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This study investigates the financial attributes, financial behaviors, financial‐advisor‐use beliefs, and investing characteristics associated with having used an automated investment solution (i.e., a robo‐advisor). Data are used from the 2015 National Financial Capability Study (both the State‐by‐State Survey and the Investor Survey) to investigate the use of robo‐advisors among 1,393 individuals with non‐retirement investment accounts. Multivariable results indicated that being younger, having low or midrange income, and having lower objective investment‐knowledge scores was positively associated with robo‐advisor use. This study provides important insight for policymakers, financial practitioners, and proprietors of robo‐advisors and other fintech products. [ABSTRACT FROM AUTHOR]

This study investigates how psychological characteristics influence saving behavior within a sample of 1,380 U.S. preretirees aged 50–70 from the Health and Retirement Study (HRS). Using the 3M Model of Motivation and Personality as a theoretical basis, structural equation model results revealed that financial self‐efficacy (FSE) directly explains saving behavior and is central to understanding the link between other psychological characteristics and the saving behavior of older adults. Through higher FSE, increased positive affect and reduced negative affect indirectly supported saving behavior. Moreover, the results revealed personality traits indirectly explained saving behavior. Conscientiousness and extroversion indirectly supported saving behavior; whereas openness to experience and neuroticism indirectly undermined saving behavior. This study connects broad personality traits with saving behavior, which provides information about how older adults' psychological composition is related to their saving practices. [ABSTRACT FROM AUTHOR]

Despite extensive research into the receipt of government food and housing assistance separately, only limited evidence informs the possibility that the receipt of assistance for one basic need could reduce the need for assistance meeting another basic need. To investigate this possibility among food insecure and low-income households we examined four years of data from each of the 2004 and 2008 panels of the Survey of Income and Program Participation. Among low-income and food insecure households we found no evidence that one type of assistance reduced later receipt of the second type of assistance. Rather, results from conditional logistic regression models indicated that receiving one type of assistance was associated with a higher probability of receiving the second type of assistance, or that there was no relationship between the two types of assistance. Factors informing these results are discussed in the context of household help-seeking and government assistance. [ABSTRACT FROM AUTHOR]

The increasing pervasiveness of high-cost alternative financial services ( AFS) has captured the attention of policymakers, consumer educators, and financial counselors. Using data from the 2009 to 2012 waves of the National Financial Capability Study ( NFCS), this article investigates AFS borrowing behaviors through the lens of a boundedly rational choice framework, with an emphasis on overconfidence. Through repeated testing of isolated samples of individuals with characteristics that make them less likely to objectively need such products, the roles of actual (objective) and perceived (subjective) financial knowledge in the decision-making process are explored. Consistent results indicate that individuals with lower objective financial knowledge and those that are overconfident in their self-assessed knowledge level are significantly more likely to utilize AFS instruments. These results suggest that a significant portion of AFS users may select these products without conducting adequate search, resulting in less than optimal financial decisions holding all else equal. [ABSTRACT FROM AUTHOR]

This article demonstrates that researchers who treat data collected via complex sampling procedures as if they were collected via simple random sample (SRS) may draw improper inferences when estimating regression models. Using complex sample data from the 2004 panel of the Survey of Income and Program Participation (SIPP) two models-one ordinary least squares ( OLS) regression and one logistic regression-were estimated using three methods: SRS with and without population weights, Taylor series linearization, and Fay's Balanced Repeated Replication (BRR). The results of the alternative models demonstrate that depending on the variables of interest, authors who fail to incorporate sample design information or fail to consider the effects of weighting may draw improper inferences from their regression models. Reasons why researchers continue to neglect complex sample-based variance are proposed and discussed, and example SAS and Stata code is offered to encourage adoption by the consumer research community. [ABSTRACT FROM AUTHOR]