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on Financial Literacy and Education |
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Issue of 2024‒09‒02
seven papers chosen by Viviana Di Giovinazzo, Università degli Studi di Milano-Bicocca |
| By: | Ozili, Peterson K |
| Abstract: | This article presents a concise review of the existing financial inclusion research in India. We use a thematic literature review methodology. We show that the Reserve Bank of India (RBI) has been at the forefront of financial inclusion in India and has used collaborative efforts to deepen financial inclusion in India. The review of existing literature shows that the major determinants of financial inclusion in India are income, age, gender, education, employment, ICT, bank branch network and nearness to a bank. The common theories used to analyse financial inclusion in India are the finance-growth theory, the diffusion of innovations theory, development economics and modernization theory, the vulnerable group theory of financial inclusion and the dissatisfaction theory of financial inclusion. The common methodologies used in the literature are surveys, questionnaires, financial inclusion index, regression estimations and causality tests. Existing studies also show that financial inclusion in India affects the level of poverty, human development, financial stability, monetary policy, and income level. Some criticisms of the financial inclusion efforts in India include the inability to meet the specific needs of the poor, poor geographical access, excessive transaction cost, inappropriate banking products, financial illiteracy and a large digital divide between tech savvy and non-tech savvy people. We also suggest some areas for future research. |
| Keywords: | ICT, Internet, financial inclusion, literature review, access to finance, causality tests, regression, India, index, theory. |
| JEL: | G20 G21 O31 |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:121526 |
| By: | Josep Gisbert (IE UNIVERSITY); José E. Gutiérrez (BANCO DE ESPAÑA) |
| Abstract: | The rise of FinTech lenders offers an opportunity to promote financial access but may disrupt banks’ banking efforts. This paper presents a banking model where an incumbent bank specializes in certain niche markets. When a FinTech lender enters, competition intensifies, reducing the bank’s gains from serving some of its niches. Although FinTech lending can help serve certain unattended niches, the bank may abandon others, creating an ambiguous impact on financial inclusion. Financial inclusion may even decline when the FinTech lender is less efficient at serving new niches and better able to compete with the bank for its customers. |
| Keywords: | FinTech, financial inclusion, soft information, regulatory arbitrage, economic growth |
| JEL: | G21 G23 G28 |
| Date: | 2024–08 |
| URL: | https://d.repec.org/n?u=RePEc:bde:wpaper:2426 |
| By: | Nidhaleddine Ben Cheikh; Christophe Rault |
| Abstract: | While the financial inclusion would induce greater pollutant emissions through its impact of economic activity, the increased access to financial services may unleash investments in green technologies. This papier investigates whether the financial inclusion influences the dynamic of carbon dioxide (CO2) emissions in a sample of 70 countries during the last decade. We implement panel threshold techniques to explore the possible regime shifts in the environmental quality. Our results reveal that an increased financial access impacts air pollution depending on the level of economic development. While financial inclusion would increase CO2 emissions under lower-income regimes, the environment quality seems to be enhanced with more inclusiveness at later stages of development. Sounder environmental policies are needed for less developed countries to align financial inclusion initiatives with sustainable economic development. |
| Keywords: | financial inclusion, carbon emissions, panel threshold modelling |
| JEL: | C23 O16 O44 Q53 Q56 |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_11237 |
| By: | Wen, Xin; Cheng, Zhiming; Tani, Massimiliano |
| Abstract: | We explore the link between child gender and household financial decisions within a cultural environment that strongly favours having a son. Using data from the China Household Finance Survey (CHFS), we find that the presence of a daughter is associated with a lower saving rate, consistent with the hypothesis that the relative under-supply of unmarried women generates a less competitive marriage market for families with daughters vs. those with sons. As a result, such families have lower incentives to endow their daughters with bigger asset pools to enhance their marital prospects. The correlation becomes more pronounced as the daughter approaches marriageable age, and it is more common among families where the head has low financial literacy and limited education and lives in rural areas. |
| Keywords: | daughter, household investment decisions, family savings, marriage market |
| JEL: | D14 G11 G51 J12 |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:glodps:1474 |
| By: | Carmen Sainz Villalba; Kai A. Konrad |
| Abstract: | This paper analyzes the relationship between financial literacy, perception of own preference or eccentricity, and the willingness or desire to delegate the planning for pensions to government regulation and the willingness or desire to have government regulation on savings plans for the population as a whole. By using an online survey conducted with Bilendi&Respondi, we correlate the variables of people’s perception of how different they are from others with respect to their pension plan preferences, how informed they are about financial matters in general, and what are their preferences toward the government intervention of savings plans. The empirical approach is inspired by theory results of Konrad (2023). His game-theory analysis suggest that two factors increase the citizen’s desire for autonomous economic decision-making: eccentricity of own preferences, and own expertise/knowledge and decisions skills. Our work corroborates these two hypotheses in the specific context of pension savings decisions. Furthermore, we also analyze what are the factors that determine the difference between wanting to be regulated themselves and wanting others to be regulated. We find that people that want less intervention for themselves and are more informed want, on average, more government intervention for others. |
| Keywords: | Paternalism, Autonomy, Delegation, Knowledge, Eccentricity, Other-regarding preferences |
| JEL: | D78 D03 |
| URL: | https://d.repec.org/n?u=RePEc:mpi:wpaper:tax-mpg-rps-2023-10 |
| By: | Stephen L Cheung; Nathan Rogut |
| Abstract: | We experimentally test an intervention designed to reduce investors’ disposition effect by prompting them to identify their worst asset, from the standpoint of its impact on future portfolio performance. We find that this intervention is mildly effective, and significantly more so for participants who correctly identify their worst asset, and/or sell the asset they identify. We also find that participants who correctly understand diversification in a financial literacy questionnaire exhibit larger disposition effects in the experiment. The latter finding raises concerns over the external validity of standard experimental paradigms used to study the disposition effect. |
| Keywords: | behavioural finance, portfolio choice, disposition effect, diversification. |
| Date: | 2024–08 |
| URL: | https://d.repec.org/n?u=RePEc:syd:wpaper:2024-17 |
| By: | Hurlin, Christophe (University of Orleans); Pérignon, Christophe (HEC Paris) |
| Abstract: | This survey proposes a theoretical and practical reflection on the use of machine learning methods in the context of the Internal Ratings Based (IRB) approach to banks' capital requirements. While machine learning is still rarely used in the regulatory domain (IRB, IFRS 9, stress tests), recent discussions initiated by the European Banking Authority suggest that this may change in the near future. While technically complex, this subject is crucial given growing concerns about the potential financial instability caused by the banks' use of opaque internal models. Conversely, for their proponents, machine learning models offer the prospect of better measurement of credit risk and enhancing financial inclusion. This survey yields several conclusions and recommendations regarding (i) the accuracy of risk parameter estimations, (ii) the level of regulatory capital, (iii) the trade-off between performance and interpretability, (iv) international banking competition, and (v) the governance and operational risks of machine learning models. |
| Keywords: | Banking; Machine Learning; Artificial Intelligence; Internal models; Prudential regulation; Regulatory capital |
| JEL: | C10 C38 C55 G21 G29 |
| Date: | 2023–06–25 |
| URL: | https://d.repec.org/n?u=RePEc:ebg:heccah:1480 |