financial literacy research papers

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Published: 24 January 2019

Financial literacy and the need for financial education: evidence and implications

Annamaria Lusardi 1

Swiss Journal of Economics and Statistics volume 155 , Article number: 1 ( 2019 ) Cite this article

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1 Introduction

Throughout their lifetime, individuals today are more responsible for their personal finances than ever before. With life expectancies rising, pension and social welfare systems are being strained. In many countries, employer-sponsored defined benefit (DB) pension plans are swiftly giving way to private defined contribution (DC) plans, shifting the responsibility for retirement saving and investing from employers to employees. Individuals have also experienced changes in labor markets. Skills are becoming more critical, leading to divergence in wages between those with a college education, or higher, and those with lower levels of education. Simultaneously, financial markets are rapidly changing, with developments in technology and new and more complex financial products. From student loans to mortgages, credit cards, mutual funds, and annuities, the range of financial products people have to choose from is very different from what it was in the past, and decisions relating to these financial products have implications for individual well-being. Moreover, the exponential growth in financial technology (fintech) is revolutionizing the way people make payments, decide about their financial investments, and seek financial advice. In this context, it is important to understand how financially knowledgeable people are and to what extent their knowledge of finance affects their financial decision-making.

An essential indicator of people’s ability to make financial decisions is their level of financial literacy. The Organisation for Economic Co-operation and Development (OECD) aptly defines financial literacy as not only the knowledge and understanding of financial concepts and risks but also the skills, motivation, and confidence to apply such knowledge and understanding in order to make effective decisions across a range of financial contexts, to improve the financial well-being of individuals and society, and to enable participation in economic life. Thus, financial literacy refers to both knowledge and financial behavior, and this paper will analyze research on both topics.

As I describe in more detail below, findings around the world are sobering. Financial literacy is low even in advanced economies with well-developed financial markets. On average, about one third of the global population has familiarity with the basic concepts that underlie everyday financial decisions (Lusardi and Mitchell, 2011c ). The average hides gaping vulnerabilities of certain population subgroups and even lower knowledge of specific financial topics. Furthermore, there is evidence of a lack of confidence, particularly among women, and this has implications for how people approach and make financial decisions. In the following sections, I describe how we measure financial literacy, the levels of literacy we find around the world, the implications of those findings for financial decision-making, and how we can improve financial literacy.

2 How financially literate are people?

2.1 measuring financial literacy: the big three.

In the context of rapid changes and constant developments in the financial sector and the broader economy, it is important to understand whether people are equipped to effectively navigate the maze of financial decisions that they face every day. To provide the tools for better financial decision-making, one must assess not only what people know but also what they need to know, and then evaluate the gap between those things. There are a few fundamental concepts at the basis of most financial decision-making. These concepts are universal, applying to every context and economic environment. Three such concepts are (1) numeracy as it relates to the capacity to do interest rate calculations and understand interest compounding; (2) understanding of inflation; and (3) understanding of risk diversification. Translating these concepts into easily measured financial literacy metrics is difficult, but Lusardi and Mitchell ( 2008 , 2011b , 2011c ) have designed a standard set of questions around these concepts and implemented them in numerous surveys in the USA and around the world.

Four principles informed the design of these questions, as described in detail by Lusardi and Mitchell ( 2014 ). The first is simplicity : the questions should measure knowledge of the building blocks fundamental to decision-making in an intertemporal setting. The second is relevance : the questions should relate to concepts pertinent to peoples’ day-to-day financial decisions over the life cycle; moreover, they must capture general rather than context-specific ideas. Third is brevity : the number of questions must be few enough to secure widespread adoption; and fourth is capacity to differentiate , meaning that questions should differentiate financial knowledge in such a way as to permit comparisons across people. Each of these principles is important in the context of face-to-face, telephone, and online surveys.

Three basic questions (since dubbed the “Big Three”) to measure financial literacy have been fielded in many surveys in the USA, including the National Financial Capability Study (NFCS) and, more recently, the Survey of Consumer Finances (SCF), and in many national surveys around the world. They have also become the standard way to measure financial literacy in surveys used by the private sector. For example, the Aegon Center for Longevity and Retirement included the Big Three questions in the 2018 Aegon Retirement Readiness Survey, covering around 16,000 people in 15 countries. Both ING and Allianz, but also investment funds, and pension funds have used the Big Three to measure financial literacy. The exact wording of the questions is provided in Table 1 .

2.2 Cross-country comparison

The first examination of financial literacy using the Big Three was possible due to a special module on financial literacy and retirement planning that Lusardi and Mitchell designed for the 2004 Health and Retirement Study (HRS), which is a survey of Americans over age 50. Astonishingly, the data showed that only half of older Americans—who presumably had made many financial decisions in their lives—could answer the two basic questions measuring understanding of interest rates and inflation (Lusardi and Mitchell, 2011b ). And just one third demonstrated understanding of these two concepts and answered the third question, measuring understanding of risk diversification, correctly. It is sobering that recent US surveys, such as the 2015 NFCS, the 2016 SCF, and the 2017 Survey of Household Economics and Financial Decisionmaking (SHED), show that financial knowledge has remained stubbornly low over time.

Over time, the Big Three have been added to other national surveys across countries and Lusardi and Mitchell have coordinated a project called Financial Literacy around the World (FLat World), which is an international comparison of financial literacy (Lusardi and Mitchell, 2011c ).

Findings from the FLat World project, which so far includes data from 15 countries, including Switzerland, highlight the urgent need to improve financial literacy (see Table 2 ). Across countries, financial literacy is at a crisis level, with the average rate of financial literacy, as measured by those answering correctly all three questions, at around 30%. Moreover, only around 50% of respondents in most countries are able to correctly answer the two financial literacy questions on interest rates and inflation correctly. A noteworthy point is that most countries included in the FLat World project have well-developed financial markets, which further highlights the cause for alarm over the demonstrated lack of the financial literacy. The fact that levels of financial literacy are so similar across countries with varying levels of economic development—indicating that in terms of financial knowledge, the world is indeed flat —shows that income levels or ubiquity of complex financial products do not by themselves equate to a more financially literate population.

Other noteworthy findings emerge in Table 2 . For instance, as expected, understanding of the effects of inflation (i.e., of real versus nominal values) among survey respondents is low in countries that have experienced deflation rather than inflation: in Japan, understanding of inflation is at 59%; in other countries, such as Germany, it is at 78% and, in the Netherlands, it is at 77%. Across countries, individuals have the lowest level of knowledge around the concept of risk, and the percentage of correct answers is particularly low when looking at knowledge of risk diversification. Here, we note the prevalence of “do not know” answers. While “do not know” responses hover around 15% on the topic of interest rates and 18% for inflation, about 30% of respondents—in some countries even more—are likely to respond “do not know” to the risk diversification question. In Switzerland, 74% answered the risk diversification question correctly and 13% reported not knowing the answer (compared to 3% and 4% responding “do not know” for the interest rates and inflation questions, respectively).

These findings are supported by many other surveys. For example, the 2014 Standard & Poor’s Global Financial Literacy Survey shows that, around the world, people know the least about risk and risk diversification (Klapper, Lusardi, and Van Oudheusden, 2015 ). Similarly, results from the 2016 Allianz survey, which collected evidence from ten European countries on money, financial literacy, and risk in the digital age, show very low-risk literacy in all countries covered by the survey. In Austria, Germany, and Switzerland, which are the three top-performing nations in term of financial knowledge, less than 20% of respondents can answer three questions related to knowledge of risk and risk diversification (Allianz, 2017 ).

Other surveys show that the findings about financial literacy correlate in an expected way with other data. For example, performance on the mathematics and science sections of the OECD Program for International Student Assessment (PISA) correlates with performance on the Big Three and, specifically, on the question relating to interest rates. Similarly, respondents in Sweden, which has experienced pension privatization, performed better on the risk diversification question (at 68%), than did respondents in Russia and East Germany, where people have had less exposure to the stock market. For researchers studying financial knowledge and its effects, these findings hint to the fact that financial literacy could be the result of choice and not an exogenous variable.

To summarize, financial literacy is low across the world and higher national income levels do not equate to a more financially literate population. The design of the Big Three questions enables a global comparison and allows for a deeper understanding of financial literacy. This enhances the measure’s utility because it helps to identify general and specific vulnerabilities across countries and within population subgroups, as will be explained in the next section.

2.3 Who knows the least?

Low financial literacy on average is exacerbated by patterns of vulnerability among specific population subgroups. For instance, as reported in Lusardi and Mitchell ( 2014 ), even though educational attainment is positively correlated with financial literacy, it is not sufficient. Even well-educated people are not necessarily savvy about money. Financial literacy is also low among the young. In the USA, less than 30% of respondents can correctly answer the Big Three by age 40, even though many consequential financial decisions are made well before that age (see Fig. 1 ). Similarly, in Switzerland, only 45% of those aged 35 or younger are able to correctly answer the Big Three questions. Footnote 1 And if people may learn from making financial decisions, that learning seems limited. As shown in Fig. 1 , many older individuals, who have already made decisions, cannot answer three basic financial literacy questions.

Financial literacy across age in the USA. This figure shows the percentage of respondents who answered correctly all Big Three questions by age group (year 2015). Source: 2015 US National Financial Capability Study

A gender gap in financial literacy is also present across countries. Women are less likely than men to answer questions correctly. The gap is present not only on the overall scale but also within each topic, across countries of different income levels, and at different ages. Women are also disproportionately more likely to indicate that they do not know the answer to specific questions (Fig. 2 ), highlighting overconfidence among men and awareness of lack of knowledge among women. Even in Finland, which is a relatively equal society in terms of gender, 44% of men compared to 27% of women answer all three questions correctly and 18% of women give at least one “do not know” response versus less than 10% of men (Kalmi and Ruuskanen, 2017 ). These figures further reflect the universality of the Big Three questions. As reported in Fig. 2 , “do not know” responses among women are prevalent not only in European countries, for example, Switzerland, but also in North America (represented in the figure by the USA, though similar findings are reported in Canada) and in Asia (represented in the figure by Japan). Those interested in learning more about the differences in financial literacy across demographics and other characteristics can consult Lusardi and Mitchell ( 2011c , 2014 ).

Gender differences in the responses to the Big Three questions. Sources: USA—Lusardi and Mitchell, 2011c ; Japan—Sekita, 2011 ; Switzerland—Brown and Graf, 2013

3 Does financial literacy matter?

A growing number of financial instruments have gained importance, including alternative financial services such as payday loans, pawnshops, and rent to own stores that charge very high interest rates. Simultaneously, in the changing economic landscape, people are increasingly responsible for personal financial planning and for investing and spending their resources throughout their lifetime. We have witnessed changes not only in the asset side of household balance sheets but also in the liability side. For example, in the USA, many people arrive close to retirement carrying a lot more debt than previous generations did (Lusardi, Mitchell, and Oggero, 2018 ). Overall, individuals are making substantially more financial decisions over their lifetime, living longer, and gaining access to a range of new financial products. These trends, combined with low financial literacy levels around the world and, particularly, among vulnerable population groups, indicate that elevating financial literacy must become a priority for policy makers.

There is ample evidence of the impact of financial literacy on people’s decisions and financial behavior. For example, financial literacy has been proven to affect both saving and investment behavior and debt management and borrowing practices. Empirically, financially savvy people are more likely to accumulate wealth (Lusardi and Mitchell, 2014 ). There are several explanations for why higher financial literacy translates into greater wealth. Several studies have documented that those who have higher financial literacy are more likely to plan for retirement, probably because they are more likely to appreciate the power of interest compounding and are better able to do calculations. According to the findings of the FLat World project, answering one additional financial question correctly is associated with a 3–4 percentage point greater probability of planning for retirement; this finding is seen in Germany, the USA, Japan, and Sweden. Financial literacy is found to have the strongest impact in the Netherlands, where knowing the right answer to one additional financial literacy question is associated with a 10 percentage point higher probability of planning (Mitchell and Lusardi, 2015 ). Empirically, planning is a very strong predictor of wealth; those who plan arrive close to retirement with two to three times the amount of wealth as those who do not plan (Lusardi and Mitchell, 2011b ).

Financial literacy is also associated with higher returns on investments and investment in more complex assets, such as stocks, which normally offer higher rates of return. This finding has important consequences for wealth; according to the simulation by Lusardi, Michaud, and Mitchell ( 2017 ), in the context of a life-cycle model of saving with many sources of uncertainty, from 30 to 40% of US retirement wealth inequality can be accounted for by differences in financial knowledge. These results show that financial literacy is not a sideshow, but it plays a critical role in saving and wealth accumulation.

Financial literacy is also strongly correlated with a greater ability to cope with emergency expenses and weather income shocks. Those who are financially literate are more likely to report that they can come up with $2000 in 30 days or that they are able to cover an emergency expense of $400 with cash or savings (Hasler, Lusardi, and Oggero, 2018 ).

With regard to debt behavior, those who are more financially literate are less likely to have credit card debt and more likely to pay the full balance of their credit card each month rather than just paying the minimum due (Lusardi and Tufano, 2009 , 2015 ). Individuals with higher financial literacy levels also are more likely to refinance their mortgages when it makes sense to do so, tend not to borrow against their 401(k) plans, and are less likely to use high-cost borrowing methods, e.g., payday loans, pawn shops, auto title loans, and refund anticipation loans (Lusardi and de Bassa Scheresberg, 2013 ).

Several studies have documented poor debt behavior and its link to financial literacy. Moore ( 2003 ) reported that the least financially literate are also more likely to have costly mortgages. Lusardi and Tufano ( 2015 ) showed that the least financially savvy incurred high transaction costs, paying higher fees and using high-cost borrowing methods. In their study, the less knowledgeable also reported excessive debt loads and an inability to judge their debt positions. Similarly, Mottola ( 2013 ) found that those with low financial literacy were more likely to engage in costly credit card behavior, and Utkus and Young ( 2011 ) concluded that the least literate were more likely to borrow against their 401(k) and pension accounts.

Young people also struggle with debt, in particular with student loans. According to Lusardi, de Bassa Scheresberg, and Oggero ( 2016 ), Millennials know little about their student loans and many do not attempt to calculate the payment amounts that will later be associated with the loans they take. When asked what they would do, if given the chance to revisit their student loan borrowing decisions, about half of Millennials indicate that they would make a different decision.

Finally, a recent report on Millennials in the USA (18- to 34-year-olds) noted the impact of financial technology (fintech) on the financial behavior of young individuals. New and rapidly expanding mobile payment options have made transactions easier, quicker, and more convenient. The average user of mobile payments apps and technology in the USA is a high-income, well-educated male who works full time and is likely to belong to an ethnic minority group. Overall, users of mobile payments are busy individuals who are financially active (holding more assets and incurring more debt). However, mobile payment users display expensive financial behaviors, such as spending more than they earn, using alternative financial services, and occasionally overdrawing their checking accounts. Additionally, mobile payment users display lower levels of financial literacy (Lusardi, de Bassa Scheresberg, and Avery, 2018 ). The rapid growth in fintech around the world juxtaposed with expensive financial behavior means that more attention must be paid to the impact of mobile payment use on financial behavior. Fintech is not a substitute for financial literacy.

4 The way forward for financial literacy and what works

Overall, financial literacy affects everything from day-to-day to long-term financial decisions, and this has implications for both individuals and society. Low levels of financial literacy across countries are correlated with ineffective spending and financial planning, and expensive borrowing and debt management. These low levels of financial literacy worldwide and their widespread implications necessitate urgent efforts. Results from various surveys and research show that the Big Three questions are useful not only in assessing aggregate financial literacy but also in identifying vulnerable population subgroups and areas of financial decision-making that need improvement. Thus, these findings are relevant for policy makers and practitioners. Financial illiteracy has implications not only for the decisions that people make for themselves but also for society. The rapid spread of mobile payment technology and alternative financial services combined with lack of financial literacy can exacerbate wealth inequality.

To be effective, financial literacy initiatives need to be large and scalable. Schools, workplaces, and community platforms provide unique opportunities to deliver financial education to large and often diverse segments of the population. Furthermore, stark vulnerabilities across countries make it clear that specific subgroups, such as women and young people, are ideal targets for financial literacy programs. Given women’s awareness of their lack of financial knowledge, as indicated via their “do not know” responses to the Big Three questions, they are likely to be more receptive to financial education.

The near-crisis levels of financial illiteracy, the adverse impact that it has on financial behavior, and the vulnerabilities of certain groups speak of the need for and importance of financial education. Financial education is a crucial foundation for raising financial literacy and informing the next generations of consumers, workers, and citizens. Many countries have seen efforts in recent years to implement and provide financial education in schools, colleges, and workplaces. However, the continuously low levels of financial literacy across the world indicate that a piece of the puzzle is missing. A key lesson is that when it comes to providing financial education, one size does not fit all. In addition to the potential for large-scale implementation, the main components of any financial literacy program should be tailored content, targeted at specific audiences. An effective financial education program efficiently identifies the needs of its audience, accurately targets vulnerable groups, has clear objectives, and relies on rigorous evaluation metrics.

Using measures like the Big Three questions, it is imperative to recognize vulnerable groups and their specific needs in program designs. Upon identification, the next step is to incorporate this knowledge into financial education programs and solutions.

School-based education can be transformational by preparing young people for important financial decisions. The OECD’s Programme for International Student Assessment (PISA), in both 2012 and 2015, found that, on average, only 10% of 15-year-olds achieved maximum proficiency on a five-point financial literacy scale. As of 2015, about one in five of students did not have even basic financial skills (see OECD, 2017 ). Rigorous financial education programs, coupled with teacher training and high school financial education requirements, are found to be correlated with fewer defaults and higher credit scores among young adults in the USA (Urban, Schmeiser, Collins, and Brown, 2018 ). It is important to target students and young adults in schools and colleges to provide them with the necessary tools to make sound financial decisions as they graduate and take on responsibilities, such as buying cars and houses, or starting retirement accounts. Given the rising cost of education and student loan debt and the need of young people to start contributing as early as possible to retirement accounts, the importance of financial education in school cannot be overstated.

There are three compelling reasons for having financial education in school. First, it is important to expose young people to the basic concepts underlying financial decision-making before they make important and consequential financial decisions. As noted in Fig. 1 , financial literacy is very low among the young and it does not seem to increase a lot with age/generations. Second, school provides access to financial literacy to groups who may not be exposed to it (or may not be equally exposed to it), for example, women. Third, it is important to reduce the costs of acquiring financial literacy, if we want to promote higher financial literacy both among individuals and among society.

There are compelling reasons to have personal finance courses in college as well. In the same way in which colleges and university offer courses in corporate finance to teach how to manage the finances of firms, so today individuals need the knowledge to manage their own finances over the lifetime, which in present discounted value often amount to large values and are made larger by private pension accounts.

Financial education can also be efficiently provided in workplaces. An effective financial education program targeted to adults recognizes the socioeconomic context of employees and offers interventions tailored to their specific needs. A case study conducted in 2013 with employees of the US Federal Reserve System showed that completing a financial literacy learning module led to significant changes in retirement planning behavior and better-performing investment portfolios (Clark, Lusardi, and Mitchell, 2017 ). It is also important to note the delivery method of these programs, especially when targeted to adults. For instance, video formats have a significantly higher impact on financial behavior than simple narratives, and instruction is most effective when it is kept brief and relevant (Heinberg et al., 2014 ).

The Big Three also show that it is particularly important to make people familiar with the concepts of risk and risk diversification. Programs devoted to teaching risk via, for example, visual tools have shown great promise (Lusardi et al., 2017 ). The complexity of some of these concepts and the costs of providing education in the workplace, coupled with the fact that many older individuals may not work or work in firms that do not offer such education, provide other reasons why financial education in school is so important.

Finally, it is important to provide financial education in the community, in places where people go to learn. A recent example is the International Federation of Finance Museums, an innovative global collaboration that promotes financial knowledge through museum exhibits and the exchange of resources. Museums can be places where to provide financial literacy both among the young and the old.

There are a variety of other ways in which financial education can be offered and also targeted to specific groups. However, there are few evaluations of the effectiveness of such initiatives and this is an area where more research is urgently needed, given the statistics reported in the first part of this paper.

5 Concluding remarks

The lack of financial literacy, even in some of the world’s most well-developed financial markets, is of acute concern and needs immediate attention. The Big Three questions that were designed to measure financial literacy go a long way in identifying aggregate differences in financial knowledge and highlighting vulnerabilities within populations and across topics of interest, thereby facilitating the development of tailored programs. Many such programs to provide financial education in schools and colleges, workplaces, and the larger community have taken existing evidence into account to create rigorous solutions. It is important to continue making strides in promoting financial literacy, by achieving scale and efficiency in future programs as well.

In August 2017, I was appointed Director of the Italian Financial Education Committee, tasked with designing and implementing the national strategy for financial literacy. I will be able to apply my research to policy and program initiatives in Italy to promote financial literacy: it is an essential skill in the twenty-first century, one that individuals need if they are to thrive economically in today’s society. As the research discussed in this paper well documents, financial literacy is like a global passport that allows individuals to make the most of the plethora of financial products available in the market and to make sound financial decisions. Financial literacy should be seen as a fundamental right and universal need, rather than the privilege of the relatively few consumers who have special access to financial knowledge or financial advice. In today’s world, financial literacy should be considered as important as basic literacy, i.e., the ability to read and write. Without it, individuals and societies cannot reach their full potential.

See Brown and Graf ( 2013 ).

Abbreviations

Defined benefit (refers to pension plan)

Defined contribution (refers to pension plan)

Financial Literacy around the World

National Financial Capability Study

Organisation for Economic Co-operation and Development

Programme for International Student Assessment

Survey of Consumer Finances

Survey of Household Economics and Financial Decisionmaking

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Acknowledgements

This paper represents a summary of the keynote address I gave to the 2018 Annual Meeting of the Swiss Society of Economics and Statistics. I would like to thank Monika Butler, Rafael Lalive, anonymous reviewers, and participants of the Annual Meeting for useful discussions and comments, and Raveesha Gupta for editorial support. All errors are my responsibility.

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Lusardi, A. Financial literacy and the need for financial education: evidence and implications. Swiss J Economics Statistics 155 , 1 (2019). https://doi.org/10.1186/s41937-019-0027-5

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Open access
Published: 27 May 2024

Knowledge creates value: the role of financial literacy in entrepreneurial behavior

Shulin Xu 1 &
Kangqi Jiang 2

Humanities and Social Sciences Communications volume 11 , Article number: 679 ( 2024 ) Cite this article

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Under the backdrop of economic globalization and the digital economy, entrepreneurial behavior has emerged not only as a focal point of management research but also as an urgent topic within the domain of family finance. This paper scrutinizes the ramifications of financial literacy on household entrepreneurial behavior utilizing data from China’s sample of the China Household Finance Survey spanning the years 2015 and 2017. Employing the ordered Probit model, we pursue our research objectives. Our findings suggest that financial literacy exerts immediate, persistent, and evolving positive effects on households’ engagement in entrepreneurial activities and their proclivity toward entrepreneurship. Through the mitigation of endogeneity in the regression model, the outcomes of the two-stage regression corroborate the primary regression results. An examination of heterogeneity unveils noteworthy disparities between urban and rural areas, as well as gender discrepancies, in how financial literacy influences household entrepreneurial behavior. Furthermore, this study validates three potential pathways—namely income, social network, and risk attitude channels—demonstrating that financial literacy significantly augments household income, expands social networks, and enhances risk attitudes. Moreover, through supplementary analysis, we ascertain that financial education amplifies the impact of financial literacy on entrepreneurial behavior. Our study contributes to the enrichment of human capital theory and modern entrepreneurship theory. It advocates for robust efforts by governments and financial institutions to widely disseminate financial knowledge and foster family entrepreneurship, thereby fostering the robust and stable operation of both the global financial market and the job market.

The influence of psychological capital and social capital on women entrepreneurs’ intentions: the mediating role of attitude

Improving the entrepreneurial ability of rural migrant workers returning home in China: Study based on 5,675 questionnaires

Similar but yet different: individual cognitive traits and family contingencies as antecedents of intrapreneurship and self-employment

Introduction.

With the advancement of the global digital economy, entrepreneurship has increasingly emerged as a pivotal strategy for corporate strategic development (Cheng et al., 2024 ) and for the accumulation of residents’ wealth. Entrepreneurial behavior entails the optimization and integration of one’s own resources to generate substantial economic or social value. Individuals are expected to possess organizational and managerial abilities and to deliberate upon and determine the operational strategies for services, technologies, and equipment to engage in rational entrepreneurial endeavors (Levesque and Minniti, 2006 ). Entrepreneurial activities play a crucial role in fostering labor market prosperity, achieving social equity, enhancing the flow of social capital, and sustaining the healthy and stable functioning of the social economy (Hombert et al., 2020 ; Schmitz, 1989 ). They also hold promise for alleviating the current economic crisis through the exploitation of renewable energy sources (Abou Houran, 2023 ) and enhancing firm productivity (Tao et al., 2023 ). According to human capital theory, as posited by Becker ( 2009 ), human capital encompasses the cumulative knowledge, skills, cultural sophistication, and health status of an individual. Financial literacy, as a form of scarce human capital, constitutes a significant driver of entrepreneurial decision-making and motivation. On the one hand, the migration of individuals possessing high financial literacy fosters the transfer of theoretical knowledge and technical expertise, while the symbiotic interaction of knowledge, skills, and capabilities nurtures a reservoir of knowledge and entrepreneurial dynamism. On the other hand, individuals with elevated financial literacy are more likely to enhance their awareness and identification of opportunities within an imbalanced market, thereby bolstering their self-awareness and catalyzing independent innovation and entrepreneurship. Moreover, in line with modern entrepreneurship theory, Alvarez and Busenitz ( 2001 ) contend that entrepreneurial opportunities are endogenous. Entrepreneurs equipped with the requisite skills and knowledge pertaining to entrepreneurship are better positioned to identify and exploit opportunities. Additionally, they possess extensive and efficacious social networks, enabling them to access valuable information and resources conducive to enhancing entrepreneurial performance. Against the backdrop of economic globalization and the digital economy, governments worldwide are actively encouraging entrepreneurial engagement. They have enacted financial support policies and preferential tax measures to enhance the domestic entrepreneurial ecosystem and to galvanize individuals’ entrepreneurial potential. For instance, the Chinese government introduced numerous policies aimed at fostering entrepreneurial endeavors in 2018. Similarly, the U.S. government is proactively implementing several initiatives to foster an environment conducive to the flourishing of small and medium-sized enterprises, striving to institute permanent tax relief measures for small businesses.

However, the enhancement of the entrepreneurial environment can engender a proliferation of entrepreneurial opportunities (Segaf, 2023 ). Yet, the ability of entrepreneurs to seize such opportunities for proactive entrepreneurship remains constrained by numerous factors, including the development of the digital economy (Sussan and Acs, 2017 ; Firmansyah et al., 2023 ; Zhao and Weng, 2024 ), social networks (Karlan, 2007 ; Qi and Chun, 2017 ), human capital (Dawson et al., 2014 ), risk attitudes (Osman, 2014 ), government regulations (Black and Strahan, 2002 ), institutional environments (Burtch et al., 2018 ; Lan et al., 2018 ), institutional changes within universities (Eesley et al., 2016 ), financial constraints (Hurst and Lusardi, 2004 ; Asongu et al., 2020 ), policy interventions (Sharipov and Zaynuidinova, 2020 ), cognitive abilities (Haynie et al., 2012 ), personal beliefs regarding character and opportunity (Pidduck et al., 2023 ), household background, income levels, and trust (Kwon and Arenius, 2010 ). Entrepreneurial activities entail the identification and exploitation of entrepreneurial opportunities and the utilization of entrepreneurial resources. These endeavors invariably entail considerations of business management, financial matters, and professional concerns. Entrepreneurs must possess adequate financial literacy to ensure the rationality of entrepreneurial decision-making, the judicious allocation of entrepreneurial resources, the mitigation of venture capital risks, and the effective operation of enterprises. Drawing from a review of international experiences, scholars predominantly emphasize macroeconomic environments (Arin et al., 2015 ), institutional frameworks, cultural disparities (Liang et al., 2018 ), credit constraints (Ma et al., 2018 ), liquidity constraints (Beck et al., 2018 ), as well as micro-level factors such as social networks (Yueh, 2009 ), and information availability (Companys and McMullen, 2007 ), when examining the determinants of entrepreneurial activities.

From a current static perspective, existing studies indicate a close association between financial literacy and a range of financial behaviors and economic outcomes. A wealth of evidence demonstrates that financial literacy fosters household income growth (Behrman et al., 2012 ), facilitates the expansion of social networks (Kinnan and Townsend, 2012 ; Suresh, 2024 ), and enhances residents’ risk attitudes (Mishra, 2018 ), all of which can also impact entrepreneurial behavior. Thus, we posit that financial literacy may influence household entrepreneurial activities through three primary channels. Firstly, prior research has affirmed that higher levels of financial literacy correlate with enhanced information acquisition and processing abilities, leading to more informed decision-making (Forbes and Kara, 2010 ; Molina-García et al., 2023 ), fostering healthier and more rational investment philosophies and habits. These factors, in turn, contribute to improved investment returns and elevated household income levels. Household entrepreneurial activities necessitate sufficient financial support for use as entrepreneurial funds, and throughout the entrepreneurial process, a continuous stream of funds is required for operational and managerial purposes. Household wealth and income serve as the principal resources for family entrepreneurship, indispensable for entrepreneurial endeavors.

Secondly, studies by Korkmaz et al. ( 2021 ), Mishra ( 2018 ), and Mushafiq et al. ( 2023 ) reveal that heightened levels of financial literacy correlate with an increased likelihood of risk-taking or risk-neutrality and diminished tendencies toward risk aversion. This indicates that enhancing financial literacy significantly bolsters individuals’ risk appetites and reduces risk aversion. Entrepreneurship inherently entails risk-taking behavior and a willingness to embark on new ventures. Therefore, risk attitudes are intricately linked to entrepreneurial behavior. Research by Van Praag and Cramer ( 2001 ), as well as Long et al. ( 2023 ), spanning a 41-year study of 5800 Danish students, illustrates significant disparities in entrepreneurial willingness among individuals with varying risk preferences, with risk-conscious individuals exhibiting stronger inclinations towards entrepreneurship. Thirdly, Hong et al. ( 2004 ) and Chen et al. ( 2023 ) posit that financial literacy may proliferate through word-of-mouth or observational learning methods, thereby expanding social network structures. Social networks, as a distinct form of family capital alongside physical and human capital, facilitate risk-sharing (Munshi and Rosenzweig, 2016 ) and augment the likelihood of accessing formal or informal financing (Kinnan and Townsend, 2012 ). It is widely acknowledged that family entrepreneurial activities, to some extent, depend on the support offered by family members, relatives, and friends in terms of information, financing, and business operations and management (Munshi and Rosenzweig, 2016 ). Consequently, broader family social networks correlate with heightened probabilities of choosing entrepreneurship. Financial literacy can effectively mitigate information asymmetry in financial markets by enhancing family social networks, reducing monitoring costs and risky borrowing, and addressing adverse selection and moral hazard issues, thereby alleviating financing constraints and fostering family entrepreneurial activities.

The aforementioned analysis offers insights into the impact of financial literacy on household entrepreneurial activities. Nevertheless, a pivotal inquiry remains: can financial literacy effectively bolster the likelihood of family entrepreneurial choices and entrepreneurial motivation in the long term, thereby dynamically enhancing family entrepreneurial behavior? Furthermore, the urban–rural dichotomy and gender disparities in financial literacy prevalent in numerous countries may introduce variations in the current, long-term, and dynamic effects of financial literacy on residents’ entrepreneurial behavior. This prompts us to explore the existence of such disparities and whether the mechanisms underlying these differences are mediated through income, social networks, and risk attitudes. To address these gaps in the literature and elucidate the raised questions, we propose to establish a robust empirical framework. This framework will enable us to examine how financial literacy influences local households’ entrepreneurial behavior. Figure 1 illustrates our theoretical framework, delineating how financial literacy impacts household entrepreneurial activities through three primary channels.

Theoretical design and framework.

This study empirically examines the immediate, long-term, and evolving impacts of financial literacy on household entrepreneurial activities using data from the China Household Finance Survey (CHFS) for the years 2015 and 2017. We employ the ordered Probit model to fulfill our research objectives. The findings indicate that financial literacy exerts immediate, enduring, and evolving positive effects on households’ involvement in entrepreneurial activities and their propensity toward entrepreneurship. Accounting for the endogeneity of the regression model, the results from the two-stage regression reinforce the primary regression outcomes. Heterogeneity analysis reveals significant urban–rural disparities and gender differences in the influence of financial literacy on household entrepreneurial behavior. Additionally, this research substantiates three potential pathways: income, social network, and risk attitude channels. It demonstrates that financial literacy significantly enhances household income, expands social networks, and improves risk attitudes. Further analysis reveals that financial education amplifies the impact of financial literacy on entrepreneurial behavior.

Our contributions are multifaceted: Firstly, this study advances the understanding of entrepreneurial behavior in several dimensions. Previous research primarily focuses on factors influencing entrepreneurial behavior, such as social networks (Karlan, 2007 ), human capital (Dawson et al., 2014 ), risk attitudes (Osman, 2014 ), government regulation (Black and Strahan, 2002 ), institutional environments (Lu and Tao, 2010 ), financial constraints (Hurst and Lusardi, 2004 ), cognitive ability (Haynie et al., 2012 ), household background, and trust (Kwon and Arenius, 2010 ). Few studies delve into the influence of financial literacy on entrepreneurial behaviors. We address this gap and find that financial literacy positively impacts entrepreneurial behaviors. Secondly, we measure entrepreneurial behavior at the family level, including initiative entrepreneurship in the household finance domain, thereby expanding the existing literature beyond the use of new ventures as a measurement indicator. Most importantly, our study contributes to the enrichment of human capital theory and entrepreneurship theory within the realm of household finance, providing valuable insights into the theoretical understanding of the relationship between financial literacy and entrepreneurial behavior. Thirdly, in mechanism analysis, our study is the first to investigate the three channels through which financial literacy affects household entrepreneurial behavior using CHFS data from 2015 and 2017. Lastly, our study conducts heterogeneity analysis and presents evidence of significant urban-rural disparities and gender heterogeneity in the impact of financial literacy on household entrepreneurial behavior. Furthermore, this research enhances the comprehension of the relationship between financial literacy and financial behavior. While prior studies predominantly focus on the immediate effect of financial literacy on financial behavior, our study delves deeper. We not only explore the immediate impact of financial literacy on entrepreneurial behavior but also probe into its long-term and dynamic improvement characteristics, elucidating the internal mechanisms driving these effects. For policymakers, our research provides a theoretical foundation and empirical validation to formulate entrepreneurship policies. By comprehensively understanding how financial literacy influences household entrepreneurial behavior and acknowledging the heterogeneous effects across urban–rural divides and gender disparities, governments can tailor policies to effectively support and promote entrepreneurship, thereby fostering economic growth and development. Based on the conclusions of this study, governments can fully consider residents’ financial literacy and enhance various influencing channels while encouraging innovation and entrepreneurship, thereby facilitating wealth accumulation, enhancing family welfare, and elevating the national level of innovation and entrepreneurship in entrepreneurial activities. For businesses, our research underscores the pivotal role of financial literacy in entrepreneurial activities, constituting an indispensable aspect of “entrepreneurship.” In the actual operation and management processes of enterprises, managers should prioritize the cultivation of financial literacy, as it can aid in cost reduction and the expansion of social networks, thereby realizing the healthy and stable operation of enterprises.

In the rest of this paper, the section “Literature review” reviews the relevant literature. Section “Methodology” outlines the empirical model and introduces the variables and datasets. Section “Empirical results” describes and discusses the empirical results. Section “Heterogeneity analysis” reports a heterogeneous analysis in geography, gender and income level. The section “Potential mechanism analysis” and “Further analysis: the role of financial education” discusses three channels and analyses. Section “Conclusion” concludes and policy implications.

Literature review

Factors affecting financial literacy.

The financial literacy level of respondents is primarily influenced by both micro and macro environments. Concerning microelements, empirical evidence provided by Lusardi and Mitchell ( 2014 ) suggests that men tend to exhibit higher financial literacy levels than women, largely due to women’s perceived lack of self-confidence. Notably, only elderly women demonstrate high levels of self-assurance, alongside robust investment motivation and financial management interest (Bucher‐Koenen et al., 2017 ). Furthermore, Van Rooij et al. ( 2011 ) contend that age and financial literacy follow a hump-shaped distribution pattern, indicating that young individuals under 15 and seniors over 60 typically exhibit the lowest levels of financial literacy, while the middle-aged group tends to have the highest level. The accumulation of social experience serves to enhance the financial literacy level of the middle-aged demographic (Fong et al., 2021 ; Gamble et al., 2015 ). Moreover, Lusardi et al. ( 2012 ) found a positive correlation between the number of years of education and financial literacy, implying that higher levels of education contribute to the advancement of financial literacy.

The influence of macro-elements on financial literacy permeates various facets, shaping the financial knowledge and skills of young individuals through diverse formal and informal channels such as families, schools, communities, and workplaces (Grohmann et al., 2015 ). Lusardi et al. ( 2010 ) elucidated a direct correlation between the financial literacy of young individuals and the educational level and financial behavior of their parents. Moreover, Lachance ( 2014 ) uncovered that the educational level of neighbors also impacts children’s financial literacy. Danes and Haberman ( 2007 ) observed that while short-term financial literacy education and training exert some effect, direct parental education remains a more potent influencer of children’s financial literacy. Furthermore, parents’ active involvement in financial education and training programs contributes significantly to shaping children’s financial literacy. However, the literature presents mixed findings regarding the efficacy of financial education initiatives. Mandell ( 2008 ) found no enduring effects of financial education in high school on personal financial behavior, whereas Fernandes et al. ( 2014 ) suggested that financial literacy education has a limited impact, with its effectiveness waning over time. Conversely, Bruhn et al. ( 2013 ) and Lührmann et al. ( 2015 ) argued that financial education substantially enhances high school students' financial literacy. Moreover, Song ( 2020 ) conducted a field experiment in China, demonstrating that short-term financial education projects can effectively elevate financial literacy levels, thereby improving financial behavior among individuals with low financial literacy. Regarding social security mechanisms, extant literature indicates that improvements in social security significantly correlate with enhancements in residents’ financial literacy (Lusardi and Mitchell, 2011 ). Additionally, the social milieu plays a pivotal role, with countries experiencing high inflation rates and communities characterized by a high level of financial literacy, transparent banking policies, and frequent interactions with financially literate groups positively influencing individuals’ financial literacy levels (Lachance, 2014 ; Lusardi and Mitchell, 2011 ).

With the rapid proliferation of digital technology in the economic sphere, digitization has emerged as a ubiquitous topic of discussion among scholars (Chen and Jiang, 2024 ; Koskelainen et al., 2023 ; Jiang et al., 2024 ). The digitization of conventional financial industries and the entry of internet companies have catalyzed the growth of the digital finance sector (Jiang et al., 2022 ). Pertinent literature delves into the relationship between the advancement of digital finance and financial literacy (Prete, 2022 ; Yang et al., 2023 ). For instance, Yang et al. ( 2023 ), utilizing data from the China Household Finance Survey, found that financial literacy significantly fosters individuals’ engagement in digital finance, with this effect displaying notable heterogeneity. Drawing from cross-national data, Prete ( 2022 ) observed that the utilization of digital payment tools and platforms correlates with elevated levels of financial literacy. Koskelainen et al. ( 2023 ) endeavored to explore how varied aspects of digitization, encompassing digital financial behaviors, digital interventions, and financial technology, influence individuals’ financial literacy. Furthermore, they propose methodologies for constructing a metric of digital financial literacy.

Entrepreneurial behavior

Existing research concentrates on the determinants of entrepreneurial behavior, encompassing both macroelements and microelements. Macroelements comprise the economic environment, institutional framework, cultural disparities, credit and liquidity constraints, social networks, and information environment.

Economic development stimulates market demand for entrepreneurs and fosters entrepreneurial activities (Arin et al., 2015 ; AlOmari, 2024 ). Zhao and Weng ( 2024 ) observed that the advancement of the digital economy enhances urban innovation activities. Utilizing cross-cultural entrepreneurial cognition models, Lim et al. ( 2010 ) validated the impact of institutions on entrepreneurial activities. A nation’s formal institutions can dictate its level of economic freedom, influencing households’ entrepreneurial motivations and the types of entrepreneurial ventures pursued (McMullen et al., 2008 ; Kshetri, 2023 ). Asoni and Sanandaji ( 2014 ) demonstrated that proportional taxes do not significantly affect entrepreneurial activities, whereas progressive taxes notably boost entrepreneurship. Dong et al. ( 2022 ) revealed that local leadership turnover may serve as a barrier to entrepreneurship. Additionally, the environment for protecting private property rights is intertwined with entrepreneurial activities (Levine and Rubinstein, 2017 ; Hou et al., 2023 ). The deregulation of bank branches has intensified competition within the banking sector while greatly enhancing credit accessibility, thereby promoting household entrepreneurship (Black and Strahan, 2002 ). In terms of cultural disparities, Mora ( 2013 ) posited that such differences lead to variations in entrepreneurial ideas and behavioral tendencies, with entrepreneurial activities more likely to flourish in a cultural milieu characterized by low uncertainty, fostering independent thinking, valuing wealth, and eschewing conformity (Lee et al., 2020 ). Freytag and Thurik ( 2007 ), drawing upon data from European and American countries, concluded that culture exerts a positive and significant impact on entrepreneurial preferences but does not significantly influence actual entrepreneurial activities.

The primary challenge encountered by entrepreneurial endeavors is liquidity constraints (Banerjee and Newman, 1993 ; Ma et al., 2018 ). Banerjee and Newman ( 1993 ) contend that financial support in the form of low-interest loans, financing guarantees, and credit assurances alleviates financing constraints during entrepreneurial pursuits, thereby mitigating business risks. Information asymmetry may curtail the availability of credit services for entrepreneurs and impede household entrepreneurial activities (Stiglitz and Weiss, 1981 ). Wang ( 2012 ) constructed models for employment and housing decision-making, revealing that liquidity constraints influence the interaction between personal wealth and entrepreneurial decision-making. The emergence of digital finance and the Internet has mitigated information asymmetry, moral hazard, and adverse selection, safeguarding entrepreneurs’ financial security (Beck et al., 2018 ; Qing et al., 2024 ). Furthermore, it has expanded product sales channels and enhanced the accessibility of cost-effective financial services (Berger and Udell, 2002 ; He and Maire, 2023 ), thereby fostering household entrepreneurial behavior. However, Hurst and Lusardi ( 2004 ) posit that credit constraints are not the primary impediment to entrepreneurial activities, as entrepreneurs can mitigate such constraints through savings and informal credit channels.

Social networks play a pivotal role in entrepreneurial endeavors. A robust social network can furnish material capital, technical expertise, vital information, and emotional support for household entrepreneurship (Yueh, 2009 ; Yates et al., 2023 ). Social networks effectively alleviate information asymmetry, mitigate adverse selection and moral hazard (Karlan, 2007 ; Kerr and Mandorff, 2023 ), and serve as an implicit guarantee mechanism, reducing the likelihood of default on non-governmental loans (Karlan, 2007 ). Consequently, social networks diminish liquidity constraints, thereby promoting households’ inclination towards entrepreneurship. According to entrepreneurial vigilance theory, information asymmetry gives rise to entrepreneurial opportunities, underscoring the significance of information disparities in entrepreneurial activities (Companys and McMullen, 2007 ; Wang et al., 2024 ). Trust fosters the flow of information among different social groups, cultivating social capital, and residents with greater entrepreneurial opportunities are more inclined towards entrepreneurship (Kwon and Arenius, 2010 ).

Microelements encompass human capital and psychological characteristics. Regarding human capital, Berkowitz and DeJong ( 2005 ) contend that individuals with higher education levels can swiftly and accurately identify potential entrepreneurial opportunities and efficiently allocate internal and external resources. However, compared to those with average education levels, individuals with higher education face higher opportunity costs, leading to lower entrepreneurial motivation. Additionally, some studies find no significant effect of education on entrepreneurial activities (Van der Sluis et al., 2008 ) or observe a non-linear U-shaped relationship (Poschke, 2013 ). Mankiw and Weinzierl ( 2011 ) ascertain that a lack of personal ability significantly dampens households’ entrepreneurial spirit. Entrepreneurial behavior necessitates the acquisition, organization, and analysis of information, with cognitive ability reflecting an individual’s capacity to process, store, and extract information. Thus, Haynie et al. ( 2012 ) posit that cognitive ability may influence an individual’s entrepreneurial activities. Other studies explore the relationship between an individual’s age (Caliendo et al., 2014 ), gender (Koellinger et al., 2013 ), marital status, political outlook (Yueh, 2009 ), entrepreneurial training (Blattman et al., 2014 ), work experience (Lazer, 2005 ), type of employment (Djankov et al., 2005 ), health status (Rey-Martí et al., 2016 ), management elements (Cheng et al., 2022 ), education (Cui and Bell, 2022 ; Adeel et al., 2023 ; Lin et al., 2023 ), entrepreneurial identity (Stevenson et al., 2024 ), and entrepreneurial behavior.

Concerning household wealth, the majority of studies posit a positive correlation between household wealth and entrepreneurial behavior (Evans and Jovanovic, 1989 ). Some studies also explore the impact of accidental exogenous events and policy reforms leading to increased wealth on household entrepreneurial behavior (Blattman et al., 2014 ). In terms of psychological characteristics, extant literature primarily discusses the effect of risk attitude on entrepreneurial behavior. Most studies demonstrate that individual risk preference significantly influences entrepreneurial behavior, with risk-tolerant individuals exhibiting a greater propensity for entrepreneurial activities (Osman, 2014 ). However, Hu ( 2014 ) suggests that risk-neutral individuals are more inclined to engage in active entrepreneurial activities, whereas risk-averse and risk-tolerant individuals are more predisposed to becoming waged workers.

Existing research predominantly concentrates on the determinants of financial literacy and entrepreneurial behavior. Few studies explore the impact of financial literacy on entrepreneurial behavior. This study aims to address this gap.

Methodology

Refer to prior studies (Dong et al., 2022 ; Yang et al., 2023 ; Zhao and Li, 2021 ; Xu et al., 2023 ; Graña-Alvarez et al., 2024 ), this study uses the ${{\rm {Probit}}}$ model to study the current and long-term effects of financial literacy on household entrepreneurial behavior. The basic regression equation is as follows:

When we study the current effect, ${{{\rm {Entrepre}}}}_{i}$ refers to entrepreneurship behavior of household $i$ in 2015. ${{{\rm {Literacy}}}}_{i}$ represents financial literacy of household i in 2015. ${X}_{i}^{{\prime} }$ refers to control variables in 2015, including ${{\rm {gender}}}$ , ${{\rm {Age}}}$ , ${{{\rm {Age}}}}^{2}$ , ${{\rm {Health}}}$ , ${{\rm {Marriage}}}$ , ${{\rm {Education}}}$ , ${{\rm {RL}}}$ , ${{\rm {RN}}}$ , ${{\rm {RA}}}$ , ${\rm {{CPC}}}$ , ${{\rm {FS}}}$ , ${{\rm {Assets}}}$ , ${{\rm {NC}}}$ , ${{\rm {NE}}}$ , ${{\rm {House}}}$ , and ${{\rm {NU}}}$ . 1 ${\mu }_{i}$ is the error term. In the above regression model, we control the province-fixed effect. The current effect is a static effect based on cross-sectional data, which mainly examines whether the current financial literacy can affect the current household entrepreneurial behavior. Most existing studies only use cross-sectional data to consider current effects.

When we study the long-term effect, ${{{\rm {Entrepre}}}}_{i}$ refers to entrepreneurship behavior of household $i$ in 2017. ${{{\rm {Literacy}}}}_{i}$ represents the financial literacy of household $i$ in 2015. Other designs remain unchanged. The long-term effect is mainly to test whether financial literacy can have an effect on lagging entrepreneurial behavior.

Furthermore, we use the ${{\rm {ordered}}\; {\rm {Probit}}}$ model to study the dynamic effect of financial literacy on household entrepreneurial behavior as follows:

Where ${{{\rm {Entrepre}}}}_{i}^{* }$ represents the changes in entrepreneurial behavior household $i$ during 2015–2017, it is an ordered variable, denoted by −1, 0, and 1, respectively. ${{{\rm {Literacy}}}}_{i}$ represents financial literacy of household $i$ in 2015. ${\varphi }_{i}$ refers to control variables in 2015. The expression of $F$ $\left(\cdot \right)$ function in the model ( 2 ) is as follows:

Where ${{{\rm {Entrepre}}}}_{i}^{* {\prime\prime} }$ is the latent variable of ${{{\rm {Entrepre}}}}_{i}^{* }$ . ${\varepsilon }_{1} < {\varepsilon }_{2} < L < {\varepsilon }_{3}$ all are tangent points. ${{{\rm {Entrepre}}}}_{i}^{* {\prime\prime} }$ has to satisfy:

Financial literacy

Following prior studies (Lusardi and Mitchell, 2014 ; Zhao and Li, 2021 ), Table 1 reports the descriptive statistics of the answers to questions related to financial literacy as survey respondents’ financial literacy level denoted as ${{{\rm {Literacy}}}1}_{i}$ . It shows that 28.67%, 16.39%, and 51.94% of the households answered the questions of interest rate calculation, inflation understanding, and venture capital correctly, respectively, indicating that most Chinese households do not understand and calculate inflation. A total of 48.17% of the households incorrectly answered the questions about interest rate calculation, implying that Chinese households lack the ability to calculate the interest rate.

Factor analysis is also often used to measure financial literacy. Following Lusardi and Mitchell ( 2014 ), we believe that the level of financial literacy represented by wrong answers and failure to answer differs. Considering this, we construct two dummy variables for each question. Therefore, we obtain six dummy variables, including dum1–dum6. The KMO test results in Table 2 show that factor analysis is reasonable. Finally, this study selects the factors with an eigenvalue greater than one as respondents’ financial literacy denoted as ${{\rm {Literacy}}}2$ .

Referring to Zhao and Li ( 2021 ), the explained variable in this study is household entrepreneurial behavior, including ${{\rm {Enterpre}}}1$ and ${{\rm {Entrepre}}}2$ , $\,{{Entrepre}1}^{* }$ , and $\,{{{\rm {Entrepre}}}2}^{* }$ . ${{\rm {Entrepre}}}1$ measures whether the interviewed household participates in entrepreneurial behavior and is equal to one when the household is engaged in a self-employed business operation. ${{\rm {Entrepre}}}2$ measures whether the entrepreneurial behavior of entrepreneurial families is active and is equal to 1 if the reason for the household’s participation in entrepreneurship is “want to be the boss”, “earn more”, and “want to be more flexibles and free”. ${{{\rm {Entrepre}}}1}^{* }$ represents the changes in entrepreneurial behavior of households during 2015–2017. ${{{\rm {Entrepre}}}2}^{* }$ represents the changes in initiative entrepreneurship of households during 2015–2017. Its construction method is shown in Table 3 .

The survey data collected by the China Household Finance Survey in 2015 and 2017 are used in this paper. This database collects a large amount of information about Chinese residents through scientific surveys and statistical methods, and it is widely used in scientific research. The CHFS has designed relevant questions about the financial literacy of the interviewees. Samples with missing values are excluded. Table 4 provides the descriptive statistics of the variables. It is worth mentioning that CHFS has been widely adopted (Zhao and Li, 2021 ; Yang et al., 2023 ).

Empirical results

Financial literacy and entrepreneurial behavior.

Columns (1)–(4) in Table 5 report the estimated results of the current effect. The estimated coefficients of financial literacy in columns (1) and (2) are significant at the level of 5% and 1%, respectively, indicating that the improvement of financial literacy can significantly improve the possibility of household entrepreneurship. This result shows that financial literacy is an important determinant of household entrepreneurship decision-making, and it is the driver of household entrepreneurial activities. We found an interesting conclusion from the estimation results of the control variables. From the results in columns (1)–(4), we find that the education level of the head of the household is significantly negatively correlated with the household entrepreneurial behavior. However, the impact of our financial literacy on household entrepreneurial behavior was positive. This result seems to go against our intuition. We think that because financial literacy education is different from general education. Ordinary education mainly emphasizes the popularization and popularization of knowledge, while financial literacy education should be a kind of targeted specialized education. This conclusion supports the conclusion of the majority of the current literature.

The regression model may suffer endogenous problems. Endogeneity mainly comes from two aspects. First, a reverse causal relationship exists between financial literacy and household entrepreneurial choice. The accumulation of entrepreneurial experience may also lead to improved financial literacy. Second, the respondents may guess the answers to financial questions, leading to inaccurate measurement of financial literacy. Following Bucher-Koenen and Lusardi ( 2011 ) and Jappelli and Padula ( 2013 ), we selected the highest educational level among parents as an instrumental variable. We chose this instrumental variable for two main reasons. First, the family is the first place where individuals acquire and learn knowledge after they are born. Generally speaking, the higher the education level of parents, the more emphasis they will put on the education of their children. Parents with a high level of education can better help their children develop study habits and guide their children to receive more and better education through precepts and deeds and subtle influences in the daily life of the family. This will allow them to know more about their computing power and knowledge of economics and finance and possibly have a higher level of financial literacy. Second, the educational level of parents is determined before their children start a business and is independent of the entrepreneurial decisions of their children’s families. This suggests that parents’ educational level is strictly exogenous relative to their children’s entrepreneurial decisions. Therefore, we think it is appropriate to use parental education level as an instrumental variable. The problem that cannot be ignored is that parents with higher education levels are more likely to provide more resources for their children to start a business through their relationship network. We address this issue by controlling the parental network in our model. The results show that both the correlation test and the exogenous test of the instrumental variable of parental education level have passed, which verifies the validity of the instrumental variable to a certain extent. The results in Columns (3) and (4) in Table 5 support our conclusion.

Columns (5)–(8) in Table 5 report the estimated results of the current effect of financial literacy on household initiative entrepreneurship ( ${{\rm {Entrepre}}}2$ ). The results in columns (5) and (6) of Table 5 show that the estimated coefficients of financial literacy are significant at the level of 10%, indicating that financial literacy can help raise the household’s motivation for entrepreneurship in the current period and promote the initiative in entrepreneurship. Columns (7) and (8) in Table 5 , The DWH test, first-stage estimated and instrumental variables show that financial literacy will help raise the household’s motivation for entrepreneurship in the current period and promote the initiative in entrepreneurship.

Table 6 reports the estimated results of the long-term effect of financial literacy on household entrepreneurial behavior. No matter what index is used to measure financial literacy, the estimated coefficient of financial literacy is statistically significantly positive, indicating that financial literacy is beneficial to increasing the probability of households participating in entrepreneurial activities and taking the initiative in entrepreneurship in the long term.

Table 7 reports the estimation results of the ordered ${{\rm {Probit}}}$ model to estimate the dynamic improvement effect of financial literacy on household entrepreneurial behavior. In Table 7 , columns (1) and (2) show that no matter what index is used to measure financial literacy, the estimated coefficient of financial literacy is statistically significantly positive. After controlling endogenous concerns, we can obtain consistent results in columns (3) and (4). Columns (5)–(8) in Table 7 , no matter what index is used to measure financial literacy, the estimated coefficient of financial literacy is statistically significantly positive. We find that the improvement of financial literacy level is helpful in promoting the development of household entrepreneurial decision-making and initiative in entrepreneurship.

The above empirical results suggest that improving financial literacy levels may significantly promote family participation in entrepreneurial activities and household initiative in entrepreneurship. This conclusion is consistent with the conclusion of Xu et al. ( 2023 ), indicating that financial literacy may have current, long-term, and dynamic effects on some financial behaviors. This effect has the characteristics of current, long-term, and dynamic improvement. This study provides a reasonable explanation for the findings that financial literacy adds to entrepreneurs’ understanding of business activities and market dynamics, enabling them to discover entrepreneurial opportunities better.

Robustness checks

We conduct the robustness checks by replacing the proxy index of financial literacy. We construct three dummy variables, namely, ${{\rm {Dum}}}1$ , ${{\rm {Dum}}}3$ , and ${{\rm {Dum}}}$ 5. We use these three dummy variables to replace the explanatory variable ${{\rm {Entrepre}}}1$ or ${{\rm {Entrepre}}}2$ in the model (1) and model (2). ${{\rm {Dum}}}1$ means the answers the interest rate calculation question correctly, ${{\rm {Dum}}}2$ means the answers the inflation question correctly, ${{\rm {Dum}}}3$ means the answers the inflation question correctly. Table 8 reports the corresponding estimated results. The estimated coefficients of ${{\rm {Dum}}}1$ and ${{\rm {Dum}}}3$ are not significant. However, no matter what index is used to measure financial literacy, the estimated coefficient of ${{\rm {Dum}}}5$ is statistically significantly positive, indicating that venture capital literacy can significantly improve household entrepreneurial activities and motivation to initiate entrepreneurship.

In addition, we use respondents’ attention to economic and financial information to measure it denoted as ${Attention}$ . We use ${attention}$ to replace the explanatory variable ${Literacy}1$ or ${Literacy}2$ in the model (1) and model (2). Table 9 results show that the estimated coefficient of ${Attention}$ is statistically significantly positive. It shows that attention to financial and economic information can significantly improve household entrepreneurial activity and motivation to initiate entrepreneurship, which also indicates that the influence of financial literacy is robust.

Heterogeneity analysis

Urban–rural differences.

Significant differences exist between urban and rural areas in China’s economic environment, and household entrepreneurship behavior may show varying tendencies in different environments. Therefore, the effect of financial literacy on household entrepreneurship may have urban–rural heterogeneity. Table 10 reports the estimated results. Combining the size of the explanatory variable coefficient and the test results of inter-group coefficient difference, we find that the effect of financial literacy on households’ participation in entrepreneurial activities is more pronounced for households in urban areas. However, the effect of financial literacy on the initiative in entrepreneurship is more pronounced for households in rural areas.

Regarding the findings, this study provides a reasonable explanation. Compared with rural areas, urban areas have higher economic and financial development. Highly skilled personnel are also more abundant in urban areas, which leads to more opportunities for entrepreneurship. Therefore, the relationship between financial literacy and the possibility of households’ participating in entrepreneurial activities is stronger for households in urban areas. The level of income and financial development in rural areas is low, and the degree of financing constraints on households is severe. Compared with urban households who have already participated in entrepreneurial activities, rural households who have already participated in entrepreneurial activities are more eager to quickly realize “being your own boss,” “earning more,” and “being flexible and free” through initiative in entrepreneurship.

Gender differences

Gender differences in financial literacy are common in many countries (Hung et al., 2009 ). Lusardi and Mitchell ( 2014 ) found that in the United States, 38.3% of men can correctly answer three financial questions, but only 22.5% of women can. Only in their old age can women have financial investment motivation and a strong interest in household financial management (Tran et al., 2019 ). Table 11 reports the estimated results. Combining the size of explanatory variable coefficient and the test results of inter group coefficient difference, we find that the effect of financial literacy on household participation in entrepreneurial activities is more pronounced in the male sample and the effect of financial literacy on the household initiative in entrepreneurship is more pronounced in the female sample.

This study provides a reasonable explanation for the findings. Compared with women, men tend to be more confident in their economic decision-making abilities and have a stronger interest in family financial management, hoping to realize self-worth through entrepreneurship. Therefore, financial literacy has a stronger effect on men’s participation in entrepreneurial activities. Compared with men who have made entrepreneurial choices, women are more eager to realize personal financial freedom in entrepreneurship. Therefore, financial literacy has a stronger effect on women’s initiative in entrepreneurship.

Potential mechanism analysis

Income channels.

On the one hand, the income gap or expansion of income levels has changed people’s relative status, intensified “relative exploitation” and social differentiation, and affected people’s “material craving” and jealousy, thereby helping to stimulate the enthusiasm of middle- and low-income groups to start a business (Mensah and Benedict, 2010 ). On the other hand, the most important thing at the beginning of entrepreneurship is the initial capital for family entrepreneurship, and the increase in family income provides initial capital for family entrepreneurship, thereby promoting family entrepreneurial activities (Evans and Jovanovic, 1989 ). To this end, this study explores whether financial literacy will affect household entrepreneurial activities through the channel of increasing household income and income level. This study estimates the following regression model to prove the income channel that financial literacy may increase household income and income rank:

where ${{{\rm {Income}}}}_{i}$ refers to the natural logarithm of the total household income. $\,{{{\rm {Rank}}}}_{i}=1$ represents a high-income household. ${X1}_{i}$ and ${X2}_{i}$ represent control variables in 2015, including ${{\rm {gender}}}$ , ${{\rm {Age}}}$ , ${{{\rm {Age}}}}^{2}$ , ${{\rm {Health}}}$ , ${{\rm {Marriage}}}$ , ${{\rm {Education}}}$ , ${{\rm {RL}}}$ , ${{\rm {RN}}}$ , ${{\rm {RA}}}$ , ${{\rm {CPC}}}$ , ${{\rm {FS}}}$ , ${{\rm {Assets}}}$ , ${{\rm {NE}}}$ , ${{\rm {NC}}}$ , ${{\rm {House}}}$ , and ${{\rm {NU}}}$ . Other designs are consistent with the benchmark model ( 1 ). If ${\omega }_{1}$ and ${\omega }_{2}$ are significantly positive, then we can conclude that financial literacy may increase household income and income rank.

We use CHFS 2015 data to conduct empirical research to prove that financial literacy can increase household income and promote entrepreneurial activities. This study uses two indicators of total household income ( ${{\rm {Income}}}$ ) and income level ( ${{\rm {Rank}}}$ ) as household income variables. The total family income is a total indicator of income, and the income level is a relative indicator that reflects the relative level of family income. We divide the income level into two levels according to the total income of the sample. The top 50% of the total income level is defined as the high-income class, and the bottom 50% is defined as the low-income family. The endogenous problems found in the regression model are solved by the instrumental variable method. The estimation results are shown in Table 12 . It shows that the estimated coefficients for ${{\rm {Literacy}}}1$ and ${{\rm {Literacy}}}2$ are significantly positive, which indicates that income channels are possible. The regression model may suffer endogenous problems. Following Bucher-Koenen and Lusardi ( 2011 ) and Jappelli and Padula ( 2013 ), we select the highest educational level among parents as an instrumental variable. Columns (5)–(8) in Table 12 show that the estimated coefficients of financial literacy are significantly above 1%, which indicates that income channels are possible.

Social network channels

In China, the family social network is mainly based on blood and geography. One of the important means of communication and relationship between relatives and friends is to give gifts to one another during the Spring Festival and other holidays and weddings and funerals. We use CHFS 2015 data for empirical research and select the family’s cash and non-cash expenditures ( ${{\rm {Expenditure}}}$ ), income ( ${{\rm {Revenue}}}$ ), and total income and expenditure ( ${{\rm {Sum}}}$ ) during the Spring Festival and other holidays and weddings and funerals as the proxy variables for the social network. The endogenous problems found in the regression model are solved using the two-stage instrumental variable method. This study strives to prove the social network channel that financial literacy promotes families’ cash and non-cash expenditures, revenue, and total revenue and expenditure during holidays such as the Spring Festival and weddings and funerals. Our model is as following:

where ${{SN}}_{i}$ is ${{Expenditure}}_{i}$ , ${{revenue}}_{i}$ , or ${{Sum}}_{i}$ refer to the social network. ${{Expenditure}}_{i}$ represents the total cash and non-cash expenditures of the family during holidays such as the Spring Festival and weddings and funerals. ${{Revenue}}_{i}$ represents the total cash and non-cash revenue of the family. ${{Sum}}_{i}$ represents the total cash and non-cash expenditures and revenue of the family. ${X3}_{i}$ represents control variables in 2015, including ${gender}$ , ${Age}$ , ${{Age}}^{2}$ , ${Health}$ , ${Marriage}$ , ${Education}$ , ${RL}$ , ${RN}$ , ${RA}$ , ${CPC}$ , ${FS}$ , ${Assets}$ , ${NE}$ , ${NC}$ , ${House}$ , and ${NU}$ . Other designs are consistent with model (1). If ${\psi }_{1}$ is significantly positive, then we can conclude that financial literacy may expand social network.

The estimated results are shown in Table 13 . Following Bucher-Koenen and Lusardi ( 2011 ) and Jappelli and Padula ( 2013 ), we selected the highest educational level among parents as an instrumental variable. As can be seen from columns (1)–(6) in Panel A, ${Literacy}1$ and ${Literacy}2$ are both significantly positive at the 1% level. From columns (1)–(6) in Panel B, after controlling for endogenous factors, ${Literacy}1$ and ${Literacy}2$ are both statistically significantly positive at the 1% level. These results imply that social network channels are possible and reliable.

Risk attitude channels

We use CHFS 2015 data to conduct empirical research to prove that financial literacy can improve household risk attitudes and promote family entrepreneurial activities. We measure risk attitudes in multiple dimensions. First, we construct a comprehensive index of risk attitude. Risk preference ( ${{\rm {RL}}}$ ), risk neutrality ( ${{\rm {RN}}}$ ), and risk aversion ( ${{\rm {RA}}}$ ) are assigned values of 3, 2, and 1, respectively, to examine the effect of financial literacy on risk attitudes. Then, we divide risk attitudes into risk preference ( ${{\rm {RL}}}$ ), risk aversion ( ${{\rm {RA}}}$ ), and risk neutrality ( ${{\rm {RN}}}$ ) and generate dummy variables to examine the effect of financial literacy on these three types. Similarly, considering that there may be endogenous problems in the regression model, we use the instrumental variable method to solve the problem. This study strives to prove the risk attitude channel that financial literacy promotes risk attitude:

where ${{{\rm {Risk}}\_{\rm {attitude}}}}_{i}$ is ${{{\rm {RL}}}}_{i}$ , ${{{\rm {RN}}}}_{i,}$ or ${{{\rm {RA}}}}_{i}$ in model ( 8 ), and ${{{\rm {Risk}}}}_{i}$ is ${{\rm {Risk}}}$ in model ( 9 ). Risk preference ( ${{\rm {RL}}}$ ), risk aversion ( ${{\rm {RA}}}$ ), and risk neutrality ( ${{\rm {RN}}}$ ) are generated as dummy variables to examine the effect of financial literacy on the three types of risk attitudes. ${{{\rm {Risk}}}}_{i}$ is a comprehensive indicator of risk attitude. We assign the values of 3, 2, and 1 to respondents’ risk preference, risk neutrality, and risk aversion, respectively, and examine the effect of financial literacy on risk attitudes. ${X4}_{i}$ represents control variables in 2015, including ${{\rm {gender}}}$ , ${{\rm {Age}}}$ , ${{{\rm {Age}}}}^{2}$ , ${{\rm {Health}}}$ , ${{\rm {Marriage}}}$ , ${{\rm {Education}}}$ , ${{\rm {CPC}}}$ , ${{\rm {FS}}}$ , ${{\rm {Assets}}}$ , ${{\rm {NE}}}$ , ${{\rm {NC}}}$ , ${{\rm {House}}}$ , and ${{\rm {NU}}}$ . Other designs are consistent with the benchmark model ( 1 ). If ${\omega }_{3}$ and ${\sigma }_{1}$ are significantly positive, then we can conclude that financial literacy may improve risk attitude.

The estimation results are shown in Table 14 . Columns (1)–(8) in Panel A demonstrate that the marginal effect of financial literacy on risk appetite and risk neutrality is positive, while the marginal effect on risk aversion is significantly negative. This indicates that enhancing financial literacy has led to an increase in residents’ willingness to take risks and a reduction in their aversion to risk. Additionally, the positive marginal effect of financial literacy on risk attitudes further underscores its role in improving residents’ overall risk perception. Following Bucher-Koenen and Lusardi ( 2011 ) and Jappelli and Padula ( 2013 ), we selected the highest educational level among parents as an instrumental variable. The estimation results in columns (1)–(8) of Panel B indicate that after solving the endogenous problem, the estimated coefficients or marginal effect coefficients of ${{\rm {Literacy}}}1$ and ${{\rm {Literacy}}}2$ are significantly positive at the level of 5% and above. The above results confirm the rationality of the empirical evidence that financial literacy promotes family entrepreneurial behavior by improving residents’ risk attitudes.

Further analysis: the role of financial education

The aforementioned findings substantiate the significant impact of financial literacy on family entrepreneurial behavior, thereby underscoring the importance of delving deeper into strategies aimed at enhancing residents’ financial literacy within the context of family entrepreneurship. According to Lusardi and Mitchell ( 2011 ), implementing financial education programs emerges as the most effective means to bolster residents’ financial literacy. Can financial education truly serve as a catalyst for elevating residents’ financial literacy? Furthermore, can it effectively amplify the influence of financial literacy on residents’ entrepreneurial endeavors? Investigating the intricate interplay between financial literacy, financial education, and familial entrepreneurial conduct is paramount.

In initial exploration, it becomes imperative to scrutinize the correlation between financial education and the level of financial literacy. To operationalize financial education, a binary variable is constructed, wherein a value of 1 denotes participation in coursework related to economics or finance, while a value of 0 indicates otherwise. Subsequently, the variables Literacy1 or Literacy2 are introduced to replace the interpreted variable, and the variable Learn stands in place of the interpreted variable. The control variables adhere to the framework outlined in Model (1). The estimated outcomes are presented in Table 15 . Regardless of the method employed to measure financial literacy, the estimated coefficient of financial education ( Learn ) consistently demonstrates a statistically significant positive impact at the 1% significance level, suggesting that engagement in financial education initiatives can indeed enhance residents’ financial literacy levels. Additionally, three PSM methodologies are employed to scrutinize the influence of financial education on financial literacy. The estimated results, as detailed in Table 16 , consistently reveal positive and statistically significant ATT values, thereby affirming the robustness of the aforementioned findings. These robustness checks further underscore the foundational assertion, highlighting the pivotal role of financial education in enriching family financial literacy.

Moving forward, our investigation extends to assessing whether financial education can effectively augment the influence of financial literacy on family entrepreneurial behavior. To address this inquiry, we construct an interaction term, denoted as Literacy × Learn, which captures the combined impact of financial education and financial literacy. This interaction term is incorporated into the analysis. Table 17 presents the estimated results. Irrespective of the method employed to measure financial literacy, the estimated coefficient of Literacy × Learn consistently displays a statistically significant positive association. This signifies that financial education effectively amplifies the impact of financial literacy on family entrepreneurial behavior.

An intriguing discovery emerges from our analysis: the estimated marginal effect coefficient for the interaction terms of Literacy1 × Learn or Literacy2 × Learn is notably positive, surpassing the coefficient of financial literacy alone. This observation suggests a close relationship between the impact of financial literacy on entrepreneurial behavior and individuals’ exposure to financial education. Consequently, our study substantiates that financial education serves as a moderating variable in shaping the influence of financial literacy on residents’ entrepreneurial behavior, effectively augmenting its impact. In practical terms, nationwide financial education initiatives and inclusive activities led by the People’s Bank of China, in collaboration with other financial institutions, have yielded noteworthy results over time. However, the current lack of enthusiasm and initiative among residents toward learning may hinder their engagement with financial education programs. Yet, with the proliferation of financial education efforts, this apathy is expected to wane, paving the way for increased attention and participation in financial education and training endeavors.

Theoretical implications

Our study draws upon human capital theory and modern entrepreneurship theory to empirically analyze the present, long-term, and evolving effects of financial literacy on household entrepreneurial behaviors, utilizing data from the CHFS in 2015 and 2017. The findings reveal that financial literacy exerts immediate, persistent, and evolving positive effects on households’ engagement in entrepreneurial activities and their propensity towards entrepreneurship. Addressing the endogeneity of the regression model, the results from the two-stage regression analysis corroborate the primary regression findings. Heterogeneity analysis highlights significant disparities between urban and rural areas as well as gender differences in how financial literacy influences household entrepreneurial behavior. Moreover, this study validates three potential mechanisms: income, social network, and risk attitude channels. We observe that financial literacy significantly enhances household income, broadens social networks, and fosters improved risk attitudes. Furthermore, our analysis indicates that financial education reinforces the impact of financial literacy on entrepreneurial behavior. These research findings carry significant theoretical implications, enriching both human capital theory and modern entrepreneurship theory.

Practical implications

This research carries significant implications for policymakers and stakeholders alike. Firstly, governments should recognize the pivotal role of financial literacy and embark on comprehensive initiatives to promote it through various channels, including television programs, radio broadcasts, informational brochures, training sessions, and specialized lectures. Establishing a sustained mechanism for the dissemination of financial literacy is crucial for enhancing the financial acumen of our nation’s populace. Secondly, special emphasis should be placed on promoting financial literacy in rural areas and among women. Collaborative efforts with financial institutions can facilitate targeted and tailored financial education projects aimed at these demographics, thereby fostering inclusivity and empowerment. By addressing the disparities in financial literacy, governments can pave the way for more equitable access to financial resources and opportunities. Thirdly, governments should actively promote financial education activities, including entrepreneurship training programs. These initiatives can mitigate the inhibitory effects of low financial literacy on entrepreneurial pursuits and enhance the management capabilities of entrepreneurs. By equipping individuals with the necessary skills and knowledge, such programs contribute to the resilience and dynamism of China’s financial market and stimulate growth in the employment landscape. In conclusion, concerted efforts to promote financial literacy and education are essential for advancing economic prosperity, fostering entrepreneurship, and ensuring inclusive development. By prioritizing these initiatives, policymakers can lay the foundation for a more resilient and prosperous future for China’s economy and society.

Future research and limitations

While our study has yielded significant insights, there are several avenues that merit further exploration in future research endeavors. Firstly, the complex relationship between cultural diversity and entrepreneurial behavior warrants deeper investigation. Unfortunately, due to the lack of detailed data on cultural diversity at the market segment level, this aspect remains largely unexplored in our study. Future research could delve into this aspect to better understand how cultural factors influence entrepreneurial decisions. Secondly, our analysis is constrained by the utilization of cross-sectional data from 2015 and 2017. Access to longitudinal data covering a broader timeframe could provide more nuanced insights and facilitate stronger conclusions. Therefore, future studies could benefit from employing larger datasets and extended panel data to comprehensively analyze the dynamics of the relationship between financial literacy and entrepreneurial behavior over time. Thirdly, the simplicity of the questionnaire used in our study may limit the depth of understanding regarding residents’ entrepreneurial behavior. Future research could address this limitation by employing more sophisticated questionnaires developed through an interdisciplinary approach, incorporating insights from psychology and other relevant fields. This holistic approach may offer a more nuanced understanding of residents’ entrepreneurial behavior, thereby enhancing the validity and reliability of the findings.

Furthermore, with the advent of the digital age, integrating elements of digitization or digital technology into academic research has become imperative. In our future research endeavors, we aim to expand our focus in several key areas. Firstly, we will explore the determinants of digital entrepreneurial behavior, examining how digital technologies influence entrepreneurial decisions and strategies. Secondly, we will emphasize the importance of digital financial literacy in shaping entrepreneurial behavior, considering how individuals’ proficiency in digital financial tools and platforms impacts their entrepreneurial activities. Lastly, we will endeavor to leverage digital technology to enhance causal identification in empirical analysis, employing innovative methodologies to better understand the mechanisms underlying the relationship between financial literacy and entrepreneurial behavior in the digital era.

Data availability

The datasets generated during and/or analyzed during the current study are available in the Harvard Dataverse repository: https://doi.org/10.7910/DVN/NRZ1K1 .

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Acknowledgements

We thank the support provided by the STU Scientific Research Initiation Grant [Grant No. STF24004T] and the National Natural Science Foundation of China [Grant No. 72203047].

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Xu, S., Jiang, K. Knowledge creates value: the role of financial literacy in entrepreneurial behavior. Humanit Soc Sci Commun 11 , 679 (2024). https://doi.org/10.1057/s41599-024-03201-3

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Financial literacy, financial advice, and financial behavior

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In this survey, we review the voluminous body of literature on the measurement and the determinants of financial literacy. Wherever possible, we supplement existing findings with recent descriptive evidence of German households’ financial literacy levels based on the novel Panel on Household Finances dataset, a large-scale survey administered by the Deutsche Bundesbank and representative of the financial situation of households in Germany. Prior research not only documents generally low levels of financial literacy but also finds large heterogeneity in financial literacy across the population, suggesting that economically vulnerable groups are placed at further disadvantage by their lack of financial knowledge. In addition, we assess the literature evaluating financial education as a means to improve financial literacy and financial behavior. Our survey suggests that the evidence with respect to the effectiveness of the programs is rather disappointing. We also review the role of individuals’ financial literacy for the use of professional financial advice and assess whether expert intervention can serve as a substitute to financial literacy. We conclude by discussing several directions for future research.

Does Financial Literacy Progress Over Time? An Analysis of Three Surveys in Italy

Financial Literacy and Financial Behavior: An Evidence of Linkage in Albanian Context

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1 Introduction

In recent years, consumers across the globe have taken on greater responsibility with regards to their personal financial well-being. Sweeping changes in the pension landscape have marked the principal catalyst for this increased autonomy of consumers by passing financial decisions including saving, investing, and decumulating wealth to employees and retirees. Where in the past, employees in many countries relied on social security and employer-sponsored defined benefit pension plans, with the increasing shift to defined-contribution pension plans, households are now being given greater control and responsibility over the long-term investments funding their retirement. At the same time, consumers have to find their bearings in a market characterized by a growing complexity which requires both a firm understanding of increasingly sophisticated products and the ability to judge the quality of guidance received about these products.

In Germany, this trend towards consumer autonomy has been further accelerated by two developments. First, the 2001 reform of the public pension system transformed a statutory pension scheme established at the foundation of the Federal Republic of Germany which had provided generations of retirees with sufficient funds into a system featuring multiple pillars of old-age provision. Specifically, this shift involved a substantial reduction of state-granted benefits and ever since requires employees to participate in state-subsidized pension plans (most prominently the so-called Riester plan) as well as occupational and private pension plans in order to fill the gap in retirement income. The second aspect relates to how German households have traditionally accumulated wealth: large parts of the population predominantly rely on savings deposits and thus forego excess returns of equity investments. While this extreme risk aversion has always been a challenge to profitable asset management, the ongoing period of interest rates next to zero renders established savings patterns entirely ineffective and urges for new investment strategies to provide for retirement. Taken together, these developments turn millions of German households into financial market participants, even though the vast majority have below-average experience as compared to individual investors in other economies like, e.g., the U.S. with a long-term equity culture.

Against this background, a natural question to ask is whether today’s households are well-equipped to successfully manage their personal financial affairs. In this review, we address this question and thereby focus on consumers’ financial literacy, i.e. their knowledge of key financial concepts as well as their ability to apply this knowledge to make informed financial decisions. Footnote 1

To preview the evidence provided by some of the studies we survey in greater detail in subsequent sections of the paper, research not only documents generally low levels of financial literacy but also finds large heterogeneity in financial literacy across the population. For example, Bucher-Koenen and Lusardi ( 2011 ) assess financial literacy in Germany and provide evidence that knowledge of basic financial concepts is particularly low among women, the less educated, and those living in East Germany, hence suggesting that economically vulnerable groups are placed at further disadvantage by their lack of financial knowledge.

Moreover, low levels of financial literacy have been linked to suboptimal financial behavior likely to have long-term consequences. Hilgert et al. ( 2003 ) find that low literate individuals are generally less likely to engage in a wide range of recommended financial practices. More specifically, Bucher-Koenen ( 2011 ) finds that Riester participation is disproportionately low among those German households with the lowest levels of financial literacy, although this group is eligible for the relatively highest government subsidies (see, e.g., Coppola and Gasche 2011 ). In the U.S., Choi et al. ( 2011 ) investigate contributions to 401(k) plans by employees who are eligible for an employer match and find that a large fraction of these employees either do not participate at all or contribute less than the amount required to be granted the full employer match, thus foregoing matching contributions which cumulate to substantial losses over time. These and other findings in the literature have sparked public discussion pointing to a need for financial literacy in a world in which individuals now shoulder greater personal financial responsibility. Accordingly, the assessment of consumers’ financial competence as well as the effect of financial education initiatives on economic outcomes has attracted considerable attention in recent years and the academic literature on financial literacy is rapidly evolving.

We conducted an ad-hoc query using the Web of Science Footnote 2 and searched for the terms ‘financial literacy’ or ‘financial knowledge’ in the publication titles. Figure 1 reports the rapid increase in publications on the topic as of March 2016. Specifically, the first 3-year period from 2002 to 2004 featured an average of one publication per year whereas roughly 26 papers per year were published between 2013 and 2015. As can be also inferred from Fig. 1 , the increasing relevance of financial literacy becomes even more obvious when using citations generated by financial literacy publications as a benchmark. From 2004 to 2006, the Web of Science database counts no more than two citations per year while in the most recent 3-year period, i.e. 2013–2015, this number jumps to an annual average of 346 citations.

Number of and citations triggered by publications on financial literacy and financial knowledge, per year. Notes : This figure plots the number of studies with the terms “financial literacy” and “financial knowledge” in the title. Numbers stem from search quieries using the scientific citation index “Web of Science” which provides access to multiple databases that reference cross-disciplinary research. See Sect. 1 for further details

Table 1 lists the 20 most frequently cited publications we obtained from our Web of Science query. Interestingly, these top-cited papers are published in journals covering a broad array of disciplines in economics and business administration, including accounting, economics, economic psychology, finance, and marketing. The most important publication outlet is the Journal of Consumer Affairs , i.e. a marketing-related journal, which accounts for a total of eight publications in the top 20. Economics journals come second and the remaining disciplines close behind.

In this survey, we offer an assessment of the voluminous body of literature on the measurement and the determinants of financial literacy. In addition, we assess the literature dealing with the effectiveness of financial education when it comes to improving financial literacy and financial behavior. At this, we complement the excellent reviews provided by Hastings et al. ( 2013 ) and Lusardi and Mitchell ( 2014 ) along at least three different lines. First, while these surveys focus on U.S.-based evidence, we adopt a different perspective and instead put emphasis on what is known about financial literacy in Germany, since German consumers face financial decisions substantially different from those of U.S. their counterparts. Wherever possible, we supplement existing findings with recent descriptive evidence of German households’ financial literacy levels based on the novel Panel on Household Finances (PHF) dataset, a large-scale survey administered by the Deutsche Bundesbank and representative of the financial situation of households in Germany. Footnote 3

Second, we review the role of individuals’ financial literacy for the use of professional financial advice. Recently, a lot of contributions have addressed the question whether financial advice may substitute for financial capabilities or if the two approaches to improve consumer financial decision making instead should rather be considered complements. One goal of this paper is to present a comprehensive survey of the literature contributions discussing this question which seeks to inform policymakers about the effectiveness of interventions regulating the supply side of financial products and services on the one hand versus enabling the demand side by means of financial education initiatives on the other hand.

Third, we aim at providing the reader with some of the tools necessary to contribute to the research on financial literacy. To this end, we describe different methodological approaches to proxy for individuals’ financial capabilities absent a direct measure of financial literacy. Moreover, we highlight potential endogeneity concerns when it comes to establishing cause-and-effect relationships as well as methodological approaches to address endogeneity in the context of financial literacy research. Finally, we supplement the literature review with a number of useful overviews over the host of different sources providing the raw data necessary to address relevant research questions.

While this review focuses on the empirics of financial literacy research, the body of literature on individuals’ financial knowledge and abilities also comprises important theoretical work (e.g. Delavande et al. 2008 ; Jappelli and Padula 2013 , 2015 ; Lusardi et al. 2013 ). Most of the theoretical contributions develop intertemporal consumption frameworks to model individuals’ decision to invest in financial literacy as well as its effect on households’ general savings and investment decisions, i.e. endogenizing their decision to invest in financial knowledge. Footnote 4

The remainder of the paper is structured as follows. Section 2 discusses conceptualizations of financial literacy and describes and assesses different approaches to measure it. In Sect. 3 , we review the evidence on financial literacy levels for various different economies around the world, while Sect. 4 surveys the literature on the determinants of financial literacy. Section 5 discusses the voluminous body of literature contributions investigating the link between financial literacy and financial behavior and addresses endogeneity concerns arising when capturing this connection. Section 6 reviews alternative approaches proposed to improve consumers’ financial behavior as well as an evaluation of their effectiveness. Section 7 concludes, draws policy implications, and suggests avenues for further research.

2 Measuring financial literacy

2.1 conceptual definitions.

How do consumers perform when it comes to managing their personal finances? Clearly, assessing the role of financial literacy as an input to effective financial decision making first of all requires a clear definition of financial literacy as well as a universal understanding of how it is conceptualized.

2.1.1 Definitions of financial literacy

The term financial literacy was introduced in the U.S. by the Jump$tart Coalition for Personal Financial Literacy in 1997, defining the concept as “the ability to use knowledge and skills to manage one’s financial resources effectively for lifetime financial security” . Later, also in the U.S., this characterization was adopted in a universal definition provided by the President’s Advisory Council on Financial Literacy (PACFL 2008 ). However, Hung et al. ( 2009 ), in their review of competing financial literacy concepts, find that the literature has proposed several definitions and lacks a universally accepted notion of what financial literacy really means. They document a large variety of conceptual definitions and show that each of them stresses different dimensions of financial literacy, i.e. actual and perceived knowledge of financial matters as well as the ability to apply that knowledge, but also individual financial experience and even sound financial behavior. In another extensive review of financial literacy operationalizations, Huston ( 2010 ) surveys 71 studies using 52 different data sets and corroborates that there is no such thing as a standardized conceptualization of financial literacy. 72% of studies did not even include an explicit definition. Moreover, there was no universally accepted meaning of financial literacy among those studies which did propose financial literacy definitions. Finally, the terms financial literacy and financial knowledge were used interchangeably by almost half of all studies under review. Like other standardized concepts of literacy such as computer literacy or health literacy, however, Huston ( 2010 ) stresses that “financial literacy should be conceptualized as having two dimensions — understanding (personal finance knowledge) and use (personal finance application)” (p. 306). A similar understanding is given in Hung et al. ( 2009 ), who consolidate the various definitions they review and propose an overarching conceptualization specifying financial literacy as the “knowledge of basic economic and financial concepts, as well as the ability to use that knowledge and other financial skills to manage financial resources effectively for a lifetime of financial well - being” (p. 12). A recent definition employed in the 2012 Program for International Student Assessment (PISA) has been provided by the Organization for Economic Cooperation and Development (OECD 2014 ) and includes both the knowledge and the application domain: “Financial literacy is knowledge and understanding of financial concepts and risks, and the skills, motivation and confidence to apply such knowledge and understanding in order to make effective decisions across a range of financial contexts, to improve the financial well - being of individuals and society, and to enable participation in economic life” (p. 33).

2.1.2 Cognitive abilities versus financial literacy

There is an ongoing debate as to how financial literacy is distinct from related concepts like numeracy and cognitive abilities. Hastings et al. ( 2013 ) document that respondents with higher cognitive abilities and more comfortable with numerical calculations on average exhibit higher levels of financial literacy. They also review a number of studies which find a positive relationship between cognitive abilities and numeracy on the one hand and sound financial behavior on the other hand (e.g., Banks and Oldfield 2007 ; Grinblatt et al. 2009 ; Christelis et al. 2010 ). Thus, Hung et al. ( 2009 ) argue that, for designing effective programs to improve financial literacy, it is important to differentiate general cognitive abilities from core aspects of financial literacy. Footnote 5 Lusardi et al. ( 2010 ) address this point of criticism by analyzing both a measure of financial literacy and a proxy for cognitive ability obtained from the National Longitudinal Survey of Youth (NLSY). On the one hand, the authors confirm a positive correlation between financial literacy and cognitive ability. However, they also show that cognitive factors cannot account for the entire variation in measured financial literacy levels, thereby leaving room for other dimensions of financial literacy.

2.2 Test-based measures of financial literacy

In their review of financial literacy measures used in 18 different studies, Hung et al. ( 2009 ) document that test-based or performance-based approaches have become prevalent in order to capture financial literacy. Test questions are usually drawn from household surveys and refer to knowledge of financial products (e.g., knowledge of stocks, bonds, mutual funds, or mortgages), knowledge of financial concepts (e.g., inflation, risk diversification, or the time value of money), and to general mathematical and numerical skills. The individual level of financial literacy of a given survey respondent is then obtained using different means of aggregating these questions. While some studies measure financial literacy using simple indicator variables (Jappelli 2010 ; Gathergood 2012 ), several other authors rely on more advanced techniques such as principal component analysis (e.g. Behrmann et al. 2012 ; Klapper et al. 2013 ; Lusardi et al. 2014 ), iterated principal factor analysis (e.g. van Rooij et al. 2011b ), or cluster analysis (e.g. Lusardi and Tufano 2015 ). Yet, results regarding the relationship of financial literacy with financial behavior have been shown to be largely robust to the technique applied to condense the underlying questions.

2.2.1 The Big Three

Hung et al. ( 2009 ) show that the various test-based measures they review are generally highly correlated with each other and when the questions are worded identically, answers feature high test–retest reliability across different survey waves. Thus, in the following, we will focus on three specific test questions introduced by Lusardi and Mitchell ( 2008 ) in a special module of the 2004 Health and Retirement Study (HRS). Footnote 6 These questions have been widely adopted in the U.S. and elsewhere and have become known as the Big Three . Footnote 7 The first one of this parsimonious set of questions addresses individuals’ numeracy and their ability to do simple calculations and is worded as follows Footnote 8 :

Suppose you had $100 in a savings account and the interest rate was 2% per year. After 5 years, how much do you think you would have in the account if you left the money to grow: [ more than $102 ; exactly $102; less than $102; do not know; refuse to answer.]

The second question refers to inflation and money illusion:

Imagine that the interest rate on your savings account was 1% per year and inflation was 2% per year. After 1 year, would you be able to buy: [more than, exactly the same as, or less than today with the money in this account; do not know; refuse to answer.]

Finally, the third question tests if respondents are familiar with the concept of risk diversification:

Do you think that the following statement is true or false? ‘Buying a single company stock usually provides a safer return than a stock mutual fund.’ [true; false ; do not know; refuse to answer.]

Although the Big Three generally do not demand advanced financial knowledge, only 34% of respondents in the original survey were able to answer all three questions correctly (Lusardi and Mitchell 2014 ). Straightforwardly, individuals who fail to correctly answer the first two questions will likely experience difficulties when facing even basic financial decisions characterized by an investment today and returns in the future. Providing the correct answer to the third question requires some knowledge about stocks and stock mutual funds as well as about the concept of risk diversification and thus indicates if respondents are able to effectively manage their financial assets.

2.2.2 Beyond the Big Three

In subsequent analyses, surveys were extended by additional questions beyond the Big Three so as to capture other dimensions of financial literacy. Specifically, Lusardi and Mitchell added two more items measuring knowledge in asset pricing and mortgages to the 2009 National Financial Capability Study (NFCS). In a recent large scale survey of financial literacy levels in more than 140 national economies, Klapper et al. ( 2015 ) elicit four quiz questions closely related to the Big Three . Thereby, the survey addresses four fundamental concepts for financial decision-making: risk diversification Footnote 9 (related to the third question of the Big Three), inflation Footnote 10 (very similar to the second question of the Big Three ), numeracy Footnote 11 (new question, previously not included in the Big Three ) and compound interest Footnote 12 (an advancement of the first question of the Big Three as this question actually refers to the concept of interest compounding).

Recently, the OECD has adopted an even broader perspective on the measurement of financial literacy for the 2012 PISA assessment (OECD 2014 ). An expert group consisting of regulators, academics and practitioners from different countries designed questions in three dimensions: knowledge and understanding (content), approaches and mental strategies (processes) and financial situations (contexts), reflecting real-life situations of 15-year-old students. The assessment consists of 40 finance-related questions as well as questions in the areas of mathematics and reading abilities. Students were asked to analyze simple graphs, calculate interest rates or evaluate payment checks and invoices. Thus, the financial literacy measure designed for the PISA assessment differs from the Big Three along two dimensions. First, the questions asked cover a much larger array of financial issues and place emphasis on financial decisions faced by 15-year-old students. Second, due to a more extensive battery of questions, financial literacy levels elicited in the PISA assessment capture more nuances of knowledge and abilities related to personal finance matters.

2.2.3 Caveats of test-based financial literacy measures

Although test-based approaches towards measuring financial capabilities—most prominently the Big Three —have now become the international benchmark for the assessment of financial literacy, there is little evidence on whether this set of questions is indeed a superior approach to capturing financial literacy. Hastings et al. ( 2013 ) emphasize that it is generally unclear if questions are a suitable means for measuring financial capability and, if so, which questions lend themselves most effectively for identifying it. Specifically, the authors criticize that surveys eliciting financial literacy levels do not incentivize respondents to provide carefully considered answers reflecting their actual knowledge. Besides, study designs usually do not permit participants to tap into other sources of information in order to prepare their decisions. Yet, accessing the internet, talking to friends and family, or consulting with a financial advisor Footnote 13 are important channels of expertise used by many consumers to compensate for their individual lack of financial literacy when making real-life financial decisions. Ignoring them likely biases the observed impact of financial literacy on financial behavior.

Another shortcoming of test-based measures of financial literacy is their sensitivity to framing. Specifically, Lusardi and Mitchell ( 2011a , b ) and van Rooij et al. ( 2011b ) document that the answers of survey participants differ significantly based on the wording of the test questions. In fact, the percentage of correct answers doubled in the latter study when the wording for the third question of the Big Three was “ buying company stock usually provides a safer return than a stock mutual fund” as compared to phrasing the question reversely, i.e. “ buying a stock mutual fund usually provides a safer return than a company stock” . Hence, Lusardi and Mitchell ( 2014 ) conclude that some answers classified as “correct” might instead reflect simple guessing of respondents and highlight that measurement error might be an issue when eliciting financial ability based on test questions. Footnote 14

Finally, Meyer et al. ( 2015 ) document that the quality of data obtained from household surveys has declined in recent years. This development owes to increasing non-participation of households ( unit nonresponse ), a tendency of not answering certain questions ( item nonresponse ), and, finally, increased measurement error due to greater inaccuracy of the participating households when answering the survey questions. Although this trend is not limited to items related to financial literacy, it constitutes an additional issue regarding the reliability of recent surveys on financial literacy.

2.3 Self-assessed financial literacy

An alternative approach to eliciting financial literacy levels which has also become prevalent in the literature involves asking survey respondents for a self-assessment of their financial capabilities. The corresponding item is usually worded as follows (Lusardi and Mitchell 2014 , p. 11) Footnote 15 :

On a scale from 1 to 7, where 1 means very low and 7 means very high, how would you assess your overall financial knowledge?’

Comparing test-based and self-assessed financial literacy, the literature reveals that individuals tend to be overly confident about how much they really know (e.g., Agnew and Szykman 2005 ). Footnote 16 Given the far-reaching consequences of many financial decisions, this overconfidence might be a problem, especially in situations where individuals are not aware of this bias (Lusardi and Mitchell 2014 ). In particular, older people tend to have a high confidence in their financial literacy although they do rather poorly on the test questions as well as with respect to their actual financial behavior (Lusardi and Tufano 2015 ; Lusardi and Mitchell 2011a , c ; Gamble et al. 2015 ). In a cross-country study including American, Dutch, and German households, Bucher-Koenen et al. ( 2016 ) recently document gender differences not only in test-based but also in self-reported levels of financial literacy. Specifically, women are less likely to respond correctly to the Big Three and also assign themselves lower scores than men, i.e. suggesting overconfidence in financial capabilities which seems especially pronounced among males. In another recent study for Germany, Bannier and Neubert ( 2016a ) corroborate the gender gap in confidence regarding financial literacy. Analyzing data drawn from the SAVE survey Footnote 17 they show that, while men are generally overconfident with respect to their financial knowledge, women instead tend to be under confident. Finally, recent contributions on self-assessed versus test-based measures discuss whether or not high levels of confidence in one’s own financial knowledge may be beneficiary for individuals. While Lusardi and Mitchell ( 2014 ) highlight the problems associated with overconfidence, Bannier and Neubert ( 2016a ) document a positive correlation between overconfidence and investment performance for the group of highly-educated men. Footnote 18

An interesting question is how test-based and self-assessed levels of financial literacy relate to each other. Indeed, the literature finds that self-assessed financial literacy and observed financial behavior do not always correlate strongly (Collins et al. 2009 ; Hastings and Mitchell 2011 ). Agnew and Szykman ( 2005 ), for instance, document a median correlation of 0.49 between actual and self-assessed financial literacy scores, a finding which is qualitatively corroborated in Lusardi and Mitchell ( 2009 ) and Parker et al. ( 2012 ). Moreover, both types of measures have been shown to be individually associated with financial decisions (e.g., Hastings et al. 2013 ; Asaad 2015 ; Allgood and Walstad 2016 ). Specifically, Parker et al. ( 2012 ) show that both self-reported and test-based financial literacy are predictive for retirement planning and savings. Likewise, van Rooij et al. ( 2011b ) find that both self-assessed and objectively measured financial literacy predict individuals’ propensity to hold stocks. Bannier and Neubert ( 2016b ) extend this research by showing that self-assessed financial knowledge associates with riskier investments (in discount certificates, hedge funds), while objectively measured financial literacy correlates strongly with less risky standard investments (in stocks, mutual funds, or real estate trusts). Moreover, the authors observe a gender gap in that this difference in risk taking based on individuals’ own perception of their financial abilities is more pronounced for women. In a recent study, Allgood and Walstad ( 2016 ) use a combined measure of test-based and self-assessed financial literacy and find that both financial literacy measures appear to independently correlate with financial behavior, leading them to conclude that self-assessed financial literacy may be as important as test-based financial literacy in explaining financial outcomes. Finally, Kramer ( 2014 ) and von Gaudecker ( 2015 ) compare individuals’ test-based financial literacy levels with how financially literate they perceive themselves and suggest a role for overconfidence which reduces individuals’ propensity to demand professional financial advice (see Sect. 6.2 ).

2.4 Proxies for financial literacy

2.4.1 socio-demographic proxies.

Absent a survey-based measure of financial literacy, a number of studies have turned to different proxies for subjects’ financial literacy levels. Given the robust correlations between several socio-demographic characteristics and measured financial literacy (see Sect. 4.1 ), several contributions lacking an observable measure of financial capabilities exploit this evidence and use respondents’ demographics in order to capture their financial literacy. Corresponding proxies for financial sophistication used in the literature include (disposable) income and wealth (Dhar and Zhu 2006 ; Vissing-Jorgensen 2003 ; Calvet et al. 2007 , 2009 ) as well as age (Calvet et al. 2007 , 2009 ; Georgarakos and Pasini 2011 ), educational attainment (Christiansen et al. 2008 ; Calvet et al. 2007 , 2009 ), professional status (Calvet et al. 2009 ), and even IQ (Grinblatt et al. 2011 , 2012 ). Likewise, both Chalmers and Reuter ( 2012 ) and Hackethal et al. ( 2012 ) use subsets of these demographics to proxy for financial literacy in their analyses.

A methodologically advanced approach to infer a demographics-based proxy of financial literacy recently applied in Stolper ( 2016 ) combines individuals’ demographic characteristics as well as directly measured levels of financial literacy by drawing on two different datasets each of which contains an identical set of demographics for a given cohort. The difference between the two datasets, however, is that only one of them contains the explanatory variable of interest, i.e. a direct measure of financial literacy, while the other features the financial outcome of interest but lacks a financial literacy measure. To overcome this data limitation, the author resorts to the imputation method proposed by Browning and Leth-Petersen ( 2003 ) and designed to link datasets featuring the above-mentioned properties. Following Graham et al. ( 2009 ) and Korniotis and Kumar ( 2013 ), who apply this approach to infer individuals’ perceived competence and smartness, respectively, the author proceeds in two steps to obtain a demographics-based financial literacy variable. First, he estimates an empirical model of financial literacy using the first wave of the PHF survey which contains both a direct measure of financial literacy and several of the demographic characteristics that have been shown to explain a significant proportion of the cross-sectional variation in people’s financial literacy levels (see Sect. 4.1 ). In a second step, the author then employs this model to predict the financial literacy levels of the households sampled in the primary dataset which only contains the respective demographics. Specifically, he uses the coefficient estimates obtained from the PHF-based model and plugs in the relevant demographic characteristics available in the primary dataset in order to construct a variable capturing predicted financial literacy.

2.4.2 Outcomes-based proxies

Given the drawbacks of test-based measures, some have proposed alternative approaches towards capturing financial literacy. Instead of surveying households, a natural way to infer financial literacy levels from other available information is to look at individuals’ readily observable financial behavior and use the quality of their financial decisions as a proxy for their financial literacy. Such outcomes-based proxies for financial literacy comprise observed risk diversification in equity portfolios (Goetzmann and Kumar 2008 ; Grinblatt and Keloharju 2001 ), prior investment experience (Goetzmann and Kumar 2008 ; Nicolosi et al. 2009 ; Seru et al. 2010 ), and the propensity to invest in complex financial instruments (Genesove and Mayer 2001 ; Goetzmann and Kumar 2008 ). Following this idea, Calvet et al. ( 2009 ) draw on the security accounts of a large-scale panel comprising 4.8 million Swedish households and construct an index of financial sophistication based on the sampled households’ (observable) ability to avoid poor financial decisions such as holding underdiversified portfolios, displaying inertia in risk taking, and exhibiting a disposition effect. Clearly, such an outcomes-based strategy crucially hinges on increased data availability. Nevertheless, as Hastings et al. ( 2013 ) point out, using consumers’ actual financial behavior as an indicator may be a more effective approach to predict future outcomes than the existing standard which, as described above, relies on more general proxies of financial literacy such as the Big Three .

3 Financial literacy around the world

Few studies lend themselves for an inclusion to a cross-country assessment of general financial literacy levels of consumers across different countries. Straightforwardly, a major data limitation is that we have to compare identical literacy measures that have been applied in studies carried out in many countries, ultimately leaving us with only few cross-country assessments.

3.1 Financial literacy of adult consumers

To qualify for inclusion, all studies under review with respect to financial literacy levels of adults must employ the original set of the Big Three or slight variations of it; Table 2 reports the corresponding results and provides supplementary descriptives obtained from the PHF survey. In what follows, we discuss these results in light of recent contributions to the literature as well as the various studies Hastings et al. ( 2013 ) and Lusardi and Mitchell ( 2014 ) review in their survey papers. Footnote 19

Table 2 is structured as follows. Panel A reports results for our analyses on the PHF survey. Subsequent panels document previous findings documented in the literature. Panel B (Panel C) displays results for upper-income countries (middle-income countries), Panel D provides evidence for lower-income countries, while Panel E refers to transition economies.

Generally, we document large cross-country variation in proficiency levels. As can be seen in Table 2 , the share of individuals answering all Big Three questions correctly amounts to 59% (based on the PHF data) and 53% (according to the SAVE data) of respondents. This implies that financial literacy levels documented for Germany range among the highest worldwide. Among respondents in the two transition economies Russia and Romania, by contrast, the respective numbers are as low as 4%. Moreover, while proficiency levels are relatively highest in upper-income countries (Panel B), absolute levels of financial literacy are still rather low in this group. The mean fraction of survey participants answering all Big Three questions correctly is 35% for these countries as compared to only 13% for middle-income countries (Panel C) and 4% for transition economies (Panel E). Footnote 20 When disaggregating the numbers at the level of the individual question, the tests that require knowledge about interest rates and inflation seem roughly equally difficult for survey participants. Specifically, the mean fraction of correct answers amounts to 63% for the question on interest rates and 60% for the question on inflation. Corroborating the evidence documented in the original study conducted by Lusardi and Mitchell ( 2008 ), the question on risk diversification appears to be the most difficult one. Here, on average only 46% of respondents were able to provide the correct answer.

Lusardi and Mitchell ( 2014 ) document that, despite their parsimonious design, the Big Three do a good job differentiating individual levels of financial capabilities in the population. Specifically, 34.3% of respondents of the 2004 HRS pioneer survey got all, 35.8% got two, 16.3% got one, and 9.9% got none of the questions right. Based on our evidence drawn from the German PHF data, we find that, by and large, this feature still holds. When focusing on the likelihood of answering either one of the three questions correctly, we find that 59.0% of respondents answered all Big Three questions correctly, while only 26.4% (10.0, 4.7%) got two (one, zero) questions right.

Recently, Klapper et al. ( 2015 ) provide a direct cross-country comparison of financial literacy levels by analyzing data from the Standard & Poors Ratings Services Global Financial Literacy Survey (S&P Global FinLit Survey) conducted in 2014. Footnote 21 In this survey, the four test questions introduced in Sect. 2.2 were added to the Gallup World Poll survey and answered by about 150,000 randomly selected adults (aged 15 and above) in 144 national economies either face-to-face or by telephone. The authors classify an individual as being financially literate if she answers at least three of the four test questions correctly. They also document a large heterogeneity across countries. Internationally, Australia, Canada, Denmark, Finland, Germany, Israel, the Netherlands, Norway, Sweden, and the United Kingdom host the most financially knowledgeable citizens: more than 65% of adults in these countries are classified as being financially literate. With a fraction of 71% literate citizens, Scandinavian countries lead the ranking. Germany follows suit (66%). By contrast, the percentage of financially literate adults turns out remarkably low for many countries in South America, Africa, and in South Asia. Generally, roughly only one in three adults is classified as financially literate in about half of the countries included in the survey. With a proportion of only roughly 13% financially literate adults, the Republic of Yemen as well as Afghanistan and Albania score lowest in this cross-country assessment of individual financial ability.

3.2 Financial literacy of adolescents

Unlike most other datasets discussed in this review, a comprehensive cross-country survey conducted on behalf of the OECD has recently assessed the financial capabilities of adolescents. Hence, this large-scale survey among 15-year old students administered by the OECD in 2012 extends the international evidence on financial literacy levels by studying the young, whose financial decisions are arguably most likely to have long-term consequences.

Figure 2 plots mean proficiency levels of more than 29,000 students, who are representative of as much as nine million 15-year olds in the 18 participating countries, Footnote 22 and reveals considerable variation in cross-country financial literacy levels among the young, as well.

Mean financial literacy scores, by country (PISA assessment 2012). Notes : This figure plots mean financial literacy proficiency levels of more than 29,000 students representative of as much as nine million 15-year-olds in the OECD economies Australia, Belgium (Flemish Community), Czech Republic, Estonia, France, Israel, Italy, New Zealand, Poland, Slovak Republic, Slovenia, Spain and the U.S. as well as the partner countries Colombia, Croatia, Latvia, Russia and Shanghai-China. See Sect. 3.2 for further details

As plotted in Fig. 2 , 16 out of the 18 countries under review feature financial literacy levels fairly close to the OECD normalized average of 500 points. In this group, the country-specific mean scores range between 466 (Italy) and 541 (Belgium). Footnote 23 Thus, for the vast majority of countries under review, average student proficiency levels are either in Level 2 (400 to less than 475 points) or in Level 3 (475 to less than 550 points). Importantly, the OECD defines Level 2 as an international benchmark for the lower bound of financial capabilities, i.e. marking the threshold between financial literate and financially illiterate individuals. Footnote 24 There are two outliers in this rather homogeneous picture. Students from Shanghai-China perform best with a mean score of 603, Columbian students perform poorest with a mean score of 379. Consequently, the average student from Columbia features Level 1-proficiency (326 to less than 400 points) and, according to the OECD classification, fails to meet the requirements necessary for basic financially literacy. Regarding the surveyed students’ individual proficiency, Lusardi ( 2015 ) documents that about 15% of students perform at or below Level 1-proficiency. Footnote 25

3.3 Overview of international data on financial literacy

Table 3 provides the reader with an up-to-date international overview of available surveys that have elicited financial literacy levels among their respective respondents. Panel A lists the available surveys for Germany, Panel B contains European household surveys and Panel C (Panel D) refers to surveys conducted in the U.S. (in other countries).

Besides reporting details on initiators and respondents of the different surveys, Table 3 also provides information about the test-based measurement approach applied (e.g. financial knowledge or cognition). Moreover, the table provides information on whether the Big Three questions were implemented Footnote 26 as well as if the survey has been completed in the past or features ongoing waves. Finally, we indicate whether the data obtained in the survey is publicly available for researchers.

4 Determinants of financial literacy

After having surveyed the evidence on how financial literacy is distributed across countries, we now turn to the question if there are common determinants related to peoples’ individual financial literacy levels.

4.1 Demographic characteristics

A robust finding across countries is that financial literacy levels are lowest among the young and the old (e.g., Lusardi and Mitchell 2011a , c ). Thus, we generally observe a hump-shaped distribution of financial literacy with respect to age. Low literacy among the young might be problematic since this group faces financial decisions that influence their (financial) well-being for decades to come. This is one reason why the OECD included a battery of financial literacy questions in the 2012 PISA assessment for 15-year old students as increasing financial literacy for this group seems to be particularly promising. Footnote 27 Low levels of financial literacy among the old is also problematic as individuals aged 60 and older hold about 50% of the wealth in the U.S. (Finke et al. 2016 ). With respect to cognitive changes associated with aging, Gamble et al. ( 2015 ) show that a decrease in episodic memory is associated with decreasing abilities in numeracy. In addition, a decrease in semantic memory associated with aging comes along with a decrease in financial knowledge. In consequence, a decrease in cognitive abilities is associated with decreasing financial literacy for the elderly. With respect to the magnitude of the effect of aging, Finke et al. ( 2016 ) find that financial literacy scores decline by about 1% a year for people older than 60. As already mentioned in Sect. 2.3 , there is a wide discrepancy between test-based and self-assessed financial literacy for the elderly as this group shows high levels of overconfidence: Gamble et al. ( 2015 ) and Finke et al. ( 2016 ) show that confidence in financial abilities does not decline with age, making the elderly particularly vulnerable to financial scams and fraud (Deevy et al. 2012 ). Analyzing the SAVE survey, Bucher-Koenen and Lusardi ( 2011 ) underscore this evidence for Germans. Specifically, they also document a hump-shaped distribution of financial literacy levels with respect to respondents’ age and find that the least financially literate are individuals aged 65 and above. Admittedly, however, the negative correlation between age and financial literacy documented in the above-mentioned studies might as well be interpreted as a cohort effect: for instance, older people arguably have less investing experience in the pre-401(k) era and the proportion of individuals with higher educational attainment is lower among older cohorts.

We draw on the PHF to investigate if this widely observed age-literacy-pattern continues to hold in a recent survey among German households and find that the hump-shaped relationship between respondents’ financial capabilities and their age is indeed corroborated in the PHF data. Specifically, people older than 65 score lowest, since only about 47% of this group are able to answer all Big Three tasks correctly. The second lowest percentage is documented for the group of people that are younger than 30 years old (58%). Ultimately, the cohort of Germans in their forties are found to be most financially literate (70%).

4.1.2 Gender

Another robust finding across many countries is a gender gap with respect to financial literacy (Lusardi and Mitchell 2009 ; Lusardi and Tufano 2009 , 2015 ; Lusardi et al. 2010 ; Hung et al. 2009 ; Mottola 2013 ; Bucher-Koenen et al. 2016 ; Agnew and Harrison 2015 , Klapper et al. 2015 ): men usually score higher on measured financial literacy than women. Two channels have been found to drive this result. On the one hand, women give fewer correct answers in test questions. Lusardi and Mitchell ( 2014 ), for instance, document that in the U.S. the fraction of men having all Big Three questions right is 38.3%, while the respective number for women is 22.5%. On the other hand, women seem less confident regarding their financial capabilities as they are more likely to choose the “do not know” category. According to Lusardi and Mitchell ( 2014 ) 50.0% of women in the U.S. indicate that they do not know the answer to at least one of the Big Three questions, while the respective fraction for men is 34.3%. A number of studies try to explain this finding arguing with traditional role models (Hsu 2011 ) suggesting that women only have an incentive to invest in financial literacy late in their lives (Fonseca et al. 2012 ), differing levels of confidence (Bucher-Koenen et al. 2016 ), and diverging interests in financial matters (Brown and Graf 2013 ). However, none of the approaches can entirely explain the gender gap, thus making the issue a promising avenue for further research.

Again, we use the PHF survey to investigate if the gender gap can be observed for recently collected German data, too. As can been seen in Fig. 3 b, we indeed observe a moderate, yet statistically significant gender gap in the PHF survey for Germany. The fraction of participants answering all Big Three questions correctly is 64% for male and 57% for female respondents, respectively. Note that previous evidence obtained from the 2009 wave of the SAVE survey (Bucher-Koenen and Lusardi 2011 ) documented a larger gender gap among German consumers. Specifically, the authors find that almost 60% of male respondents give correct answers to all Big Three questions as opposed to only roughly 48% of surveyed females.

Percentage providing correct answers to all Big Three questions, by demographic groups. a Financial literacy levels by age. b Financial literacy levels by gender. c Financial literacy levels by educational attainment. d Financial literacy levels by employment status. e Financial literacy levels by income. f Financial literacy levels by wealth. Notes : This figure plots the percentage of individuals surveyed in the first wave of the Panel on Household Finances (PHF) who have answered all Big Three questions correctly, sorted on respondents’ demographic characteristics (age, gender, educational attainment, employment status, income, wealth). See Sect. 4.1 for further details

4.1.3 Education

Furthermore, the majority of contributions to the literature document a positive correlation between formal education and financial literacy (Lusardi and Mitchell 2011c ; Christelis et al. 2010 ; Lusardi 2012 ). For example, Lusardi and Mitchell ( 2014 ) report that in the Netherlands 69.8% of individuals with a university degree answer all Big Three questions correctly, whereas among the least educated, the respective percentage amounts to only 28.0%. Of course, it is important to analyze whether the positive correlation might be driven by cognitive abilities of respondents rather than by formal education. However, few studies try to separate cognition from the effect of formal education. Lusardi et al. ( 2010 ), e.g., find that formal education is a relevant factor even after controlling for cognitive abilities.

Figure 3 c reports the evidence we draw from the PHF data and turns out consistent with the general finding that formal education correlates positively with financial literacy. Among those respondents featuring the highest educational attainment, an overwhelming majority of almost 90% manage to answer all Big Three questions correctly, whereas for the group of least educated individuals, the respective fraction comes to only 53%. Footnote 28 At this, the novel data we analyze broadly confirm earlier evidence for Germany provided by Bucher-Koenen and Lusardi ( 2011 ) who also document a positive relationship between education and financial literacy based on the SAVE survey.

4.1.4 Professional status, income, and wealth

Furthermore, the PHF survey collects information about participants’ professional status. Figure 3 d shows that the self-employed are significantly more likely to answer the Big Three questions correctly, a finding which has also been documented in Bucher-Koenen and Lusardi ( 2011 ). Finally, a number of contributions have found a positive association between individuals’ income and wealth levels and their levels of financial literacy (e.g., Hung et al. 2009 ; Lusardi and Tufano 2015 ; Lusardi and Mitchell 2011c ; Klapper et al. 2015 ). As can be seen in Fig. 3 e, f, we again confirm this finding for the PHF survey. With respect to income, 76% of the individuals in the highest income quintile managed to answer all Big Three questions correctly. The respective fraction for the lowest income quintile turns out significantly lower (50%). We find a similar result with respect to wealth; 73% of the individuals in the highest wealth quintile answer all Big Three questions correctly, whereas the respective fraction for the lowest wealth quintile is 51%. Footnote 29

4.2 Additional patterns

Recently, some contributions have examined the impact of peoples’ financial socialization on their financial literacy levels. For example, Grohmann et al. ( 2015 ) identify three potential channels of financial socialization: family, school and work and find that two of the three channels, i.e. family and school, indeed have a positive impact on the financial literacy of the adult subjects in their study. Regarding peoples’ family background, Lusardi et al. ( 2010 ) analyze financial literacy levels of young adults and relate them to the financial literacy levels observed for other members of the households in which they were raised. The authors document a positive correlation between financial literacy levels documented for the young adults and both financial literacy scores and educational attainment of their parents. Footnote 30 Moreover, financial behaviors of the respondents’ parents and their educational background are shown to independently influence financial literacy levels measured for their children. Finally, in a related study on the role of financial socialization, Lachance ( 2014 ) finds that even the educational attainment of respondents’ neighbors on average impacts their financial literacy levels.

5 The role of financial literacy for financial behavior

5.1 endogeneity concerns, 5.1.1 sources of endogeneity.

As mentioned above, the relevance of financial literacy crucially depends on its impact with regard to sound financial behavior. Consequently, a voluminous literature analyzes the question whether high levels of financial literacy trigger superior financial decision making. As we will review shortly, the majority of papers document a positive correlation between measures of financial literacy and sound financial behavior in various domains. Footnote 31 However, absent true randomized control experiments allowing for direct causal inference, the effect of financial literacy on the quality of individual financial decisions is difficult to pin down. Since most evidence on the impact of financial literacy stems from non-experimental research, endogeneity presents a pervasive issue which should be considered carefully when examining the role of financial literacy for financial outcomes. While endogeneity does not rule out the possibility that financial literacy improves individuals’ financial decision making per se , it complicates interpreting the magnitudes of the estimated effects as they are almost surely upwardly biased in magnitude (Hastings et al. 2013 ).

What causes endogeneity and how does it impact inference? Omitted variables are one of the three sources of endogeneity and refer to those explanatory variables that should be included in the model but in fact are not. If the positive correlation between financial literacy and good financial decisions observed in a given setting likely owes to some underlying third factor which contributes to both higher levels of financial literacy and better financial outcomes, endogeneity enters the model by way of one or more omitted variables. In statistical terms, the inability to explicitly include these determinants in the regression equation means that instead of appearing among the explanatory variables, the impact of these omitted variables appears in the error term, thus distorting estimators and making reliable inference virtually impossible.

Indeed, financial literacy might not be distributed randomly and those individuals exhibiting high levels of financial literacy might share certain characteristics like superior numerical abilities, intelligence, motivation to deal with personal finances, or patience. The literature documents several instances of such hard-to-capture factors likely to influence both financial literacy and financial behavior. Meier and Sprenger ( 2010 ) show that those who voluntarily participate in financial education programs are more future-oriented. Hastings and Mitchell ( 2011 ) find that those who show patience in an experiment also have a higher propensity to save additional amounts for retirement in their pension accounts. In the same vein, Bucher-Koenen and Lusardi ( 2011 ) hypothesize that there might exist an omitted variable bias stemming from missing information on individuals’ ability or motivation to deal with financial matters.

Additionally, a positive correlation between financial literacy and sound financial decision making could stem from reverse causality. Specifically, does financial literacy improve financial behavior or does being involved in certain financial activities instead lead to greater financial literacy? Again, the literature provides a number of examples of potential endogeneity due to a reverse causation channel. Disney et al. ( 2015 ) investigate the effect of financial literacy on the decision to seek credit counseling and argue that financial literacy may develop endogenously with the receipt of credit counseling. Bucher-Koenen and Lusardi ( 2011 ) hypothesize that individuals with higher levels of financial literacy might better recognize the need and the financial benefits of saving for retirement and thus be more inclined to enroll in a savings plan. They acknowledge, however, that it may as well be retirement planning which affects financial literacy rather than the other way around: Those who have planned for retirement have acquired some level of financial literacy simply by virtue of their savings plan participation. Likewise, the finding of Hilgert et al. ( 2003 ) that most individuals cite personal experience as the most important source of their financial learning suggests that some element of reverse causality is likely.

Finally, endogeneity may also arise from measurement error when it comes to the financial literacy variables, e.g. the possibility that answers to test-based financial literacy measures might not measure “true” financial knowledge. As mentioned above, Lusardi and Mitchell ( 2009 ), for instance, show that the Big Three are sensitive to framing, i.e. implying that some answers judged to be “correct” are likely attributable to guessing rather than skill.

5.1.2 Towards a causal interpretation of the effect of financial literacy on financial behavior

The standard approach to address endogeneity is finding an instrumental variable (IV) for the endogenous regressor and use this IV in a two-stage least squares (2SLS) regression in order to produce consistent parameter estimates. Generally, a clear understanding of the economics governing the question of interest is key to identifying a valid instrument. A good example of instrument choice is given in van Rooij et al. ( 2011b ) who document a positive relationship between stock market participation and financial literacy which is not only consistent with financially savvy investors having knowledge about expected excess returns of stocks, but also with shareholders learning from their investment experience. Footnote 32 To establish causality, the authors resort to IV estimation and instrument financial literacy with information regarding the personal finances of their siblings and parents, respectively. Specifically, they asked respondents whether the financial situation of their oldest sibling is either worse or the same or better than their own financial situation and also collected information on how they assess the level of financial knowledge of their parents. Why do these items make particularly good IVs? For one, these instruments for financial literacy are exogenous with respect to respondents’ stock market participation since, arguably, the financial experience of others is beyond their control. At the same time, however, respondents likely learn from their families, thereby increasing their own literacy. Footnote 33 Hence, the instruments affect the outcome (the respondent’s propensity to participate in the stock market) only via their effect on the endogenous variable (the respondent’s financial literacy level), i.e. satisfy both the relevance and the exclusion condition required to hold for a valid IV.

Observational studies using carefully chosen IVs are sometimes regarded as being equivalent to quasi experiments regarding their power to support causal claims (Angrist and Krueger 2001 ). However, a few general comments are in order when discussing the IV regression approach. First, since the error term is unobservable, one cannot empirically test the exclusion condition, i.e. whether or not an instrument is correlated with the regression error term. Consequently, there is no way to statistically ensure that an endogeneity problem has been solved. Moreover, Roberts and Whited ( 2013 ) stress that truly exogenous instruments are difficult to find and, in particular, that it should be rigorous economic arguments rather than formal falsification tests that eventually decide over the instrument’s validity.

5.1.3 Is there an endogeneity bias in the effect of financial literacy on financial behavior?

Evidence on the question of whether or not there is an endogeneity bias caused by omitted variables, reverse causality, or measurement error in studies examining links between measured financial literacy and financial behavior is rather inconsistent. In their review of 11 studies estimating both OLS and IV specifications from their data, Lusardi and Mitchell ( 2014 ) find that the IV financial literacy estimates always prove to be larger than the ordinary least squares estimates and conclude that, if anything, non-instrumented estimates of financial literacy underestimate the true effect. This evidence is a strong case for substantial measurement error biasing the OLS estimates, since the magnitude of the coefficients should be upwardly biased if omitted variables and reverse causality were the only sources of endogeneity. By contrast, Fernandes et al. ( 2014 ), who conduct a meta-analysis of the relationship between financial literacy and financial outcomes and—unlike Lusardi and Mitchell ( 2014 )—consider standardized coefficients, find significantly smaller effects for 24 studies using both instrumental variables and OLS estimation lacking those controls. They conjecture that non-instrumented regression models in fact overestimate the effect of financial literacy, which reflects endogeneity bias predominantly owing to omitted variables and reverse causality in the OLS designs. Additionally, they test the proposition that designs using instruments for financial literacy and 2SLS are similar to quasi experiments with regards to their ability to support causal inferences—in which case effect sizes should be comparable to what one finds in intervention studies that manipulate financial literacy by means of providing financial education to the treatment group. However, rejecting this claim, they find that intervention studies on average show much smaller effects than econometric studies with instrumental variables and question the validity of instruments used for financial literacy in the studies they review in their meta-analysis. Based on these findings, the authors conclude that past work supporting a causal role for financial literacy might need revisiting on methodological grounds.

Taken together, both the relevance of endogeneity concerns and the tools to remedy potential endogeneity bias are discussed rather controversially in the literature. Outside of controlled experiments, there is no way to ensure that endogeneity problems are eliminated or sufficiently mitigated to allow for reliable causal inferences. Thus, addressing endogeneity concerns by way of IVs should always rest on the strength of the researcher’s arguments supporting the identification strategy.

In what follows, we survey the literature on the impact of financial literacy on financial decision making in various different domains. While we will not explicitly discuss potential endogeneity concerns in the contributions under review, the reader should keep in mind that these issues might still apply.

5.2 Savings and investment decisions

5.2.1 retirement planning.

With respect to investment and savings decisions, arguably most research has been conducted on whether financial sophistication has a positive impact on retirement planning (e.g., Lusardi and Mitchell 2007 , 2008 ; van Rooij et al. 2011a ). Analyzing German survey data, Bucher-Koenen and Lusardi ( 2011 ) provide evidence for a strong correlation between financial literacy and retirement planning. Regarding the Big Three , the authors show that about 70% of the households who have planned for retirement give correct answers to all Big Three questions, whereas the respective fraction is only 54% for non-planners. Studies analyzing financial behavior in the U.S. also find that individuals with low levels of financial literacy are less likely to plan for their retirement (e.g., Lusardi and Mitchell 2007 , 2011b ). In a recent study, Clark et al. ( 2015 ), using a dataset that links administrative data on investment success with financial literacy, document a positive relationship between individuals’ financial literacy and their propensity to participate in a 401(k) plan as well as the profitability of the respective investments. A related strand of literature has also documented a positive relation between financial literacy and savings behavior (e.g., Lusardi and Mitchell 2011c ; Chan and Stevens 2008 ; Behrman et al. 2012 ), i.e. providing additional evidence that financially literate individuals exhibit a greater tendency to plan ahead.

5.2.2 Stock market participation

Another robust finding in the literature is a positive correlation between stock market participation and financial literacy (e.g., Kimball and Shumway 2006 ; Christelis et al. 2010 ; van Rooij et al. 2011b ; Balloch et al. 2015 ; Clark et al. 2015 ). Specifically, van Rooij et al. ( 2011b ) document that financial sophistication is positively related to stock market participation of retail investors in the Netherlands. Analyzing U.S. survey data, Yoong ( 2011 ) confirms that financially sophisticated individuals are more likely to hold stocks and mutual funds. In a related study among retail investors in the U.S., Balloch et al. ( 2015 ) find that, besides trust, stock market literacy positively correlates with their likelihood of stock market participation. In addition, they show a positive association between financial sophistication and the conditional magnitude of investing in stocks for those households who do hold stocks in their portfolios. Finally, Jappelli and Padula ( 2015 ) present an intertemporal choice model in which individuals can invest in financial literacy. Drawing on cross-country data, the authors find empirical support for the model’s main prediction, i.e. that stock market participation and financial literacy are positively correlated.

5.2.3 Investment choices

A related strand of literature analyzes the association between financial literacy and trading behavior (e.g., Feng and Seasholes 2005 ; Bilias et al. 2010 ; Hoffmann et al. 2013 ; Bucher-Koenen and Ziegelmeyer 2014 ; Guiso and Viviano 2015 ) and the corresponding studies generally document a positive impact of financial literacy as financially sophisticated investors tend to commit less investment mistakes. Footnote 34 In a recent contribution, Bucher-Koenen and Ziegelmeyer ( 2014 ) use the financial crisis as a natural experiment to examine individual investors’ ability to cope with sudden economic shocks and document that low literate households are significantly more likely to sell off assets that have lost in value, thereby making paper losses permanent. Shunning stock markets altogether is also associated with a decrease in expected returns on investments (Bucher-Koenen and Ziegelmeyer 2014 ). Other research in the field has documented that financial literacy is associated with smart choices when it comes to the selection of financial products. Müller and Weber ( 2010 ), for instance, investigate the role of financial literacy for mutual fund selection and show that financially sophisticated German retail investors pay lower front-end loads, are less biased in their past return estimates, and are more likely to correctly assess the risk profile of their fund investments. In a related laboratory study, Choi et al. ( 2009 ) show that many U.S. investors—even those with high self-assessed financial literacy levels—fail to choose a fee minimizing portfolio even in a setting where fees are the only relevant distinguishing characteristic of the investments and differences in fees are considerable. Moreover, a number of studies has documented a positive link between financial literacy and portfolio diversification: highly literate investors tend to manage their risks significantly better than the group of low literate individuals (e.g., Calvet et al. 2007 ; Goetzmann and Kumar 2008 ; Guiso and Jappelli 2008 ; von Gaudecker 2015 ; Clark et al. 2015 ).

5.2.4 Investment performance

The literature also documents a positive link between financial literacy and sound investment decisions. Calvet et al. ( 2007 , 2009 ) show for investors in Sweden a positive correlation between financial sophistication and account performance and conclude that richer and financially more sophisticated individuals invest more efficiently. Likewise, Clark et al. ( 2015 ) document a positive correlation between financial sophistication and excess stock returns among U.S. individuals, while von Gaudecker ( 2015 ) finds that this group of retail investors is more likely to hold well-diversified portfolios. Deuflhard et al. ( 2014 ) analyze interest rate levels for savings accounts of Dutch consumers. They find that financial literacy is positively associated with higher returns on these accounts. By contrast, Bodnaruk and Simonov ( 2015 ) provide evidence against the common finding of a positive relation between financial sophistication and investment performance. In particular, the authors have access to the private portfolios of Swedish mutual fund managers—arguably highly sophisticated market participants—and show that this unique group of individual investors neither outperform, nor diversify their risks more effectively as compared to similar investors in terms of age, gender, education, income, and wealth.

5.2.5 Additional evidence

Finally, the literature documents a positive role of financial capabilities in a variety of other domains. For example, Shen et al. ( 2016 ) document for Taiwan that individuals with higher levels of financial literacy are less likely to engage in financial disputes. Banks et al. ( 2015 ) find for the U.K. that financial literacy and numeracy are significantly positively related to individuals’ propensity to shop around for an annuity when receiving funds from their defined contribution pensions. In an early contribution to the literature, Hilgert et al. ( 2003 ) find a strong correlation between financial sophistication and day-to-day financial management skills such as cash-flow and credit management. Finally, de Bassa Scheresberg ( 2013 ) documents a positive relation between consumers’ financial literacy and their individual likelihood to hold precautionary savings.

5.3 Financing decisions

5.3.1 high-cost borrowing.

Compared to the large body of literature linking financial literacy to saving and investment decisions, evidence on the role of consumers’ financial capabilities for their financing behavior is scarce. Not surprisingly, the literature typically documents a negative correlation between financial literacy and mistakes in financing decisions: the less financially literate individuals are, the more likely they are to make poor financing decisions. Most prominently, there is solid evidence that low levels of financial literacy are associated with high-cost borrowing and suboptimal mortgage choices (e.g., Moore 2003 ; Lusardi and Tufano 2015 ; Lusardi and de Bassa Scheresberg 2013 ; Disney and Gathergood 2013 ). Lusardi and Tufano ( 2015 ) show for the U.S. that individuals exhibiting low levels of financial literacy use high-cost borrowing and pay higher transaction costs and fees. Lusardi and de Bassa Scheresberg ( 2013 ) also examine high-cost borrowing in the U.S., including payday loans, pawn shops and auto title insurance. They also confirm that low literate individuals are substantially exposed to high-cost methods of borrowing. Disney and Gathergood ( 2013 ) confirm this finding for the U.K. by showing that low levels of financial literacy are associated with an excessive use of high-cost credit like payday loans or mail order catalogue debt.

5.3.2 Costly credit card practices and excessive debt accumulation

Other recent studies document that individuals with low levels of financial literacy are significantly less likely to use their credit cards efficiently (e.g., Lusardi and Tufano 2015 ; Mottola 2013 ; Allgood and Walstad 2013 ). Analyzing U.S. adults, Allgood and Walstad ( 2013 ) find a robust negative relation between financial literacy and costly credit card practices. The authors also show that the influence of self-assessed financial literacy on costly credit card practices is greater than that of test-based financial literacy, providing evidence that the two concepts are distinct from each other. Footnote 35 Analyzing the same dataset, Mottola ( 2013 ) also confirms that the financially literate respondents are less often found to exhibit costly credit card behaviors such as being charged a late fee for late payment or not paying down credit card debt in full. In addition, some studies show that a lack of financial literacy is associated with excessive debt accumulation (e.g., Stango and Zinman 2009 ; Lusardi and Tufano 2015 ). Analyzing U.S. consumers, Lusardi and Tufano ( 2015 ) show that the least sophisticated with respect to debt literacy are exposed to excessive debt loads and the authors also find that this group is not able to judge their debt positions. Finally, Gerardi et al. ( 2013 ) find that numerical abilities—a skill set which is positively associated with financial sophistication—are strongly negatively correlated with mortgage defaults.

6 Towards improved financial decision making

6.1 financial education, 6.1.1 the case for financial education.

The arguments in favor of financial education are straightforward. Common sense suggests that introducing financial education initiatives will increase financial literacy, and improved financial literacy, in turn, relates to better financial decision making (Alsemgeest 2015 ). Accordingly, governments around the world have identified financial education as an intuitive remedy in order to help individuals mastering their personal financial affairs (Fernandes et al. 2014 ; Willis 2011 ). For example, policy makers in the U.S. have embraced financial literacy as a means to avoid poor financial decision making and launched a number of financial education initiatives in the wake of the financial crisis. Most prominently, the Office for Financial Education, a subdivision of the Consumer Financial Protection Bureau (CFPB) which was established in the wake of the financial crisis, has an explicit mandate to develop a strategy to increase the financial literacy of U.S. consumers as well as to make recommendations for the launch of programs to improve financial education outcomes.

Although great effort is put in financial education, the question whether educating individuals in the financial domain is beneficial remains controversial both from a theoretical and an empirical perspective. Accordingly, Willis ( 2008 , 2011 ) provides a number of arguments against financial education. First, she questions whether financial literacy programs can improve consumers’ financial knowledge to an extent that truly qualifies them for the complexity of novel financial products. In particular, she suggests that “the predicate belief in the effectiveness of financial literacy education lacks empirical support. Moreover, the belief is implausible, given the velocity of change in the financial marketplace, the gulf between current consumer skills and those needed to understand today’s complex nonstandardized financial products, the persistence of biases in financial decision making, and the disparity between educators and financial - services firms in resources with which to reach consumers.” (p. 197). Second, she is concerned that individuals’ perceived confidence might increase due to financial education while their actual abilities have not significantly improved which might lead to even poorer financial decision making. Third, she suspects financial education to weaken the position of consumers as related initiatives might come along with a “regulation-through-education model” which blames individuals for bad financial outcomes and thus prevents effective market regulation (Willis 2008 ). Finally, she pledges for a division of labor as consumers usually do not serve as their own doctors and lawyers and, following this notion, should not serve as their own financial experts, either.

6.1.2 Selected financial education initiatives and the costs of financial education

Although the systematic conceptualization of financial literacy is a rather recent development, financial education programs have a long tradition, at least in the U.S. These programs have been initiated by either policymakers, the financial services industry, employees, or nonprofit organizations. Footnote 36 Hastings et al. ( 2013 ) report that financial education interventions in the U.S. date back as long as to the 1950s. Tang and Peter ( 2015 ) document that the number of U.S. states in which a personal finance course is required for high school graduation has risen from 13 in 2009 to 17 in 2013, thus highlighting the increased relevance of the topic. The authors also report that the financial services industry is very active in encouraging financial education as, e.g., 98% of U.S. community banks sponsor financial literacy programs and 72% provide an individual program for customers.

Table 4 provides a list of selected financial education programs and we include this list for scholars interested in researching specific programs with respect to their effectiveness. We compiled the list of initiatives by searching the literature on financial education programs and by searching the web for respective keywords. Since we cannot do justice to the large number of financial education programs initiated around the world, we focus on initiatives carried out in German-speaking countries (Panel A) and extend this sample by selected programs in other countries arguably most relevant for previous research on financial literacy (Panel B).

As can be inferred from the table, the initiatives differ in terms of the initiator (e.g. banks, endowments, supranational organizations), the target group (e.g. adults, teenagers, low-income individuals), the educational approach (e.g. in-class teaching or online courses), the intensity of the intervention, and, finally, whether the effectiveness of the respective program has received an academic evaluation.

In what follows, we will review the literature assessing the effectiveness of the different financial education programs. Clearly, the implementation of such programs comes at a cost and, furthermore, their specific content might be biased by initiators’ incentives as well as political agendas. With regard to costs, Fernandes et al. ( 2014 ) highlight that educational interventions are not only associated with real costs but might create much larger opportunity costs. Taking high school education as an example, introducing personal finance courses is most likely associated with replacing other important elective courses. With respect to politically differing views of the world, left-wing governments might want to implement other curricula as opposed to right-wing or market-liberal governments. As far as the financial education initiatives of the financial services industry are concerned, these programs will most likely omit important topics like, e.g., fees. So, these programs would hardly teach participants to buy index funds instead of actively managed funds although refraining from actively managed funds is generally regarded as good financial behavior.

6.1.3 The effectiveness of financial education programs

A voluminous literature evaluates the association of financial education and test-based financial literacy (e.g., Mandell 2008 ; Walstad et al. 2010 ; Heinberg et al. 2010 ; Lührmann et al. 2015 ) as well as financial behavior (e.g., Bernheim et al. 2001 ; Servon and Kaestner 2008 ; Clark et al. 2015 ; Lührmann et al. 2015 ). The literature usually approaches the topic as follows: A particular financial education intervention is analyzed with respect to its impact on measured financial literacy and—in most assessments—on financial behavior. One way to elicit potential changes in financial literacy levels involves measuring test-based literacy scores prior to educating subjects about the financial matters of interest and at some point in time after they have received the respective manipulation (e.g., Walstad et al. 2010 ). Alternatively, the financial literacy scores of a treatment and a control group are contrasted after a given educational intervention (e.g., Lührmann et al. 2015 ). The effectiveness of the programs is usually measured by tracking self-reported financial behavior of the participants which is elicited by means of a questionnaire (e.g., Lusardi and Mitchell 2007 ; Bell et al. 2009 ; Lührmann et al. 2015 ).

Fernandes et al. ( 2014 ) have recently conducted a meta-analysis in which they include the entire universe of published and unpublished studies on financial education interventions and standardize effect sizes reported in the original studies when aggregating the respective findings. Thus, the conclusions derived from this meta-analysis are arguably less prone to criticism on methodological grounds. The authors evaluate as much as 90 studies in which a financial education intervention has been examined and conclude that, on aggregate, financial education interventions explain no more than 0.1% of the variance in financial behavior. Moreover, they confirm prior findings showing that the already small effects of financial education initiatives tend to decline over time. Specifically, they show that even large interventions have only little impact when financial decisions are made 20 months or later after the subject has received a financial education unit. Taken together, Fernandes et al. ( 2014 ) confirm—on more solid empirical grounds—the conclusions drawn in earlier studies which survey the literature on financial education (Hastings et al. 2013 ; Hung et al. 2009 ), i.e. a lack of conclusive evidence as to whether a positive impact of financial education can be observed for consumers’ financial behavior. Recently, Lührmann et al. ( 2015 ) extend the literature by an assessment of the effectiveness of a financial education program carried out among German high school students ( My Finance Coach ) and generally find a positive impact of that intervention on students’ financial knowledge. With respect to financial behavior, the evidence depends on the different financial domains examined. While students participating in the program on average exhibit a higher propensity to suppress impulsive purchases, the authors do not find evidence of a significant increase with regard to savings.

6.1.4 Reasons for ineffectiveness and potential remedies

Fernandes et al. ( 2014 ) highlight that their findings should not be interpreted as evidence against the usefulness of financial education since a large number of financial education programs has never been evaluated and non-assessed initiatives obviously did not enter the sample. A number of reasons for the rather surprising finding of little effectiveness of educational interventions have been discussed in the literature. First, Fernandes et al. ( 2014 ) as well as Lusardi and Mitchell ( 2014 ), question the quality and motivation of teachers with respect to personal finance issues. As such, Way and Holden ( 2009 ), for example, find that less than 20% of high school teachers felt well prepared to teach personal finance topics. Moreover, individuals are heterogeneous in various dimensions. Lusardi and Mitchell ( 2013 ) show in a theoretical model that due to this heterogeneity, not everyone should change its behavior after receiving standardized financial training.

Moreover, while the average impact of financial education may be low, the literature has identified several circumstances in which an intervention might be promising. Lusardi and Mitchell ( 2014 ), in their review of related research, claim that financial education programs have to be targeted to specific groups in order to incorporate the heterogeneity of individuals. For example, the authors argue that females are ideal targets for specific financial literacy programs, since—other than the average male subject—they are aware of their low financial literacy levels. In their meta-analysis, Fernandes et al. ( 2014 ) have identified future directions for designing more successful programs. Specifically, they suggest that improving individuals’ soft skills—e.g. their confidence to be proactive and their willingness to take investment risks—is likely more promising than teaching financial knowledge about, e.g., compound interest. In addition, since the authors find that the effect of financial education declines over time, promising programs should be designed as just - in - time interventions tied to a particular decision. In a recent study, Goedde-Menke et al. ( 2017 ) even suggest that one potential explanation for why financial literacy programs are mostly ineffective is the very fact that being financially literate is typically equated with having specific financial knowledge rather than having a basic understanding of fundamental economic concepts. In their study among German adolescents, the authors document that basic economic skills beneficially relate to both individual debt attitudes and behaviors while financial literacy levels turn out to be insignificant. Accordingly, they conclude that a stronger consideration of fundamental economic concepts in financial literacy programs might be a fruitful way to increase their effectiveness.

6.2 Financial advice as a substitute for financial literacy?

6.2.1 financial advice versus financial education.

While financial education programs have enjoyed strong political support as a means to address poor financial decision-making, Willis ( 2011 ) stresses that, besides the fact that they are unable to turn everyone into a financial expert, this should not be the path to take for reasons of efficient division of labor alone (see Sect. 6.1 ). Thus, instead of trying to educate inexperienced individuals, an alternative way to enhance the quality of their decisions on a market for financial services and products characterized by a growing complexity might be to delegate the job by relying on the services offered by professional financial advisors. Footnote 37 Indeed, a large proportion of households seek expert advice when making financial decisions. Bluethgen et al. ( 2008 ) indicate that roughly 80% of individual investors in Germany turn to financial advisors for their investment decisions. In the U.S., 81% of the households investing in mutual funds, outside a retirement plan, rely on financial advice (ICI 2007 ), and 75% of them seek advice before conducting stock market or mutual fund transactions (Hung and Yoong 2010 ).

However, the potential benefits of financial advice hinge on two important conditions. First, the advice itself must be accurate, suitable, and consistent with the client’s goals. Whether financial expert intervention indeed benefits consumers remains controversial, though. While some studies concerned with household finance suggest that financial counseling can help individuals develop better financial practices and reduce their debt levels and delinquency rates (Collins and O’Rouke 2010 ; Agarwal et al. 2011 ), the evidence as to whether individuals’ investment decisions benefit from expert financial advice is rather mixed. It could be shown that professionally-managed portfolios are better diversified (Bluethgen et al. 2008 ; Gerhardt and Hackethal 2009 ) and exhibit weaker disposition effects (Shapira and Venezia 2001 ) than portfolios of self-directed retail investors. Yet, a number of contributions in the field find that advised accounts are on average associated with higher costs, lower returns and inferior risk-return tradeoffs (Bergstresser et al. 2009 ; Hackethal et al. 2012 ; Kramer 2012 ) and conclude that advisors do not add value through their investment recommendations when judged relative to passive investment benchmarks (Foerster et al. 2014 ). Also, while there is some consensus that advice can improve retail investor portfolio decisions if conflicts of interest are mitigated (Bhattacharya et al. 2012 ; Hung and Yoong 2010 ), a typical advisor’s incentive structure does in fact create a conflict of interest, leading advisors to reinforce biases of their clients instead of correcting them (Mullainathan et al. 2012 ) and tilt their recommendations towards costly transactions (Hoechle et al. 2015 ).

Notably, however, while the German government has done little to improve consumers’ financial literacy by means of financial education initiatives, addressing the supply-side issues of retail financial markets has been the top priority of German regulatory authorities in recent years. With respect to financial advice, for instance, regulators now require banks to ask their clients for their prior investment experience before advising them on risky financial products. Moreover, financial advisors are required to assess the risk propensity of their clients before they are allowed to provide them with recommendations. Additionally, banks are obliged to provide advisees with product information sheets disclosing arguably decision-relevant characteristics of financial products. Finally, regulators require advisors to prepare a detailed transcript of each client meeting which has to be authorized by the advisee. The rationale behind these regulations is that the reasons which prevent people from benefiting from financial advice are essentially rooted in the supply side and increasing access to neutral advice should solve the problem of poor financial decision-making. Similarly, regulatory authorities in the Netherlands and in the U.K. have recently enforced a new legislation prohibiting commissions for brokers and advisors altogether. Taken together, we state that regulators in Germany and elsewhere in the world have implemented a number of different measures banning incentives for biased financial advice. In what follows, we thus do not focus on potential conflicts of interest with respect to financial advice.

6.2.2 Financial literacy and the demand for financial advice

A second condition which must hold for professional financial advice to be able to substitute for financial literacy, is that low literate individuals must of course seek the support of professional advisors in the first place. Otherwise, measures imposed by regulators to protect consumers arguably will not benefit those who need them most. Thus, knowledge about how financial literacy relates to the demand for financial advice has recently received increasing attention among academics and policymakers.

The notion that financial advice can substitute for low levels of financial literacy rests on the assumption that less knowledgeable individuals face higher hurdles with regards to the collection and processing of information and thus save more on information and search costs when turning to an advisor. Moreover, low literate households may be less aware of potential conflicts of interest arising from advisors’ typical incentive structures and hence more willing to assign an advisor with planning their personal finances (Inderst and Ottaviani 2009 ). Georgarakos and Inderst ( 2011 ) sketch an analytical framework of individual behavior in the context of financial advice using a “cheap-talk”-game in which uninformed investors must decide whether or not to trust the advice they receive whereas informed advisors can opt to ignore the advice. Thus, in their model, consumer information and financial advice are substitutes. Using a large-scale survey among households in 15 EU countries, the authors empirically confirm that trust only matters for the less literate consumers. Similarly, Disney et al. ( 2015 ) recently analyze the decision of indebted consumers in the U.K. to ask for financial advice in the form of credit counseling and conclude that professional counseling substitutes for financial literacy: answering an additional financial literacy question correctly reduces the likelihood of an individual seeking assistance by roughly 60%. As can be seen from Table 5 , which provides a summary of the empirical evidence regarding the link between financial literacy and advice-seeking, other studies also provide evidence pointing to a negative relationship between financial literacy and the demand for expert financial advice. In the U.S., Hung and Yoong ( 2010 ) conduct an experiment among defined-contribution plan holders in the RAND American Life Panel and show that the least sophisticated were most likely to take advice, and Chalmers and Reuter ( 2012 ), applying a demographics-based financial literacy proxy, find that younger, less highly educated, and less well-paid (i.e. on average less financially sophisticated) university employees are more likely to demand financial advice on defined-contribution retirement planning.

However, a growing number of studies in the field challenge the negative relationship between peoples’ knowledge in financial matters and their propensity to seek expert assistance and instead point to a complementarity between financial literacy and financial advice. Bucher-Koenen and Koenen ( 2015 ) present a model in which advisors have an incentive to provide better advice to consumers who they perceive to be better informed, thus pointing to the fact that financial literacy and the quality of financial advice are complements rather than substitutes. In their analytical framework, it is assumed that advisees with better financial knowledge more likely understand the advice they obtain. This in turn provides the advisor with more incentives to develop sound recommendations for the financially sophisticated investors. Drawing on the 2008 and 2009 waves of the German SAVE household survey, the authors find that smarter investors indeed receive better advice, thus confirming their model predictions. In a related study, Bhattacharya et al. ( 2012 ) find that those customers of a German online broker who opted to obtain financial advice in a field study were among the most financially literate clients, and Hackethal et al. ( 2012 ) show that advisors of a large German retail bank are matched with wealthier and older investors (proxied to be more financially sophisticated), which also points to a complementarity of financial literacy and financial advice. The authors interpret their findings with respect to both the demand-side and the supply-side of advice. On the one hand, higher opportunity costs of time may induce wealthier clients to make use of financial advice, although they are relatively better prepared to perform the task themselves. On the other hand, financial advisors with commission-based compensation systems should have an incentive to prefer clients with substantial amounts of assets who are more likely to generate significant trading fees.

Empirical evidence indicating that professional financial advice serves as a complement rather than a substitute for financial literacy is not limited to the German market, though. In the US, Collins ( 2012 ) uses data from the 2009 FINRA Financial Capability Survey and finds that individuals with higher incomes, higher educational attainment, and higher levels of financial literacy are most likely to receive financial advice. Similarly, Finke ( 2013 ) draws on the 2008 wave of the National Longitudinal Survey and documents that financial sophistication increases the demand for financial advice: those individuals most likely to seek advice are not those who are most prone to make financial mistakes. Corroborating this empirical evidence, van Rooij et al. ( 2011b ) exploit the Dutch Household Survey (DHS) and show that people who are less financially literate rely more on informal sources of financial advice, such as friends and family.

Finally, the finding that low literate individuals rely less on expert advice also ties in with psychological evidence, which challenges the notion that people are sophisticated enough to turn to advice in order to overcome their own lack of financial capability. By contrast, this literature suggests that individuals who do not know much about a subject tend not to recognize their ignorance and therefore typically fail to seek better information (Kruger and Dunning 1999 ).

6.2.3 Test-based versus self-assessed financial literacy and the role of overconfidence in seeking financial advice

In a recent contribution, Kramer ( 2014 ) suggests that the ambiguous results as to the role of financial knowledge for advice-seeking may at least partly be explained by the different approaches that have been employed to elicit financial literacy. He concludes that studies using self-assessed financial literacy typically find a negative relationship with demanding advice, while those that rely on test-based financial literacy report a positive or insignificant relationship. This discrepancy between the role of self-assessed versus test-based financial literacy implies a role for overconfidence as proposed in the model of Guiso and Jappelli ( 2006 ) in which overconfident investors are less willing to rely on information provided by financial advisors, banks or brokers and more likely to collect information directly because they perceive their self-collected information to be of better quality than it actually is. Using the DHS survey data, Kramer ( 2014 ) explicitly differentiates between self-reported and objectively elicited financial literacy and shows that confidence in one’s own knowledge is negatively related to asking for help, while actual expertise is not significantly associated with seeking professional financial advice. This finding is confirmed in another recent study based on the DHS data, which analyzes the role of financial literacy and financial advice for households’ portfolio diversification and does not find a significant association between financial literacy and the likelihood of turning to financial advice (von Gaudecker 2015 ). However, most losses from insufficient diversification are spotted among overconfident investors, which neither are financially literate nor consult with financial advisors.

6.2.4 How does financial literacy relate to the propensity to follow advice?

While seeking financial advice is an important step for the low literate in order to arrive at more informed decisions, one would also like to know if they choose to follow the advice they receive in order to properly assess the potential of professional advice as a substitute for financial literacy. Clearly, financial advice does not translate into sound financial decisions if individuals do not act on the recommendations of their advisors. Surprisingly, however, the question of whether advisees in fact implement the advice they receive is still largely unanswered and very few contributions have considered the role of financial literacy when it comes to following expert advice. The rightmost column of Table 5 summarizes the empirical evidence pertaining to this link.

Calcagno and Monticone ( 2015 ) present a stylized model of strategic interaction between advisees and better informed advisors with conflicts of interest. Unlike previous research, however, the authors allow for different degrees of interaction intensity ranging from consulting the advisor in order to enhance one’s information set to completely delegating all decisions to her. Consistent with the framework of Bucher-Koenen and Koenen ( 2015 ), the model predicts that the more financially sophisticated are more likely to consult with financial advisors because they anticipate that they will receive valuable information from their advisors. However, once low literate individuals decide to seek the help of financial experts, they are more likely to delegate the decision-making entirely to the advisor. Using data from a survey among the retail customers of Italy’s largest bank, the authors empirically confirm the model predictions showing that financial literacy indeed appears to play a role when it comes to how people implement the advice which they receive from their advisors.

Several studies drawing on German data corroborate the negative relationship between financial literacy and the propensity to follow financial advice. Hackethal et al. ( 2011 ), who study the trading behavior of advised retail clients using data from German brokerage accounts, find that they are less likely to implement the advice given to them when their financial sophistication is higher. Bucher-Koenen and Koenen ( 2015 ) also document a negative relationship between financial knowledge and advisees’ self-reported propensity to follow advisors’ recommendations. Finally, Stolper ( 2016 ) directly matches the recommendations of financial advisors at a German advisory firm with their clients’ post-advice account activity and find that the degree of following the advice is highest for those exhibiting the lowest levels of financial literacy.

6.2.5 Discussion

To rationalize the ambiguous impact of financial literacy on the use of financial advice, it is argued in the literature that financial sophistication carries two dimensions, i.e. the ability to understand advice on the one hand, and the literacy to question it as well as to process information privately (a possibility which Bucher-Koenen and Koenen 2015 , refer to as outside option ), on the other hand. While the skills to understand the advice increase the propensity of demanding it, the competence to challenge the advice, along with the ability to collect and handle private information, reduces the likelihood of following it. This is because the financially sophisticated advisee understands the advice and only opts to follow it if she prefers the recommendations to searching on her own, while she ignores it otherwise.

To conclude, the evidence on whether financial advice can be considered a substitute for financial literacy is inconsistent. While some studies document the required negative relationship between the two potential channels to improve financial decision-making, several studies challenge this view by showing that those who would benefit the most from advice are least likely to seek it. Once the advice has been obtained, however, recent contributions to the literature suggest that it is indeed the low literate who are most likely to follow it.

7 Conclusion

7.1 summary.

We review the literature on the rapidly evolving field of financial literacy. Interestingly, although the topic has become an important field in academia and also attracts the attention of policymakers around the globe, a universally accepted definition of the term has not yet been offered. Consequently, it comes to no surprise that there is no common operationalization, either. Instead, various measures for financial literacy have been developed, mostly based on a set of questions included in household surveys. Initially proposed as a starting point to measure financial literacy, Lusardi and Mitchell ( 2008 ) have developed a parsimonious set of three questions related to financial literacy which have now become known as the Big Three . By now, these questions have become the gold standard in measuring individuals’ financial knowledge and abilities and have been incorporated in many household surveys around the world, including the novel PHF survey for Germany.

Focusing on the empirical evidence regarding the Big Three questions, we document that the level of financial literacy is generally rather low and we also find substantial differences between national economies and demographic cohorts. In particular, financial literacy turns out to be considerably lower in transition economies and lower-income economies as compared to industrial economies, a finding which is also corroborated in the recently conducted Standard and Poors FinLit Survey (Klapper et al. 2015 ). According to Klapper et al. ( 2015 ) as well as our analyses of the data provided by the PHF survey, financial literacy levels of German citizens are among the highest in the world. However, even in Germany almost half of the survey participants are not able to answer all Big Three questions correctly, leaving room for substantial improvements of financial literacy. In addition, in Germany and elsewhere, the elderly and the young as well as the least educated and lowest-income individuals possess particularly low literacy levels. These groups have the highest propensity to commit financial mistakes. Thus, policy makers and interest groups around the world have put considerable effort in increasing peoples’ financial literacy. As becomes obvious from our review of the literature, however, the educational initiatives yielded rather disappointing results and apparently, their capability to improve the quality of financial behavior is limited. Thus, improving the effectiveness of the programs seems key in order to literate individuals to sufficient levels. We also review the current literature on financial advice, since financial advice might act as a substitute for financial literacy, thereby improving individuals’ financial decision making without treating them to extensive financial education programs. By and large, the corresponding evidence is inconclusive but promising if moral hazard issues leading to conflicts of interests in the advisor-advisee relationship can be effectively mitigated or even eliminated.

7.2 Directions for future research

In what follows, we would like to highlight a number of topics which—from our perspective—represent fruitful avenues for future research. First, the majority of research on financial literacy has been conducted with a geographic focus on the U.S. and there is far less evidence available for Europe, e.g. for Germany. Does this focus on the U.S. pose an issue to our knowledge about individuals’ financial literacy? We believe the answer is yes: financial decisions faced by U.S. citizens and German citizens, for instance, differ a great deal.

Specifically, one of the major financial issues pertaining to the asset side of a U.S. household’s balance sheet is the investment decision concerning 401(k) plans as part of a company pension scheme. How much should one contribute to the plan in order to maximize matching of the employer and how should the contributions be invested wisely across asset classes and financial products? In Germany, unlike in the U.S., decisions regarding defined contribution plans are much less relevant. On the one hand, the public pension system is still comparably generous and payments from corporate pension plans for retirees are of subordinate importance. On the other hand, plan participants in Germany usually do not have the discretion to determine the asset allocation of contributions. Thus, financial literacy is not as relevant when it comes to this decision. Although the designs of company pension schemes differ substantially between the two countries, a German household’s choice whether or not to participate in state-subsidized private pensions schemes (most prominently Riester plans) is comparable to decisions faced when dealing with 401(k) plans along several dimensions. Consequently, we encourage more research in the vein of Coppola and Gasche ( 2011 ) in the future.

From a German perspective, we currently see one additional major issue with respect to financial literacy and financial decision making that is rarely addressed in the literature, most probably because it is rather specific to Germans savers: due to a lack of knowledge and experience regarding stockholdings and equity mutual fund investments, an overwhelming majority of German households is still exclusively invested in savings products. Clearly, this investment strategy is quasi deterministically associated with a loss in household purchasing power in times of interest levels persistently close to zero. We believe that extending the conceptualization and measurement of financial literacy including knowledge about the long-run distributional characteristics of stock investment returns can be a promising avenue to increase the below-average willingness to participate in the stock market observed among Germans.

Turning the attention to the liability side of the household’s balance sheet, U.S. Americans and Germans also face very different challenges. While households in the U.S. were exposed to highly complex mortgage arrangements prior to the subprime crisis, plain vanilla debt contracts have been dominant in Germany ever since. In addition, issues like illiterate credit card use have typically been much less of an issue in Germany since credit card balances are charged against the cardholder’s bank account on a monthly basis. Thus, financial debt literacy appears less of an issue in Germany than in the U.S.

Recently, there has been notable progress in fostering research outside the U.S. The PHF survey, for instance, gives researchers the opportunity to relate financial literacy to various demographics as well as to a number of financial decisions of households. With the second wave of the PHF survey available for scientific use since April 2016, scholars are now able to conduct detailed analyses of households’ financial situation across subjects and over time. We are looking forward to interesting and novel insights concerning the relationship between financial literacy and financial behavior in the German context based on this rich dataset. For future cross-country analyses, it is crucial that survey data is elicited using a consistent methodological approach (e.g. identical selection and training criteria for interviewers) in all participating countries to ensure comparability of outcomes. The launch of the Eurosystem Household Finance and Consumption Survey (HFCS)—the German part of it covered via the PHF—marks a first step in this direction. Similarly, we embrace other cross-country initiatives such as the above-mentioned OECD initiative and S&P’s Finlit Survey both of which elicit consistent and readily comparable data across a number of different countries.

Although we observe a positive development with regard to cross-country household surveys, we have to acknowledge that research based on household surveys is anything but unproblematic. As Meyer et al. ( 2015 ) have shown, household surveys are subject to issues regarding the quality of data elicited. Related challenges affect both the measurement of financial literacy itself and the financial behavior captured in surveys on households’ financial situation. We believe that linking individuals’ financial literacy directly with their real-world financial decisions, as is done in Choi et al. ( 2011 ), Clark et al. ( 2015 ) and Stolper ( 2016 ), for instance, is a promising approach in order to enhance the quality of empirical results obtained in financial literacy research.

Finally, the research we review in this paper relates to the relevance of financial literacy in the context of household finance. Although financial mistakes associated with low financial literacy correlate with high costs for households, low levels of financial literacy might also be important in a business context. Footnote 38 Decision makers in blue-collar business, for instance, often are not especially knowledgeable in financial matters. Yet, they frequently make a range of finance-related decisions such as paying invoices in due time and aggregating costs for estimates they give. Of course, one could argue that individuals are less prone to financial mistakes if they act as professionals. However, the literature on behavioral biases has documented less severe but still significant investment mistakes conducted by, for instance, money managers (e.g., Kaustia et al. 2008 ). In this spirit, the research of Bodnaruk and Simonov ( 2015 ) is an interesting example for simultaneously analyzing individuals’ financial behavior in the private and in the professional domain. To us, it appears that financial literacy in the business context is an interesting and still largely under-researched subject: as can be inferred from Table 1 , 19 out of the 20 most cited papers focus on financial decisions of households, the only exception being McDaniel et al. ( 2002 ), who discuss financial literacy in the context of audit committees.

7.3 Policy recommendations

As far as policy recommendations are concerned, we propose a holistic approach. Based on the empirical evidence on individuals’ financial literacy level that we review in this paper, it seems important to pursue a policy mix that does not treat financial literacy and financial education separately but instead incorporates their interdependence with potential substitutes like financial advice, the implementation of an intelligent choice architecture and a thoughtful regulation concerning financial products offered to households. Indeed, this multi-dimensional approach is currently the way of choice in many countries. Moreover, even though evidence regarding the effectiveness of financial education programs with respect to financial decision making is at best mixed, we want to highlight the relevance of enabling citizens when it comes to financial matters. Prior to the financial crisis, many private (and professional) market participants bought products whose underlying mechanisms they did not understand, e.g. overly complex certificates or mortgage backed securities (MBS). Collectively, these financial products were dismissed as toxic or—quoting investment legend Warren Buffet—as “ weapons of mass destruction ”. However, financial innovations have served their goal to improve and facilitate financial products and services for the most part. In fact, functioning financial markets require peoples’ acceptance of financial innovations and sufficient knowledge and ability regarding financial matters is an indispensable foundation for this acceptance.

Section 2.1 of this paper provides details on the conceptualization of financial literacy.

The Web of Science (formerly known as Web of Knowledge ) is a scientific citation index maintained by Thomson Reuters which provides access to multiple databases that reference cross-disciplinary research and allows for in-depth exploration of specialized areas within an academic or scientific discipline.

See the Appendix to this paper for a detailed description of the PHF data.

For an excellent review of the theory of financial literacy, the reader is referred to Lusardi and Mitchell ( 2014 ).

For a comprehensive evaluation of initiatives to improve consumers’ financial literacy, see Sect. 6.1 .

The Health and Retirement Study (HRS) is a survey among U.S. households aged 50 and older. See Table 3 for details on the different surveys employed in the studies we review in this paper.

See Table 2 for a survey.

Correct answers are displayed in bold.

The first question reads: “Suppose you have some money. Is it safer to put your money into one business or investment, or to put your money into multiple businesses or investments?".

The wording of the second question is: “Suppose over the next 10 years the prices of the things you buy double. If your income also doubles, will you be able to buy less than you can buy today, the same as you can buy today, or more than you can buy today?”.

The third question reads: “Suppose you need to borrow 100 US dollars. Which is the lower amount to pay back: 105 US dollars or 100 US dollars plus three percent?”.

The wording of the fourth question is: “Suppose you put money in the bank for two years and the bank agrees to add 15% per year to your account. Will the bank add more money to your account the second year than it did the first year, or will it add the same amount of money both years?”.

For details regarding the impact of individuals’ financial literacy on their use of financial advice, see Sect. 6.2 .

See Sect. 5.1 for a detailed discussion of how measurement error affects inference.

Note that some studies use alternative concepts of self-assessed financial literacy, which, however, yield broadly comparable results. Specifically, Hastings et al. ( 2013 ) use the 2009 NFCS to compare three different measures of self-reported financial capability (self-assessed overall financial knowledge, self-assessed mathematical knowledge, and self-assessed capability at dealing with financial matters) for various demographic subgroups and find that the different constructs are all highly correlated with each other.

Exceptions to this behavioral trait are Japanese individuals (Sekita 2011 ).

Unlike in the DHS and SHARE surveys, replies in the PHF and SAVE datasets stem from one individual per household. As described in Bucher-Koenen and Lusardi ( 2011 ), SAVE draws on a randomly chosen household member who has information on the household’s finances . Thus, the individual completing the questionnaire is not necessarily the household head. Consistent with this approach, interviews in the PHF were conducted with financially knowledgeable persons familiar with the household’s financial situation (one per household), who again need not necessarily be the head of the surveyed household. Hence, owing to their largely similar elicitation modes, the PHF and SAVE data are to a great extent comparable regarding respondents’ answers.

At the same time, however, Bannier and Neubert ( 2016a ) find a negative association between female under confidence and financial planning outcomes, which turns out statistically significant for the subgroup of highly-educated women.

Note, however, that findings across the different studies are not always readily comparable, since the individual surveys naturally differ in terms of year of data, survey mode, and size of sampled cohort.

Note that mean values reported in this section are equally-weighted across the sampled studies.

In a related study, Japelli ( 2010 ) conducts a cross-country assessment of economic literacy in 55 countries based on the IMD World Competitive Yearbook (WCY). Note, however, that Japelli ( 2010 ) differs from the studies surveyed above in two respects. First, economic literacy is distinct from financial literacy. Second, he provides insights on literacy levels of senior business leaders, while our focus is on private households.

The analysis comprises the OECD economies Australia, Belgium (Flemish Community), Czech Republic, Estonia, France, Israel, Italy, New Zealand, Poland, Slovak Republic, Slovenia, Spain and the U.S. as well as the partner countries Colombia, Croatia, Latvia, Russia and Shanghai-China. Please note that Germany did not participate in this OECD study.

Note that in statistical terms, the differences between the country scores reported in Fig. 2 and the OECD average—with the exception of the U.S.—all turn out significant at all conventional levels.

For a detailed description of the different proficiency levels see Lusardi ( 2015 ).

Within the countries under review, the percentage of financially illiterate students range from 2% (Shanghai-China) to 56% (Columbia).

A complete list of questions raised in each household survey is available upon request.

See Sect. 6.1 for a detailed discussion of the costs and benefits of financial education initiatives.

Bannier and Neubert ( 2016a ), drawing on the SAVE data, show that the effect of formal education is strongest for women.

Note, however, that the literature has produced mixed results as to whether causality runs from wealth to financial literacy or rather the other way round. While Monticone ( 2010 ) documents that wealth has a positive (albeit small) effect on the degree of financial knowledge, wealth has been shown to be endogenous in other contributions. Van Rooij et al. ( 2012 ), e.g., provide evidence of a strong positive association between financial literacy and financial wealth and argue that it is financial literacy, which facilitates wealth accumulation. In a related study, Lusardi et al. ( 2013 ) develop a life-cycle model with endogenous financial knowledge accumulation and conclude that it explains a large proportion of wealth inequality.

The effect of childhood experience on financial behavior is also analyzed in Bucciol and Veronesi ( 2014 ) and Webley and Nyhus ( 2006 , 2013 ).

Intuitively, we have to agree on a definition of sound financial behavior in order to be able to interpret this relationship. Depending on the context, this proves a nontrivial task. While investing in the stock market, for instance, is generally considered smart, individuals with extreme levels of risk aversion or short-term liquidity needs might not be well-advised to do so. In what follows, however, we adopt the literature consensus and thus, e.g., classify index fund investments (as opposed to investments in actively managed mutual funds) as sound financial decisions.

For further examples of particularly strong instruments for financial literacy, see Lusardi and Mitchell ( 2014 ).

van Rooij et al. ( 2011b ) argue that the negative correlation between respondents’ financial literacy levels and the financial condition of their siblings and the financial knowledge of their parents, respectively, support the notion of a learning channel rather than the existence of family fixed effects. Note that the underlying assumption is that respondents learn from the negative experience of their family members.

In a related study, Koestner et al. ( 2017 ) identify investment experience as another potential channel to mitigate investment mistakes.

See Sect. 2.3 for a detailed discussion of this issue.

Collins ( 2012 ) surveys the role of nonprofit providers in financial education.

Yet another approach to support peoples’ financial decision making process exploits a robust finding in behavioral economics, i.e. that different formulations of otherwise identical choice options (so-called frames ) affect individuals’ behavior. Accordingly, a mindful framing of peoples’ decision environment (referred to as choice architecture ) may be an additional avenue towards improved financial behavior. Indeed, this approach is promoted by, e.g., Choi et al. ( 2004 ) and Thaler and Benartzi ( 2004 ) who find that opt-out regimes in 401(k) pension plans result in a large and persistent increase in pension participation rates relative to conventional opt-in arrangements.

Please note that the Kreditanstalt für Wiederaufbau (KfW) as of the 2014 wave inserted financial literacy questions into the Gründungsmonitor survey of entrepreneurs in Germany. In particular, the respondents have to self-assess their financial literacy as well as to answer the Big Three and three other questions on financial literacy.

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Acknowledgements

We gratefully acknowledge the comments of Christina Bannier and Wolfgang Breuer, the editors, as well as two anonymous referees. Moreover, we would like to thank Dennis Bär, Daniel Czaja, Lea Meyer and Tobias Meyll for excellent research assistance.

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Appendix: Panel on Household Finances (PHF): data description

We draw on novel survey data on household finance and wealth provided by the Deutsche Bundesbank in the Panel on Household Finances (PHF) which is representative of the German population. In the first wave of the PHF, face-to-face computer aided interviews were conducted between September 2010 and July 2011 with the financially knowledgeable persons (one per household) in a sample of 3565 households in total. Questions cover a wide range of items related to the household balance sheet including financial and non-financial assets as well as household debt. This information is then supplemented with demographic and psychological characteristics of the household members as well as a household-specific financial literacy score. The PHF features (a) survey weights to adjust for the oversampling of wealthy households during the data collection and (b) multiple imputations in order to mitigate the issue of missing data due to item non-response. We make use of the survey weights and the corresponding replicate weights to adjust point estimates as well as variance and standard error estimates in all our baseline analyses. Note that this correction of the sampling design does not materially affect our results (corresponding tables available upon request). Similarly, for the independent variables, we use the average of the five imputed values provided in the data. For robustness, we re-estimate our main model using multiple imputations via Rubin’s rule (Rubin 1996 ). Results remain virtually unchanged and are also available upon request.

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Stolper, O.A., Walter, A. Financial literacy, financial advice, and financial behavior. J Bus Econ 87 , 581–643 (2017). https://doi.org/10.1007/s11573-017-0853-9

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The Economic Importance of Financial Literacy: Theory and Evidence

Annamaria lusardi.

The George Washington University School of Business, Duques Hall, Suite 450E, Washington, DC 20052, Tel: (202) 994-8410

Olivia S. Mitchell

Department of Insurance & Risk Management, The Wharton School, Univ. of Pennsylvania, 3620 Locust Walk, St. 3000 SH-DH, Philadelphia, PA 19104, Tel: (215) 898-0424

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.

1. Introduction

Financial markets around the world have become increasingly accessible to the ‘small investor,’ as new products and financial services grow widespread. At the onset of the recent financial crisis, consumer credit and mortgage borrowing had burgeoned. People who had credit cards or subprime mortgages were in the historically unusual position of being able to decide how much they wanted to borrow. Alternative financial services, including payday loans, pawn shops, auto title loans, tax refund loans, and rent-to-own shops have also become widespread. 1 At the same time, changes in the pension landscape are increasingly thrusting responsibility for saving, investing, and decumulating wealth onto workers and retirees, whereas in the past, older workers relied mainly on Social Security and employer-sponsored defined benefit (DB) pension plans in retirement. Today, by contrast, Baby Boomers mainly have defined contribution (DC) plans and Individual Retirement Accounts (IRAs) during their working years. This trend toward disintermediation increasingly is requiring people to decide how much to save and where to invest, and during retirement, to take on responsibility for careful decumulation so as not to outlive their assets while meeting their needs. 2

Despite the rapid spread of such financially complex products to the retail marketplace, including student loans, mortgages, credit cards, pension accounts, and annuities, many of these have proven to be difficult for financially unsophisticated investors to master. 3 Therefore, while these developments have their advantages, they also impose on households a much greater responsibility to borrow, save, invest, and decumulate their assets sensibly by permitting tailored financial contracts and more people to access credit. Accordingly, one goal of this paper is to offer an assessment of how well-equipped today’s households are to make these complex financial decisions. Specifically we focus on financial literacy , by which we mean peoples’ ability to process economic information and make informed decisions about financial planning, wealth accumulation, debt, and pensions. In what follows, we outline recent theoretical research modeling how financial knowledge can be cast as a type of investment in human capital. In this framework, those who build financial savvy can earn above-average expected returns on their investments, yet there will still be some optimal level of financial ignorance. Endogenizing financial knowledge has important implications for welfare, and this perspective also offers insights into programs intended to enhance levels of financial knowledge in the larger population.

Another of our goals is to assess the effects of financial literacy on important economic behaviors. We do so by drawing on evidence about what people know and which groups are the least financially literate. Moreover, the literature allows us to tease out the impact of financial literacy on economic decision-making in the United States and abroad, along with the costs of financial ignorance. Because this is a new area of economic research, we conclude with thoughts on policies to help fill these gaps; we focus on what remains to be learned to better inform theoretical/empirical models and public policy.

2. A Theoretical Framework for Financial Literacy

The conventional microeconomic approach to saving and consumption decisions posits that a fully rational and well-informed individual will consume less than his income in times of high earnings, thus saving to support consumption when income falls (e.g. after retirement). Starting with Modigliani and Brumberg (1954) and Friedman (1957) , the consumer is posited to arrange his optimal saving and decumulation patterns to smooth marginal utility over his lifetime. Many studies have shown how such a life cycle optimization process can be shaped by consumer preferences (e.g. risk aversion and discount rates), the economic environment (e.g. risky returns on investments and liquidity constraints), and social safety net benefits (e.g. the availability and generosity of welfare schemes and Social Security benefits), among other features. 4

These microeconomic models generally assume that individuals can formulate and execute saving and spend-down plans, which requires them to have the capacity to undertake complex economic calculations and to have expertise in dealing with financial markets. As we show below in detail, however, few people seem to have much financial knowledge. Moreover, acquiring such knowledge is likely to come at a cost. In the past, when retirement pensions were designed and implemented by governments, individual workers devote very little attention to their plan details. Today, by contrast, since saving, investment, and decumulation for retirement are occurring in an increasingly personalized pension environment, the gaps between modeling and reality are worth exploring, so as to better evaluate where the theory can be enriched, and how policy efforts can be better targeted.

Though there is a substantial theoretical and empirical body of work on the economics of education, 5 far less attention has been devoted to the question of how people acquire and deploy financial literacy. In the last few years, however, a few papers have begun to examine the decision to acquire financial literacy and to study the links between financial knowledge, saving, and investment behavior ( Delavande, Rohwedder, and Willis 2008 ; Jappelli and Padula 2013 ; Hsu 2011 ; and Lusardi, Michaud, and Mitchell 2013 ). 6 For instance, Delavande, Rohwedder, and Willis (2008) present a simple two-period model of saving and portfolio allocation across safe bonds and risky stocks, allowing for the acquisition of human capital in the form of financial knowledge ( à la Ben-Porath, 1967 , and Becker, 1975 ). That work posits that individuals will optimally elect to invest in financial knowledge to gain access to higher-return assets: this training helps them identify better-performing assets and/or hire financial advisers who can reduce investment expenses. Hsu (2011) uses a similar approach in an intra-household setting where husbands specialize in the acquisition of financial knowledge, while wives increase their acquisition of financial knowledge mostly when it becomes relevant (such as prior to the death of their spouses). Jappelli and Padula (2013) also consider a two-period model but additionally sketch a multi-period life cycle model with financial literacy endogenously determined. They predict that financial literacy and wealth will be strongly correlated over the life cycle, with both rising until retirement and falling thereafter. They also suggest that in countries with generous Social Security benefits, there will be fewer incentives to save and accumulate wealth and, in turn, less reason to invest in financial literacy.

Each of these studies represents a useful theoretical advance, yet none incorporates key features now standard in theoretical models of saving – namely borrowing constraints, mortality risk, demographic factors, stock market returns, and earnings and health shocks. These shortcomings are rectified in recent work by Lusardi, Michaud, and Mitchell (2011 , 2013 ), which calibrates and simulates a multi-period dynamic life cycle model where individuals not only select capital market investments but also undertake investments in financial knowledge. This extension is important in that it permits the researchers to examine model implications for wealth inequality and welfare. Two distinct investment technologies are considered: the first is a simple technology which pays a fixed low rate of return each period ( R ¯ = 1 + r ¯ ) , similar to a bank account, while the second is a more sophisticated technology providing the consumer access to a higher stochastic expected return, R ∼ ( f t ) , which depends on his accumulated level of financial knowledge. Each period, the stock of knowledge is related to what the individual had in the previous period minus a depreciation factor: thus f t +1 = δ f t + i t , where δ represents knowledge depreciation (due to obsolescence or decay), and gross investment in knowledge is indicated with i t . The stochastic return from the sophisticated technology follows the process R ∼ ( f t + 1 ) = R ¯ + r ( f t + 1 ) + σ ε ε t + 1 (where ε t is a N(0,1) iid shock and σ ε refers to the standard deviation of returns on the sophisticated technology). To access this higher expected return, the consumer must pay both a direct cost (c), and a time and money cost ( π ) to build up knowledge. 7

Prior to retirement, the individual earns risky labor income ( y ) from which he can consume or invest so as to raise his return (R) on saving (s) by investing in the sophisticated technology. After retirement, the individual receives Social Security benefits which are a percentage of pre-retirement income. 8 Additional sources of uncertainty include stock returns, medical costs, and longevity. Each period, therefore, the consumer’s decision variables are how much to invest in the capital market, consume ( c ), and whether to invest in financial knowledge.

Assuming a discount rate of β and η o , η y , and ε which refer, respectively, to shocks in medical expenditures, labor earnings, and rate of return, the problem takes the form of a series of Bellman equations with the following value function V d ( s t ) at each age as long as the individual is alive ( p e , t > 0):

The utility function is assumed to be strictly concave in consumption and scaled using the function u ( c t / n t ) where n t is an equivalence scale capturing family size which changes predictably over the life cycle; and by education, subscripted by e . End-of-period assets ( a t +1 ) are equal to labor earnings plus the returns on the previous period’s saving plus transfer income (tr) , minus consumption and costs of investment in knowledge (as long as investments are positive; i.e., κ > 0. Accordingly, a t + 1 = R ∼ κ ( f t + 1 ) ( a t + y e , t + t r t − c t − π ( i t ) − c d I ( κ t > 0 ) ) 9 .

After calibrating the model using plausible parameter values, the authors then solve the value functions for consumers with low/medium/high educational levels by backward recursion. 10 Given paths of optimal consumption, knowledge investment, and participation in the stock market, they then simulate 5,000 life cycles allowing for return, income, and medical expense shocks. 11

Several key predictions emerge from this study. First, endogenously-determined optimal paths for financial knowledge are hump-shaped over the life cycle. Second, consumers invest in financial knowledge to the point where their marginal time and money costs of doing so are equated to their marginal benefits; of course, this optimum will depend on the cost function for financial knowledge acquisition. Third, knowledge profiles differ across educational groups because of peoples’ different life cycle income profiles.

Importantly, this model also predicts that inequality in wealth and financial knowledge will arise endogenously without having to rely on assumed cross-sectional differences in preferences or other major changes to the theoretical setup. 12 Moreover, differences in wealth across education groups also arise endogenously; that is, some population subgroups optimally have low financial literacy, particularly those anticipating substantial safety net income in old age. Finally, the model implies that financial education programs should not be expected to produce large behavioral changes for the least educated, since it may not be worthwhile for the least educated to incur knowledge investment costs given that their consumption needs are better insured by transfer programs. 13 This prediction is consistent with Jappelli and Padula’s (2013) suggestion that less financially informed individuals will be found in countries with more generous Social Security benefits (see also Jappelli 2010 ).

Despite the fact that some people will rationally choose to invest little or nothing in financial knowledge, the model predicts that it can still be socially optimal to raise financial knowledge for everyone early in life, for instance by mandating financial education in high school. This is because even if the least educated never invest again and let their knowledge endowment depreciate, they will still earn higher returns on their saving which generates a substantial welfare boost. For instance, providing pre-labor market financial knowledge to the least educated group improves their wellbeing by an amount equivalent to 82 percent of their initial wealth ( Lusardi, Michaud, and Mitchell 2011 ). The wealth equivalent value for college graduates is also estimated to be substantial, at 56 percent. These estimates are, of course, specific to the calibration, but the approach underscores that consumers would benefit from acquiring financial knowledge early in life even if they made no new investments thereafter.

In sum, a small but growing theoretical literature on financial literacy has made strides in recent years by endogenizing the process of financial knowledge acquisition, generating predictions that can be tested empirically, and offering a coherent way to evaluate policy options. Moreover, these models offer insights into how policymakers might enhance welfare by enhancing young workers’ endowment of financial knowledge. In the next section, we turn to a review of empirical evidence on financial literacy and how to measure it in practice. Subsequently, we analyze existing studies on how financial knowledge matters for economic behavior in the empirical realm.

3. Measuring Financial Literacy

Several fundamental concepts lie at the root of saving and investment decisions as modeled in the life cycle setting described in the previous section. Three such concepts are: (i) numeracy and capacity to do calculations related to interest rates , such as compound interest; (ii) understanding of inflation ; and (iii) understanding of risk diversification . Translating these into easily-measured financial literacy metrics is difficult, but Lusardi and Mitchell (2008 , 2011b , c ) have designed a standard set of questions around these ideas and implemented them in numerous surveys in the United States and abroad.

Four principles informed the design of these questions. The first is Simplicity : the questions should measure knowledge of the building blocks fundamental to decision-making in an intertemporal setting. The second is Relevance : the questions should relate to concepts pertinent to peoples’ day-to-day financial decisions over the life cycle; moreover, they must capture general rather than context-specific ideas. Third is Brevity : the number of questions must be kept short to secure widespread adoption; and fourth is Capacity to differentiate , meaning that questions should differentiate financial knowledge to permit comparisons across people. These criteria are met by the three financial literacy questions designed by Lusardi and Mitchell (2008 Lusardi and Mitchell (2011b ), worded as follows:

Suppose you had $100 in a savings account and the interest rate was 2% per year. After 5 years, how much do you think you would have in the account if you left the money to grow: [more than $102, exactly $102, less than $102? Do not know, refuse to answer.]
Imagine that the interest rate on your savings account was 1% per year and inflation was 2% per year. After 1 year, would you be able to buy: [more than, exactly the same as, or less than today with the money in this account? Do not know; refuse to answer.]
Do you think that the following statement is true or false? ‘Buying a single company stock usually provides a safer return than a stock mutual fund.’ [Do not know; refuse to answer.]

The first question measures numeracy or the capacity to do a simple calculation related to compounding of interest rates. The second question measures understanding of inflation, again in the context of a simple financial decision. The third question is a joint test of knowledge about ‘stocks’ and ‘stock mutual funds’ and of risk diversification, since the answer to this question depends on knowing what a stock is and that a mutual fund is composed of many stocks. As is clear from the theoretical models described earlier, many decisions about retirement savings must deal with financial markets. Accordingly, it is important to understand knowledge of the stock market as well as differentiate between levels of financial knowledge.

Naturally any given set of financial literacy measures can only proxy for what individuals need to know to optimize behavior in intertemporal models of financial decision-making. 14 Moreover, measurement error is a concern, as well as the possibility that answers might not measure ‘true’ financial knowledge. These issues have implications for empirical work on financial literacy, to be discussed below.

Empirical Evidence of Financial Literacy in the Adult Population

The three questions above were first administered to a representative sample of U.S. respondents age 50 and older, in a special module of the 2004 Health and Retirement Study (HRS). 15 Results, summarized in Table 1 , indicate that this older U.S. population is quite financially illiterate: only about half could answer the simple 2 percent calculation and knew about inflation, and only one third could answer all three questions correctly ( Lusardi and Mitchell 2011b ). This poor showing is notwithstanding the fact that people in this age group had made many financial decisions and engaged in numerous financial transactions over their lifetimes. Moreover, these respondents had experienced two or three periods of high inflation (depending on their age) and witnessed numerous economic and stock market shocks (including the demise of Enron), which should have provided them with information about investment risk. In fact, the question about risk is the one where respondents answered disproportionately with “Do not know.”

Financial Literacy Patterns in the United States

Source: Authors’ computations from HRS 2004 Planning Module

Note: DK = respondent indicated “don’t know.”

These same questions were added to several other U.S. surveys thereafter, including the 2007–2008 National Longitudinal Survey of Youth (NLSY) for young respondents (ages 23–28) ( Lusardi, Mitchell, and Curto 2010 ); the RAND American Life Panel (ALP) covering all ages ( Lusardi and Mitchell 2009 ); and the 2009 and 2012 National Financial Capability Study ( Lusardi and Mitchell 2011d ). 16 In each case, the findings underscore and extend the HRS results, in that for all groups, the level of financial literacy in the U.S. was found to be quite low.

Additional and more sophisticated concepts were then added to the financial literacy measures. For instance, the 2009 and 2012 National Financial Capability Survey included two items measuring sophisticated concepts such as asset pricing and understanding of mortgages/mortgage payments. Results revealed additional gaps in knowledge: for example, data from the 2009 wave show that only a small percentage of Americans (21%) knew about the inverse relationship between bond prices and interest rates ( Lusardi 2011 ). 17 A pass/fail set of 28 questions by Hilgert, Hogarth, and Beverly (2003) covered knowledge of credit, saving patterns, mortgages, and general financial management, and the authors concluded most people earned a failing score on these questions as well. 18 Lusardi, Mitchell and Curto (2012) also examine a set to questions measuring financial sophistication in addition to basic financial literacy and found that a large majority of older respondents are not financially sophisticated. Additional surveys have also examined financial knowledge in the context of debt. For example, Lusardi and Tufano (2009a , b ) examined ‘debt literacy’ regarding interest compounding and found that only one-third of respondents knew how long it would take for debt to double if one were to borrow at a 20 percent interest rate. This lack of knowledge confirms conclusions from Moore’s (2003) survey of Washington state residents, where she found that people frequently failed to understand interest compounding along with the terms and conditions of consumer loans and mortgages. Studies have also looked at different measures of “risk literacy” ( Lusardi, Schneider, and Tufano 2011 ). Knowledge of risk and risk diversification remains low even when the questions are formulated in alternative ways (see, Kimball and Shumway 2006 ; Yoong 2011 ; and Lusardi, Schneider, and Tufano 2011 ). In other words, all of these surveys confirm that most U.S. respondents are not financially literate.

Empirical Evidence of Financial Literacy among the Young

As noted above, it would be useful to know how well-informed people are at the start of their working lives. Several authors have measured high school students’ financial literacy using data from the Jump$tart Coalition for Personal Financial Literacy and the Council for Financial Education (CEE). Because those studies included a long list of questions, they provide a rather nuanced evaluation of what young people know when they enter the workforce. As we saw for their adult counterparts, most high school students in the U.S. receive a failing financial literacy grade ( Mandell 2008 ; Markow and Bagnaschi 2005 ). Similar findings are reported for college students ( Chen and Volpe 1998 ; and Shim, Barber, Card, Xiao, and Serido 2010 ).

International Evidence on Financial Literacy

The three questions mentioned earlier and that have been used in several surveys in the United States have also been used in several national surveys in other countries. Table 2 reports the findings from the twelve countries that have used these questions and where comparisons can be made for the total population. 19 For brevity, we only report the proportion of correct and do not know answers to each questions and for all questions.

Comparative Statistics on Responses to Financial Literacy Questions around the World

The table highlights a few key findings. First, few people across countries can correctly answer three basic financial literacy questions. In the U.S., only 30 percent can do so, with similar low percentages in countries having well-developed financial markets (Germany, the Netherlands, Japan, Australia and others), as well as in nations where financial markets are changing rapidly (Russia and Romania). In other words, low levels of financial literacy found in the U.S. are also prevalent elsewhere, rather than being specific to any given country or stage of economic development. Second, some of what adult respondents know is related to national historical experience. For example, Germans and Dutch are more likely to know the answer to the inflation question, whereas many fewer people do in Japan, a country that has experienced deflation. Countries that were planned economies in the past (such as Romania and Russia) displayed the lowest knowledge of inflation. Third, of the questions examined, risk diversification appears to be the concept that people have the most difficulty grasping. Virtually everywhere, a high share of people respond that they ‘do not know’ the answer to the risk diversification question. For instance, in the U.S., 34 percent of respondents state they do not know the answer to the risk diversification question; in Germany 32 percent and the Netherlands 33 percent do so; and even in the most risk-savvy country of Sweden and Switzerland, 18 and 13 percent respectively report they do not know the answer to the risk diversification question.

The Organisation for Economic Co-operation and Development (OECD) has been a pioneer in highlighting the lack of financial literacy across countries. For example, an OECD report in 2005 documented extensive financial illiteracy in Europe, Australia, and Japan, among others. 20 More recently, Atkinson and Messy (2011 Atkinson and Messy (2012) confirmed the patterns of financial illiteracy mentioned earlier in the text across 14 countries at different stages of development in four continents, using a harmonized set of financial literacy as in the three questions that were used in many countries. 21

The goal of evaluating student financial knowledge around the world among the young (high school students) has recently been taken up by the OECD’s Programme for International Student Assessment (PISA), 22 which in 2012 added a module on financial literacy to its review of proficiency in mathematics, science, and reading. Accordingly, 15-year olds around the world will be able to be compared with regard to their financial knowledge. In so doing, PISA has taken the position that financial literacy should be recognized as a skill essential for participation in today’s economy.

Objective versus Subjective Measures of Financial Literacy

Another interesting finding on financial literacy is that there is often a substantial mismatch between peoples’ self-assessed knowledge versus their actual knowledge , where the latter is measured by correct answers to the financial literacy questions posed. As one example, several surveys include questions asking people to indicate their self-assessed knowledge, as the following questions used in the United States and also in the Netherlands and Germany:

On a scale from 1 to 7, where 1 means very low and 7 means very high, how would you assess your overall financial knowledge?’

Even though actual financial literacy levels are low, respondents are generally rather confident of their financial knowledge and, overall, they tend to overestimate how much they know ( Table 3 ). For instance in the 2009 U.S. Financial Capability Study, 70 percent of respondents gave themselves score of 4 or higher (out of 7), but only 30 percent of the sample could answer the factual questions correctly ( Lusardi 2011 ). Similar findings were reported in other U.S. surveys and in Germany and the Netherlands ( Bucher-Koenen, Lusardi, Alessie and van Rooij 2012 ). One exception is Japan, where respondents gave themselves low grades in financial knowledge. In other words, though actual financial literacy is low, most people are unaware of their own shortcomings.

Comparative Statistics on Responses to Self-reported Financial Literacy

Note: This table reports respondents’ answers to the question: “On a scale from 1 to 7, where 1 means very low and 7 means very high, how would you assess your overall financial knowledge?” Note that the question posed in Lusardi and Mitchell (2009) is different and asks the following: “How would you assess your understanding of economics (on a 7-point scale;1 means very low and 7 means very high)?” In Japan, respondents were asked whether they think that they know a lot about finance on a 1–5 point scale ( Sekita 2011 ).

Financial Literacy and Framing

Peoples’ responses to survey questions cannot always be taken at face value, a point well-known to psychometricians and economic statisticians. One reason, as noted above, is that financial literacy may be measured with error, depending on the way questions are worded. To test this possibility, Lusardi and Mitchell (2009) and van Rooij, Lusardi, and Alessie (2011) randomly asked two groups of respondents the same risk question, but randomized their order of presentation. Thus half the group received format (a) and the other half format (b), as follows:

Buying a stock mutual fund usually provides a safer return than a company stock. True or false?

They found that people’s responses were, indeed, sensitive to how the question was worded in both the U.S. American Life Panel ( Lusardi and Mitchell 2009 ) and the Dutch Central Bank Household Survey (DHS; van Rooij, Lusardi, and Alessie 2011 ). For example, fewer DHS respondents responded correctly when the wording was ‘buying a stock mutual fund usually provides a safer return than a company stock’; conversely, the fraction of correct responses doubled when shown the alternative wording: ‘buying a company stock usually provides a safer return than a stock mutual fund.’ This was not simply due to people using a crude rule of thumb (such as always picking the first as the correct answer), since that would generate a lower rather than a higher percentage of correct answers for version (a). Instead, it appeared that some respondents did not understand the question, perhaps because they were unfamiliar with stocks, bonds, and mutual funds. What this means is that some answers judged to be ‘correct’ may instead be attributable to guessing. In other words, analysis of the financial literacy questions should take into account the possibility that these measures may be noisy proxies of true financial knowledge levels. 23

4. Disaggregating Financial Literacy

To draw out lessons about which people most lack financial knowledge, we turn next to a disaggregated assessment of the data. In what follows, we briefly review evidence by age and sex, race/ethnicity, income and employment status, and other factors of interest to researchers.

Financial Literacy Patterns by Age

The theoretical framework sketched above implies that the life cycle profile of financial literacy will be hump-shaped, and survey data confirm that financial literacy is, in fact, lowest among the young and the old. 24 This is a finding which is robust across countries and we report a selected set of countries in Figure 1 .

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Financial Literacy Across Demographic Groups (Age, Sex, and Education)

Note: Data for Figure 1c are taken from Lusardi and Mitchell, 2011d (USA); Alessie, van Rooij, and Lusardi, 2011 (Netherlands), Bucher-Koenen and Lusardi, 2011 (Germany), and Brown and Graf, 2013 (Switzerland).

Of course with cross-sectional data, one cannot cleanly disentangle age from cohort effects, so further analysis is required to identify these clearly, and below we comment further on this point ( Figure 1a ). Nevertheless, it is of interest that older people give themselves very high scores regarding their own financial literacy, despite scoring poorly on the basic financial literacy questions ( Lusardi and Mitchell 2011b ; Lusardi and Tufano 2009a ) and not just in the US but other countries as well ( Lusardi and Mitchell, 2011c ). Similarly, Finke, Howe, and Houston (2011) develop a multidimensional measure of financial literacy for the old and confirm that, though actual financial literacy falls with age, peoples’ confidence in their own financial decision-making abilities actually increases with age. The mismatch between actual and perceived knowledge might explain why financial scams are often perpetrated against the elderly ( Deevy, Lucich, and Beals 2012 ).

Financial Literacy Differences by Sex

One striking feature of the empirical data on financial literacy is the large and persistent gender difference described in Figure 1b . Not only are older men generally more financially knowledgeable than older women, but similar patterns also show up among younger respondents as well ( Lusardi, Mitchell, and Curto 2010 ; Lusardi and Mitchell 2009 ; Lusardi and Tufano 2009a , b ). Moreover, these gaps persist across both the basic and the more sophisticated literacy questions ( Lusardi, Mitchell, and Curto 2012 ; Hung, Parker, and Yoong 2009 ).

One twist on the differences by sex, however, is that while women are less likely to answer financial literacy questions correctly than men, they are also far more likely to say they ‘do not know’ an answer to a question, a result that is strikingly consistent across countries ( Figure 1b ). 25 This awareness of their own lack of knowledge may make women ideal targets for financial education programs.

Because these sex differences in financial literacy are so persistent and widespread across surveys and countries, several researchers have sought to explain them. Consistent with the theoretical framework described earlier, Hsu (2011) proposed that some sex differences may be rational, with specialization of labor within the household leading married women to build up financial knowledge only late in life (close to widowhood). Nonetheless, that study did not explain why financial literacy is also lower among single women in charge of their own finances. Studies of financial literacy in high school and college also revealed sex differences in financial literacy early in life ( Chen and Volpe 2002 ; Mandell 2008 ). 26 Other researchers seeking to explain observed sex differences concluded that traditional explanations cannot fully account for the observed male/female knowledge gap ( Fonseca, Mullen, Zamarro, and Zissimopolous 2012 ; Bucher-Koenen, Lusardi, Alessie, and van Rooij 2012 ). Fonseca, Mullen, Zamarro, and Zissimopoulos (2012) suggested that women may acquire or ‘produce’ financial literacy differently from men, while Bucher-Koenen, Lusardi, Alessie, and van Rooij (2012) pointed to a potentially important role for self-confidence that differs by sex. Brown and Graf (2013) also showed that sex differences are not due to differential interest in finance and financial matters between women and men.

To shed more light on women’s financial literacy, Mahdavi and Horton (2012) examined alumnae from a highly selective U.S. women’s liberal arts college. Even in this talented and well-educated group, women’s financial literacy was found to be very low. In other words, even very well educated women are not particularly financially literate, which could imply that women may acquire financial literacy differently from men. Nevertheless this debate is far from closed, and additional research will be required to better understand these observed sex differences in financial literacy.

Literacy Differences by Education and Ability

As illustrated in Figure 1c , there are substantial differences in financial knowledge by education: specifically, those without a college education are much less likely to be knowledgeable about basic financial literacy concepts, as reported in several U.S. surveys and across countries ( Lusardi and Mitchell 2007a , 2011c ). Moreover, numeracy is especially poor for those with low educational attainment ( Christelis, Jappelli, and Padula 2010 , Lusardi, 2012 ).

How to interpret the finding of a positive link between education and financial savvy has been subject to some debate in the economics literature. One possibility is that the positive correlation might be driven by cognitive ability ( McArdle, Smith, and Willis 2009 ), implying that one must control on measures of ability when seeking to parse out the separate impact of financial literacy. Fortunately, the NLSY has included both measures of financial literacy and of cognitive ability (i.e., the Armed Services Vocational Aptitude Battery). Lusardi, Mitchell, and Curto (2010) did find a positive correlation between financial literacy and cognitive ability among young NLSY respondents, but they also showed that cognitive factors did not fully account for the variance in financial literacy. In other words, substantial heterogeneity in financial literacy remains even after controlling on cognitive factors.

Other Literacy Patterns

There are numerous other empirical regularities in the financial literacy literature, that are again persistent across countries. Financial savvy varies by income and employment type, with lower-paid individuals doing less well and employees and the self-employed doing better than the non-employed ( Lusardi and Tufano 2009a ); Lusardi and Mitchell 2011c ). Several studies have also reported marked differences by race and ethnicity, with African Americans and Hispanics displaying the lowest level of financial knowledge in the U.S. context ( Lusardi and Mitchell 2007a , b , 2011d ). These findings hold across age groups and many different financial literacy measures ( Lusardi and Mitchell 2009 ). Those living in rural areas generally score worse than their city counterparts ( Klapper and Panos 2011 ). These findings might suggest that financial literacy is more easily acquired via interactions with others, in the workplace or in the community. 27 Relatedly, there are also important geographic differences in financial literacy; for example, Fornero and Monticone (2011) report substantial financial literacy dispersion across regions in Italy and so does Beckmann (2013) for Romania Bumcrot, Lin, and Lusardi (2013) report similar differences across U.S. states.

The literature also points to differences in financial literacy by family background. For instance, Lusardi, Mitchell, and Curto (2010) linked financial literacy of 23–28-year-old NLSY respondents to characteristics of the households in which they grew up, controlling for a set of demographic and economic characteristics. Respondents’ financial literacy was also significantly positively correlated with parental education (in particular, that of their mothers), and whether their parents held stocks or retirement accounts when the respondents were teenagers. Mahdavi and Horton (2012) reported a connection between financial literacy and parental background; in this case, fathers’ education was positively associated with their female children’s financial literacy. 28 In other words, financial literacy may well get its start in the family, perhaps when children observe their parents’ saving and investing habits, or more directly by receiving financial education from parents ( Chiteji and Stafford 1999 ; Li 2009 ; Shim, Xiao, Barber, and Lyons 2009 ).

Other studies have noted a nationality gap in financial literacy, with foreign citizens reporting lower financial literacy than the native born ( Brown and Graf 2013 ). Others have found differences in financial literacy according to religion ( Alessie, Van Rooij and Lusardi, 2011 ) and political opinions ( Arrondel, Debbich and Savignac 2013 ). These findings may also shed light on how financial literacy is acquired.

To summarize, while financial illiteracy is widespread, it is also concentrated among specific population sub-groups in most countries studied to date. Such heterogeneity in financial literacy suggests that different mechanisms may be appropriate for tracking the causes and possible consequences of the shortfalls. In the U.S., those facing most challenges are the young and the old, women, African-Americans, Hispanics, the least educated, and those living in rural areas. To date, these differences have not been fully accounted for, though the theoretical framework outlined above provides guidelines for explaining some of these.

5. How Does Financial Literacy Matter?

We turn next to a discussion of whether and how financial literacy matters for economic decision-making. 29 Inasmuch as individuals are increasingly being asked to take on additional responsibility for their own financial well-being, there remains much to learn about these facts. And as we have argued above, when financial literacy itself is a choice variable, it is important to disentangle cause from effect. For instance, those with high net worth who invest in financial markets may also be more likely to care about improving their financial knowledge, since they have more at stake. In what follows, we discuss research linking financial literacy with economic outcomes, taking into account the endogeneity issues as well.

Financial Literacy and Economic Decisions

The early economics literature in this area began by documenting the link between financial literacy and several economic behaviors. For example Bernheim (1995 , 1998 ) was among the first to emphasize that most U.S. households lacked basic financial knowledge and that they also used crude rules of thumb when engaging in saving behavior. More recently, Calvet, Campbell, and Sodini (2007 Calvet, Campbell, and Sodini (2009) evaluated Swedish investors’ actions that they classified as ‘mistakes.’ While that analysis included no direct financial literacy measure, the authors did report that poorer, less educated, and immigrant households (attributes associated with low financial literacy, as noted earlier) were more likely to make financial errors. Agarwal, Driscoll, Gabaix, and Laibson (2009) also focused on financial ‘mistakes’, showing that these were most prevalent among the young and the old, groups which normally display the lowest financial knowledge.

In the wake of the financial crisis of 2008–9, the U.S. federal government has also begun to express substantial concern about another and more extreme case of mistakes, namely where people fall prey to financial scams. As often noted, scams tend to be perpetrated against the elderly, since they are among those with the least financial savvy and often have accumulated some assets. 30 A survey of older financial decision makers (age 60+) indicated that more than half of them reported having made a bad investment, and one in five of those respondents felt they had been misled or defrauded but failed to report the situation ( FINRA 2006 ). As Baby Boomers age, this problem is expected to grow ( Blanton 2012 ), since this cohort is a potentially lucrative target.

Several researchers have examined the relationships between financial literacy and economic behavior. It is much harder to establish a causal link between the two and we will discuss the issue of endogeneity and other problems in more detail below. Hilgert, Hogarth, and Beverly (2003) uncovered a strong correlation between financial literacy and day-to-day financial management skills. Several other studies both in the United States and other countries have found that the more numerate and financially literate are also more likely to participate in financial markets and invest in stocks ( Kimball and Shumway 2006 ; Christelis, Jappelli, and Padula 2010 ; van Rooij, Lusardi, and Alessie 2011 ; Yoong 2011 ; Almenberg and Dreber 2011 ; Arrondel, Debbich, and Savignac 2012 ). Financial literacy can also be linked to holding precautionary savings ( de Bassa Scheresberg 2013 ).

The more financially savvy are also more likely to undertake retirement planning, and those who plan also accumulate more wealth ( Lusardi and Mitchell 2007a , b , 2011a , 2011b ). Some of the first studies on the effects of financial literacy were linked to its effects on retirement planning in the United States and these studies have been replicated in most of the countries covered in Table 2 , showing that the correlation between financial literacy and different measures of retirement planning is quite robust. 31 Studies breaking out specific components of financial literacy tend to conclude that what matters most is advanced financial knowledge (for example, risk diversification) and the capacity to do calculations ( Lusardi and Mitchell 2011d ; Alessie, van Rooij, and Lusardi 2011 ; Fornero and Monticone 2011 ; Klapper and Panos 2011 ; Sekita 2011 ).

Turning to the liability side of the household balance sheet, Moore (2003) reported that the least financially literate are also more likely to have costly mortgages. Campbell (2006) pointed out that those with lower income and less education (characteristics strongly related to financial illiteracy) were less likely to refinance their mortgages during a period of falling interest rates. Stango and Zinman (2009) concluded that those unable to correctly calculate interest rates out of a stream of payments ended up borrowing more and accumulating less wealth. Lusardi and Tufano (2009a ) confirmed that the least financially savvy incurred high transaction costs, paying higher fees and using high-cost borrowing. In their study, the less knowledgeable also reported that their debt loads were excessive, or that they were unable to judge their debt positions. Similarly, Mottola (2013) found that those with low financial literacy were more likely to engage in costly credit card behavior, and Utkus and Young (2011) concluded that the least literate were also more likely to borrow against their 401(k) and pension accounts.

Moreover, both self-assessed and actual literacy is found to have an effect on credit card behavior over the life cycle ( Allgood and Walstad, 2013 ). A particularly well-executed study by Gerardi, Goette, and Meier (2013) matched individual measures of numerical ability to administrative records that provide information on subprime mortgage holders’ payments. Three important findings flowed from this analysis. First, numerical ability was a strong predictor of mortgage defaults. Second, the result persisted even after controlling for cognitive ability and general knowledge. Third, the estimates were quantitatively important, as will be discussed in more detail below, an important finding for both regulators and policymakers.

Many high-cost methods of borrowing have proliferated over time, with negative effects for less savvy consumers. 32 For instance, Lusardi and de Bassa Scheresberg (2013) examined high-cost borrowing in the U.S. including payday loans, pawn shops, auto title loans, refund anticipation loans, and rent-to-own shops. They concluded that the less financially literate were substantially more likely to use high-cost methods of borrowing, a finding that is particularly strong among young adults (age 25–34) ( Bassa Scheresberg 2013 ). While most attention has been devoted to the supply side, these studies suggest it may also be important to look at the demand side and the financial literacy of borrowers. The large number of mortgage defaults during the financial crisis has likewise suggested to some that debt and debt management is a fertile area for mistakes; for instance, many borrowers do not know what interest rates were charged on their credit card or mortgage balances ( Moore 2003 ; Lusardi 2011 ; Disney and Gathergood 2012 ). 33

It is true that education can be quite influential in many of these arenas. For instance, research has shown that the college educated are more likely to own stocks and less prone to use high-cost borrowing ( Haliassos and Bertaut 1995 ; Campbell 2006 ; Lusardi and de Bassa Scheresberg 2012 ). Likewise, there is a very strong positive correlation between education and wealth-holding ( Bernheim and Scholz 1993 ). But for our purposes, including controls for educational attainment in empirical models of stock holding, wealth accumulation, and high-cost methods of borrowing, does not diminish the statistical significance of financial literacy and in fact it often enhances it ( Lusardi and Mitchell 2011b ; Behrman, Mitchell, Soo, and Bravo 2012 ; van Rooij, Lusardi, and Alessie 2011 , 2012 ; Lusardi and de Bassa Scheresberg 2013 ). Evidently, general knowledge (education) and more specialized knowledge (financial literacy) both contribute to more informed financial decision-making. In other words, investment in financial knowledge appears to be a specific form of human capital, rather than being simply associated with more years of schooling. Financial literacy is also linked to the demand for on-the-job training ( Clark, Ogawa, and Matsukura 2010 ) and being able to cope with financial emergencies ( Lusardi, Schneider, and Tufano 2011 ).

Costs of Financial Ignorance Pre-retirement

In the wake of the financial crisis, many have become interested in the costs of financial illiteracy as well as its distributional impacts. For instance, in the Netherlands, van Rooij, Lusardi, and Alessie (2011) estimate that being in the 75 th versus the 25 th percentile of the financial literacy index equals around €80,000 in terms of differential net worth (i.e., roughly 3.5 times the net disposable income of a median Dutch household). They also point out that an increase in financial literacy from the 25 th to the 75 th percentile for an otherwise average individual is associated with a 17–30 percentage point higher probability of stock market participation and retirement planning, respectively. In the U.S., simulations from a life-cycle model that incorporates financial literacy shows that financial literacy alone can explain more than half the observed wealth inequality ( Lusardi, Michaud, and Mitchell 2013 ). This result is obtained by comparing wealth to income ratios across education groups in models with and without financial literacy, which allows individuals to earn higher returns on their savings. For this reason, if the effects of financial literacy on financial behavior can be taken as causal, the costs of financial ignorance are substantial.

In the U.S., investors are estimated to have foregone substantial equity returns due to fees, expenses, and active investment trading costs, in an attempt to ‘beat the market.’ French (2008) calculates that this amounts to an annual total cost of around $100 billion, which could be avoided by passive indexing. Since the least financially literate are unlikely to be sensitive to fees, they are most likely to bear such costs. Additionally, many of the financially illiterate have been shown to shun the stock market, which Cocco, Gomes, and Maenhout (2005) suggested imposed welfare losses amounting to four percent of wealth. The economic cost of under-diversification computed by Calvet, Campbell, and Sodini (2007) is also substantial: they concluded that a median investor in Sweden experienced an annual return loss of 2.9 percent on a risky portfolio, or 0.5 percent of household disposable income. But for one in 10 investors, these annual costs were much higher, 4.5 percent of disposable income.

Costs of financial ignorance arise not only in the saving and investment arena, but also influence how consumers manage their liabilities. Campbell (2006) reported that suboptimal refinancing among U.S. homeowners resulted in 0.5–1 percent per year higher mortgage interest rates, or in aggregate, $50–100 billion annually. And as noted above, the least financially savvy are least likely to refinance their mortgages. Gerardi, Goette, and Meier (2013) showed that numerical ability may have contributed substantially to the massive defaults on subprime mortgages in the recent financial crisis. According to their estimates, those in the highest numerical ability grouping had about a 20 percentage point lower probability of defaulting on their subprime mortgages than those in the lowest financial numeracy group.

One can also link ‘debt literacy’ regarding credit card behaviors that generate fees and interest charges to paying bills late, going over the credit limit, using cash advances, and paying only the minimum amount due. Lusardi and Tufano (2009a ) calculated the “cost of ignorance” or transaction costs incurred by less-informed Americans and the component of these costs related to lack of financial knowledge. Their calculation of expected costs had two components—the likelihood and the costs of various credit card behaviors. These likelihoods were derived directly from empirical estimates using the data on credit card behavior, debt literacy, and a host of demographic controls that include income. They showed that, while less knowledgeable individuals constitute only 29 percent of the cardholder population, they accounted for 42 percent of these charges. Accordingly, the least financially savvy bear a disproportionate share of the costs associated with fee-inducing behaviors. Indeed, the average fees paid by those with low knowledge were 50 percent higher than those paid by the average cardholder. And of these four types of charges incurred by less-knowledgeable cardholders, one-third were incremental charges linked to low financial literacy.

Another way that the financially illiterate spend dearly for financial services is via high-cost forms of borrowing, including payday loans. 34 While the amount borrowed is often low ($300 on average), such loans are often made to individuals who have five or more such transactions per year ( Center for Responsible Lending 2004 ). It turns out that these borrowers also frequently fail to take advantage of other, cheaper opportunities to borrow. Agarwal, Skiba, and Tobacman (2009) studied payday borrowers who also have access to credit cards, and they found that two-thirds of their sample had at least $1,000 in credit card liquidity on the day they took out their first payday loan. This points to a pecuniary mistake: given average charges for payday loans and credit cards and considering a two-week payday loan of $300, the use of credit cards would have saved these borrowers substantial amounts – around $200 per year (and more if they took out repeated payday loans). While there may be good economic reasons why some people may want to keep below their credit card limits, including unexpected shocks, Bertrand and Morse (2011) determined that payday borrowers often labored under cognitive biases, similar to those with low financial literacy ( Lusardi and de Bassa Scheresberg 2013 ).

Costs of Financial Ignorance in Retirement

Financial knowledge impacts key outcomes including borrowing, saving, and investing decisions not only during the worklife, but afterwards, in retirement, as well. In view of the fact that people over the age of 65 hold more than $18 trillion in wealth, 35 this is an important issue.

Above we noted that financial literacy is associated with greater retirement planning and greater retirement wealth accumulation. 36 Hence it stands to reason that the more financially savvy will likely be better financially endowed when they do retire. A related point is that the more financially knowledgeable are also better informed about pension system rules, pay lower investment fees in their retirement accounts, and diversify their pension assets better ( Arenas de Mesa, Bravo, Behrman, Mitchell, and Todd 2008 ; Chan and Stevens 2008 ; Hastings, Mitchell, and Chyn 2011 ). 37 To date, however, relatively little has been learned about whether more financially knowledgeable older adults are also more successful at managing their resources in retirement, though the presence of scams among the elderly suggests that this topic is highly policy-relevant.

This is a particularly difficult set of decisions requiring retirees to look ahead to an uncertain future when making irrevocable choices with far-reaching consequences. For instance, people must forecast their (and their partner’s) survival probabilities, investment returns, pension income, and medical and other expenditures. Moreover, many of these financial decisions are once-in-a-lifetime events, including when to retire and claim one’s pension and Social Security benefits. Accordingly, it would not be surprising if financial literacy enhanced peoples’ ability to make these important and consequential decisions.

This question is especially relevant when it comes to the decision of whether retirees purchase lifetime income streams with their assets, since by so doing, they insure themselves from running out of income in old age. 38 Nevertheless, despite the fact that this form of longevity protection is very valuable in theory, relatively few payout annuities are purchased in practice in virtually every country ( Mitchell, Piggott, and Takayama 2011 ). New research points to the importance of framing and default effects in this decision process ( Agnew and Szkyman 2011 ; Brown, Kapteyn, and Mitchell 2013 ). This conclusion was corroborated by Brown, Kapteyn, Luttmer, and Mitchell (2011) , who demonstrated experimentally that people valued annuities less when they were offered the opportunity to buy additional income streams, and they valued annuities more if offered a chance to exchange their annuity flows for a lump sum. 39 Importantly for the present purpose, the financially savvy provided more consistent responses across alternative ways of eliciting preferences. By contrast, the least financially literate gave inconsistent results and respond to irrelevant cues when presented with the same set of choices. In other words, financial literacy appears to be highly influential in helping older households equip themselves with longevity risk protection in retirement.

Much more must be learned about how peoples’ financial decision-making abilities change with age, and how these are related to financial literacy. For instance, Agarwal, Driscoll, Gabaix, and Laibson (2009) reported that the elderly pay much more than the middle-aged for 10 financial products; 40 the 75-year-olds in their sample paid about $265 more per year for home equity lines of credit than did the 50-year-olds. How the patterns might vary by financial literacy is not yet known, but it might be that those with greater baseline financial knowledge are better able to deal with financial decisions as they move into the second half of their lifetimes. 41

Coping with Endogeneity and Measurement Error

Despite an important assembly of facts on financial literacy, relatively few empirical analysts have accounted for the potential endogeneity of financial literacy and the problem of measurement error in financial literacy alluded to above. In the last five years or so, however, several authors have implemented instrumental variables (IV) estimation to assess the impact of financial literacy on financial behavior, and the results tend to be quite convincing. To illustrate the ingenuity of the instruments used, Table 4 lists several studies along with the instruments used in their empirical analysis. Some of the descriptive evidence on financial literacy discussed earlier may explain why these instruments may be anticipated to predict financial literacy.

Instrumental Variable (IV) Estimation of the Effect of Financial Literacy on Behavior

It is useful to offer a handful of comments on some of the papers with particularly strong instruments. Christiansen, Joensen, and Rangvid (2008) used the opening of a new university in a local area—arguably one of the most exogenous variables one can find— as instrument for knowledge, and they concluded that economics education is an important determinant of investment in stocks. Following this lead, Klapper, Lusardi and Panos (2012) used the number of public and private universities in the Russian regions and the total number of newspapers in circulation as instruments for financial literacy. They found that financial literacy affected a variety of economic indicators including having bank accounts, using bank credit, using informal credit, having spending capacity, and the availability of unspent income. Lusardi and Mitchell (2009) instrumented financial literacy using the fact that different U.S. states mandated financial education in high school in different states and at different points in time and they interacted these mandates with state expenditures on education. Behrman, Mitchell, Soo, and Bravo (2012) employed several instruments including exposure to a new educational voucher system in Chile to isolate the causal effects of financial literacy and schooling attainment on wealth. Their IV results showed that both financial literacy and schooling attainment were positively and significantly associated with wealth levels.

Van Rooij, Lusardi, and Alessie (2011) instrumented financial literacy with the financial experiences of siblings and parents, since these were arguably not under respondents’ control, to rigorously evaluate the relationship between financial literacy and stock market participation. The authors reported that instrumenting greatly enhanced the measured positive impact of financial literacy on stock market participation. These instruments were also recently used by Agnew, Bateman and Thorp (2013) to assess the effect of financial literacy on retirement planning in Australia. Bucher-Koenen and Lusardi (2011) used political attitudes at the regional level in Germany as an instrument, arguing that free-market oriented supporters are more likely to be financially literate, and the assumption is that individuals can learn from others around them. The study by Arrondel, Debbich, and Savignac (2013) also shows some differences in financial literacy across political affiliation.

Interestingly, in all these cases, the IV financial literacy estimates always proves to be larger than the ordinary least squares estimates ( Table 4 ). This might be that people affected by the instruments have large responses or there is severe measurement error, but on the other hand, it seems clear that the non-instrumented estimates of financial literacy may underestimate the true effect.

Despite these advances, one might worry that other omitted variables could still influence financial decisions in ways that could bias results. For example, unobservables such as discount rates ( Meier and Sprenger 2008 ), IQ ( Grinblatt, Keloharju, and Linnainmaa 2011 ), or cognitive abilities could influence saving decisions and portfolio choice ( Delavande, Rohwedder, and Willis 2008 ; Korniotis and Kumar 2011 ). If these cannot be controlled for, estimated financial literacy impacts could be biased. However, Alessie, van Rooij, and Lusardi’s (2011) work using panel data and fixed-effects regression as well as IV estimation confirmed the positive effect of financial literacy on retirement planning, and several studies, as mentioned earlier (c.f., Gerardi, Goette and Meier 2013 ), account explicitly for cognitive ability. Nevertheless, they show that numeracy has an effect above and beyond cognitive ability.

A different way to parse out the effects of financial literacy on economic outcomes is to use a field experiment in which one group of individuals (the treatment group) is exposed to a financial education program and their behavior is then compared to that of a second group not thus exposed (the control group). Yet even in countries with less developed financial markets and pension systems, financial literacy impacts are similar to those found when examining the effect of financial literacy on retirement planning and pension participation ( Lusardi and Mitchell 2011c ). For example, Song (2011) showed that learning about interest compounding produces a sizeable increase in pension contributions in China. Randomized experimental studies in Mexico and Chile demonstrated that more financially literate individuals were more likely to choose pension accounts with lower administrative fees ( Hastings and Tejeda-Ashton 2008 ; Hastings and Mitchell 2011 ; Hastings, Mitchell, and Chyn 2011 ). More financially sophisticated individuals in Brazil were also less affected by their peers’ choices in their financial decisions ( Bursztyn, Ederer, Ferman, and Yuchtman 2013 ).

The financial crisis has also provided a laboratory to study the effects of financial literacy against a backdrop of economic shocks. For example, when stock markets dropped sharply around the world, investors were exposed to large losses in their portfolios. This combined with much higher unemployment has made it even more important to be savvy in managing limited resources. Bucher-Koenen and Ziegelmeyer (2011) examined the financial losses experienced by German households during the financial crisis and confirmed that the least financially literate were more likely to sell assets that had lost value, thus locking in losses. 42 In Russia, Klapper, Lusardi, and Panos (2012) found that the most financially literate were significantly less likely to report having experienced diminished spending capacity and had more available saving. Additionally, estimates from different time periods implied that financial literacy better equips individuals to deal with macroeconomic shocks.

Given this evidence on the negative outcomes and costs of financial illiteracy, we turn next to financial education programs to remedy these shortfalls.

6. Assessing the Effects of Financial Literacy Programs

Another way to assess the effects of financial literacy is to look at the evidence on financial education programs whose aims and objectives are to improve financial knowledge. Financial education programs in the U.S. and elsewhere have been implemented over the years in several different settings: in schools, workplaces, and libraries, and sometimes population subgroups have been targeted. As one example, several U.S. states mandated financial education in high school at different points in time, generating ‘natural experiments’ utilized by Bernheim, Garrett, and Maki (2001) , one of the earliest studies in this literature. Similarly, financial education in high schools has recently been examined in Brazil and Italy ( Bruhn, Legovini, and Zia 2012 ; Romagnoli and Trifilidis 2012 ). In some instances, large U.S. firms have launched financial education programs (c.f. Bernheim and Garrett (2003) , Clark and D’Ambrosio (2008) , and Clark, Morrill, and Allen (2012a , b )). Often the employer’s intention is to boost defined benefit pension plan saving and participation ( Duflo and Saez 2003 , 2004 ; Lusardi, Keller, and Keller 2008 ; Goda, Manchester, and Sojourner 2012 ). Programs have also been adopted for especially vulnerable groups such as those in financial distress ( Collins and O’Rourke 2010 ).

Despite the popularity of the programs, only a few authors have undertaken careful evaluations of the impact of financial education programs. Rather than detailing or reviewing the existing literature, 43 here we instead draw attention to the key issues which future researchers must take into account when evaluating the effectiveness of financial education programs. 44 We also highlight key recent research not reviewed in prior surveys.

A concern emphasized above in Section 2 is that evaluation studies have sometimes been conducted without a clear understanding of how financial knowledge is developed. That is, if we define financial literacy as a form of human capital investment, it stands to reason that some will find it optimal to invest in financial literacy while others will not. Accordingly, if a program were to be judged based on specific behavioral changes such as increasing retirement saving or participation in retirement accounts, it should be recognized that the program is unlikely, both theoretically and practically, to change everyone’s behavior in the same way. 45 For example, a desired outcome from a financial education program might be to boost saving. Yet for some, it may not be optimal to save; for others, it might be rational to reduce debt. Hence, unless an evaluator focused on the household portfolio problem including broader saving measures, a program might (incorrectly) be judged a failure.

A related concern is that, since such a large portion of the population is not financially knowledgeable about even the basic concepts of interest compounding, inflation, and risk diversification, it is unlikely that short exposure to financial literacy training would make much of a dent in consumers’ decision-making prowess. For this reason, offering a few retirement seminars or sending employees to a benefit fair can be fairly ineffective ( Duflo and Saez 2003 , 2004 ). Additionally, few studies have undertaken a careful cost-benefit analysis, which should be a high priority for future research.

The evidence reported previously also shows there is substantial heterogeneity in both financial literacy and financial behavior, so that programs targeting specific groups are likely to be more effective than one-size-fits-all financial education programs. For example, Lusardi, Michaud and Mitchell (2013) show theoretically that there is substantial heterogeneity in individual behavior, implying that not everyone will gain from financial education. Accordingly, saving will optimally be zero (or negative) for some, and financial education programs in this case would not be expected to change that behavior. In other words, one should not expect a 100 percent participation rate in financial education programs. In this respect, the model delivers an important prediction: in order to change behavior, financial education programs must be targeted to specific groups of the population since people have different preferences and economic circumstances.

As in other fields of economic research, program evaluations must also be rigorous if they are to persuasively establish causality and effectiveness. As noted by Collins and O’Rourke (2010) , the ‘golden rule’ of evaluation is the experimental approach in which a ‘treatment’ group exposed to financial literacy education is compared with a ‘control’ group that is not (or that is exposed to a different treatment). Thus far, as noted above, few financial educational programs have been designed or evaluated with these standards in mind, making it difficult to draw inferences. A related point is that confounding factors may bias estimated impacts unless the evaluation is carefully structured. As an example, we point to the debate over the efficacy of teaching financial literacy in high school, a discussion that will surely be fed by the new financial literacy module in the 2012 PISA mentioned above. Some have argued against financial education in school (e.g., Willis 2008 ), drawing on the findings from the Jump$tart Coalition for Personal Financial Literacy ( Mandell 2004 , 2008 ). The Jump$tart studies concluded that students scored no better in financial literacy tests even if they attended school in states having financial education; in fact, in some cases, Mandell (1997 , 2008 ) found that they scored even worse than students in states lacking these programs. Yet subsequent analyses ( Walstad, Rebeck, and MacDonald 2010 ) pointed out that this research was incomplete as it did not account for course content, test measurement, teacher preparation, and amount of instruction. These points were underscored by Tennyson and Nguyen (2001) who revisited the Jump$tart data by looking more closely at state education requirements for personal finance education. They concluded that when students were mandated to take a financial education course, they perform much better than students in states with no personal finance mandates. Accordingly, there is reason to believe that mandating personal finance education may, in fact, be effective in increasing student knowledge—but only when it requires significant exposure to personal finance concepts.

It is likewise risky to draw inferences without knowing about the quality of teaching in these courses. For instance, Way and Holden (2009) examined over 1,200 K–12 teachers, prospective teachers, and teacher education faculty representing four U.S. census regions, along with teachers’ responses to questions about their personal and educational backgrounds in financial education. Almost all of the teachers recognized the importance of and need for financial education, yet fewer than one-fifth stated they were prepared to teach any of the six personal finance concepts normally included in the educational rubrics. Furthermore, prospective teachers felt least competent in the more technical topics including risk management and insurance, as well as saving and investing. Interestingly, these are also the concepts that the larger adult population struggles with, as noted above. That study concluded that state education mandates appeared to have no effect on whether teachers took courses in personal finance, taught the courses, or felt competent to teach such a course, consistent with the fact that the states mandating high school financial education did not necessarily provide or promote teacher training in the field.

It would also be valuable to further investigate whether the knowledge scores actually measured what was taught in school and whether students self-selected into the financial education classes. Walstad, Rebeck, and MacDonald (2010) used a quasi-experimental set up to assess a well-designed video course covering several fundamental concepts for both students and teachers. The test they employed was aligned with what was taught in school, and it measured students’ initial levels of understanding of personal finance so as to capture improvements in financial knowledge. Results indicated a significant increase in personal finance knowledge among the ‘treated’ students, suggesting that carefully crafted experiments can and do detect important improvements in knowledge. This is an area that would benefit from additional careful evaluative research ( Collins and O’Rourke 2010 ).

Compared to the research on schooling, evaluating workplace financial education seems even more challenging. There is evidence that employees who attended a retirement seminar were much more likely to save and contribute to their pension accounts ( Bernheim and Garrett 2003 ). Yet those who attended such seminars could be a self-selected group, since attendance was voluntary; that is, they might already have had a proclivity to save.

Another concern is that researchers have often little or no information on the content and quality of the workplace seminars. A few authors have measured the information content of the seminars ( Clark and D’Ambrosio 2008 ; Lusardi, Keller, and Keller 2008 ) and conducted pre- and post- evaluations to detect behavioral changes or intentions to change future behavior. Their findings, including in-depth interviews and qualitative analysis, are invaluable for shedding light on how to make programs more effective. One notable recent experiment involved exposing a representative sample of the U.S. population to short videos explaining several fundamental concepts including the power of interest compounding, inflation, risk diversification, all topics that most people fail to comprehend ( Heinberg, Hung, Kapteyn, Lusardi, and Yoong 2010 ). Compared to a control group who did not receive such education, those exposed to the informational videos were more knowledgeable and better able to answer hypothetical questions about saving decisions. 46 While more such research is needed, when researchers target concepts using carefully-designed experiments, they are more likely to detect changes in knowledge and behavior critical for making financial decisions.

A related challenge is that it may be difficult to evaluate empirically how actual workers’ behavior changes after an experimental treatment of the type just discussed. Goda, Manchester, and Sojourner (2012) asked whether employee decisions to participate in and contribute to their company retirement plan were affected by information about the correlation between retirement savings and post-retirement income. Since the computation involves complex relationships between contributions, investment returns, retirement ages, and longevity, this is an inherently difficult decision. In that study, employees were randomly assigned to control and treatment groups; the treatment group received an information intervention while nothing was sent to the control group. The intervention contained projections of the additional account balance and retirement income that would result from additional hypothetical contribution amounts, customized to each employee’s current age. Results showed that the treatment group members were more likely than the control group to boost their pension contributions and contribution rates; the increase was an additional 0.17 percent of salary. Moreover, the treatment group felt better informed about retirement planning and was more likely to have figured out how much to save. This experiment is notable in that it rigorously illustrates the effectiveness of interventions—even low-cost informational ones—in increasing pension participation and contributions. 47

Very promising work assessing the effects of financial literacy has also begun to emerge from developing countries. Frequently analysts have focused on people with very low financial literacy and in vulnerable subgroups which may have the most to gain. Many of these studies have also used the experimental method described above, now standard in development economics research. These studies contribute to an understanding of the mechanisms driving financial literacy as well as economic advances for financial education program participants. One example, by Carpena, Cole, Shapiro, and Zia (2011) , sought to disentangle how financial literacy programs influence financial behavior. The authors used a randomized experiment on low income urban households in India who underwent a five-week comprehensive video-based financial education program with modules on savings, credit, insurance and budgeting. They concluded that financial education in this context did not increase respondent numeracy, perhaps not surprisingly given that only four percent of respondents had a secondary education. Nevertheless, financial education did positively influence participant awareness of and attitudes toward financial products and financial planning tools.

In a related study, Cole, Giné, Tobacman, Topalova, Townsend, and Vickery (2013) found that demand for rainfall insurance was higher in villages where individuals were more financially literate. Cai, de Janvry, and Sadoulet (2013) showed that lack of financial education was a major constraint on the demand for weather insurance in rural China and that financial training could significantly improve take-up rates. Moreover, Song (2011) showed that when Chinese farmers were taught about interest compounding, it produced a sizeable increase in pension contributions. 48 This is encouraging given the evidence, even in developing countries, of lack of knowledge about interest compounding and the preliminary results on teaching this concept using videos.

In sum, while much effort has been devoted to examining the effectiveness of financial education programs in a variety of settings, relatively few studies have been informed by either a suitable theoretical model or a carefully-designed empirical approach. And since the theory predicts that not everyone will invest in financial knowledge, it is unreasonable to expect all ‘treated’ by a program will dramatically change their behavior. Moreover, a short program that is not tailored to specific groups’ needs is unlikely to make much difference. For these reasons, future analysts would do well to emulate the more recent rigorous field experiments that trace how both knowledge and behavior changes result from additional purpose-designed financial information and training.

7. Implications and Discussion

As we have shown, a relatively parsimonious set of questions measuring basic concepts such as interest compounding, inflation, and risk diversification has now become the starting point for evaluating levels of financial literacy around the world. Using these questions, researchers have demonstrated that low levels of financial knowledge are pervasive, suggesting that it will be quite challenging to provide the tools to help people function more effectively in complex financial and credit markets requiring sophisticated financial decision-making. While research in this field continues to spread, it seems clear that there are likely to be important benefits of greater financial knowledge, including savvier saving and investment decisions, better debt management, more retirement planning, higher participation in the stock market, and greater wealth accumulation. Though it is challenging to establish a causal link between financial literacy and economic behavior, both instrumental variables and experimental approaches suggest that financial literacy plays a role in influencing financial decision making, and the causality goes from knowledge to behavior.

Much work remains to be done. Very importantly, there has been no carefully-crafted cost-benefit analysis indicating which sorts of financial education programs are most appropriate, and least expensive, for which kinds of people. Some research from developing countries speaks to this point, comparing educational treatments with other approaches such as simplifying decisions ( Cole, Sampson, and Zia 2011 ; Drexel, Fischer, and Schoar 2011 ), but this remains a high priority area. In any event, the estimated aggregate costs of financial illiteracy point to possibly high returns, especially in the areas of consumer debt and debt management.

A related issue has to do with which sorts of problems are best suited to remedying through financial education, versus removing choice options from consumers’ menus altogether or simplifying the options that people face. In this vein, Thaler and Sunstein (2010) have emphasized the importance of devoting careful attention to the design of the environments in which people make choices, or the so-called ‘choice architecture.’ An important example arises in the context of employer-provided pensions, which in the past left it to individual employees to decide whether to save and how to invest their defined contribution contributions. When employers automatically enroll workers into these plans rather than let them opt in, this can dramatically increase pension participation (from less than 40 to close to 90 percent, as reported in one of the seminal work in this area, i.e., Madrian and Shea 2001 ). Several other studies also note that automatic enrollment leads to large and persistent increases in pension participation ( Choi, Laibson, and Madrian 2004 ; Choi, Laibson, Madrian and Metrick 2006 ; Thaler and Benartzi 2004 ), and better diversified portfolios ( Mitchell and Utkus 2012 ).

Moreover, in the wake of the recent financial crisis, attention has been increasingly devoted to methods of protecting people from their own financial illiteracy and inability to make informed financial decisions. The fact that unsophisticated consumers may not appreciate and take advantage of the many opportunities offered by complex financial markets leaves them at the mercy of scams ( Deevy, Lucich, and Beals 2012 ) and in turn, has given rise to protective legislation. For instance the Dodd-Frank Act of 2010, establishing the U.S. Consumer Financial Protection Bureau, had as a key goal the development of a government entity that could better protect consumers and specify uniform standards for financial products. 49 Campbell, Jackson, Madrian, and Tufano (2011) recently reviewed the theoretical and empirical consumer protection literature, making a case for consumer financial regulation. As they noted, in a system of individual responsibility where individuals must make important economic decisions instead of having governments and employers do so centrally, it will be important to reduce search costs, for example via standardized and centralized information. Similarly, for contracts or decisions that people engage in infrequently (such as buying a home or saving for retirement) and where there are few chances to learn from experience, it may be useful to structure the information provided and make it easily understood.

The debate about the role of regulation versus financial education is still ongoing. In our view, it would be useful to enhance cross-fertilization between behavioral economics and its focus on choice architecture, and the group proposing to educate people about financial basics; that is, it need not be an ‘either/or’ choice. Similar, regulation and financial education are not necessarily substitutes, as they can also complement each other. 50 As Thaler, Sunstein, and Balz (2010 : np) note: ‘choice architects do not always have the best interests of the people they are influencing in mind.’ Moreover, expanding automatic enrollment to the decumulation phase by implementing automatic annuitization of pensions upon retirement (a topic of current policy debate) might be deleterious to those having to cut consumption during their work lives and render some ineligible for government benefit programs after retirement (such as Medicaid or Supplemental Security Income). Likewise, pension plan sponsors have tended to establish very low saving targets in their default auto-enrollment arrangements, fearing that employees might not participate in their plans if the default contribution rates were high. For instance, auto-enrollment contribution rates for new hires in the paper by Madrian and Shea (2001) mentioned earlier, were set at three percent of salary, whereas a six percent contribution rate would have entitled workers to receive a 50 percent employer match. In that setting, the low default saving rate did not prod workers to take full advantage of the employer match. 51 Moreover, the three percent default set by the firm was taken by employees as a signal of a ‘suggested target’ saving level, since many of them reduced their contributions to three percent even if they had saved more previously. Additional examples of people treating the default as an employer-endorsed target include Beshears, Choi, Laibson, and Madrian (2012) , who showed that workers tended to stick to the ‘wrong’ default for long periods of time. Interestingly, those likely to do so were disproportionately low income and less educated, those likely to be the least financially literate.

The human capital approach to financial literacy suggests that there will be substantial heterogeneity in both financial knowledge and economic behavior, so it is unlikely that any one default rate or environment will enhance wellbeing for everyone. Thus if workers are carrying credit card debt or high-interest mortgages, it may be more sensible to pay off these debts rather than raise their pension contributions. Similarly, borrowing from one’s 401(k) plan may be more cost-effective for financially strapped households, versus taking out higher-cost debt elsewhere ( Lu, Mitchell, and Utkus 2010 ). And of course, only about half of the U.S. workforce is employed at firms that offer pensions, so the remaining several million employees without pensions would not benefit from automatic enrollment.

If, as argued previously, saving decisions are very complex, one way to help people save may be to find ways to simplify those decisions. For example, it could be useful to find ways to move people to action. Such a strategy is analyzed by Choi, Laibson, and Madrian (2004) , who studied the effects of Quick Enrollment, a program that gave workers the option of enrolling in the employer-provided saving plan by opting into a preset default contribution rate and asset allocation. Here, and unlike the default scenario, workers had a choice of whether or not to enroll, but the decision was much simplified as they did not need to set their contribution rates or how to allocate their assets.

Another approach designed to simplify the decision to save and, in addition, motivate employees to make an active choice involves a planning aid distributed to new hires during employee orientation ( Lusardi, Keller, and Keller 2008 ). This planning aid broke down the process of enrolling in supplementary pensions into several small steps, describing to participants what they needed to do to be able to enroll online. It also provided several pieces of information to help overcome barriers to saving, such as describing the low minimum amount of income employees can contribute (in addition to the maximum) and indicating the default fund that the employer has chosen for them (a life-cycle fund). While the program evaluation was not performed in an experimental setting, the study provided several useful insights. The qualitative data collected reveals important heterogeneity across employees, even within the same firm. Results also showed that economic incentives such as employer matches or tax advantages need not exhaust the list of options to induce people to save. The authors also concluded that employees were more prone to decision-making at some times rather than others. For example, starting a new job is a good time to think about saving, often because people must make decisions about their pension contributions.

In the developing country context, more work is also needed to assess whether simplification can help uneducated individuals make better financial decisions. This can include using simple financial instruments such as checking accounts, to more complex contracts such as insurance and decisions related to entrepreneurial activities. Early research has been promising: Drexel, Fischer, and Schoar (2011) showed that a simplified rule-of-thumb training program enhanced business practices and outcomes among microentrepreneurs in the Dominican Republic. Kast, Meier, and Pomeranz (2012) also found that self-help peer groups and text messaging boosted employee saving patterns in Chile.

An alternative method of enhancing peoples’ performance in an increasingly financially complex world might be to outsource the job, by relying on financial advice. Some have argued it is not feasible or even desirable to make everyone be a financial expert ( Willis 2008 , 2011 ). Of course financial education programs do not turn ordinary consumers into experts, just as courses on literature do not make students into professional writers. Also individuals must make many financial decisions not requiring professional advice from opening checking accounts to paying credit cards. Yet some decisions, such as saving for retirement and making investment choices, do require rather sophisticated knowledge, so turning to advisors could be desirable. In the U.S., at least, only a small fraction of households currently consults financial advisors, bankers, certified public accountants, or other such advice professionals, with most still relying on informal sources of advice ( Mitchell and Smetters 2013 ). Even among those who indicate they might be willing to use professional investment advice, two-thirds state they would probably implement only those recommendations that were in line with their own ideas ( Employee Benefit Research Institute 2007 ). In other words, financial advice might not have a large impact if individuals fail to seek out and act on the recommendations of their advisors.

Additionally, there are many different types of ‘advice professional’ credentials, each regulated by different private and/or public sector entities. Accordingly it may be difficult or even impossible for consumers to determine whether the quality of advice provided is accurate, suitable, and consistent with their own goals. For instance, advisor compensation structures sometimes are not well-aligned with household interests. And those least likely to be knowledgeable may also face obstacles in identifying good advice sources: for example, Collins (2011) and Finke (2013) argued that financial literacy and financial advice are complements rather than substitutes. 52

Relatively little is known about the effects of financial advice and whether it can improve financial decision-making. Some preliminary evidence suggests that financial counseling can be effective in reducing debt levels and delinquency rates ( Agarwal, Amromin, Ben-David, Chomsisengphet, and Evanoff 2011 ; Collins and O’Rouke 2010 ; Elliehausen, Lundquist, and Staten 2007 ; and Hirad and Zorn 2002 ). In practice, however, most people continue to rely on the help of family and friends for their financial decisions.

8. Conclusions and Remaining Questions

In the wake of the global financial crisis, policymakers around the world have expressed deep concern about widespread lack of financial knowledge. Efforts are also underway to fill these gaps with specific programs to ‘identify individuals who are most in need of financial education and the best ways to improve that education’ ( OECD 2005 ). The U.S. President’s Advisory Council on Financial Literacy ( PACFL 2008 , np) noted that ‘far too many Americans do not have the basic financial skills necessary to develop and maintain a budget, to understand credit, to understand investment vehicles, or to take advantage of our banking system. It is essential to provide basic financial education that allows people to better navigate an economic crisis such as this one.’ U.S. Federal Reserve Board Chairman Bernanke (2011 : 2) has similarly opined: ‘In our dynamic and complex financial marketplace, financial education must be a lifelong pursuit that enables consumers of all ages and economic positions to stay attuned to changes in their financial needs and circumstances and to take advantage of products and services that best meet their goals. Well-informed consumers, who can serve as their own advocates, are one of the best lines of defense against the proliferation of financial products and services that are unsuitable, unnecessarily costly, or abusive.’

Despite policy agreement on the need to fill these gaps, analysts and policymakers have much to learn about the most cost-effective ways to build financial knowledge in the population at large. The literature to date has showed that many people are financially illiterate, around the world, as we have sketched here. Econometric models and experiments have done much to confirm the causal impact of financial literacy on economic decision-making, and to separately identify this effect from other factors, including education and cognitive ability. Research on efforts to enhance financial literacy suggest that some interventions work well, but additional experimental work is critical to control for endogeneity and confirm causality.

Several key tasks remain. First, theoretical models of saving and financial decision-making must be further enriched to incorporate the fact that financial knowledge is a form of human capital. Second, efforts to better measure financial education are likely to pay off, including gathering information on teachers, training programs, and material covered. Third, outcomes beyond what have been studied to date are likely to be of interest, including borrowing for student loans, investment in health, reverse mortgage patterns, and when to claim Social Security benefits, decisions that all have far-reaching economic consequences. Additional experimental research would be useful, to learn more about the directions of causality between financial knowledge and economic wellbeing, though the early results offered here are promising. While the costs of raising financial literacy are likely to be substantial, so too are the costs of being liquidity-constrained, over-indebted, and poor.

Acknowledgments

The research reported herein was performed pursuant to a grant from the TIAA-CREF Institute; additional research support was provided by the Pension Research Council and Boettner Center at the Wharton School of the University of Pennsylvania. The authors thank the editor, Janet Currie, four anonymous referees, and Tabea Bucher-Koenen, Pierre-Carl Michaud, Maarten van Rooij, and Stephen Utkus for suggestions and comments, and Carlo de Bassa Scheresberg, Hugh Kim, Donna St. Louis, and Yong Yu for research assistance. Opinions and conclusions expressed herein are solely those of the authors and do not represent the opinions or policy of the funders or any other institutions with which the authors are affiliated.

1 See Lusardi (2011) and FINRA Investor Education Foundation (2009 and FINRA Investor Education Foundation (2012).

2 In the early 1980’s, around 40 percent of U.S. private-sector pension contributions went to DC plans; two decades later, almost 90 percent of such contributions went to retirement accounts (mostly 401(k) plans; Poterba, Venti, and Wise 2008 ).

3 See, for instance, Brown, Kapteyn, and Mitchell (2013)

4 For an older review of the saving literature see Browning and Lusardi (1996) ; recent surveys are provided by Skinner (2007) and Attanasio and Weber (2010) . A very partial list of the literature discussing new theoretical advances includes Cagetti (2003) ; Chai, Horneff, Maurer, and Mitchell (2012) ; DeNardi, French, and Jones (2011) ; French (2005 , 2008 ); Gourinchas and Parker (2002) ; Hurst and Aguiar (2005 Hurst and Aguiar (2007) ; and Scholz, Seshadri, and Khitatrakun (2006) .

5 Glewwe (2002) and Hanusheck and Woessman (2008) review the economic impacts of schooling and cognitive development.

6 Another related study is by Benitez-Silva, Demiralp, and Liu (2009) who use a dynamic life cycle model of optimal Social Security benefit claiming against which they compare outcomes to those generated under a suboptimal information structure where people simply copy those around them when deciding when to claim benefits. The authors do not, however, allow for endogenous acquisition of information.

7 This cost function is assumed to be convex, though the authors also experiment with alternative formulations, which do not materially alter results. Kézdi and Willis (2011) also model heterogeneity in beliefs about the stock market, where people can learn about the statistical process governing stock market returns, reducing transactions costs for investments. Here, however, the investment cost was cast as a simplified flat fixed fee per person, whereas Lusardi, Michaud, and Mitchell (2013) evaluate more complex functions of time and money costs for investments in knowledge.

8 There is also a minimum consumption floor; see Lusardi, Michaud, and Mitchell (2011 , 2013 ).

9 Assets must be non-negative each period and there is a nonzero mortality probability as well as a finite length of life.

10 Additional detail on calibration and solution methods can be found in Lusardi, Mitchell, and Michaud (2011 in Lusardi, Mitchell, and Michaud (2013) .

11 Initial conditions for education, earnings, and assets are derived from Panel Study of Income Dynamics (PSID) respondents age 25–30.

12 This approach could account for otherwise “unexplained” wealth inequality discussed by Venti and Wise (1998 Venti and Wise (2001) .

13 These predictions directly contradict at least one lawyer’s surmise that “[i]n an idealized first-best world, where all people are far above average, education would train every consumer to be financially literate and would motivate every consumer to use that literacy to make good choices” ( Willis 2008 ).

14 See Huston (2010) for a review of financial literacy measures.

15 For information about the HRS, see http://hrsonline.isr.umich.edu/

16 Information on the 2009 and 2012 National Financial Capability Study can be found here: http://www.usfinancialcapability.org/

17 Other financial knowledge measures include Kimball and Shumway (2006) , Lusardi and Mitchell (2009) , Yoong (2011) , Hung, Parker, and Yoong (2009) , and the review in Huston (2010) . Related surveys in other countries examined similar financial literacy concepts (see, the Dutch Central Bank Household Survey, which has investigated and tested measures of financial literacy and financial sophistication, Alessie, Van Rooij, and Lusardi 2011 ).

18 Similar findings are reported for smaller samples or specific population subgroups (see Agnew and Szykman 2011 ; Utkus and Young 2011 ).

19 The Central Bank of Austria has used these questions to measure financial literacy in ten countries in Eastern Europe and we report the findings for Romania, where financial literacy has been studied in detail ( Beckman, 2013 ). These questions have also been fielded in Mexico and Chile ( Hastings and Tejeda-Ashton 2008 ; Hastings and Mitchell 2011 ; Behrman, Mitchell, Soo and Bravo 2012 ), India and Indonesia ( Cole, Sampson, and Zia 2011 ). They have also been used to measure financial literacy among Sri Lankan entrepreneurs ( de Mel, McKenzie, and Woodruff 2008 ) and a sample of U.S.-based migrants from El Salvador ( Ashraf, Aycinena, Martinez, and Yang 2011 ). We do not report the estimates for these countries because they do not always work with representative samples of the population or use samples that can be compared with the statistics reported in Table 2 .

20 Researchers have also examined answers to questions on mathematical numeracy in the England Longitudinal Survey of Ageing (ELSA; Banks and Oldfield 2007 ), and in the Survey of Health, Ageing, and Retirement in Europe (SHARE; Christelis, Jappelli, and Padula 2010 ).

21 Their survey uses eight financial literacy questions and focuses on fundamental concepts including the three main concepts discussed earlier.

22 For more information on the Financial Literacy Framework in PISA, see: http://www.oecd.org/pisa/pisaproducts/46962580.pdf

23 In the 2008 HRS, the financial literacy questions were modified to assess the sensitivity of peoples’ answers to the way in which the questions were worded. Results confirmed sensitivity to question wording, especially for the more sophisticated financial concepts ( Lusardi, Mitchell, and Curto 2012 ). Behrman, Mitchell, Soo and Bravo (2012) developed a financial literacy index employing a two-step weighting approach, whereby the first step weighted each question by difficulty and the second step applied principal components analysis to take into account correlations across questions. Resulting scores indicated how financially literate each individual was in relation to the average and to specific questions asked. The results confirmed that the basic financial literacy questions designed by Lusardi and Mitchell (2011b ) receive the largest weights.

24 Earlier we made mention of the widespread lack of financial and economic knowledge among high school and college students. At the other end of the work life, financial literacy also declines with age, as found in the 2004 HRS module on financial literacy on people age 50+ and in many other countries ( Lusardi and Mitchell 2011b , c ).

25 While statistics are only reported for four countries in Figure 1b , the prevalence of “do not know” responses by women is found in all of the twelve countries listed in Table 2 .

26 It may be possible but untested so far that women, for example young ones, expect they would have someone later in life (a husband or companion) to take care of their finances.

27 This might also help account for the sex differences mentioned above, since in many cultures, men are more likely than women to interact daily with financially knowledgeable individuals.

28 Other studies discussing financial socialization of the young include Hira, Sabri, and Loibl (2013) and the references cited therein.

29 For a review of the role of financial literacy in the consumer behavior literature, see Hira (2010) .

30 In 2011 Americans submitted over 1.5 million complaints about financial and other fraud, up 62 percent in just three years; these counts are also likely understatements ( FTC 2012 ). Financial losses per capita due to fraud have also increased over time: the median loss per victim rose from $218 in 2002 to $537 in 2011. Similarly the SEC (2012) warns about scams and fraud and other potential consequences of very low financial literacy, particularly among the most vulnerable groups.

31 The link between financial literacy and retirement planning also robust to the measure of financial literacy used (basic versus sophisticated financial knowledge; Lusardi and Mitchell 2009 , 2011d ), how planning is measured ( Lusardi and Mitchell 2007a , 2009a , 2011b ; Alessie, van Rooij, and Lusardi 2011 ), and which controls are included in the empirical estimation ( van Rooij, Lusardi, and Alessie 2011 ).

32 The alternative financial services (AFS) industry has experienced tremendous growth in the United States: in 2009, the Federal Deposit Insurance Corporation estimated the industry to be worth at least $320 billion in terms of transactional services ( FDIC 2009 ).

33 Disney and Gathergood (2012) reported that UK consumer credit customers systematically underestimated the cost of borrowing, while the least financially literate had higher average debt-to-income ratios.

34 Americans paid about $8 billion in finance charges to borrow more than $50 billion from payday lenders in 2007; the annual interest rates on such loans are often very high, over 400%. See Bertrand and Morse (2011) and the references therein.

35 See for instance Laibson (2011) .

36 See for instance Ameriks, Caplin, and Leahy (2003) ; van Rooij, Lusardi, and Alessie (2012) ; and Lusardi and Mitchell (2007a , b ; 2009 ). It is worth noting that education also plays a role, as pointed out by Poterba, Venti, and Wise (2013) who find a substantial association between education and the post-retirement evolution of assets. For example, for two-person households, assets growth between 1998 and 2008 was greater for college graduates than for those with less than a high school degree, producing over $600,000 in assets for the richest quintile, to $82,000 for the lowest asset quintile. As in the theoretical model described previously, households with different levels of education will invest in different assets, allowing them to earn different rates of return. It remains to be seen whether this is because of differential financial literacy investments, or simply due to general knowledge gleaned through education.

37 Gustman, Steinmeier, and Tabatabai (2010) note that financial knowledge is not the same thing as cognitive functioning, since the latter is not associated with greater knowledge of retirement plan rules.

38 Several authors have also linked financial literacy and knowledge about retirement saving. For instance, Agnew, Szykman, Utkus, and Young (2007) show that employees who were the least financially knowledgeable were 34 percent less likely to participate voluntarily, and 11 percent less likely to be automatically enrolled, in their in their company’s 401(k) plan.

39 These findings are not attributable to differences in individuals’ subjective life expectancies, discount rates, risk aversion, borrowing constraints, political risk, or other conventional explanations ( Brown, Kapteyn, Luttmer, and Mitchell 2011 ).

40 These include credit card balance transfers; home equity loans and lines of credit; auto loans; credit card interest rates; mortgages; small business credit cards; credit card late-payment fees; credit card over-limit fees; and credit card cash-advance fees.

41 This could be particularly important inasmuch as Korniotis and Kumar (2011) find that cognitive decline is fastest with age for the less educated, lower earners, and minority racial/ethnic groups.

42 Part of this behavior could also be due to liquidity constraints.

43 See for instance Collins and O’Rourke (2010) ; Gale, Harris and Levine (2012) ; Hastings, Madrian, and Skimmyhorn (2012) ; Hathaway and Khatiwada (2008) ; Lusardi and Mitchell (2007b ); Lyons, Palmer, Jayaratne, and Scherpf (2006) ; and Martin (2007) . Hira (2010) provides a broad overview of research on financial education over a long time span.

44 Two good discussions by Fox, Bartholomae, and Lee (2005) and Lyons and Neelakantan (2008) highlight the limitations of existing financial education program evaluations.

45 Moreover, practitioner discussions often refer to ‘financial capability,’ a term often identified with behavior change rather than knowledge.

46 The difference in the knowledge of risk diversification, tax benefits of retirement accounts, and the benefits of employers’ matches between the two groups (measured by the proportion of correct answers) was on the order of 10 percentage points. While these videos were targeted to young adults, older respondents who viewed them also increased knowledge and capacity to correctly answer questions concerning saving decisions ( Heinberg, Hung, Kapteyn, Lusardi, and Yoong, 2010 ).

47 A discussion of successful strategies to improve financial literacy and financial education programs is provided in Crossan (2011)

48 For as broad perspective on how financial education programs can be made more effective in developing countries see Holzmann (2011) .

49 Among other things, the Bureau’s mandate is to promote financial education and monitor financial markets for new risks to consumers; see http://www.consumerfinance.gov/the-bureau/ .

50 For instance, the Director of the Consumer Financial Protection Bureau, Richard Cordray, has been a strong supporter of financial education in high school and in the workplace.

51 Note, however, that when left to their own devices, many employees simply fail to enroll in pensions and hence fail to exploit the employer match at all , if or when one is available.

52 A detailed analysis of the issues surrounding financial advice appears in Mitchell and Smetters (2013) .

Contributor Information

Annamaria Lusardi, The George Washington University School of Business, Duques Hall, Suite 450E, Washington, DC 20052, Tel: (202) 994-8410.

Olivia S. Mitchell, Department of Insurance & Risk Management, The Wharton School, Univ. of Pennsylvania, 3620 Locust Walk, St. 3000 SH-DH, Philadelphia, PA 19104, Tel: (215) 898-0424.

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How to Promote Financial Literacy Within Your Institution

In last month’s blog , we introduced the concept of institutional financial literacy: the ability of faculty and staff across the institution to understand where the institution stands at any given time with respect to key elements of its financial position as measured on its balance sheet and income statement. Financial literacy cultivates a common understanding of financial health that provides context for leadership’s decisions and a common language to address issues. It is also an essential tool for cultivating the next generation of campus leaders, who must understand that academic growth and strategic initiatives cannot succeed without sufficient financial resources to support them.

Given the importance of institutional financial literacy, why is it uncommon to find it on most college and university campuses? The answer often lies in assumptions on both the financial and academic sides of the institution. These assumptions can be summarized in two simple questions. On the financial side, the question is, “Why do I need to share?” On the academic side, the question is, “Why do I need to care?”

The need to share—and care—about financial information

Finance officers may be reluctant to share financial data for several reasons. Finance is by its nature risk adverse; sharing financial information opens the possibility for misinterpretation of that information. Finance officers may also believe that faculty and staff are simply not interested in the information, especially if it conveys the need to limit spending. Faculty may, in fact, have the mindset that finance officers want to keep them from spending (just as finance officers may have the mindset that faculty do not want to hear about financial limitations).

To move beyond these mindsets—which reinforce the “why do I need to share” and “why do I need to care” questions—requires a leap of faith on both sides. Finance officers need to understand that without transparency around financial information, and a frank assessment of where the institution stands financially, faculty members cannot be expected to think about their role in ensuring the institution’s long-term sustainability. And faculty members must understand that financial information is not meant to block their ideas for growth or new strategic initiatives, but to demonstrate why those ideas must be supported by sufficient resources to enable them to become a reality.

The need to overcome a resistance to sharing and caring about financial information is particularly acute if the institution is facing a gap between its expenses and available resources. If finance does not share the existence of that gap, the gap is likely to become even wider. And if faculty do not understand the need to take action to help to close the gap, their programs and positions may become even more vulnerable to reductions or elimination.

Promoting financial literacy

Although finance is the source of the information that promotes financial literacy, it does not have sole responsibility for the success of a financial literacy initiative. Other members of the leadership team (including the president and provost), the board of trustees, and department heads must also be committed to promoting the effort.

Last month’s blog identified five financial “vital signs” that should be the focus of a financial literacy effort: unrestricted cash, revenue, expenses, debt, and risk. Not all the metrics used to report on these vital signs will be purely financial: enrollment and retention numbers, for example, will be key metrics to describe revenue and risk. The most important thing is to use the same metrics consistently, report on them regularly, and explain whether movement in the metrics is good or bad for the institution.

For finance officers, a simplified version of a rating action report from one of the rating agencies can serve as a template for financial literacy reporting. These reports draw upon key metrics to support the rationale for the rating, and then identify factors that could lead to a rating upgrade or a rating downgrade. Similarly, a financial literacy report can describe the key metrics for each of the institution’s vital signs, indicate whether there has been a positive or negative change in these metrics from the last report, and use these metrics and trends to define a current state of financial health (e.g., declining, stable, or improving). It can then identify what factors, over the long term, could improve or impair the institution’s financial health. In the simplest terms, the report could identify which long-term trends would make the institution happy, and which would make it sad.

Most importantly, a financial literacy report should identify which actions could make long-term trends more likely to result in a happy outcome for the institution. Ideally, these actions will link back to the institution’s strategic plan. And the report should also identify what financial results will be required from these actions—again, ideally linked back to the institution’s financial plan—to make the strategic plan a reality.

Promoting financial literacy thus serves two important purposes. It makes everyone aware of the institution’s current financial health, and whether that health is holding stable, improving, or declining. And it makes everyone aware of what will be required to ensure the institution’s financial health over the long term.

The worst possible outcome is for awareness of an institution’s financial health to come only when it is too late for a recovery. No matter what an institution’s financial health is today, promoting financial literacy helps to ensure that changes to that health will be known to all and addressed in a timely and effective manner.

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Expert Advice on Financial Literacy for First-Generation College Students

In today’s rapidly changing financial landscape, understanding personal finance is crucial for everyone, especially first-generation college students. This knowledge is essential not only for managing everyday expenses but also for choosing meaningful research paper topics in finance and other academic fields. Mastering financial literacy is a key factor in their success throughout college and into their future careers.

This article will highlight the importance of financial literacy, explain fundamental financial concepts, and provide expert advice and resources to help first-generation college students manage their finances effectively.

Key Financial Concepts Every Student Should Know

Before diving into the intricacies of budgeting and financial planning, it is essential for first-generation college students to understand some fundamental financial concepts:

Income and Expenses: Understanding the importance of tracking income and expenses is crucial for effective financial management. Students should be aware of their income sources, such as part-time jobs or financial aid, and their monthly expenses, including rent, tuition, textbooks, and other necessary items.
Budgeting: Creating a budget helps students allocate their income towards different expense categories. It provides a clear picture of their financial situation and allows them to identify areas where they can cut back on unnecessary spending.
Student Loans and Grants: Familiarity with the terms and conditions of student loans and grants is crucial to making informed decisions about borrowing money for education. Students should understand the interest rates, repayment plans, and potential consequences of defaulting on loans.

Building a Solid Financial Foundation

Budgeting basics for college students.

One of the most important skills for first-generation college students to acquire is budgeting. Budgeting not only allows students to manage their daily expenses but also helps them develop financial discipline. Here are some basic steps to creating an effective budget:

Track your income and expenses: Keep a record of all your income sources, such as part-time jobs or scholarships, and track your monthly expenses. This will help you understand where your money is going and identify areas where you can cut back.
Create spending categories: Divide your expenses into categories such as housing, transportation, food, and entertainment. Assign a specific portion of your income to each category based on your priorities.
Set savings goals: It’s crucial to allocate a portion of your income towards savings. Whether it’s for emergencies or future goals, saving regularly will provide you with a financial safety net and help you achieve your long-term objectives.

Understanding Student Loans and Grants

For many first-generation college students, student loans and grants are essential for financing their education. Understanding the different types of loans and grants available can help students make informed decisions and minimize their debt burden. Here are some key points to consider:

Types of loans: Students should be familiar with both federal and private student loan options. Federal loans typically offer lower interest rates and more flexible repayment options, while private loans may have higher interest rates but provide additional funding when federal loans fall short.
Repayment options: Different repayment options are available for student loans, such as standard repayment, income-driven repayment plans, and loan forgiveness programs. It’s crucial for students to understand these options and choose the one that best suits their financial situation.
Grants and scholarships: Students should actively search for grants and scholarships to reduce their reliance on loans. These forms of financial aid do not require repayment and can significantly lower the overall cost of education.

Expert Advice on Managing College Finances

Tips for minimizing student debt.

One of the main concerns for first-generation college students is the accumulation of debt. Here are some expert tips to minimize student debt:

Explore all financial aid options: Research and apply for scholarships, grants, and work-study programs to lower the need for loans.
Live frugally: Adopting a minimalist lifestyle and cutting unnecessary expenses can significantly reduce the need for additional borrowing.
Consider community college or trade school: Starting at a community college or pursuing a trade can be a more affordable alternative to a traditional four-year university.

Making the Most of Financial Aid

Navigating the world of financial aid can be challenging. Here are some tips to ensure first-generation college students make the most of their financial aid:

Complete the Free Application for Federal Student Aid (FAFSA): The FAFSA is essential for determining eligibility for federal grants, loans, and work-study programs. Be sure to complete it accurately and before the deadline.
Research institutional aid: Many colleges and universities offer institutional grants and scholarships. Research and apply for these additional sources of financial support.
Stay informed: Regularly check your financial aid package and be aware of any changes or requirements. Keep in touch with your school’s financial aid office for any updates or questions.

Resources for Enhancing Financial Literacy

Online tools for financial planning.

With advancements in technology, numerous online tools and apps can help first-generation college students manage their finances effectively. Here are some popular options:

Mint: Mint is a free online budgeting tool that allows users to track their income, expenses, and savings goals in one place. It provides visual representations and alerts to help users stay on top of their finances.
You Need a Budget: You Need a Budget, commonly known as YNAB, offers a comprehensive budgeting system that focuses on allocating every dollar towards specific categories. YNAB provides detailed reports and guides users toward financial stability.

Books and Courses on Financial Literacy

Reading books and taking courses on financial literacy can provide first-generation college students with in-depth knowledge and practical skills. Here are some recommended resources:

Book: “I Will Teach You to Be Rich” by Ramit Sethi
Course: “Personal Finance for Dummies” on Udemy

Future Financial Planning for College Students

Importance of saving and investing early.

While college is a time of limited resources, it’s never too early for first-generation college students to start thinking about long-term financial planning. Here’s why saving and investing early is crucial:

Compound interest: By starting to save and invest early, students can benefit from the power of compound interest. Even small contributions can grow significantly over time.
Financial goals: Saving and investing early allows students to set and achieve specific financial goals, such as saving for a down payment on a house or starting a retirement fund.

Preparing for Post-College Financial Responsibilities

As graduation approaches, first-generation college students need to be prepared for post-college financial responsibilities. Here are some key points to consider:

Student loan repayment: Understand the grace period and repayment terms of your student loans. Create a plan to manage your loan payments effectively.
Building an emergency fund: Start setting aside funds for unexpected expenses. An emergency fund provides a safety net against financial setbacks.
Invest in retirement: Consider opening a retirement account or contributing to an employer-sponsored retirement plan, such as a 401(k), to secure your financial future.

In Conclusion

Financial literacy is a critical skill for first-generation college students to develop. By understanding the importance of financial literacy, building a solid financial foundation, seeking expert advice, and utilizing available resources, these students can navigate the complexities of college finance effectively. Armed with the knowledge and tools necessary to make sound financial decisions, first-generation college students can pave the way for a successful future.

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Expert Advice on Financial Literacy for First-Generation College Students

Posted on June 4, 2024

Key Financial Concepts Every Student Should Know

Before diving into the intricacies of budgeting and financial planning, it is essential for first-generation college students to understand some fundamental financial concepts:

Income and Expenses: Understanding the importance of tracking income and expenses is crucial for effective financial management. Students should be aware of their income sources, such as part-time jobs or financial aid, and their monthly expenses, including rent, tuition, textbooks, and other necessary items.
Budgeting: Creating a budget helps students allocate their income towards different expense categories. It provides a clear picture of their financial situation and allows them to identify areas where they can cut back on unnecessary spending.
Student Loans and Grants: Familiarity with the terms and conditions of student loans and grants is crucial to making informed decisions about borrowing money for education. Students should understand the interest rates, repayment plans, and potential consequences of defaulting on loans.

Building a Solid Financial Foundation

Budgeting basics for college students.

Track your income and expenses: Keep a record of all your income sources, such as part-time jobs or scholarships, and track your monthly expenses. This will help you understand where your money is going and identify areas where you can cut back.
Create spending categories: Divide your expenses into categories such as housing, transportation, food, and entertainment. Assign a specific portion of your income to each category based on your priorities.
Set savings goals: It’s crucial to allocate a portion of your income towards savings. Whether it’s for emergencies or future goals, saving regularly will provide you with a financial safety net and help you achieve your long-term objectives.

Understanding Student Loans and Grants

Types of loans: Students should be familiar with both federal and private student loan options. Federal loans typically offer lower interest rates and more flexible repayment options, while private loans may have higher interest rates but provide additional funding when federal loans fall short.
Repayment options: Different repayment options are available for student loans, such as standard repayment, income-driven repayment plans, and loan forgiveness programs. It’s crucial for students to understand these options and choose the one that best suits their financial situation.
Grants and scholarships: Students should actively search for grants and scholarships to reduce their reliance on loans. These forms of financial aid do not require repayment and can significantly lower the overall cost of education.

Expert Advice on Managing College Finances

Tips for minimizing student debt.

One of the main concerns for first-generation college students is the accumulation of debt. Here are some expert tips to minimize student debt:

Explore all financial aid options: Research and apply for scholarships, grants, and work-study programs to lower the need for loans.
Live frugally: Adopting a minimalist lifestyle and cutting unnecessary expenses can significantly reduce the need for additional borrowing.
Consider community college or trade school: Starting at a community college or pursuing a trade can be a more affordable alternative to a traditional four-year university.

Making the Most of Financial Aid

Navigating the world of financial aid can be challenging. Here are some tips to ensure first-generation college students make the most of their financial aid:

Complete the Free Application for Federal Student Aid (FAFSA): The FAFSA is essential for determining eligibility for federal grants, loans, and work-study programs. Be sure to complete it accurately and before the deadline.
Research institutional aid: Many colleges and universities offer institutional grants and scholarships. Research and apply for these additional sources of financial support.
Stay informed: Regularly check your financial aid package and be aware of any changes or requirements. Keep in touch with your school’s financial aid office for any updates or questions.

Resources for Enhancing Financial Literacy

Online tools for financial planning.

With advancements in technology, numerous online tools and apps can help first-generation college students manage their finances effectively. Here are some popular options:

Mint: Mint is a free online budgeting tool that allows users to track their income, expenses, and savings goals in one place. It provides visual representations and alerts to help users stay on top of their finances.
You Need a Budget: You Need a Budget, commonly known as YNAB, offers a comprehensive budgeting system that focuses on allocating every dollar towards specific categories. YNAB provides detailed reports and guides users toward financial stability.

Books and Courses on Financial Literacy

Reading books and taking courses on financial literacy can provide first-generation college students with in-depth knowledge and practical skills. Here are some recommended resources:

Book: “I Will Teach You to Be Rich” by Ramit Sethi
Course: “Personal Finance for Dummies” on Udemy

Future Financial Planning for College Students

Importance of saving and investing early.

Compound interest: By starting to save and invest early, students can benefit from the power of compound interest. Even small contributions can grow significantly over time.
Financial goals: Saving and investing early allows students to set and achieve specific financial goals, such as saving for a down payment on a house or starting a retirement fund.

Preparing for Post-College Financial Responsibilities

As graduation approaches, first-generation college students need to be prepared for post-college financial responsibilities. Here are some key points to consider:

Student loan repayment: Understand the grace period and repayment terms of your student loans. Create a plan to manage your loan payments effectively.
Building an emergency fund: Start setting aside funds for unexpected expenses. An emergency fund provides a safety net against financial setbacks.
Invest in retirement: Consider opening a retirement account or contributing to an employer-sponsored retirement plan, such as a 401(k), to secure your financial future.

In Conclusion

IMAGES

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VIDEO

Past Papers 2022: Maths Literacy: Paper 1: Question 4.1
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The Importance of Financial Literacy

COMMENTS

The importance of financial literacy and its impact on financial
In this editorial, we provided an overview of the papers in the inaugural issue of the Journal of Financial Literacy and Wellbeing. They cover topics that are at the center of academic research, from the effects of financial education in school and the workplace to the importance of financial literacy for the macro-economy.
Financial literacy and the need for financial education: evidence and
As the research discussed in this paper well documents, financial literacy is like a global passport that allows individuals to make the most of the plethora of financial products available in the market and to make sound financial decisions. ... Financial literacy and high-cost borrowing in the United States, NBER Working Paper n. 18969, April ...
A Study on Financial Literacy and Financial Behaviour
Financial literacy helps individuals make more. assertive and e fficient decisions in the monetary context of their lives. This paper measures. the level of financial literacy of individuals and ...
PDF The Economic Importance of Financial Literacy: Theory and Evidence
In this paper, we undertake an assessment of the rapidly growing body of 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
Financial literacy and the need for financial education: evidence and
PDF | On Dec 1, 2019, Annamaria Lusardi published Financial literacy and the need for financial education: evidence and implications | Find, read and cite all the research you need on ResearchGate
Mapping Financial Literacy: A Systematic Literature Review of ...
A large number of authors who have been involved in financial literacy research in the last few decades refer to Ajzen Icek's Theory of Planned Behavior published in 1991 , which can be seen as the theory on which financial literacy is founded on. The paper from Chen and Volpe in 1998 is the first relevant paper about personal financial ...
Financial Literacy among College Students: An Empirical Analysis
This paper examines the efficacy of learning sources associated with financial literacy in young adults. We survey nearly 1,500 college undergraduate students entering classes where financial ...
Financial Literacy and Financial Education: An Overview
Financial Literacy and Financial Education: An Overview. Tim Kaiser & Annamaria Lusardi. Working Paper 32355. DOI 10.3386/w32355. Issue Date April 2024. This article provides a concise narrative overview of the rapidly growing empirical literature on financial literacy and financial education. We first discuss stylized facts on the demographic ...
Financial literacy: A systematic review and bibliometric analysis
The International Journal of Consumer Studies is a leading international consumer research journal. ... followed by a comprehensive analysis of the content of 107 papers in the identified clusters. The three major themes enumerated are—levels of financial literacy amongst distinct cohorts, the influence that financial literacy exerts on ...
The Importance of Financial Literacy: Opening a New Field
The Importance of Financial Literacy: Opening a New Field. Annamaria Lusardi & Olivia S. Mitchell. Working Paper 31145. DOI 10.3386/w31145. Issue Date April 2023. We undertake an assessment of our two decades of research on financial literacy, building on our empirical research and theoretical work casting financial knowledge as a form of ...
Full article: Role of financial literacy in achieving financial
With the need for this research clearly established, the current study formally attempts: 1) To combine the literature at the intersection of financial literacy and financial inclusion through a systematic mapping study and literature review; 2) To study the evolution of financial literacy, and financial inclusion in empirical literature; 3) To ...
Financial literacy in the digital age—A research agenda
While much of the prior research on financial literacy and personal money management was developed in a traditional analog world, it may no longer be compatible with the new and more complex financial landscape created by the pervasive diffusion of digital technologies. ... Finally, the third theme includes nine papers and describes research on ...
The interplay of skills, digital financial literacy, capability, and
This paper examines the mediating effects of digital financial literacy, financial autonomy, financial capability, and impulsivity on financial decision making and perceived financial well-being. The data come from 512 respondents in Delhi/NCR (National Capital Region), India, using a snowball-sampling technique and partial least squares ...
Financial Literacy and the Need for Financial Education: Evidence and
Thus, financial literacy refers to both knowledge and financial behavior, and this paper will analyze research on both topics. As I describe in more detail below, findings around the world are sobering. Financial literacy is low even in advanced economies with well-developed financial markets.
Knowledge creates value: the role of financial literacy in ...
This paper scrutinizes the ramifications of financial literacy on household entrepreneurial behavior utilizing data from China's sample of the China Household Finance Survey spanning the years ...
Financial literacy, financial advice, and financial behavior
First, the majority of research on financial literacy has been conducted with a geographic focus on the U.S. and there is far less evidence available for Europe, e.g. for Germany. ... 19 out of the 20 most cited papers focus on financial decisions of households, the only exception being McDaniel et al. ...
Financial literacy and responsible finance in the FinTech era
The papers in this special issue of the European Journal of Finance inform the current educational and policy agenda regarding developments in financial-literacy research, and the role of financial technology in enhancing financial capability within a responsible finance framework.
Financial Literacy, Financial Education and Economic Outcomes
In this paper, we have evaluated the literature on financial literacy, financial education, and consumer financial outcomes. This literature consistently finds that many individuals perform poorly on test-based measures of financial literacy. These findings, coupled with a growing literature on consumers' financial mistakes and documenting a ...
The Economic Importance of Financial Literacy: Theory and Evidence
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. ... (World Bank Working Paper). Financial Literacy for High School Students and Their Parents: Evidence from Brazil ...
(PDF) FINANCIAL LITERACY: FROM THEORY TO PRACTICE
According to Sudakova (2017), financial literacy is knowledge and beliefs that can influence a person's decision-making and financial planning. However, financial literacy in people aged 18-25 is ...
PDF Financial Literacy around the World
Policy Research Working Paper 6107. Financial literacy programs are fast becoming a key ingredient in financial policy reform worldwide. Yet, what is financial literacy exactly and what do we know of its effectiveness? This paper collects insights from the literature thus far and summarizes global evidence
Financial literacy in Canada: how does it affect retirement?
This paper examines financial literacy in Canada using a dataset from early 2023 that measures the knowledge of middle-aged Canadians regarding their retirement income system. We first document important financial literacy differences across gender, age, education, and labor market status. ... Research is her life's work and by combing her ...
The Influence of Financial Literacy on Green Investment Decisions
This research aims to determine the influence of financial literacy on green investment decisions. The research sample for part of the Z generation in Yogyakarta was 100 respondents. The data analysis technique used was purposive sampling. The data analysis technique uses simple linear regression analysis. The research results show that financial literacy influences green investment decisions.
How to Promote Financial Literacy Within Your Institution
Senior Vice President. Contact Expert. Promoting financial literacy serves two important purposes. First, it makes everyone aware of the institution's current financial health. Second, it makes everyone aware of what will be required to ensure the institution's financial health over the long term.
(PDF) FINANCIAL LITERACY AMONG UNIVERSITY STUDENTS
Findings shows that respondents' financial literacy was low (56.08%) which is a cause for concern and that there were substantial disparities based on socioeconomic as well as demographic factors ...
Expert Advice on Financial Literacy for First-Generation College
This knowledge is essential not only for managing everyday expenses but also for choosing meaningful research paper topics in finance and other academic fields. Mastering financial literacy is a ...
Expert Advice on Financial Literacy for First-Generation College
In today's rapidly changing financial landscape, understanding personal finance is crucial for everyone, especially first-generation college students. This knowledge is essential not only for managing everyday expenses but also for choosing meaningful research paper topics in finance and other academic fields. Mastering financial literacy is a key factor in their success throughout college ...
PDF Financial Literacy, Financial Education and Economic Outcomes National
NBER WORKING PAPER SERIES FINANCIAL LITERACY, FINANCIAL EDUCATION AND ECONOMIC OUTCOMES Justine S. Hastings Brigitte C. Madrian ... NATIONAL BUREAU OF ECONOMIC RESEARCH 1050 Massachusetts Avenue Cambridge, MA 02138 September 2012 We acknowledge financial support from the National Institute on Aging (grants R01-AG-032411-01, A2R01-AG-021650 and ...

Financial literacy and the need for financial education: evidence and implications

1 Introduction

2 How financially literate are people?

2.2 Cross-country comparison

2.3 Who knows the least?

3 Does financial literacy matter?

4 The way forward for financial literacy and what works

5 Concluding remarks

Abbreviations

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Financial Literacy and the Need for Financial Education: Evidence and Implications

Knowledge creates value: the role of financial literacy in entrepreneurial behavior

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Literature review

Entrepreneurial behavior

Methodology

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Empirical results

Robustness checks

Heterogeneity analysis

Gender differences

Potential mechanism analysis

Social network channels

Risk attitude channels

Further analysis: the role of financial education

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1 Introduction

2 Measuring financial literacy

2.1.1 Definitions of financial literacy

2.1.2 Cognitive abilities versus financial literacy

2.2 Test-based measures of financial literacy

2.2.1 The Big Three

2.2.2 Beyond the Big Three

2.2.3 Caveats of test-based financial literacy measures

2.3 Self-assessed financial literacy

2.4 Proxies for financial literacy

2.4.2 Outcomes-based proxies

3 Financial literacy around the world

3.1 Financial literacy of adult consumers