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The Economic Importance of Financial Literacy: Theory and Evidence
Open accessAbstract
This paper undertakes an assessment of a rapidly growing body of economic research on financial literacy. We start with an overview of theoretical research, which casts financial knowledge as a form of investment in human capital. Endogenizing financial knowledge has important implications for welfare, as well as policies intended to enhance levels of financial knowledge in the larger population. Next, we draw on recent surveys to establish how much (or how little) people know and identify the least financially savvy population subgroups. This is followed by an examination of the impact of financial literacy on economic decision making in the United States and elsewhere. While the literature is still young, conclusions may be drawn about the effects and consequences of financial illiteracy and what works to remedy these gaps. A final section offers thoughts on what remains to be learned if researchers are to better inform theoretical and empirical models as well as public policy. (JEL A20, D14, G11, I20, J26)
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“supports Lusardi and Mitchell (2014) view that older borrowers possess greater financial maturity.”
From Drivers of willingness to repay Parish Revolving funds (PRF) under Uganda’s Parish Development Model: a Bayesian Latent Class Logistic Regression (LCLR) approach (2026) · cites this paper as Lusardi and Mitchell (2014)
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“Financial literacy programmes reduce information asymmetry by equipping borrowers with knowledge needed to make informed repayment decisions (Hastings et al., 2013;Lusardi & Mitchell, 2014).”
From Drivers of willingness to repay Parish Revolving funds (PRF) under Uganda’s Parish Development Model: a Bayesian Latent Class Logistic Regression (LCLR) approach (2026) · cites this paper as Lusardi & Mitchell, 2014
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“Empirically, financially savvy people are more likely to accumulate wealth (Lusardi and Mitchell, 2014).”
From Financial literacy and the need for financial education: evidence and implications (2019) · cites this paper as Lusardi and Mitchell, 2014
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“even though educational attainment is positively correlated with financial literacy, it is not sufficient.”
From Financial literacy and the need for financial education: evidence and implications (2019) · cites this paper as Lusardi and Mitchell (2014)
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“supports Lusardi and Mitchell (2014) view that higher education and financial capability improve financial discipline.”
From Drivers of willingness to repay Parish Revolving funds (PRF) under Uganda’s Parish Development Model: a Bayesian Latent Class Logistic Regression (LCLR) approach (2026) · cites this paper as Lusardi and Mitchell (2014)
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Metadata
- Authors
- Lusardi, A., & Mitchell, O. S.
- Affiliations
- George Washington University (US)
- University of Pennsylvania (US)
- Venue
- Journal of Economic Literature
- Publisher
- American Economic Association
- Published
- 2014-03-01
- Volume
- 52
- Issue
- 1
- Pages
- 5-44
- ISSN
- 0022-0515 (ISSN-L)
- 2328-8175
- PMC
- PMC5450829
- OpenAlex
- W3125685058
- Cited by
- 4,698
- References
- 205
- Citations by year
- 2026: 862 · 2025: 761 · 2024: 572 · 2023: 434 · 2022: 363 · 2021: 380 · 2020: 339 · 2019: 284 · 2018: 216 · 2017: 170 · 2016: 134 · 2015: 111 · 2014: 51
- FWCI
- 656.21
- Type
- journal article
- Language
- en
- Open access
- green
- europepmc.org
- Locations
- Journal of Economic Literature (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- National Institute on Aging (U01AG009740)
- Topics
- Social Sciences › Economics, Econometrics and Finance › Finance › Financial Literacy, Pension, Retirement Analysis
- Social Sciences › Business, Management and Accounting › Accounting › Financial Literacy and Behavior
- Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
- Keywords
- financial literacy, financial knowledge, human capital, financial illiteracy, economic decision-making, financial education policy
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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