2. Data

Our data come from two waves of the FINRA Foundation's NFCS fielded as part of the RAND ALP, which is a probability based, nationally representative online panel of U.S. adults age 18 and above. The first wave was fielded in 2012 to a sample of about 2,000 adults. In July 2018, we invited the 1,455 active ALP members who had answered the 2012 NFCS questionnaire to retake the survey. Of these respondents, 1,232 started the survey and 1,170 completed it. In the analyses that follow, we include respondents who participated in both waves, even if they did not finish the survey, as long as they have a financial literacy score.Footnote ⁵ The final sample includes 1,197 individuals and 2,394 individual-time observations.Footnote ⁶ The summary statistics for the main demographic variables in the panel at baseline (in 2012) are shown in Table 1. An analysis of sample attrition, provided in the Appendix, shows that the probability of participating in the second wave of the NFCS ALP is relatively higher for Whites, middle-aged and older individuals, those with at least a Bachelor's degree, and with annual household incomes greater than $60,000 in 2012 (these demographic characteristics will be controlled for in our regression analysis).

Table 1. Sample characteristics in 2012

Source: 2012 American Life Panel.

This table reports sample averages (in 2012) of the variables used in the empirical work.

Individuals who participated in both waves are also older, more educated, and with higher incomes than the population at large.Footnote ⁷ In our 2012 sample, average age is about 50, versus 47 in the population; the proportion of female respondents is 58%, versus 51% in the population; and the proportion of White respondents is 73%, versus 67% in the population. Nearly half the sample has a college degree; in the general population, this fraction is 30%. Our sample is more closely representative of the population in terms of household income, with 54% of our sample from households earning less than $60,000, versus 57% in the population at large. These documented differences are consistent with the changes in the composition of the ALP population over time, with younger, less educated, and less affluent respondents having shown higher attrition and non-response rates. Over the six-year time span covered by our two waves of data, there are no significant changes in the demographics shown in Table 1 (most of which are constant by definition), except for a mechanical increase in age and a slight increase in household income.

3. The evolution of financial literacy over time

In both waves, respondents were administered a set of five financial literacy questions covering fundamental economics and finance concepts. These questions have become known as the Big Five (Hastings et al., Reference Hastings, Madrian and Skimmyhorn2013) and are one of several commonly used financial literacy measures. The Big Five consist of three multiple choice questions assessing aptitude with simple interest calculations (related to savings accounts and inflation) and understanding of the relationship between interest rates and bond prices and two true/false questions testing individuals' knowledge of the relationship between the length of a mortgage and the overall interest paid over the life of the loan and the concept of risk diversification. The exact wording of the questions is reported in Appendix B. We construct a financial literacy index by summing the correct responses to the financial literacy questions.

Over our six-year analysis timeframe, we find that financial literacy declines slightly in aggregate, though remains quite stable overall. Differences between the proportion of correct responses across survey waves are muted, with the largest difference being a five percentage point decline in the fraction correctly answering the risk diversification question (p-value = 0.01, other differences between correct responses are not statistically significant). Reduced correct responses are largely driven by an increase in ‘don't know’ responses. For all but the interest rate questions, there were fewer incorrect responses in 2018 than 2012 (Table 2).Footnote ⁸

Table 2. Fraction of correct and don't know responses across waves

Source: 2012 and 2018 American Life Panel.

This table reports the fraction of correct and don't know responses to the five financial literacy questions in 2012 and 2018.

Figure 1 highlights the distribution of financial literacy scores (number of correct answers) across the two waves. The average financial literacy level in 2012 is 3.53, and it drops slightly to 3.43 in 2018. Using a paired sample t-test, we reject the null that the average difference across waves is zero at any conventional significance level (p-value = 0.001). There is little difference in the proportion of respondents answering all questions correctly across the two years, though a general leftward shift of the distribution between 2012 and 2018 for scores below five is observed. Nearly half of the respondents (48%) have the same score in 2018 as in 2012, and 87% have a score in 2018 that is within one point of their score in 2012.

Figure 1. Distribution of Financial Literacy across Years.

Source: 2012 and 2018 American Life Panel.

The slight decline in average financial literacy between the two survey waves is driven primarily by reduced financial literacy among older adults. Table 3 documents the mean difference in financial literacy score between waves by age/cohort (we adopt a paired-sample t-test to assess the statistical significance of the observed difference within each cohort). The youngest cohort is 18–24 in 2012, the oldest is 65 or older in 2012. As can be seen, financial literacy decreased over the six-year observation period for all cohorts, except for the youngest, for whom it increased by 0.25 points between 2012 and 2018. The sizeable, positive change is however not statistically different from zero due to the limited number of individuals in this 18–24 age group (40 individuals) and should be interpreted with caution. The largest and only statistically significant declines in financial literacy occurs among adults above the age of 60. This is consistent with cross-sectional evidence suggesting that financial literacy declines late in life, and that the decline may be driven in part by cognitive aging (Finke et al., Reference Finke, Howe and Huston2017).

Table 3. Change in financial literacy by age cohort in 2012

Source: American Life Panel.

This table reports the average financial literacy score for the age cohort indicated in the first column in 2012 (second column) and six years later in 2018 (third column). For each age cohort, the change in the financial literacy score between 2018 and 2012 is reported in the fourth column.

**p < 0.01, *p < 0.05.

We have information on cognition from the ALP, but only at one point in time, elicited between September 2012 and May 2013 for all participants. This information is in the form of test scores on a series of computer-adaptive cognitive tests, which we aggregate in a comprehensive cognition index by summing scores across all tests (we standardize this index to have mean 0 and standard deviation 1 in the sample).Footnote ⁹ We then assign respondents to four groups corresponding to the quartiles of the index distribution in the sample. As can be seen in Table 4, we find a relationship between cognition and future decline in financial literacy. Individuals in the bottom three cognitive ability quartiles all experience slight declines in financial literacy, with the largest decline experienced by those with the lowest cognition. Those in the highest cognitive ability quartile have financial literacy scores that remain relatively unchanged across the survey waves.Footnote ¹⁰

Table 4. Financial literacy by cognition

Source: American Life Panel.

This table reports the average financial literacy score by cognitive ability quartiles. For each quartile, the second column shows the average financial literacy score in 2012, while the third column shows the average financial literacy score six years later, in 2018. The fourth column presents the change in the financial literacy score between 2018 and 2012.

**p < 0.01, *p < 0.05.

4. Financial literacy and future financial outcomes

In addition to measuring changes over time, a key feature of our longitudinal data is that they allow us to examine the predictive power of financial literacy several years into the future. The question we explore is: Controlling for observable characteristics, individual-specific traits, and current financial outcomes, does financial literacy predict future financial outcomes? The survey elicits a range of variables that can proxy for financial well-being, from subjective satisfaction with current financial situation to the capacity to face a shock, as well as variables that capture aspects of financial capability, such as retirement planning and credit/debt management. We divide these variables into positive and negative financial outcomes. The positive set includes satisfaction with overall financial situation, measured on a 10-point scale; lack or low level of financial fragility, measured by one's confidence in their ability to come up with $2,000 if an unexpected need arose within a month; and an indicator that respondents have (ever) tried to figure out how much they need to save for their retirement, which is known to be a strong predictor of wealth accumulation (Lusardi and Mitchell, Reference Lusardi and Mitchell2007). Among the negative or detrimental outcomes, we consider the extent to which respondents agree – using a 7-point scale with 1 indicating strong disagreement and 7 strong agreement – with the statement ‘I have too much debt right now,’ whether they have used alternative financial services (payday loans, pawn shops, tax-refund loans, car title loans, and rent-to-own shops) in the past five years, and whether they use credit cards in an expensive way (paying the minimum only, making a late payment, going over the limit, or using the card for a cash advance). All of these latter measures capture, to a varying degree, financial distress and difficulties with personal finances (for detail see Lusardi and Tufano, Reference Lusardi and Tufano2015).

We perform OLS regressions using each of these outcomes in 2018 as dependent variables and financial literacy as observed in 2012 as the main explanatory variable of interest. Other regressors include demographic characteristics measured in 2012 (gender, race, age, marital status, education, income, and labor force status); a composite index score for cognitive ability preferences and individual traits, namely aversion to risk and attitude toward planning; and the dependent variable itself measured at baseline (in 2012).Footnote ¹¹ We use two specifications, a parsimonious one, which only includes demographics and the lagged dependent variable, and one that accounts for individual attitudes and preferences. The estimated relationship between financial literacy and future financial outcomes is reported in Tables 5 and 6. To ensure that the sample size remains the same across specifications, we exclude from the analysis respondents with missing values of either the dependent variable or any of the explanatory variables used in the regressions. Due to skip patterns within the questionnaire, information about retirement planning and credit card use is available for only about 80% of the original sample. Hence, the regressions featuring these two outcomes as dependent variable show a reduced sample size.

Table 5. Financial literacy and future outcomes (I)

Note: This table reports the estimates of the regressions of positive financial outcome (in 2018) on financial literacy and a set of demographics. Demographics include gender, race, age, education, marital status, labor force status, and income. All explanatory variables are measured in 2012, except risk aversion and planning attitude, which are treated as constant individual traits. The set of explanatory variables also includes the dependent variable as measured in 2012. The full set of estimated coefficients is reported in Table A3 in Appendix C. Robust standard errors in parentheses **p < 0.01, *p < 0.05.

Table 6. Financial literacy and future outcomes (II)

Note: This table reports the estimates of the regressions of negative financial outcome (in 2018) on financial literacy and a set of demographics. Demographics include gender, race, age, education, marital status, labor force status, and income. All explanatory variables are measured in 2012, except risk aversion and planning attitude, which are treated as constant individual traits. The set of explanatory variables also includes the dependent variable as measured in 2012 The full set of estimated coefficients is reported in Table A4 in Appendix C. Robust standard errors in parentheses **p < 0.01, *p < 0.05.

Overall, we find that financial literacy has significant predictive power for future financial outcomes, even after controlling for current outcomes, a wide set of demographics, and individual-specific traits. Specifically, those who have higher financial literacy are more likely to be satisfied with their financial situation, more likely to be able to face a mid-size shock, and more likely to plan for retirement in the future. Estimates are sizeable. For example, a one-unit increase in the 2012 financial literacy index is associated with a 0.13-point increase in financial satisfaction in 2018. This corresponds to an almost 2.5% increase relative to mean financial satisfaction in the sample (about 6 on a 10-point scale). Thus, the effect is not only statistically significant but also economically meaningful. Similarly, individuals with higher financial literacy are about 5 percentage points more likely to be able to meet an unexpected $2,000 shock, representing a sizeable 8% increase relative to a sample proportion of 61%, consistent with the findings of Hasler et al. (Reference Hasler, Lusardi and Oggero2018). Finally, answering one more financial literacy question correctly in 2012 is associated with about a 3.5 percentage-point increase in the likelihood of having done any retirement planning in 2018, a 6% positive change from a sample proportion of 57%.

On the other hand, we find little effect of financial literacy on negative financial behavior, mostly related to debt and debt management. This suggests that poor financial decision making may be driven by factors like shocks and resource scarcity and not as much by lack of financial knowledge. In view of previous research, there exists evidence that, irrespective of financial literacy, the majority of people recognize that carrying a lot of debt, not making credit card payments on time, or using alternative financial services (which tend to charge high interest rates and fees) have negative consequences. Failure to avoid these behaviors is more plausibly driven by behavioral factors (e.g., present bias), resource constraints, and financial shocks than by lack of financial knowledge.Footnote ¹² We also estimate regressions where indicators for answering each financial literacy question correctly replace the composite financial literacy score. The results of these regressions are reported in Table A5 in the Appendix.Footnote ¹³

In the interest of space and since our focus is on financial literacy, we will comment on just a few other estimated coefficients (the complete set of estimated coefficients is provided in Appendix C): Financial outcomes do not vary significantly by gender, with the exception of the use of alternative financial services, which is less likely among women, but outcomes are very different by race, with White respondents faring much better than minorities. As might be expected, financial outcomes are generally better for those with higher income and higher education. Cognitive ability is not correlated with positive financial outcomes that have a significant association with financial literacy. In contrast, cognitive ability correlates with some negative outcomes, for which no association with financial literacy is detected. We estimate that a higher cognition score in 2012 is positively associated with the perception of having too much debt in 2018. While possibly surprising, this result may reflect the fact that individuals with better cognitive functions are also better able to assess when their debt level is excessive. More in line with expectations, cognitive ability correlates negatively with the use of AFS. Interestingly, financial outcomes are better for those who are older or retired, while risk aversion and planning attitude are not statistically significant in our regressions.

While our empirical approach addresses potential reverse causality from financial literacy to financial outcomes and vice versa, we are unable to rule out all possible sources of bias stemming from the omission of variables that correlate with financial knowledge and financial outcomes. However, since we take into account some of the traits most relevant for individual financial decision making (e.g., attitude toward financial risk and planning and cognitive ability) in our regressions, we interpret our results as evidence of a causal link between financial literacy and financial outcomes.Footnote ¹⁴ As noted above, considerable prior research has documented that higher levels of financial literacy are associated with higher levels of contemporaneously measured financial outcomes.Footnote ¹⁵ Our finding that financial literacy is relatively constant over our six-year observation period indicates that differences in the stock of financial knowledge lead to increasing disparities through the life cycle. Individuals with higher levels of current financial knowledge tend to have higher current and future levels of financial well-being relative to those with lower current levels of financial knowledge. Thus, financial literacy may be a key driver of widening inequality.

5. Heterogeneity in the relationship between financial literacy and future financial outcomes

Next, we investigate the extent to which the observed relationship between financial literacy and future financial outcomes varies across distinct segments of the population. To do this, we use our richer specification, including as explanatory variables demographics, cognitive ability, individual-specific traits (risk aversion and planning attitude), the dependent variable and financial literacy as of 2012, and estimate it separately by gender, age (individuals younger than 55 and individuals age 55 or older in 2012), and income group (households with yearly income below $60,000 and $60,000 or above in 2012). In Table 7, we report the estimated financial literacy coefficients for men and women and for the two aforementioned age and income groups, separately.

Table 7. Financial literacy and future outcomes by gender and age

Note: This table reports the estimates of the regressions of financial outcome (in 2018) on financial literacy and a set of demographics and the dependent variable in 2012 by age and gender. Separate regressions for men and women and for individuals below age 55 and age 55 or older are estimated. The set of controls is the same as in columns (2) of Tables 5 and 6. Robust standard errors in parentheses **p < 0.01, *p < 0.05.

The observed positive effect of financial literacy on an individual's future satisfaction with their financial situation detected in the entire sample appears to be mainly driven by men and individuals age 55 and older. For these two groups, one more financial literacy question answered correctly is associated with a 0.22-point increase in the future level of satisfaction with financial situation. While still positive, the corresponding coefficient is much smaller and not statistically different from zero for women and individuals younger than 55. Due to relatively small sample sizes, we cannot, however, reject the null that the effect of financial literacy on future financial satisfaction is the same between groups. The relationship between financial literacy and future financial satisfaction is similar for households with income below and above $60,000 per year, but is statistically significant only for households with income below $60,000. The link between financial literacy and future ability to meet an unexpected $2,000 expense is rather homogenous between men and women and between age groups. On the other hand, it is substantially larger for those with income below $60,000, for whom a higher financial literacy score increases the probability of being able to meet a $2,000 expense by about 6 percentage points (a sizeable 14% increase from the sample proportion of 42%), than it is for richer individuals (income greater than $60k) for whom the estimated effect is smaller (about 3 percentage points) and not statistically significant.

Women, individuals age 55 and older, and high-income households seem to benefit the most from better financial knowledge when it comes to retirement planning. For women, a one-unit increase in the financial literacy score in 2012 results in a 4.5 percentage point increase in the likelihood of planning for retirement (an effect significant at 5%) compared to only a 2 percentage point increase for men (a non-statistically significant effect). These estimates correspond to a 9% and 3% increase from the corresponding sample proportions of 51% and 63%. Similarly, the estimated 2012 financial literacy coefficients indicate an increase of nearly 5.5 percentage points in the probability of retirement planning among individuals age 55 or older (a 9% increase from the sample proportion) and of barely 2 percentage points (3.5% increase from the sample proportion) among those younger than 55. For individuals with income at or above $60,000, a higher financial literacy score in 2012 is associated with a 5.6 percentage-point increase in the likelihood of having done some retirement planning by 2018 (an 8% increase from the sample proportion of 69%); for those with income below $60,000, the estimated increase is only 1.7 percentage points and is not statistically significant. Despite such large differences, we fail to reject the null that these effects are the same between groups due to relatively large standard errors.

Concerning negative outcomes, we find evidence of some heterogeneous effects. Consistent with most of the patterns already described, women, older, and less affluent individuals appear to benefit the most from increasing levels of financial knowledge. For women, answering one more financial literacy question correctly in 2012 results in a decrease of 0.13 points on the 1–7 scale measuring having too much debt in 2018. This corresponds to a 4% decrease from a sample mean of 3.6. Conversely, there is little effect for men. Similarly, among individuals age 55 or older, a one-point increase in the financial literacy score in 2012 is associated with a decrease of 0.19 points on the having too much debt scale in 2018, representing a negative 7% change from the sample mean of 2.6. For individuals younger than 55, financial literacy is not linked to future debt management. Among those with income below $60,000, a one-unit increase in the financial literacy score in 2012 results in a decrease of 0.17 points on the having too much debt scale in 2018, which constitutes a negative 4.5% change from the sample mean of 3.8. Once again, because of relatively large standard errors, the effects by gender and age are not statistically different. We do reject the null that the effects of financial literacy on having too much debt are the same between income groups at the 5% significance level. Finally, we do not find an effect of financial literacy on either use of alternative financial services or expensive credit card behavior across demographic groups, apart from when looking at distinct age groups. Overall, the estimated coefficients are similar to those in the whole sample.

In summary, although differences among groups are generally not statistically significant, the results presented in this section point to three main patterns. One, higher financial literacy tends to benefit women more than men, which is consistent with the findings of previous work by Lusardi and Mitchell (Reference Lusardi and Mitchell2008). Two, a higher level of financial knowledge appears to be more advantageous for individuals approaching retirement age than for their younger counterparts, confirming the key role that financial knowledge plays in planning for the future and accumulating wealth over the life cycle. Three, financial knowledge seems more beneficial for low-income individuals, especially in the domains of satisfaction with finances, emergency savings, and debt management. Our empirical evidence highlights the importance of taking heterogeneity into account when assessing the effects of financial literacy, and of considering distinct financial behaviors and outcomes, which may be differentially affected by the level of financial knowledge.Footnote ¹⁶