Our findings reveal that increased levels of financial inclusion are associated with lower income inequality, indicating that broader access to financial services can facilitate wealth a
INTRODUCTION
Introduce the problem
The global financial crisis has significantly exacerbated income inequality, leading to essential expenditure cuts and rising unemployment, which in turn has suppressed wages The World Bank (2020) estimates that the recession has plunged between 88 and 115 million people in developing nations below the poverty line, worsening global inequality In response, governments and central banks have increasingly recognized the importance of financial inclusion for promoting macroeconomic stability and enhancing monetary policy effectiveness Financial inclusion, defined as ensuring timely access to affordable financial services and credit for all social groups, is now viewed as a vital strategy for achieving sustainable economic growth, poverty reduction, and income equality (United Nations, 2016).
Financial inclusion plays a crucial role in promoting social inclusion by offering accessible and usable formal financial services to underserved populations, including rural residents, women, and low-income families These groups benefit greatly from essential financial services such as savings, loans, payments, and insurance (World Bank, 2014) In recent years, significant progress has been made in financial inclusion, marked by the development of a robust service infrastructure and broad service coverage Initially, informal financial institutions, like micro-credit companies, provided loans primarily to rural communities and small enterprises However, due to a lack of regulatory oversight, some of these institutions engaged in unethical practices, resulting in financial misconduct Subsequently, traditional financial institutions, including city and rural commercial banks, as well as large state-owned banks, began to prioritize financial inclusion, establishing dedicated departments around 2017 to allocate more resources to this vital sector.
‘‘agriculture, rural areas, and farmers’', as well as small and micro enterprises, thereby providing effective support to the development of the real economy.
Financial inclusion plays a crucial role in enhancing access to essential resources for firms and households, thereby stimulating economic activity It enables previously excluded individuals to invest in education, save, and start businesses, fostering inclusive growth By allowing economic agents to engage in long-term investments, financial inclusion facilitates the efficient allocation of resources, reduces capital costs, and helps manage unexpected financial shocks Furthermore, it significantly improves daily financial management and reduces reliance on exploitative informal credit sources Recognizing its importance, developing and emerging countries are striving for universal financial inclusion.
Financial inclusion has gained considerable attention from policymakers and scholars for several reasons It is seen as a crucial strategy for achieving the United Nations' sustainable development goals, as highlighted by Demirguc-Kunt et al (2017) and Sahay et al (2015) Additionally, financial inclusion plays a significant role in promoting social inclusion across various societies, as noted by Bold et al.
Financial inclusion plays a crucial role in alleviating poverty, as it is recognized for its potential to lower poverty levels to acceptable standards Additionally, it is linked to a range of socioeconomic advantages that enhance overall community well-being.
Policymakers worldwide are investing heavily in enhancing financial inclusion to combat financial exclusion, which can be categorized into voluntary and involuntary exclusion According to the World Bank (2014), voluntary exclusion occurs when individuals or groups choose not to use financial services due to lack of necessity or cultural and religious beliefs In contrast, involuntary exclusion is driven by factors such as insufficient income, high-risk profiles, discrimination, and market failures To effectively tackle financial exclusion, policy and research efforts should focus on involuntary exclusion, as it can be addressed through targeted economic programs and policies that aim to improve income levels and mitigate risk profiles.
Asymmetric information and market flaws can jeopardize the optimal distribution of capital resources, leading to financial exclusion for some firms and households, which adversely affects equitable economic growth The UN 2030 Agenda for Sustainable Development emphasizes that financial inclusion is crucial for achieving the Sustainable Development Goals (SDGs) and reducing inequality (SDG 10) Despite progress, the Global Findex database reveals that 1.7 billion adults globally lack access to formal financial services, with 760,000 of those who have access not utilizing it due to high costs, distance, and documentation barriers For low-income households, the ability to save and access credit is vital for making profitable investments In Asia, only 27% of residents have bank accounts, and just 33% of businesses can access credit, resulting in over 1 billion adults in the region lacking formal financial services.
Financial stability is crucial for maintaining price stability and supporting the real economy by building systemic confidence and preventing events like bank runs that can destabilize nations This concern has gained prominence globally due to various financial crises since the late 1980s, including the Asian financial crisis (1997-1998) and the global financial crisis (2007-2008), which highlighted the need for vigilance over financial institutions whose issues could have widespread repercussions Critics argue that while financial inclusion is important, it should not overshadow the necessity of ensuring financial stability to mitigate the risks posed by inadequately regulated financial entities.
Research highlights that while higher financial inclusion can enhance banks' customer bases and stability by expanding their deposit pools, it may also lead to risks associated with looser lending practices Some studies suggest that efforts to increase clientele could result in a rise in non-performing loans, particularly among low-income borrowers who face higher information and transaction costs Additionally, a poor credit history among these borrowers may exacerbate financial instability Ultimately, the effect of financial inclusion on bank stability hinges on the balance between its positive and negative impacts.
Financial inclusion has become a key focus in global reform efforts, recognized for its role in promoting financial system stability and mitigating income inequality In 2019, the Fourth Plenary Session of the 19th CPC Central Committee emphasized the need to develop a modern financial system that is adaptable, competitive, and inclusive.
In August 2020, a spokesperson from the China Banking and Insurance Regulatory Commission emphasized the importance of reform, technological empowerment, and intensive management in strategically allocating inclusive financial resources and controlling credit risks Despite advancements, current financial systems remain exclusive and face rapid changes and innovations, leading to the emergence of new products and payment methods Consequently, there is a growing focus on financial inclusion, highlighting its transformative potential to drive inclusive development.
Research objective and question
Numerous studies have explored the factors influencing financial inclusion, employing suitable econometric measures at both regional and national levels, while also highlighting the importance of consistent macro-level data across countries and effective financial services for users Research indicates that financial inclusion positively impacts economic growth, financial stability, female empowerment, poverty reduction, and income inequality, establishing a solid foundation for further investigation in this area However, there remains a pressing need to understand the broader macroeconomic implications of financial inclusion, which can provide essential policy insights for policymakers These insights are crucial for designing and implementing effective economic programs and policies aimed at enhancing income levels and addressing market failures, ultimately contributing to sustainable development.
This paper enhances existing literature by integrating two key areas: financial inclusion's impact on income inequality and financial stability It introduces a novel financial inclusion metric based on comprehensive cross-country data, encompassing a diverse range of countries By leveraging demand-side data from the largest database on adult financial behaviors—such as payments, borrowing, and risk management—this study offers a deeper insight into the relationship between financial inclusion, income inequality, and financial stability This approach moves beyond traditional supply-side data, allowing for a more accurate understanding of financial behavior and identifying critical dimensions of financial inclusion that can effectively address income inequality and bolster financial stability.
This study introduces a novel country grouping based on varying stages of economic development, encompassing a wide range of examples from developed nations such as Australia, Belgium, Canada, and Finland, to developing countries like China, India, and Indonesia It further explores the intricate relationship between financial inclusion and income inequality across four distinct income level categories: high, upper-middle, lower-middle, and low By analyzing these new divisions, the research highlights the differences in the connection between financial inclusion and financial stability Our extensive cross-border analysis offers a comprehensive understanding of this relationship, laying a solid theoretical foundation to inform effective policy-making decisions.
Thus, the following research questions have been formulated based on the above discussion:
First, does financial inclusion have a negative impact on income inequality?
Second, does financial inclusion have a positive impact on financial stability?
Third, does the positive effect of financial inclusion on financial stability vary by country's economic development?
Fourth, does the positive effect of financial inclusion on financial stability vary by country's income level?
Research subject and scope
This study analyzes data from 190 countries, ensuring comprehensive coverage by excluding those with significant missing information The primary focus is to explore the relationship between financial inclusion, income inequality, and financial outcomes.
Stability by analyzing the data in 20 years, from 2002 to 2021 All data is available on the World Bank.
Research method
The study employs panel data regression, which involves observations from multiple cross-sectional units over various time periods This approach offers several advantages, including an increased sample size, the ability to analyze dynamic changes over time, and the examination of complex behavioral patterns, including time-invariant variables (Gujarati, 2011) However, panel data models face challenges such as heteroscedasticity and autocorrelation To address these issues, the authors utilized the Feasible Generalized Least Squares (FGLS) method, which mitigates the limitations of traditional panel data regression models like Ordinary Least Squares (OLS) The research was conducted using Stata and Microsoft Excel software.
Research structure
Chapter 1 Introduction In this chapter, we introduce the problem, research objective and question, research subject and scope, research method, and research structure.
Chapter 2 Literature review and research hypotheses In this chapter, we review papers related to impact of financial inclusion on the GIN I Index, and financial stability; then, we develop research hypotheses.
Chapter 3 Research models and methodology In this chapter, we present research models, sample, data, how to measure variables, and econometric methodology.
Chapter 4 Research results In this chapter, we present descriptive statistics and correlation matrix tables, test the impacts of financial inclusion on the GINI Index, the country’s economic development and financial sustainability-financial inclusion relations, and the country’s income level and financial sustainability-financial inclusion relations.
Chapter 5 Conclusion In this chapter, we sum up conclusions, recommendations and imitations.
LITERATURE REVIEWAND RESEARCH HYPOTHESES
Impact of financial inclusion on the G1NI Index
The relationship between financial inclusion and income inequality has been a significant topic in academic research, with scholars examining its impact on economic growth through various lenses and factors Theoretical frameworks suggest that flaws in financial markets, including information asymmetries and transaction costs, hinder individuals with limited financial resources from escaping poverty by restricting their access to formal financial services.
Galor and Zeira (1993) and Banerjee and Newman's (1993) models highlight the detrimental effects of imperfect credit markets on impoverished households, which struggle to secure loans for education and business ventures These limitations hinder their ability to invest in opportunities that could improve their financial situation By enhancing access to finance, we can alleviate poverty and reduce inequality, empowering low-income families to pursue education and entrepreneurship, ultimately leading to increased income levels.
The relationship between financial inclusion and income inequality remains ambiguous, as both macro and micro-level empirical evidence offers mixed results Studies conducted on individual countries and across multiple nations, utilizing various empirical and experimental methods, highlight this inconsistency While some research indicates a positive correlation between financial inclusion and increased income or consumption inequality (e.g., Kochar, 2011; Dimova & Adebowale, 2018), other studies suggest a negative relationship (Khandker, 2005; Zhang & Posso, 2019), and some reveal that this relationship can change over time (Huang & Zhang, 2020).
Research in Uttar Pradesh, India, reveals that financial development increases income inequality, as not all households benefit equally from the expansion of banking infrastructure Kochar (2011) notes that while access to formal financial services has improved through local bank branches, poor households are not utilizing these services effectively due to high entry costs and the need for financial assets This situation has led to enhanced credit availability primarily for affluent households, thereby exacerbating inequality Additionally, impoverished populations often depend on informal credit sources, such as family connections, due to a lack of collateral and social networks, allowing wealthier individuals to capitalize on financial opportunities more effectively Oechslin (2009) highlights that this disparity results in a greater income increase for the rich compared to the poor, widening the income gap Furthermore, the impact of financial inclusion varies based on whether it targets extensive or intensive margins, as noted by Demirguc-Kunt & Levine (2009) The extensive margin focuses on providing access to underserved populations, while the intensive margin deepens usage among existing users, often favoring wealthier individuals Consequently, financial development that prioritizes the intensive margin perpetuates inequality by limiting opportunities for the less affluent and maintaining the existing income divide.
Lowering fixed costs for financial services significantly enhances entrepreneurship opportunities for individuals with innovative ideas but limited collateral, while also improving access to risk management This financial development, which operates on a broad scale, particularly benefits the poor and helps reduce income inequality Numerous cross-country studies have shown a clear link between increased financial inclusion and decreased income inequality (Honohan, 2007; Sahay et al., 2015; Aslan et al., 2017; Park & Mercado, 2018; Turégano & Herrero).
Research indicates a strong negative correlation between household access to finance and income inequality, as evidenced by Honohan (2007) and the Gini Coefficient Mookerjee & Kalipioni (2010) found that countries with more bank branches per capita experience lower income inequality Park & Mercado (2018) highlighted that enhancing the accessibility and usage of financial services, such as ATMs and bank branches, plays a crucial role in reducing the income gap Similarly, Aslan et al (2017) demonstrated that increased financial service usage among the population correlates with diminished income inequality Studies utilizing various measures of financial inclusion, including account ownership and SME lending, support the idea that more inclusive financial systems lead to less unequal income distribution Furthermore, Nguyen et al (2021) emphasized the importance of institutional quality in promoting financial inclusion and reducing economic inequality in ASEAN regions Lastly, Zhang & Posso's findings underscore the impact of varying income levels across countries on these dynamics.
Research from 2019 in China shows that lower-income populations benefit more from financial inclusion than those with higher incomes, indicating a positive impact on income and a reduction in inequality, especially for lower-income groups Huang & Zhang (2020) note that while financial inclusion policies initially widen the urban-rural income gap, they ultimately help reduce it as financial infrastructure and literacy improve in rural areas over time The study highlights that the unequal expansion of financial networks, combined with limited financial literacy in rural regions, exacerbates short-term urban-rural income inequality Urban areas experience lower costs in expanding banking infrastructure, leading to a skewed distribution of financial services Despite nationwide advancements in financial inclusion, rural areas still struggle to access sufficient financial services compared to urban counterparts Thus, adopting long-term financial inclusion policies is essential for ensuring equitable economic benefits for all populations.
Research indicates that various aspects of financial inclusion—specifically access and usage—along with different financial services such as credit, savings, insurance, and payments, have distinct impacts on income inequality While studies from diverse countries and time periods yield mixed outcomes, a prevailing trend suggests that financial inclusion generally enhances income distribution Poor populations often face barriers due to lack of collateral and credit history, making them vulnerable to market imperfections like information asymmetry and high transaction costs By improving access to financial resources, financial inclusion alleviates these credit constraints, empowering low-income individuals to invest in their human and physical capital This, in turn, contributes to reducing income inequality by expanding credit availability for disadvantaged groups.
Hypothesis 1: Financial inclusion has a negative effect on income inequality
Impact of financial inclusion on financial stability
This review explores the intricate relationship between financial inclusion and financial stability through three key perspectives, leading to three significant hypotheses The first perspective posits that financial inclusion enhances overall financial stability The second focuses specifically on developing countries, asserting that increased financial inclusion contributes positively to their financial stability Lastly, the third perspective examines high-income countries, supporting the notion that financial inclusion plays a crucial role in maintaining their financial stability Each of these viewpoints is discussed in detail below.
Financial inclusion significantly contributes to a country's financial stability by broadening access to financial services, which enhances economic activities and improves living standards for the poor Research by Khan (2011) indicates that financial inclusion fosters efficiency among financial intermediaries and stabilizes retail deposits, particularly among low-income savers This stability is crucial for banks' capital and for effectively transmitting central bank monetary policies Studies by Han & Melecky (2013) and Le et al (2019) further demonstrate that increased access to banking services, such as ATMs and deposits, leads to greater financial resilience during crises However, some researchers caution that excessive participation in financial markets can raise transaction costs and information asymmetry, potentially undermining stability Ratnawati (2020) highlights the balance between financial inclusion and credit risk, noting that while more loans can lead to higher non-performing loans (NPLs), financial inclusion positively impacts banks' ability to cope with risks Additionally, Pham et al (2020) found that not all financial services positively affect stability, suggesting that while saving services bolster resilience, others may have adverse effects Overall, enhanced financial inclusion can empower marginalized groups, stimulate economic growth, and reduce poverty, thereby playing a crucial role in maintaining financial stability.
Financial inclusion, while generally beneficial, can negatively impact financial stability, as suggested by Yetman (2015) Rapid credit growth and the expansion of unregulated financial sectors may lead to a decline in loan quality and an increase in financial risks Moreover, excessive financial inclusion can result in economic imbalances, as small, unregulated entities gaining more capital can significantly influence the financial system, thereby creating systemic risks.
Nevertheless, according to the majority of the studies, we create the following hypotheses:
Hypothesis 2: Financial inclusion has a positive effect on financial stability Hypothesis 2.a: Financial inclusion positively affects Bank Z-score
Hypothesis 2.b: Financial inclusion negatively affects bank non-performing loans (NPLs)
Our research explores the relationship between financial inclusion and stability in both developing and developed countries According to Dutta & Saha (2019), financial inclusion plays a crucial role in enhancing financial stability in emerging economies While Asian markets demonstrate robust growth and development potential, they are also vulnerable to banking fragility This fragility is often influenced by factors such as poor governance, weak financial systems, inadequate risk management, and misunderstandings regarding stability determinants Furthermore, the involvement of foreign banks in the regional economy may introduce additional risks.
Research indicates that broadening financial inclusion enhances bank stability, particularly in emerging economies, but this relationship can vary based on contextual factors A strong economic environment supported by effective policy frameworks amplifies the positive effects of financial inclusion, while loose monetary policies and significant government intervention may lead to increased risk-taking and reduced stability Key elements such as regulatory measures and deposit insurance schemes can influence this relationship, with robust laws and supportive policies reinforcing the connection In low financial development countries (LFDCs), financial inclusion is vital for building resilient financial systems that can endure economic shocks Conversely, in high financial development countries (HFDCs), financial development can contribute to instability, resulting in inflation and crises that impact sectors like manufacturing The interaction between monetary policy, financial inclusion, and stability is notably stronger in HFDCs than in LFDCs While financial inclusion generally reduces economic uncertainty, further research is needed to compare its effects across different country classifications, as existing studies are limited.
Hypothesis 3: The positive effect of financial inclusion on financial stability in developing countries has a different level from developed countries
This article explores the varying impacts of financial inclusion across different income groups Previous research, such as Khan's 2011 study on middle-income countries, highlights that financial inclusion can positively influence financial stability by diversifying banking assets and improving monetary policy transmission Conversely, it may also have negative effects by leading to the emergence of subprime credit risks.
A study by Mclccky (2013) examined the correlation between financial inclusion and stability across high, middle, and low-income countries, revealing that financial inclusion significantly enhances financial stability, particularly in middle-income nations, which face unique challenges in fostering depositor confidence Further investigation is needed with larger datasets to better understand the dynamics in high and low-income countries Additionally, Dienillah et al (2018) utilized the Sarma index to measure financial inclusion and the Albulescu & Goyeau index for financial stability, finding that high-income countries exhibit greater financial stability due to robust capital markets, concentrated banking sectors, and low inflation rates Le et al (2019) highlighted that low-income individuals' active participation in the financial system can lead to increased financial inclusion but may also result in higher transaction costs and inefficiencies Given the diverse perspectives on these issues, we propose conducting a regression analysis to derive more definitive conclusions.
Hypothesis 4: The level of positive effect of financial inclusion on financial stability in high income countries is different from the others
RESEARCH MODELSAND METHODOLODY
Research models and variables
This study investigates the effects of financial inclusion on various economic indicators, specifically analyzing (1) its potential negative impact on the GINI Index, (2) its positive influence on financial stability, (3) the interaction between financial inclusion and a country's economic development, and (4) the relationship between a country's income level and financial inclusion.
Firstly, we use models developed by Le et al (2019), Omar & Inaba (2020) to investigate the impacts of financial inclusion on the GINI Index and financial sustainability as the model (1), (2) follows:
(1) GINI Indexi,t = Po + Pl.Financial inclusion!,t + (p.Controls + St + ơi + gi4
(2) Financial sustainability^ = Po + p 1 Financial inclusioni,i + (p.Controli,t+ St + Qi + Mi.t
In this analysis, we denote 'i' as the country and 't' as the time period, with St representing the time-specific error term and Qi signifying the country-specific error term that encompasses unobservable characteristics unique to each nation Additionally, Pi.t refers to a random error term The variable Controli.t includes a vector of country-level control variables that may influence both the GINI Index and financial sustainability.
To examine how a country's economic development influences the relationship between financial inclusion and financial sustainability, we incorporate a dummy variable for developing countries into our analysis This involves creating an interaction term between financial inclusion and the developing country variable, resulting in the formulation of model (3).
(3) Financial sustainabilityi.i = po + pl.Financial inclusioni.t + p2.Developing country + p3.(Financial inclusioni.t X Developing country) + (p.Controls + ôt + ơi + Pi.t
Thirdly, to test the impacts of a country's income level on the relationship between financial inclusion and financial sustainability, we add the dummy variable
(Income country) to model (2) and make an interaction term with the variable (Financial inclusion^) with an important explanatory variable being Financial inclusion,,tX Income country as model (4) follows:
(4) Financial sustainability^ = Po + Pl.Financial inclusioni.t + P2.Income country + P3.(Financial inclusioni.t X Income country) + (p.Controls + St + ơi + Pij
3.1.2 Dependent variables (the GINI index, Bank Z-score, Bank nonperforming loans)
To assess income inequality on a macro scale, the GINI index is utilized at the country level (Ratnawati, 2020; Omar & Inaba, 2020) Additionally, financial stability is measured through the Bank-Z score index (Le et al., 2019; Ratnawati, 2020) and the ratio of nonperforming loans in banks (Ratnawati, 2020) This data is sourced from the World Development Indicators and Global Financial Development available on the World Bank website.
The Gini index is a statistical measure that evaluates income or consumption distribution among individuals or households within an economy, indicating the level of inequality A Gini index score of 0 signifies perfect equality, whereas a score of 100 denotes complete inequality.
> Bank Z-score captures the probability of default of a country’s banking system
Z-score compares the buffer of a country's banking system (capitalization and returns) with the volatility of those returns It is estimated as (ROA+(equity/assets))/sd(ROA); sd(ROA) is the standard deviation of ROA, calculated for country-years with no less than 5 bank-level observations ROA, equity, and assets are country-level aggregate figures Calculated from underlying bank-by-bank unconsolidated data from Bank scope and Orbis The result is not reported if a country-year has less than 3 bank-level observations.
The ratio of nonperforming loans to total gross loans is calculated by dividing the value of nonperforming loans by the overall value of the loan portfolio, which includes all loans before accounting for specific loan-loss provisions It is essential to consider the gross value of nonperforming loans as they appear on the balance sheet, rather than merely focusing on the overdue amounts.
3.1.3 Independent variables (ATMs, Bank branches, Depositors, Borrowers, Bank accounts ratio)
Financial inclusion is assessed through five distinct methods to enhance the reliability of research findings, as highlighted in studies by Le et al (2019), Ratnawati (2020), and Polloni-Silva et al (2021) This analysis is supported by data from the World Development Indicators and Global Financial Development available on the World Bank website.
> Automated teller machines (ATMs) (per 100,000 adults): Automated teller machines are computerized telecommunications devices that provide clients of a financial institution with access to financial transactions in a public place.
Commercial bank branches, measured per 100,000 adults, are retail outlets of resident commercial banks that offer essential financial services to customers These branches operate independently from the main office but are not legally classified as separate subsidiaries.
Depositors with commercial banks are defined as the number of deposit account holders per 1,000 adults, including both public and private nonfinancial corporations and households In many countries, the data reflects the total number of deposit accounts, as specific information on individual account holders is often unavailable The primary types of deposits include checking accounts, savings accounts, and time deposits.
The number of borrowers from commercial banks, expressed per 1,000 adults, includes both nonfinancial corporations and households that have secured loans from commercial banks and similar institutions In many countries, the available data reflects the total number of loan accounts, as detailed information on individual loan account holders is often lacking.
> Bank accounts (per 1,000 adults): For each country calculated as l,000*rcportcd number of depositors/adult population in the reporting country.
The World Bank defines the annual percentage growth rate of per capita GDP as the gross domestic product divided by the mid-year population, measured in fixed domestic currency GDP at buyer prices encompasses the total added value from all permanent producers in the economy, factoring in product taxes while excluding subsidies This calculation does not account for depreciation of fixed assets or the depletion and degradation of natural resources.
Omar & Inaba (2020) indicate that higher GDP growth enhances the impact of financial inclusion on poverty reduction, as robust economic growth boosts labor demand, raises real wages for low-skilled jobs, and improves living standards in developing countries This fosters a financial inclusion system that encourages investment and financial risk management among low-income households, ultimately aiding in poverty alleviation Both the pace and pattern of economic growth are essential for improving access to finance and reducing poverty Additionally, there is a positive correlation between real GDP per capita and financial inclusion, implying that countries with higher per-capita incomes tend to have greater financial coverage While GDP growth can initially suggest a link to increased poverty and income inequality, this relationship diminishes when considering controlled variables.
Inflation, as defined by the World Bank, is measured by the consumer price index, which indicates the annual percentage change in costs for the average consumer purchasing a basket of goods and services This basket can either remain constant or vary over specific time frames, typically annually.
The relationship between inflation and income inequality is a subject of ongoing debate Proponents of the view that inflation can lessen income inequality argue that rising inflation redistributes wealth from creditors to debtors, as debtors benefit from reduced real debt burdens during periods of unexpected inflation This effect is particularly significant in nations with a high prevalence of indebted households, where inflation can help alleviate financial pressures and narrow the income gap.
Sample and data
We collected unbalanced panel data for 190 countries in the period 2002 - 2021
The study focuses on a sample of 190 countries, excluding those with significant missing data, and categorizes them based on economic development This includes 36 developed countries (18.95%) and 154 developing countries (81.05%) The classification is further divided by income level, comprising 64 high-income countries (33.68%), 51 upper-middle-income countries (26.84%), 51 lower-middle-income countries (26.84%), and 23 low-income countries (12.11%), with a small fraction (0.53%) unclassified Data collection spans from 2002 to 2021, utilizing information from the World Bank’s World Development Indicators and Global Financial Development databases, which encompass three dependent variables, five independent variables, and eight control variables To reduce the influence of outliers, certain country-year observations have been "winsorized" at the top and bottom 1% levels.
Econometric Methodology
The ordinary least squares (OLS) method estimates the slope and intercept parameters from a random sample It operates under five key Gauss-Markov assumptions: linearity in parameters, random sampling, no perfect collinearity, zero conditional mean, and homoskedasticity When these conditions are met, the OLS estimator for the parameters is considered the best linear unbiased estimator (BLUE).
Panel data models offer various advantages but also face estimation and inference challenges, including heteroscedasticity and autocorrelation among cross-sectional units To address these issues, we employ the FGLS econometric method, which effectively controls for both autocorrelation and heteroskedasticity in panel data regressions Furthermore, our regression model incorporates not only dependent and independent variables but also control variables, along with country-fixed effects and year-fixed effects to enhance the robustness of the analysis.
RESEARCH RESULTS
Descriptive statistics and correlation matrix
Table 1 Descriptive statistics for the sample of 190 countries from 2002 to 2021
Variable Obs Mean Std dev Min Max
To reduce the influence of outliers, certain country-year observation variables have been winsorized at the top and bottom 1% levels Table 1 displays the descriptive statistics for the research data sample, which encompasses 190 countries from 2002 onwards.
2021, including columns such as number of observations (Obs), average value (Mean), standard deviation (Std.dev.), lowest value (Min) and highest value (Max).
This study identifies three dependent variables based on descriptive statistics The GIN1 Index has an average of 36.967, with values ranging from 24.7 to 58.1 The Bank Z-score averages 16.344, spanning from 1.756 to 46.617 Lastly, the Bank nonperforming loans ratio (NPLs) averages 6.690%, with a range from 0.227% to 47.064%.
The study examines five independent variables related to financial inclusion, revealing that the ATMs ratio averages 59.343, ranging from 0.068 to 814.920, while the Bank branches ratio averages 46.104, with values between 0.449 and 388.482 The significant variation in these ratios is attributed to the sample comprising 18.95% developed economies and 81.05% developing economies, highlighting differing impacts of financial inclusion on financial stability based on economic development and income levels Additionally, the variables "Depositors' ratio," "Borrowers' ratio," and "Bank account ratio" have average values of 628.961, 191.965, and 5.895, respectively, with the Depositors' ratio exhibiting the highest standard deviation at 548.703, while the Bank account ratio shows the lowest standard deviation at 1.486.
The correlation matrix coefficients presented in tables 2, 3, and 4 indicate that all absolute values are below 0.8, leading the authors to conclude that multicollinearity is not present in the regression model.
Table 3 Correlation matrix with the dependent variable as Bank-Z score
Trade Inflation Population Unemployment Electricity Mobile cellular
Bank-Z ATMs Bank Depositors Borrowers Bank GDP per capita
EDI Trade Inflation Population Unemployment Electricity Mobile cellular
Table 4 Correlation matrix with the dependent variable as bank nonperforniing loans (NPLs)
Depositors Borrowers Bank GDP per capita account
FDI Trade Inflation Population Unemployment Electricity Mobile cellular
Testing the impacts of financial inclusion on the GINI Index
Table 5 Impacts of financial inclusion on the GINI Index
Gini index Gini index Gini index Gini index Gini index
Inflation CPI 0.034** 0.042*** 0.051 ** 0.101*** 0.047** Population 0.477*** 0.471*** 0.723*** 0.701*** 0.660*** Unemployment 0.177*** 0.179*** 0.230*** 0.187*** 0.235*** Electricity -0.088*** -0.098*** -0.075*** -0.119*** -0.077*** Mobile cellular -0.016*** -0.017*** -0.024*** -0.014*** -0.017***
Country fixed effects Yes Yes Yes Yes Yes
(Source: Results regressed from Stata by authors1)
To assess heteroskedasticity and autocorrelation in panel data, we employed the Breusch-Pagan Test and the Wooldridge test The results indicated a p-value of less than 0.05, leading us to reject the null hypothesis (H0) Consequently, we conclude that both heteroskedasticity and autocorrelation are present in the regression models (refer to appendix Al.a).
The regression analysis presented in model (1) of Table 5 demonstrates that financial inclusion—measured through various indicators such as the number of automated teller machines (ATMs) and commercial bank branches per 100,000 adults, as well as the number of depositors and borrowers from commercial banks per 1,000 adults—significantly reduces the GINI Index across countries The coefficients for these financial inclusion metrics are -0.0069, -0.0103, -0.0008, -0.0034, and -0.8570, indicating a negative correlation with the GINI Index at statistical significance levels ranging from 1% to 10% These findings remain robust even when control variables are included, as confirmed by the FGLS econometric method, aligning with our initial expectations.
Financial inclusion plays a vital role in lowering the fixed costs of accessing financial services, enabling entrepreneurs with innovative ideas but limited collateral to secure necessary funding It enhances access to risk management and financial development, significantly benefiting low-income individuals and contributing to reduced income inequality Numerous cross-country studies demonstrate a strong correlation between increased financial inclusion and decreased income inequality.
Testing the country’s economic development and financial sustainability-
Table 6 The difference in the relationship between financial inclusion and financial sustainability in developing countries and others.
Bank-Z score Bank-Z score Bank-Z score Bank-Z score NPLsơ' NPLs NPLs NPLs Developing countries 4.520*** 6.851*** 4.463*** 5.735*** 0.385 0.326 0.419 0.329
Year fixed effects Yes Yes Yes Yes Yes Yes Yes Yes
I statistics in parentheses * p NPLs NPLs NPLs
Year fixed effects Yes Yes Yes Yes Yes Yes Yes Yes
(*) NPLs stands for bank nonperforming loans ratio; (ATMs*Low income) and (Bank branches*Low income) are interaction variables.
(Source: Results repressed from Stafa by the authors 6 )