The moderating role of education on the financial inclusion-food poverty nexus: the case of Uganda

Globally, financial inclusion is regarded as being crucial for balancing an economy's financial system. However, despite the significance of financial inclusion, it still needs to be clarified to what extent it is practiced. In this study, the assessment of the performance of the 49 Sub Saharan Africa (SSA) countries as regards financial inclusion was carried out through the construction of a single composite Financial Inclusion Index (FII) to capture the four dimensions of financial inclusion. Z-sum score and Principal Component Analysis (PCA) was deployed to analyse the secondary data spanning from 1999 to 2023. The decision rule deployed was that if a value for Financial Inclusion Index (FII) from zero to forty-nine (0-49) this shows that there is low financial inclusion; medium financial inclusion from fifty to sixty-nine (50-69) while, a value from seventy and above (70- above) denotes the high financial inclusion) for the study period. The result revealed that all SSA countries are low that is they fall into between zero (0) to forty-nine (49) in the composite financial inclusion index in line with the decision rule. Also, the result indicated that Sao-Tome and Principe was the best performing SSA country with the highest financial inclusion penetration per thousand considered during the period of the study.

The purpose of the paper is to measure the level of financial inclusion across rural-dominated states of India and to find the reasons for the low financial inclusion scores. The CRISIL Inclusix methodology was employed using secondary data for all dimensions of financial inclusion. All the dimensions of financial inclusion were calculated separately to create a financial inclusion index for each state separately. The financial inclusion index ranges from 0 to 1 after the normalisation process. As 0 represents no financial inclusion, and 1 represents complete financial inclusion. Himachal Pradesh obtained the maximum score of 94.2 and was put in the high category, while Meghalaya received the lowest score of 16.84 and was placed in the low category. The remaining selected states, Arunachal Pradesh, Jharkhand, Uttar Pradesh, and Chhattisgarh, obtained scores of 32.8, 26.76, 26.72, and 22.68, respectively, placing them in the low category.

Financial inclusion is the delivery of financial services through receipt of transfer payments, savings, loans, insurance, short term credit and remittance at affordable costs to sections of disadvantaged and low income segments of society. It is argued that availability of banking and payments services to the entire population without discrimination is the prime objective of public policy. Therefore, having a savings account is the only a starting point of financial inclusion. MGNREGA, the flagship programme of the UPA government, was revolutionary in its promise of inclusive growth and financial inclusion, the right to work and the dignity of labour and a rational, participatory relationship with the State. While the importance of financial inclusion is widely recognized, the literature lacks a comprehensive measure that can be used to measure the extent of financial inclusion across economies. This paper attempts to find out Financial Inclusion Index(FII) through MGNREGS. The FII is a multi-dimensional index that captures information on various dimensions of financial inclusion in one single digit lying between 0 and 1, where 0 denotes complete financial exclusion and 1 indicates complete financial inclusion.

Purpose This paper aims to conduct an empirical investigation of how financial inclusion impacts women empowerment. Then, it examines the overall effect of various dimensions of financial inclusion on women empowerment in developing countries using the panel data for the time period of 2004–2019. Design/methodology/approach To overcome the problem of endogeneity, the study has used a fixed-effect model, two-stage least square GMM estimation techniques. Secondary data was collected from various websites such as WDI, UNICEF and UNESCO. Findings The results show that generally, the influence of financial inclusion on women empowerment is positive, confirming previous empirical literature results. The study found evidence that if there is more financial inclusion in the country, it will benefit women by enabling them to see their qualities and skills, which make them strong and dominant. Proper development and enhancement of those skills are only possible if proper education, awareness and space are given to express oneself. According to the results, financial development, gender parity index and women's employment positively affects women empowerment, while gender discrimination has a negative impact on women empowerment. The study highlights that to encourage women empowerment in developing countries. Governments and policymakers have to carefully check and reconsider that what are the most optimal financial inclusion programs that will help to improve the women empowerment in the country. Practical implications The study highlights that to encourage women empowerment in developing countries, governments and policymakers have to carefully check and reconsider what are the most optimal financial inclusion programs that will help to improve women empowerment in the country. Originality/value The literature does not clearly show the impact of financial inclusion dimensions on women empowerment in developing countries. Therefore, there is a need to use all the dimensions of financial inclusion to check the overall impact on women empowerment in developing countries. For this purpose, the financial inclusion index is developed. A new dimension of non-life insurance is introduced, which has not been used previously by any researcher to check financial inclusion impact.

While a large body of studies has captured macro financial inclusion on the supply side, this research paper contributes significantly to the literature on determining financial inclusion in Vietnam from the demand side. The primary target of this paper is to measure an overall financial inclusion index by employing micro data of 1,002 respondents in Vietnam from the World Bank. Additionally, based on the calculation of financial inclusion index, we investigate the determinants of financial inclusion and examine the barriers to financial inclusion in Vietnam. The ordinary least squares regression analysis and logit regression are employed to estimate the effect of demographic characteristics and the barriers to financial inclusion. The main findings reveal that people who are female, wealthier, more educated, or in the workforce exhibit a higher financial inclusion index. Besides, the financial inclusion level of high-income people is not affected by working status, while this level of middle and low-income people does. Women are also less likely to be financially included because they complain that financial institutions are too far away or because another family member has an account. Older people are more concerned about lack of documentation, lack of trust, and demand reasons. To achieve the purposes of robustness, the measurement of financial inclusion was changed following previous studies to confirm robust and stable baseline results. Accordingly, these findings contribute to issuing adequate policies that break the barriers to financial inclusion and enhance financial inclusion, especially for less educated, poor, out of the workforce, and old people.

Financial Inclusion Index Through MGNREGS in Virudhunagar District

Inclusive financial system is a key to sustainable development and growth of a nation wherein all segments of the society have timely access to financial services at an affordable cost. It facilitates safe custody of savings, availability of loan for multiple purposes, diversification of risk through investment in different avenue, coverage of risk through various insurance products, etc., which make the life of people easier and comfortable. Therefore, inclusive finance leads to prosperity and economic growth by eliminating or minimizing poverty, unequal distribution of income and dominance of indigenous bankers. Financial inclusion is not a single dimension that can be achieved directly; rather, it is a process which completes after different dimensions such as access to and usage of financial services and banking penetration are accomplished. The present study considers three main dimensions of financial inclusion: usage, penetration and accessibility. The purpose is to observe how financial inclusion is linked with economic growth in India. Spread over 2005 to 2017, the study uses Bayesian vector auto-regression model to explore the linkage of economic growth with financial inclusion and its different dimensions (accessibility, penetration, and usage). The findings show a considerable relationship between economic growth and the usage dimension of financial inclusion in India. As far as financial inclusion index is concerned, it does not explain economic growth significantly. This study is based on recent data extracted from IMF and World Bank databases. The study is useful for policymakers and banks to frame appropriate policies to achieve complete financial inclusion that would lead to a robust growth of an economy.

Dimensions of global financial inclusion and their impact on the achievement of the United Nations Development Goals

Purpose- Financial inclusion means individuals and businesses have access to useful and affordable financial products and services to deliver their needs in a responsible and sustainable way. A financial sector is measured and compared on four main features; debt is the size of financial institutions, access is the access and use of financial services by the users, efficiency is the efficiency in the provision of financial services, and stability is the stability in the provision of financial services. The purpose of this paper is to measure the level of financial inclusion of Turkey and Greece from 2000 to 2020 and compare its relationship with the economic growth and income inequality of both countries. Methodology- The World Bank data covering the 2000-2020 period is extracted from Turkey and Greece from the world bank report. The whole financial system for both countries is defined as a combination of banks, nonbanks financial institutions, and stock exchange markets. The related indicators for each of the subsectors of the financial system are determined for banks, nonbanks financial institutions, and stock exchange markets. Thus, 32 indicators for banks, 6 indicators for nonbanks, and 16 indicators for stock exchange markets are determined for the financial inclusion index. All indicators are in percentages. All individual indicators are summed for the computation of subsectoral indexes and then the growth rate in each subsectoral indexes are computed. The growth rates of each subsectoral index are summed and weighted by the subsectoral asset sizes or trading volüme. Finally, the causal relationship between the financial inclusion index, Gini coefficient, Poverty Headcount ratio, and GDP per capita was examined. Findings- The average growth rate for the financial inclusion index for the 21 years is 2,83% for Turkey and 0,97% for Greece. According to the analysis, we found that the financial inclusion index Granger-cause GDP per capita, Gini index Granger-cause financial inclusion index and there is a bidirectional relationship between the financial inclusion index and Poverty Headcount ratio for Turkey. On the other hand, there is a bidirectional relationship between GDP per capita and the financial inclusion index and a bidirectional relationship between the financial inclusion index and the Poverty Headcount ratio for Greece. Conclusion- Financial inclusion simply means a larger size of financial institutions and a variety of financial products and services available for the use of adult individuals, businesses, and governmental agencies. Economic growth is supported and accelerated by an increase in financial inclusion. The empirical analysis supports the literature that the growth in the financial inclusion index enhances a higher growth in GDP and a much higher growth in GDP per capita for both Turkey and Greece. The project titled “Istanbul as an International Financial Center” may easily improve the level of financial inclusion in Turkey. Keywords: Financial inclusion, economic growth, income inequality, financial indicators, Turkish and Greek financial markets JEL Codes: G40, G41

PurposeThe paper empirically investigates the impact of financial inclusion on food security. Subsequently, it examines the overall effect of various dimensions of financial inclusion on food security of developing countries using the panel data for the time period of 2004–2019.Design/methodology/approachTo overcome the problem of endogeneity, the study has used a fixed-effect model, two-stage least-square and system generalized method of moments estimation techniques. Secondary data was collected from various websites such as WDI, FAO, UNICEF and UNESCO.FindingsIt was found in the study that there is a significant effect of financial inclusion on food security. The evidence shows that if there is more financial inclusion in the country, it will help poor people to cope with difficult situations they face and provide them food security. Financial development, per capita income, agriculture growth and education positively affect food security, while militarization and urbanization have a negative impact on food security. The crux of the analysis is that any country's financial sector is an integral part of any country that supports food security.Originality/valueThe literature does not clearly show the impact of financial inclusion dimensions on developing countries' food security. Therefore, there is a need to use all the dimensions of financial inclusion to check the overall impact on food security. For this purpose, the financial inclusion index is developed. A new dimension of non-life insurance is introduced that has not been used previously by any researcher to check financial inclusion impact.

Financial Inclusion Through MGNREGS: Problems and Prospects

The paper examines financial inclusion in United Andhra Pradesh with focus on Rayala Seema region. It constructed Financial Inclusion Index (FII) using data on eight dimensions of financial inclusion for Andhra Pradesh for 2011. It observes that Hyderabad district leads with the highest FII rank, followed by Anantapur. Among the regions, Telangana leads with the highest FII rank, followed by Rayala Seema. Within Rayala Seema, Anantapur district leads with the highest FII rank, followed by Chittoor. None of the districts and regions falls under the category of high FII group. Most districts fall under the category of low FII group. Telangana and Rayala Seema fall under the category of medium financial inclusion with the FII value falls between 0.3 and 0.5. Thus, Rayala Seema has achieved less than half of the financial inclusion. The objective of financial inclusion and spreading it across areas is far ahead.

Purpose: The aim is to compare the selected methodologies used for constructing an Index of Financial Inclusion (IFI), as there exists conflict over the methodologies adopted to construct a financial inclusion index in the literature in terms of performance accuracy, and efficiency. The impact of dimension weights on index values has also been studied. Design/methodology/approach: An IFI has been built with three broad dimensions, banking penetration, availability, and usage of banking services with the selected methodologies. Data for the study include state/UT-wide bank data, demographical, geographical, and economic data, which are taken from Reserve Bank of India’s publications. Findings: (1) An IFI constructed with the methodologies (TOPSIS with EWM and Sarma (2015) with EWM) shows almost similar performances in terms of descriptive statistics; (2) There is only a slight difference in the financial inclusion performance between the methodologies based on Camera and Tuesta (2014) with two-stage PCA and Sarma (2008, 2015) with the subjective weights which make use of the descriptive statistics; (3) Camera and Tuesta (2014) methodology assigns a narrow weight to the index dimensions whereas, the proposed two-stage PCA model assigns a wider weight. Practical implications: The present study is useful to all the stakeholders, who are interested in the measurement of financial inclusion, say policymakers, research communities, etc., and the study offers direction to future studies on the methodology to be adopted. Originality/value – To the best of authors’ knowledge, no studies have been carried out with the same purpose. Hence, the present study is new to the IFI literature.

This study examines the impact of financial technology (fintech) on financial inclusion in India using panel data from 28 states over the period 2015-2023. Employing a fixed-effects regression model and instrumental variable approach, we analyze how digital payment adoption, mobile banking penetration, and fintech infrastructure affect various dimensions of financial inclusion. Our findings reveal that a 10% increase in digital payment adoption leads to a 7.2% improvement in the financial inclusion index, with particularly strong effects in rural and economically disadvantaged regions. The study also demonstrates that fintech adoption reduces the gender gap in financial access by 23% and increases formal credit access by 31% among previously unbanked populations. These results provide crucial insights for policymakers and financial institutions seeking to leverage technology for inclusive growth.

This paper interrogates various measures and definitions of financial inclusion (FI) and their cumulative distribution in Kenya. Lack of a substantive and reliable measure of FI hampers the formulation of evidence based policy interventions. The paper presents three measures of FI founded on formal usage of; transactionary, credit, savings/investments and insurance/pension products. The first measure is focused on the use of atleast one formal financial product from each category, the second measure develops a composite measure (index of Financial Inclusion (IFI)) aggregated from the single measures and lastly a use case measure based on the needs framework. From the single product measure; transactionary, credit, savings and insurance, uptake in 2019 averaged 79 percent, 17 percent, 53 percent and 29 percent respectively. The cumulative distribution curves revealed a strong stochastic dominance by the Nairobi sub region. A ranking of the sub regions using the IFI placed Nairobi sub region on top followed by Central and Mombasa in that order. Upper Eastern, North Eastern and North Rift sub regions took the bottom three positions. The paper recommends a sustained campaign to boost the uptake of financial services from the formal strand and particularly credit and insurance whose uptake is relatively low. The study also recommends a shift from the conventional measurement of FI based on product usage to the needs based framework founded on the use case to assess efficacy of formal financial solutions to manage liquidity, mitigate risks and manage future goals. JEL Classification Numbers: C43, C81, G02, G21, G23 Keywords: Financial Inclusion, stochastic dominance, sub region DOI : 10.7176/EJBM/11-22-07 Publication date : August 31 st 2019