Abstract

This study isolates the causal effects of financial literacy and schooling on wealth accumulation using a new household dataset and an instrumental variables (IV) approach. Financial literacy and schooling attainment are both strongly positively associated with wealth outcomes in linear regression models, whereas the IV estimates reveal even more potent effects of financial literacy. They also indicate that the schooling effect only becomes positive when interacted with financial literacy. Estimated impacts are substantial enough to imply that investments in financial literacy could have large wealth payoffs.
How Financial Literacy Affects Household Wealth Accumulation
Jere R. Behrman, Olivia S. Mitchell, Cindy K. Soo, and David Bravo*
Corresponding Author: Olivia S. Mitchell
2012 AER Papers and Proceedings
Session Title: The Effects of Financial Education and Financial Literacy
Session Chair: B. Douglas Bernheim
Discussants: Justine Hastings, William Walstad, Urvi Neelakantan, Annamaria Lusardi
January 6, 2012
* Behrman: Dept. of Economics and Sociology, School of Arts and Sciences, University of
Pennsylvania, 3718 Locust Walk, 160 McNeil, Philadelphia, PA 19104 (email:
jbehrman@econ.upenn.edu); Mitchell: Wharton School of the University of Pennsylvania, 3620
Locust Walk, 3000 SH-DH, Philadelphia, PA 19104 (email: mitchelo@wharton.upenn.edu);
Soo: Wharton School University of Pennsylvania, 3620 Locust Walk, 3000 SH-DH,
Philadelphia, PA 19104(email: csoo@wharton.upenn.edu); Bravo: Centro de Microdatos,
Universidad de Chile, Diag Paraguay #257, Torre 26, Santiago, Chile (email:
dbravo@econ.facea.uchile.cl). The authors acknowledge support from the TIAA-CREF Institute,
the Pension Research Council and Boettner Center at the Wharton School of the University of
Pennsylvania, and NIH/NIA grant AG023774-01(P.I. Petra Todd) on “Lifecycle health, work,
aging, insurance and pensions in Chile.” They also thank Luc Arrondel, Alex Gelber, Jeremy
Tobacman, Javiera Vasquez, and participants in the Wharton Applied Economics doctoral
workshop as well as the 2010 LBS TransAtlantic Doctoral Conference for helpful comments,
and Richard Derrig for sharing his PRIDIT code. Opinions and errors are solely those of the
authors and not of the institutions providing funding for this study or with which the authors are
affiliated. ©2012 Behrman, Mitchell, Soo, and Bravo. All rights reserved.
How Financial Literacy Affects Household Wealth Accumulation
Abstract
This study isolates the causal effects of financial literacy and schooling on wealth accumulation
using a new household dataset and an instrumental variables (IV) approach. Financial literacy
and schooling attainment are both strongly positively associated with wealth outcomes in linear
regression models, whereas the IV estimates reveal even more potent effects of financial literacy.
They also indicate that the schooling effect only becomes positive when interacted with financial
literacy. Estimated impacts are substantial enough to imply that investments in financial literacy
could have large wealth payoffs.
1
Traditional economic theory posits that forward-looking individuals maximize expected
lifetime utility using economic information to build retirement assets over their worklives. Yet
fewer than half of Americans have even attempted to estimate how much money they might need
in retirement, and many older adults face significant retirement saving shortfalls (Annamaria
Lusardi and Olivia S. Mitchell 2007a, b). Economic explanations for these shortfalls include
dispersion in discount rates, risk aversion, and credit constraints, but the empirical literature thus
far has been unable to account for much of observed wealth differentials (Douglas Bernheim,
Jonathan Skinner, and Steven Weinberg, 2001).
Here we evaluate whether people who find it difficult to understand their financial
environment are also less likely to accumulate wealth; our approach examines links between
wealth accumulation, and financial literacy, by which we mean the ability to process economic
information and make informed decisions about household finances. Others report positive
correlations between financial literacy and asset accumulation, but questions have been raised
about whether these associations reflect causality (Lusardi and Mitchell 2008, 2010). For
example, individuals who fail to save due to some underlying and usually unobservable factor
such as impatience may also be financially illiterate due to the same factor, making it difficult to
assess whether boosting financial education would, in fact, enhance household wealth
accumulation.
1
Moreover, in simple bivariate associations of financial literacy with wealth,
financial literacy might be proxying, in part, for other factors such as schooling attainment.
This paper makes three important contributions. First, we develop a new measure of
financial literacy that aggregates a more complete set of financial literacy questions, and that can
1
For example, Justine S. Hastings and Mitchell (2011) show that both impatience and financial
literacy are strongly correlated with retirement saving.
2
also be disaggregated to examine which aspects of financial literacy have greater marginal
influences on household wealth. Second, we draw on a unique microeconomic dataset, the
Chilean Social Protection Survey (see www.microdatos.cl), to evaluate the effects of financial
literacy for a richer range of ages and schooling than heretofore available.
Third, we use a set of
plausibly exogenous instrumental variables to control for both omitted variable and random
measurement error biases and show that financial literacy is still positively, significantly and
substantially associated with wealth outcomes even after controlling for schooling.
Our results are relevant for financial educational policy, in that we find that improved
financial literacy can make a significant difference for financial behavior, above and beyond
regular schooling. This rigorous analysis of the impact of financial literacy on wealth
accumulation should be useful in informing governments and their policy advisers, as they
consider new initiatives for financial education.
I. Financial Literacy Metrics
We measure financial literacy using a rich set of 12 questions. The “core” first three
financial literacy queries were developed and implemented in the United States Health and
Retirement Study (HRS); they have also been adopted by several other international surveys. A
second, more “sophisticated,” set of three questions was devised for a special HRS module
(Lusardi and Mitchell, 2007c) to measure more complex concepts such as compound interest,
inflation, and risk diversification. A final set of questions touches on key aspects of the Chilean
retirement system, including the mandatory contribution rate, minimum male and female
retirement ages, how pension benefits are computed, whether people know about the welfare
program for the elderly, and whether people know they can contribute to a Voluntary Pension
3
system (precise question wording and a full explanation of the approach is provided in Jere
Behrman et al., 2010).
As found in the United States, the Chilean EPS reveals that many respondents possess
little understanding of basic economic concepts and know little about the pension system. Only
half knew the correct answers to the core questions, and fewer could answer the sophisticated
financial literacy questions. Patterns are more variable for questions regarding knowledge of
pension system benefit rules and provisions: most knew the legal retirement ages, but only about
one-third knew contribution rates and only 10 percent could explain how benefits are computed.
About half the sample knew about both the guaranteed minimum benefit and the Voluntary
Savings plan.
While prior authors measure financial literacy by coding a binary outcome to one or two
key questions, we seek to use all the rich information available. Accordingly we aggregate
responses using a two-step weighting approach called PRIDIT.
2
The first step weights each
question by difficulty, applying a greater penalty for not answering correctly a question that
more of the population answers correctly but greater credit for answering correctly questions that
more respondents answer incorrectly. The second step applies principal components analysis to
take into account correlations across questions. The resulting PRIDIT scores indicate how
financially literate an individual is in relation to the average population and to specific questions
asked; it takes into account the fact that questions are more informative, ceteris paribus, the less
their answers are correlated with other questions. The final PRIDIT weights indicate how
“informative” any given question is regarding the underlying latent financial literacy variable,
2
The PRIDIT approach was developed by Patrick Brockett et al. (2002) to handle binary or
categorical indicators that proxy for a handle difficult-to-observe dependent variable.
4
relative to other questions. We find that the ‘core’ HRS financial literacy questions receive the
greatest weights, while the next most informative are the queries on pension system knowledge.
Some of the least informative include detailed knowledge on how to calculate pension benefits.
II. Data and Background
Our primary data source is the Social Protection Survey (Encuesta de Protecion Social,
EPS) we developed in collaboration with the Microdata Center of the University of Chile (David
Bravo et al. 2006). Comparable to the HRS, it provides a nationally-representative stratified
random survey covering wealth, schooling, financial literacy, work history, childhood
background, and selected personality traits. In contrast to the HRS, however, the EPS covers all
adults, not just respondents age 50+. In what follows, we limit our attention to 13,054 prime-age
respondents surveyed in 2006, namely men age 24-65 and women age 24-60.
3
Our outcomes of interest are total net wealth and its components: pension wealth, net
housing wealth, and other wealth. Pension wealth averages $38,600, or 54 percent of total net
wealth. In 1981, the Chilean government adopted a national, mandatory defined-contribution
scheme known as the AFP system; the reform required all new formal sector employees to
contribute at least 10 percent of their salaries to one of several licensed defined-contribution
pension plans.
4
We believe pension wealth is reported relatively accurately because respondents
receive annual government statements outlining their pension system accruals. Net housing
wealth is based on self-reported data on market values minus estimated mortgage debt. Other
3
In Chile the legal retirement age is 60 for women but 65 years for men.
4
Those who started working prior to 1980 could elect to join the new scheme or remain in the
previous system.
5
net wealth includes self-reported business wealth, agricultural assets, other real estate assets, and
financial investments, subtracting all forms of household debt.
In addition to these wealth measures, we also explore two possible channels via which
financial literacy and schooling might affect pension wealth, in particular. The first is an
indicator of worker attachment to the pension saving, or the “density of pension contributions
defined as the fraction of months an individual contributed to the pension system from age 18 to
the survey date. A second channel is whether the individual had attempted to calculate the money
needed for retirement.
Our primary explanatory variable in addition to financial literacy is schooling attainment
(measured conventionally). Primary school refers to grades 1-8, secondary school to grades 9-13,
and post-secondary school to grades beyond that, to a maximum of 20. The average schooling
attainment in our sample is 10.4 grades, with a standard deviation of 3.9 grades. We also control
for a rich set of demographic characteristics. Behrman et al. (2010) provide further detailed
summary statistics.
III. Empirical Findings
We first use an ordinary least squares (OLS) to investigate the relationship between
financial literacy and wealth accumulation. Consistent with previous reports, we find that
financial literacy is positively and significantly associated with total net wealth and each of its
components. Controlling for the effect of schooling reduces the magnitude of the effect of
financial literacy by almost half, suggesting that financial literacy does proxy in part for
schooling.
6
To address concerns of bias created by omitted variables or measurement error
5
in the
OLS coefficients, we also instrument for financial literacy and schooling using a set of candidate
variables that should predict financial literacy and schooling well but are likely not to affect
wealth directly or indirectly through other unobserved factors. For example, we posit that
respondents’ exposure to national schooling voucher policy changes or pension fund marketing
efforts likely affects their level of schooling and financial literacy, but do not have any direct
effects on wealth accumulation decisions. We consider three broad sets of candidate instruments:
Age-dependent variables, Family Background factors, and Respondent Personality traits.
6
Despite plausible arguments, we acknowledge that any of these variables could still affect wealth
directly
7
, and we use the Hansen’s J test of over-identifying restrictions to determine which
instruments appear truly independent of the second-stage disturbance term. We conclude that the
Hansen J statistic does have power in identifying problematic candidate instruments and use only
the variables that survive tests for both instrument strength and exogeneity.
The empirical analysis provides estimated impacts of financial literacy and schooling
using the above instrumental variable (IV) strategy. When only the PRIDIT financial literacy
index is included and instrumented, the coefficient estimates are positive, significant, substantial,
5
Estimates of noise-to-signal ratios for schooling attainment are often about 10 percent,
producing a bias towards zero of almost that magnitude (Behrman, Mark Rosenzweig, and Paul
Taubman 1994).
6
Detailed descriptions of each of these variables are provided in Behrman et al. (2010).
7
For example, family background variables such as maternal schooling could also proxy for
factors such as intergenerationally correlated ability endowments that directly affect wealth
(Behrman and Rosenzweig 2002).
7
and twice to three times larger than comparable OLS estimates. When only schooling is included
and instrumented, the coefficient estimates are positive, significant, substantial, and from 16-84
percent larger than the comparable OLS estimates. Including both instrumented schooling and
the PRIDIT financial literacy variables, the schooling effects mostly become statistically
insignificant and negative, whereas the financial literacy effects are positive, significant, and
substantial, and larger than comparable OLS estimates.
This pattern suggests that OLS estimates greatly understate the effect of financial literacy
on wealth accumulation. The IV estimates imply that a 0.2 standard deviation increase in the
PRIDIT financial literacy score would, on average, raise net wealth by $13,800, broken down
into about a $5,200 boost in pension wealth, a $1,600 rise in net housing wealth, and a gain of
$6,900 in other wealth. The same 0.2 standard deviation increase in the PRIDIT financial literacy
score would also boost the density of pension contributions by on average of three percent and
the probability of calculating retirement monetary needs by an average of 0.5 percent.
Next we add a financial literacy-schooling interaction term to the linear model; results
show that the interaction term is positive for all wealth components and substantially more
precisely estimated than the linear financial literacy and schooling terms. These findings suggest
a specification that includes only the interaction between financial literacy and schooling. In all
cases, the estimated effects for financial literacy-schooling interactions are positive and
substantial for wealth and actually somewhat bigger than in the linear model for pension and
housing wealth.
Finally, our PRIDIT measure of financial literacy allows us to assess the marginal
impacts of correct responses of the individual questions on each of the wealth outcomes. We
simulate the impact for the “core” and “sophisticated” HRS questions, and find that knowing the
8
correct answers to the HRS ”core” questions has a nearly 1.5 times greater impact than knowing
the correct answers to the sophisticated questions.
8
III. Discussion
Our findings imply, first, that using OLS to estimate the effects of financial literacy and
schooling will likely be misleading due to measurement error and unobserved factors. IV
estimates indicate that financial literacy is more important than schooling for explaining
variation in household wealth and pension contributions. Second, our improved estimates of
financial literacy impacts are substantial and potentially quite important; indeed they are large
enough to imply that investments in financial literacy could well have high payoffs. Third, we
show that some components of financial literacy, such as the HRS “core” questions, are
particularly important. This insight was not available from prior representations of financial
literacy. Fourth, we contribute to a growing body of research on the factors influencing peoples’
links with financial markets. Households that build up more net wealth, particularly via the
pension system, may be better able to smooth consumption in retirement and thus enhance risk-
sharing and wellbeing in old age. Our finding that financial literacy enhances peoples’ likelihood
of contributing to their pension saving suggests that this is a valuable pathway by which
improved financial literacy can build household net wealth.
9
In future work we hope to evaluate in more detail the costs as well as the benefits of
enhancing financial literacy levels. Meanwhile, we view as very important the central finding of
8
Detailed marginal effects for each question are available in Behrman et al. (2010).
9
Hastings, Mitchell, and Eric S. Chyn (2010) show that financial literacy can also affect
retirement saving through other channels such as the choice of investment fund or pension
manager.
9
this paper: that by investing in financial literacy, individuals, firms, and governments can
enhance household wealth and wellbeing. As Federal Reserve Board Chairman Ben Bernanke
(2010) stated in a recent speech to the National Bankers’ Association, “[H]elping people better
understand how to borrow and save wisely and how to build personal wealth is one of the best
things we can do to improve the well-being of families and communities.”
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Economists are beginning to investigate the causes and consequences of financial illiteracy to better understand why retirement planning is lacking and why so many households arrive close to retirement with little or no wealth. Our review reveals that many households are unfamiliar with even the most basic economic concepts needed to make saving and investment decisions. Such financial illiteracy is widespread: the young and older people in the United States and other countries appear woefully under-informed about basic financial concepts, with serious implications for saving, retirement planning, mortgages, and other decisions. In response, governments and several nonprofit organizations have undertaken initiatives to enhance financial literacy. The experience of other countries, including a saving campaign in Japan as well as the Swedish pension privatization program, offers insights into possible roles for financial literacy and saving programs.
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We examined financial literacy among the young using data from the 1997 National Longitudinal Survey of Youth. We showed that financial literacy is low among the young; fewer than one-third of young adults possess basic knowledge of interest rates, inflation, and risk diversification. Financial literacy is strongly related to sociodemographic characteristics and family financial sophistication. Specifically, a college-educated male whose parents had stocks and retirement savings is about 50 percentage points more likely to know about risk diversification than a female with less than a high school education whose parents were not wealthy. These findings have implications for consumer policy.
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Even among households with similar socioeconomic characteristics,sm,ling and wealth vary, considerably. Life-cycle models attribute this variation to differences ill time preference rates, risk tolerance, exposure to uncertainty, relative tastes for work and leisure at advanced ages, and income replacement rates. These factors have testable implications concerning the relation between accumulated wealth and the shape of the consumption profile. Using the Panel Study of Income Dynamics and the Consumer Expenditure Sun,ey, we find little support for these implications. The data are instead consistent with "rule of thumb," "mental accounting, " or hyperbolic discounting theories of wealth accumulation.
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A growing literature shows how consumers make mistakes in a variety of different settings pertinent to financial decision-making. Using data from a randomized experiment in Chile, we show how different ways of presenting pension management fees shape consumer choices, and how responses to pension fee information varies by level of financial literacy. Our results indicate that, in choosing pension funds, those with lower levels of education, income, and financial literacy rely more on employers, friends, and coworkers, than on fundamentals. We also find that such individuals are more responsive to information framing when interpreting the relative benefits of different investment choices.
Article
We examined financial literacy among the young using the most recent wave of the 1997 National Longitudinal Survey of Youth. We showed that financial literacy is low; fewer than one-third of young adults possess basic knowledge of interest rates, inflation and risk diversification. Financial literacy was strongly related to sociodemographic characteristics and family financial sophistication. Specifically, a college-educated male whose parents had stocks and retirement savings was about 45 percentage points more likely to know about risk diversification than a female with less than a high school education whose parents were not wealthy.
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This article introduces to the statistical and insurance literature a mathematical technique for an a priori classification of objects when no training sample exists for which the exact correct group membership is known. The article also provides an example of the empirical application of the methodology to fraud detection for bodily injury claims in automobile insurance. With this technique, principal component analysis of RIDIT scores (PRIDIT), an insurance fraud detector can reduce uncertainty and increase the chances of targeting the appropriate claims so that an organization will be more likely to allocate investigative resources efficiently to uncover insurance fraud. In addition, other (exogenous) empirical models can be validated relative to the PRIDIT-derived weights for optimal ranking of fraud/nonfraud claims and/or profiling. The technique at once gives measures of the individual fraud indicator variables’ worth and a measure of individual claim file suspicion level for the entire claim file that can be used to cogently direct further fraud investigation resources. Moreover, the technique does so at a lower cost than utilizing human insurance investigators, or insurance adjusters, but with similar outcomes. More generally, this technique is applicable to other commonly encountered managerial settings in which a large number of assignment decisions are made subjectively based on ‘‘clues,‘’ which may change dramatically over time. This article explores the application of these techniques to injury insurance claims for automobile bodily injury in detail.
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We compare wealth holdings across two cohorts of the Health and Retirement Study: the early Baby Boomers in 2004, and individuals in the same age group in 1992. Levels and patterns of total net worth have changed relatively little over time, though Boomers rely more on housing equity than their predecessors. Most important, planners in both cohorts arrive close to retirement with much higher wealth levels and display higher financial literacy than non-planners. Instrumental variables estimates show that planning behavior can explain the differences in savings and why some people arrive close to retirement with very little or no wealth.
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Two competing explanations for why consumers have trouble with financial decisions are gaining momentum. One is that people are financially illiterate since they lack understanding of simple economic concepts and cannot carry out computations such as computing compound interest, which could cause them to make suboptimal financial decisions. A second is that impatience or present-bias might explain suboptimal financial decisions. That is, some people persistently choose immediate gratification instead of taking advantage of larger long-term payoffs. We use experimental evidence from Chile to explore how these factors appear related to poor financial decisions. Our results show that our measure of impatience is a strong predictor of wealth and investment in health. Financial literacy is also correlated with wealth though it appears to be a weaker predictor of sensitivity to framing in investment decisions. Policymakers interested in enhancing retirement well-being would do well to consider the importance of these factors.
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Financial literacy and schooling attainment have been linked to household wealth accumulation. Yet prior findings may be biased due to noisy measures of financial literacy and schooling, as well as unobserved factors such as ability, intelligence, and motivation that could enhance financial literacy and schooling but also directly affect wealth accumulation. Here we use a new household dataset and an instrumental variables approach to isolate the causal effects of financial literacy and schooling on wealth accumulation. While financial literacy and schooling attainment are both strongly positively associated with wealth outcomes in linear regression models, our approach reveals even stronger and larger effects of financial literacy on wealth. It also indicates no significant positive effects of schooling attainment conditional on financial literacy in a linear specification, but positive effects when interacted with financial literacy. Estimated impacts are substantial enough to suggest that investments in financial literacy could have large positive payoffs.