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on Financial Literacy and Education |
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Issue of 2021‒02‒15
six papers chosen by |
| By: | Ali Compaoré (CERDI - Centre d'Études et de Recherches sur le Développement International - Clermont Auvergne - UCA - Université Clermont Auvergne - CNRS - Centre National de la Recherche Scientifique) |
| Abstract: | Financial inclusion refers to access to and use of formal financial services by individuals and businesses and the literature unambiguously documented that access-for-all to financial services is conducive to important economic and development outcomes. In this paper, we particularly investigate the impact of financial inclusion on non-resources tax revenue in developing countries. Based on a sample of 63 developing countries over the period 2004-2017 and drawing on the dynamic generalized method of moments (GMM), the paper finds that greater access to financial services captured by the number of ATMs per 100,000 adults increases government non-resources tax-to-GDP ratio, and this result is driven by households consumption and business expansion. Our findings provide insights on tax resources-harnessing opportunities from implementing and promoting financial inclusion policies for developing economies. |
| Keywords: | G21,H20,O11,O23 Financial inclusion,Non-resource tax-to-GDP ratio,Private consumption,Unemployment,Developing countries |
| Date: | 2020–12–29 |
| URL: | http://d.repec.org/n?u=RePEc:hal:wpaper:hal-03089935&r=all |
| By: | Setiawan, Adib Rifqi; Saputri, Wahyu Eka |
| Abstract: | This research used R&D approach 4D model goals to gain the design for a learning program to guide students in pondok pesantren on achieving financial literacy throught fiqh mu’āmalāt learning that is based on kitab kuning that validated by experts and practitioners and reliability counted based on test. |
| Date: | 2020–12–25 |
| URL: | http://d.repec.org/n?u=RePEc:osf:osfxxx:n6vhe&r=all |
| By: | Simplice A. Asongu (Yaounde, Cameroon); Alex Adegboye (Covenant University, Ogun State, Ota, Nigeria); Joseph Nnanna (The Development Bank of Nigeria, Abuja, Nigeria) |
| Abstract: | This study explores whether female economic inclusion enhances tax performance in a sample of 48 countries in Sub-Saharan Africa from 2000 to 2018. The study’s empirical evidence is based on the generalized method of moments in order to account for endogeneity concerns. Three tax performance measurements are used, notably, total taxes revenue excluding social contributions, reported tax revenue derived from natural resources sources, and total non-resource tax revenue. Three female inclusion indicators are used, namely, female employment in industry, female labour force participation, and female employment. The following empirical evidences are documented; (i) There is a negative net effect from the enhancement of female employment in the industry on the total tax revenue. (ii) There is a positive net effect of female employment in the industry on the non-resource taxes. An extended threshold analysis is performed to establish the critical masses that could further influence tax performance positively. The following thresholds are established. (i) a minimum of 15.35 “employment in industry, female (% of female employment)†for the total tax revenue and (ii) a maximum of 23.75 “employment in industry, female (% of female employment)†for the non-resource tax revenue. These critical masses are crucial for sustainable development because, below or beyond these thresholds, policy makers should complement the female economic inclusion with other economic measures designed to improve tax performance in Sub-Saharan Africa. |
| Keywords: | Gender, economic inclusion, tax performance, sustainable development, Africa |
| JEL: | H20 H71 I28 J08 J21 |
| Date: | 2020–01 |
| URL: | http://d.repec.org/n?u=RePEc:abh:wpaper:20/093&r=all |
| By: | Oluwabunmi Adejumo (Obafemi Awolowo University, Ile-Ife, Nigeria); Uchenna Efobi (Covenant University, Nigeria); Simplice A. Asongu (Yaoundé, Cameroon) |
| Abstract: | Financing sustainable development in Africa requires financing options that is best for development in the region without further escalating other societal problems. This chapter takes stock of financing options previously advocated for financing development in the African region such as development assistance and foreign investment. By considering its implication on development outcomes like poverty, inequality, and aggregate human development, some drawbacks still exist. Therefore, the chapter identifies, reconfigures and reinvents other financial flows such as mutual support networks, agricultural cooperatives, crowd funding, fiscal responsibility, other forms of informal banking, and remittances, among others to African countries for efficient provision of structures that can aid in the sustenance of development. We conclude that these alternative means of financing development could be a viable policy option to bridge income and development gaps; thereby mainstreaming the process for financial inclusion and sustainability. |
| Keywords: | Finance; Sustainable Development |
| JEL: | G20 I00 O10 |
| Date: | 2020–01 |
| URL: | http://d.repec.org/n?u=RePEc:abh:wpaper:20/071&r=all |
| By: | Ho, Tung Manh; Nguyen, Quoc-Hung; Le, Ngoc-Thang B.; Tran, Hung-Long D. |
| Abstract: | In this report, we will look at major research findings on foreign direct investment (FDI), SMEs, micro-credit programs, financial inclusion, and IFRS adoption. These topics are of increasing importance, and they have gradually become critical for academia, policymakers, and corporate sectors if they are set to investigate Vietnam’s fast-expanding economy. |
| Date: | 2021–01–12 |
| URL: | http://d.repec.org/n?u=RePEc:osf:osfxxx:p2ws4&r=all |
| By: | Majid Bazarbash |
| Abstract: | Recent advances in digital technology and big data have allowed FinTech (financial technology) lending to emerge as a potentially promising solution to reduce the cost of credit and increase financial inclusion. However, machine learning (ML) methods that lie at the heart of FinTech credit have remained largely a black box for the nontechnical audience. This paper contributes to the literature by discussing potential strengths and weaknesses of ML-based credit assessment through (1) presenting core ideas and the most common techniques in ML for the nontechnical audience; and (2) discussing the fundamental challenges in credit risk analysis. FinTech credit has the potential to enhance financial inclusion and outperform traditional credit scoring by (1) leveraging nontraditional data sources to improve the assessment of the borrower’s track record; (2) appraising collateral value; (3) forecasting income prospects; and (4) predicting changes in general conditions. However, because of the central role of data in ML-based analysis, data relevance should be ensured, especially in situations when a deep structural change occurs, when borrowers could counterfeit certain indicators, and when agency problems arising from information asymmetry could not be resolved. To avoid digital financial exclusion and redlining, variables that trigger discrimination should not be used to assess credit rating. |
| Keywords: | Credit risk;Credit;Credit ratings;Loans;Machine learning;WP,ML model,bears risk,machine learning technique,ML analysis,ML evaluation |
| Date: | 2019–05–17 |
| URL: | http://d.repec.org/n?u=RePEc:imf:imfwpa:2019/109&r=all |