for this disparity on savings behavior can be traced back to empirical evidence, namely the evidence already discussed in Sect. 2 following the research undertaken by Gerhard et al (2018): people adopt different attitudes toward savings given their distinct psychological profiles (including personality traits) and financial literacy competencies.…”