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on Financial Literacy and Education |
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Issue of 2020‒12‒21
five papers chosen by |
| By: | Georgios A. Panos; Tatja Karkkainen; Adele Atkinson |
| Abstract: | We examine the relationship between financial literacy and attitudes to cryptocurrencies, using microdata from 15 countries. Our financial literacy proxy exerts a large negative effect on the probability of currently owning cryptocurrencies. The financially literate are also more likely to be aware of cryptocurrencies, and more likely to report that they do not intend to own them. We confirm the external validity of our financial literacy proxy and findings using data from a second novel survey of retail investors in 3 Asian countries. More financially literate retail investors are more likely not to have held any cryptocurrencies. We show that the relationship between financial literacy and attitudes to cryptocurrencies is moderated by a different perception of the financial risk involved in cryptocurrencies versus alternative instruments by the more financially literate. Our findings shed light on the demand for cryptocurrencies among the general population and suggest that it is largely driven by unsophisticated users. |
| Keywords: | Financial Literacy, Cryptocurrencies, Attitudes, Bitcoin, Financial Risk |
| JEL: | B26 D18 E41 G11 G53 |
| Date: | 2020–11 |
| URL: | http://d.repec.org/n?u=RePEc:gla:glaewp:2020_26&r=all |
| By: | Marco Angrisani; Jeremy Burke; Annamaria Lusardi; Gary Mottola |
| Abstract: | We administered the FINRA Foundation’s National Financial Capability Study questionnaire to members of the RAND American Life Panel (ALP) in 2012 and 2018. Using this unique, longitudinal data set, we investigate the evolution of financial literacy over time and shed light on the causal effect of financial knowledge on financial outcomes. Over a six-year observation period, financial literacy appears to be rather stable, with a slight tendency to decline at older ages. Moreover and importantly, financial literacy has significant predictive power for future financial outcomes, even after controlling for baseline outcomes and a wide set of demographics and individual characteristics that influence financial decision making. This estimated relationship is significantly stronger for older individuals, for women, and for those with lower income than for their counterparts in the study. Altogether, our findings suggest that differences in the stock of financial knowledge may lead to increasing inequality over the life course. |
| JEL: | D14 G51 G53 |
| Date: | 2020–11 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:28125&r=all |
| By: | Florian Exler; Igor Livshits; James MacGee; Michèle Tertilt |
| Abstract: | There is active debate over whether borrowers’ cognitive biases create a need for regulation to limit the misuse of credit. To tackle this question, we incorporate overoptimistic borrowers into an incomplete markets model with consumer bankruptcy. Lenders price loans, forming beliefs—type scores—about borrowers’ types. Since over-optimistic borrowers face worse income risk but incorrectly believe they are rational, both types behave identically. This gives rise to a tractable theory of type scoring as lenders cannot screen borrower types. Since rationals default less often, the partial pooling of borrowers generates cross-subsidization whereby overoptimists face lower than actuarially fair interest rates. Over-optimists make financial mistakes: they borrow too much and default too late. We calibrate the model to the US and quantitatively evaluate several policies to address these frictions: reducing the cost of default, increasing borrowing costs, imposing debt limits, and providing financial literacy education. While some policies lower debt and filings, they do not reduce overborrowing. Financial literacy education can eliminate financial mistakes, but it also reduces behavioral borrowers’ welfare by ending crosssubsidization. Score-dependent borrowing limits can reduce financial mistakes but lower welfare. |
| Keywords: | Consumer Credit, Over-Optimism, Financial Mistakes, Bankruptcy, Financial Literacy, Financial Regulation, Type Score, Cross-Subsidization |
| JEL: | E21 E49 G18 K35 |
| Date: | 2020–11 |
| URL: | http://d.repec.org/n?u=RePEc:bon:boncrc:crctr224_2020_245&r=all |
| By: | Simplice A. Asongu (Yaounde, Cameroon); Rexon T. Nting (University of Wales, London, UK) |
| Abstract: | The study has investigated the comparative importance of financial access in promoting gender inclusion in African countries. Gender inclusion is proxied by the female labour participation rate while financial channels include: financial system deposits and private domestic credit. The empirical evidence is based on non-contemporary Fixed Effects regressions. In order to provide more implications on comparative relevance, the dataset is categorised into income levels (middle income versus (vs.) low income); legal origins (French civil law vs. English common law); religious domination (Islam vs. Christianity); openness to sea (coastal vs. landlocked); resource-wealth (oil-poor vs. oil-rich) and political stability (stable vs. unstable). Six main hypotheses are tested, notably, that middle income, English common law, Christianity, coastal, oil-rich and stable countries enjoy better levels of “financial access†-induced gender inclusion compared to respectively, low income, French civil law, Islam, landlocked, oil-poor and unstable countries. All six tested hypothesis are validated. This is the first study on the comparative importance of financial access in gender economic participation. |
| Keywords: | Inequality; Gender Inclusion; Financial development; Africa |
| JEL: | I30 L96 O16 O55 |
| Date: | 2020–01 |
| URL: | http://d.repec.org/n?u=RePEc:agd:wpaper:20/089&r=all |
| By: | Georgios A. Panos; Theocharis Kromydas; Michael Osborne; Robert E. Wright |
| Abstract: | Literacy is a multi-dimensional concept. In this chapter, seven potential dimensions of literacy are considered: (1) Mathematical literacy, (2) Foreign language literacy, (3) Digital literacy, (4) Financial literacy, (5) Political literacy, (6) Environmental literacy, and (7) Health literacy. Data from the Glasgow-based Integrated Multimedia City Data (iMCD) project included information that allows for the operationalization of these dimensions. Multiple-regression analysis is used to explore the correlates of these dimensions of literacy. One key finding is that there are gender differences in all the dimensions of literacy. There are large advantages in favour of males with respect to political, digital, financial, and environmental literacy, health and mathematical literacy. The only advantage in the favour of females is foreign language literacy. |
| JEL: | G53 I22 O33 Z13 |
| Date: | 2020–10 |
| URL: | http://d.repec.org/n?u=RePEc:gla:glaewp:2020_27&r=all |