Microfinance as a Catalyst for Sustainable Development: A Cross-National Comparative Study of the Environmental and Social Impacts

Abstract

This study examines the role of microfinance institutions (MFIs) in advancing sustainable development by integrating environmental and social objectives into their operations. Using panel data from 30 MFIs across nine countries (2018–2023), the analysis applies Ordinary Least Squares (OLS), Instrumental Variables (2SLS), and Generalized Method of Moments (GMM) to assess policy impacts over time. “Access to environmental finance” is used as a validated instrument to address endogeneity. Results show that green lending and environmental risk management significantly reduce greenhouse gas emissions and improve gender empowerment. Larger institutions with stronger governance achieve better outcomes, and dynamic models (GMM) confirm the persistence of these effects over time. The findings highlight the importance of regulatory support, green finance infrastructure, and institutional capacity-building for scaling sustainable microfinance.

1. Introduction

Microfinance Institutions (MFIs) originated in the mid-20th century as tools for poverty alleviation, gaining international traction after the success of the Grameen Bank in the 1970s [1]. Initially focused on financial inclusion for underserved populations, MFIs have since evolved into multifaceted development actors, whose mandate now extends beyond traditional microcredit to encompass broader objectives aligned with the Sustainable Development Goals (SDGs), including environmental sustainability, gender equality, and inclusive economic growth [2,3].

In this evolving context, MFIs are increasingly engaging with innovative sustainability-oriented practices, such as clean energy financing, green agriculture, and support for eco-friendly microenterprises [4,5]. These initiatives reflect a paradigm shift in the microfinance sector—one that integrates environmental and social objectives with financial services. Despite this growing relevance, scholarly research has not fully kept pace with these developments. Most existing studies have focused on microfinance’s contributions to poverty reduction, economic empowerment, and gender equality [6,7], while the intersection of microfinance with green and sustainability initiatives remains underexplored, particularly in regard to how institutional characteristics, such as governance structures, size, and sustainability-focused policies, interact with external environmental and regulatory contexts [8,9].

This study addresses these critical gaps by investigating how MFIs incorporate environmental and social sustainability into their operations and evaluating the measurable impacts of such efforts. It applies a theoretical framework that draws from both stakeholder theory and the resource-based view [10,11], enabling a nuanced analysis of how internal capabilities and external partnerships contribute to sustainable development outcomes. To achieve these objectives, the study employs a comparative case study approach grounded in data from MFIs operating across both developing and developed countries. The selected institutions demonstrate varying degrees of integration between sustainability initiatives and core operations, offering a diverse basis for comparison. The research is guided by two central questions: how do MFIs integrate both environmental and social sustainability into their operational frameworks?

The study broadens its empirical base by including a wider range of MFIs across diverse regions, incorporating both developed and developing countries. Stratified sampling techniques are employed to ensure representativeness and improve generalizability by capturing institutional variation across different sizes, models, and geographies. Furthermore, the rationale for selecting key instrumental variables, such as the availability of environmental finance and regional regulatory mandates, is clearly articulated, and statistical diagnostics, including correlation tests, weak instrument diagnostics, and over-identification tests, are conducted to ensure robustness of causal inference [12,13]. Recognizing the limitations of purely cross-sectional analyses, the study integrates longitudinal elements where available and employs dynamic panel data models, specifically the Generalized Method of Moments (GMM), to assess lagged and persistent effects of sustainability-focused policies over time [14].

By addressing underexplored intersections between microfinance and sustainability, this study contributes to the emerging field of sustainable microfinance. It extends existing literature by examining how institutional governance, resource configurations, and external environments coalesce to influence environmental and social performance [9,11]. Moreover, the integration of both quantitative indicators, such as portfolio quality, client outreach, and environmental loan ratios, and qualitative insights derived from interviews with MFI staff, clients, and policymakers provides a well-rounded, interdisciplinary perspective. This mixed-methods approach supports more informed conclusions and offers actionable insights for practitioners and policymakers.

Ultimately, the findings from this cross-national comparative study reveal best practices and common challenges in aligning microfinance operations with sustainability objectives. They illuminate the key institutional and contextual drivers that enable or hinder success and offer policy-relevant recommendations for enhancing the developmental impact of MFIs. The remainder of the paper is structured as follows: the next section presents a thematic literature review, followed by a detailed explanation of the methodology, including data sources, empirical models, and sampling strategy. This is followed by the presentation of empirical findings and analysis, interpretation of key results in light of theory and practice, and finally, the conclusion, which highlights implications, limitations, and directions for future research.

2. Literature Review

Existing studies, arranged thematically, have examined the role of microfinance in advancing gender equality, financial inclusion, and economic empowerment. Early research focused primarily on poverty alleviation e.g., [15], while more recent studies have explored how MFIs contribute to sustainability goals through integrated financial and social services [11,16]. Several empirical investigations support this transition. The research in [17] shows that gender inclusivity significantly enhances the social efficiency of MFIs, while [18] finds that MFI outreach is strongly influenced by the level of development in the traditional financial sector. Ref. [4] provides evidence that micro-credit can contribute to broader development objectives under specific institutional conditions. Additionally, Ref. [19] emphasizes the nuanced impact of subsidies on MFI efficiency, revealing that well-targeted support mechanisms can improve both financial sustainability and social performance.

Over time, the scope of MFIs has expanded beyond traditional financial inclusion to encompass broader sustainability goals. This evolution reflects the increasing importance of aligning microfinance practices with global development frameworks such as the United Nations Sustainable Development Goals (SDGs), which emphasize poverty reduction, gender equality, environmental sustainability, and decent work [20]. Ref. [8] argues that MFIs have undergone a strategic shift, adapting their missions to meet the complex demands of social and environmental development while maintaining financial viability. This trend is supported by studies that highlight the integration of environmental risk management, green lending, and climate-resilient agriculture into microfinance operations [4,5]. Moreover, Ref. [21] emphasizes that MFIs, when equipped with appropriate institutional capacity and supported by enabling policy environments, can contribute meaningfully to SDG-aligned outcomes, such as reduced carbon footprints, community resilience, and inclusive economic growth. These shifts also suggest a growing recognition among scholars and practitioners that MFIs can act as policy instruments, not only for poverty alleviation but also for broader ecological and social transformation.

Existing studies, arranged thematically, have examined the role of microfinance in promoting gender equality and economic empowerment. Chronologically, earlier research emphasized poverty alleviation, while recent studies explore the intersection with sustainability [9,10,11,12]. However, the intersection of microfinance with green initiatives, such as clean energy financing, green agriculture, and eco-friendly business models, has received less attention [4,5]. Recent research suggests that partnerships between MFIs and the formal financial sector can create an inclusive financial system that achieves development, job creation, and inequality reduction objectives [1], indicating the potential for microfinance to contribute to a wider range of sustainability goals beyond just poverty alleviation and financial inclusion.

To strengthen the analytical foundation, recent studies emphasize the importance of expanding empirical coverage across countries and institutional types [8]. Stratified sampling techniques are increasingly recommended to capture diverse MFI characteristics, such as size, legal status, and target clientele, to improve generalizability [13]. This is particularly relevant for studies adopting comparative case approaches, where national and institutional variations strongly influence sustainability outcomes.

Our study addresses these gaps by examining how MFIs’ governance structures, institutional size, and sustainability-focused policies influence environmental and social outcomes. Furthermore, it explores the interplay of institutional characteristics and external factors, providing a theoretical grounding in stakeholder theory and resource-based views [10,11].

Microfinance has been shown to contribute not only to poverty reduction and financial sustainability but also to economic empowerment, improved well-being, and social and political empowerment for women, addressing gender equality goals [6,18].

However, limited attention has been given to the integration of microfinance with green initiatives and their broader implications for sustainable development [22,23]. Further, microfinance has been identified as a unique development tool that works toward reducing poverty and maintaining self-sustainability.

Recent literature emphasizes the use of instrumental variables and panel data to assess sustainability impacts. Studies such as [14] highlight potential biases in cross-sectional data, recommending the use of longitudinal models, like GMM, to assess persistent and lagged effects. Moreover, Refs. [4,22] advocate for careful justification of instruments—such as access to environmental finance—and the use of diagnostics to validate causal inference.

Given the underexplored potential of microfinance to drive environmental and social sustainability, the study also integrates insights from recent work, such as [5,21].

Recent studies, including [11,21], have been integrated to provide updated insights. The literature on microfinance and sustainability has been restructured to emphasize three thematic areas.

First, Environmental Finance examines how MFIs promote clean energy adoption and ecological farming practices. Ref. [22] shows that MFIs with formal environmental management policies contribute more effectively to climate resilience. Ref. [5] provides a comprehensive review of MFIs’ green lending programs, while Ref. [24] outlines how developing countries are experimenting with green finance mechanisms through microfinance.

For example, Refs. [10,21] highlight the role of governance mechanisms in driving sustainability within MFIs in the MENA region, providing insights into their potential to expand formal financial systems. MFIs are increasingly recognized as pivotal contributors to advancing sustainable development agendas. However, empirical studies examining how these institutions incorporate sustainability into their operational models remain sparse.

Second, Sustainability Practices explore the adoption of sustainability-focused policies and programs by MFIs, providing insights into how these practices align with the SDGs. Third, Poverty Alleviation examines the critical role of MFIs in reducing inequality and fostering economic empowerment, particularly among marginalized populations. These thematic subheadings integrate recent studies, such as [6,13], to offer updated perspectives on the multifaceted contributions of MFIs to sustainable development.

The main objective of microfinance is to expand the outreach of financial services in order to alleviate poverty [2,25]. By providing access to small-scale monetary services, such as credit, savings, and insurance, microfinance enables individuals in poverty to bypass the barriers of traditional banking systems. Existing empirical research has explored the financial sustainability of MFIs, with [1,26] emphasizing that MFIs must balance outreach and sustainability.

Sustainable MFIs operate profitably without subsidies, demonstrating that financial sustainability does not necessarily compromise the depth and breadth of outreach [8].

Recent contributions also examine the internal drivers of sustainability, including leadership and organizational diversity. Ref. [10] argue that sustainable leadership and inclusive governance can significantly influence the success of green microfinance strategies. Gender diversity within management is also noted as a moderating factor in improving social performance outcomes.

Ref. [21] investigate key influencing factors and development strategies for MFIs, providing actionable insights into improving their financial and operational sustainability. Additionally, Ref. [6] highlights the role of financial literacy in empowering women through green microfinance, reinforcing the importance of integrating educational components into microfinance initiatives.

Faith-based dimensions are explored by [1,27], who demonstrate how religious institutions offering microfinance services contribute to broader social and environmental goals.

Finally, Refs. [18,21] examine how financial development and institutional characteristics, such as funding sources and geographic scope, influence sustainability outcomes. Systematic reviews have examined how microfinance can support sustainable poverty reduction, emphasizing the importance of governance and regional context [1,28].

These existing empirical studies show that focusing on financial sustainability does not necessarily harm outreach. However, conventional portfolio models often fail to account for sustainability, requiring more holistic evaluation tools, such as fuzzy logic and composite sustainability indices [21].

Based on the existing literature, we propose the following hypotheses:

H1. 

MFIs that incorporate environmental and social sustainability into their operational models will have a positive impact on environmental and social outcomes, as measured by indicators such as greenhouse gas emissions, energy/water consumption, waste management, poverty alleviation, and women’s empowerment.

This hypothesis is supported by prior empirical evidence demonstrating that MFIs with sustainability-oriented policies, such as green lending and environmental risk management, generate measurable improvements in development outcomes. Ref. [22] found that MFIs with formal environmental strategies were more effective in promoting ecological responsibility. Similarly, Ref. [21] identified a significant correlation between green microfinance practices and positive environmental performance. Additional support comes from [10], who emphasized the importance of gender-responsive governance in green microfinance, and [6], who linked microfinance access with women’s empowerment. Ref. [7] further affirms that well-structured MFIs contributed to poverty alleviation and improved well-being in Sub-saharan Africa.

H2. 

The sustainability performance of MFIs, as measured by a composite metric capturing the balance between financial, environmental, and social objectives, will be positively associated with their overall institutional characteristics, such as size, age, and geographic scope, as well as the adoption of sustainability-focused policies and programs.

This hypothesis is grounded in literature emphasizing the role of institutional capacity in supporting sustainable outcomes. Ref. [8] argues that organizational characteristics, such as scale and legal status, affect MFI sustainability. Ref. [11] highlights the influence of governance and internal capabilities in enhancing performance. Ref. [13] demonstrates that institutional diversity and structure significantly shape the success of sustainability strategies across regions. Ref. [1] discusses the trade-offs between outreach and financial sustainability, while Ref. [12] underscore the importance of leadership and board diversity in embedding sustainability into MFI operations.

3. Research Method

Our study aims to investigate how MFIs incorporate sustainability into their operational models and the resulting impact on environmental and social outcomes. This study employed a comparative case study approach, analyzing data from multiple countries where MFIs have demonstrated a commitment to integrating sustainability into their practices.

By combining empirical econometric analysis with descriptive and correlational insights, the research investigates the effectiveness of sustainability-focused financial strategies in driving development outcomes. The sample consists of 30 MFIs from nine countries: Afghanistan, Albania, Angola, Argentina, India, Kenya, Ghana, Mexico, and Peru. The study period spans from 2018 to 2023, allowing for longitudinal analysis. To ensure broad representation across institutional types, a stratified purposive sampling method was employed.

Table 1. Sample of Microfinance Institutions by Country (2018–2023).

Country	Microfinance Institution
India	Bandhan Bank Svavlamban Microfinance Satin Creditcare Network Ujjivan Financial Services
Kenya	Equity Bank Juhudi Kilimo Kenya Women Microfinance Bank Faulu Microfinance Bank
Peru	Edyficar MiBanco Micredito
Mexico	Compartamos Banco Financiera Independencia Fondo Microfinanza Te Creemos
Ghana	Sinapi Aba ID Ghana Opportunity International Savings and Loans
Afghanistan	FINCA Afghanistan, OXUS Afghanistan, MISFA
Albania	NOA Albania, FED Invest, BESA Fund
Angola	KixiCredito, NovoBanco Angola, KixiMais
Argentina	FIE Argentina, Banco de la Gente, Fundación Pro Mujer

provides a detailed overview of the MFIs included in the study, categorized by country and institutional profile.

Table 2. Descriptive Statistics of Key Variables.

Variable	Mean	SD	Min	Max
GHG Emissions (tons CO2 eq.)	150.25	75.50	50	300
Water Usage (cubic meters)	2500.75	1250.25	500	5000
Waste Diverted from Landfill (tons)	10.50	5.25	2.00	20.00
Gender Empowerment Index	0.78	0.12	0.55	0.95
Household Income (USD)	4500	2250	1500	9000
Asset Ownership Index	0.65	0.15	0.40	0.90
Institutional Size (total assets USD)	5,000,000	2,500,000	1,000,000	10,000,000
Green Lending Ratio (%)	25.00	12.50	5.00	50.00

Sources: Global Reporting Initiative (GRI), United Nations Development Programme (UNDP), and Microfinance Information Exchange (MIX) databases. (https://data.worldbank.org, https://hdr.undp.org, https://www.findevgateway.org, Previously: https://www.themix.org).

outlines the distribution of key variables, providing context for the study’s quantitative analysis. A stratified purposive sampling approach was used to capture variation across MFI size, governance, and geography, enhancing both representativeness and relevance [8,13].

The data highlights substantial variation across institutions and regions. For instance, greenhouse gas (GHG) emissions range from 50 to 300 tons of CO₂ equivalent, with a mean of 150.25, reflecting differing environmental footprints. Similarly, water usage varies widely, from 500 to 5000 cubic meters, suggesting diverse operational scales. Social indicators, such as the Gender Empowerment Index (mean = 0.78) and Asset Ownership Index (mean = 0.65), capture socioeconomic inclusiveness, while financial variables, like household income (mean = USD 4500) and institutional size (mean = USD 5,000,000), reflect economic conditions and organizational capacity. The Green Lending Ratio, with a mean of 25%, points to varying degrees of sustainability focus among institutions.

Qualitative data were obtained through semi-structured interviews conducted between 2018 and 2023 with MFI managers, frontline staff, borrowers, and local community partners.

These interviews explored sustainability practices and operational challenges and were triangulated with institutional documents and third-party reports to reduce bias. While qualitative insights are not used in econometric modeling, they contextualize quantitative findings and highlight best practices and implementation gaps. To support the analysis,

Table 3. Definitions and sources of variables.

Variables	Definition	Sources
Environmental impact	Measures of greenhouse gas emissions, energy/water consumption, and waste management within the client businesses financed by the MFIs	World Bank and UNDP
Social impact	Indicators of poverty alleviation, gender empowerment, and community development, such as changes in household income, asset ownership, and decision-making power	World Bank, UNDP, national statistics, and MIX Market
Sustainability performance	Composite metrics that capture the institution’s balance between financial, environmental, and social objectives	World Bank, UNDP, and MIX Market
Institutional characteristics	The size, age, and geographic scope of the MFIs	World Bank, UNDP, and MIX Market
Sustainability-focused policies and programs	Measures of green lending, environmental risk management, and social impact initiatives	World Bank, institution records, client-level data, and staff interviews
Contextual factors	Macroeconomic conditions, regulatory environment, and the level of competition	World Bank, national statistics, MIX Market, and expert interviews

UNDP: United Nations Development Programme.

provides detailed definitions and sources for all variables used in the study.

The empirical strategy employs a multi-stage econometric framework to evaluate both immediate and persistent effects of MFIs’ sustainability policies. First, Ordinary Least Squares (OLS) models are used to assess the direct relationships between institutional characteristics, sustainability initiatives, and contextual factors on environmental and social impacts. The baseline regression models are as follows:

$$\begin{array}{ll}\hfill Environmental Impact it& \\ & =\beta 0+\beta 1 Institutional Characteristics it+\beta 2 Sustainability\\ & - focused Policies and Programs it+\beta 3 Contextual Factors it+\epsilon it\end{array}$$

$$\begin{array}{ll}\hfill Social Impact it& \\ & =\beta 0+\beta 1 Institutional Characteristics it+\beta 2 Sustainability\\ & - focused Policies and Programs it+\beta 3 Contextual Factors it+\epsilon it\end{array}$$

where:

• β0: The intercept term.
• β1: A vector of coefficients representing the effect of institutional characteristics on environmental or social impact.
• β2: A vector of coefficients representing the effect of sustainability policies on environmental or social impact.
• β3: A vector of coefficients representing the effect of contextual factors on environmental or social impact.
• ϵ: The error term.

Given the risk of endogeneity, particularly between sustainability policies and development outcomes, the second stage applies an Instrumental Variable (IV) approach. The instrument used is “access to environmental finance,” which reflects the availability of national or institutional green funding mechanisms. This instrument is validated both theoretically and empirically through correlation analysis and weak instrument diagnostics, including first-stage F-statistics above the conventional threshold of 10 [8,10,21]. The IV-enhanced models are as follows:

$$\begin{array}{ll}\hfill Environmental Impact it& \\ & =\beta 0+\beta 1 Institutional Characteristics it+\beta 2 Sustainability\\ & - focused Policies and Programs it+\beta 3 Contextual Factors it+\beta 4 Vit+\epsilon it\end{array}$$

$$\begin{array}{ll}Social Impact& =\beta 0+\beta 1 Institutional Characteristics+\beta 2 Sustainability-focused Policies and Programs\\ & + \beta 3 Contextual Factors+\beta 4 Vit+\epsilon it\end{array}$$

where:

• IV: The instrumental variable, “access to environmental finance”, which captures the availability of funding for green microfinance initiatives.
• β4: A coefficient representing the effect of the instrumental variable on the dependent variable.

To capture policy persistence and temporal dynamics, the third stage employs a dynamic panel model using the Generalized Method of Moments (GMM). This technique controls for unobserved heterogeneity, simultaneity, and autocorrelation by including lagged dependent variables. The GMM specification is as follows:

$$\begin{array}{ll}\hfill \Delta Environmental Impact it& \\ & =\mathit{\alpha }0+\mathit{\alpha }1 Environmental Impact it-1+\mathit{\alpha }2 Institutional Characteristics it+\mathit{\alpha }3 Sustainability\\ & - focused Policies and Programs it+\mathit{\alpha }4 Contextual Factors it+\mu t+vi\end{array}$$

$$\begin{array}{ll}\Delta Social Impact it& =\mathit{\alpha }0+\mathit{\alpha }1 Social Impact it-1+\mathit{\alpha }2 Institutional Characteristics it+\mathit{\alpha }3 Sustainability\\ & - focused Policies and Programs it+\mathit{\alpha }4 Contextual Factors it+\mu t+vi\end{array}$$

where:

• ΔEnvironmental Impac t: Change in environmental impact at time t.
• Environmental Impact t−1: Lagged environmental impact.
• μt: Time-specific effects.
• vi: Unobserved individual-specific effects.

The GMM estimation was performed using Arellano-Bond one-step and two-step procedures implemented in Stata 17.0 and R(ivreg), to ensure robustness and consistency of estimators.

Table 4. Correlation Matrix of Variables.

	EI	SI	S	GOV	G L	ER Mgmt.	C L P	MC	A Env. F	SI P
Environmental Impact	1.0	0.62	0.45	0.43	0.51	0.47	0.39	0.31	0.48	0.23
Social Impact	0.64	1.0	0.49	0.46	0.45	0.38	0.35	0.28	0.41	0.52
Size	0.48	0.51	1.0	0.35	0.38	0.32	0.25	0.21	0.33	0.27
Governance	0.46	0.48	0.37	1.0	0.41	0.39	0.34	0.25	0.29	0.31
Green Lending	0.53	0.47	0.39	0.44	1.0	0.43	0.36	0.27	0.42	0.19
Environmental Risk Mgmt.	0.49	0.41	0.33	0.41	0.46	1.0	0.33	0.24	0.37	0.17
Country-Level Policies	0.42	0.37	0.27	0.38	0.4	0.36	1.0	0.32	0.3	0.22
Macroeconomic Conditions	0.34	0.32	0.24	0.3	0.29	0.31	0.35	1.0	0.25	0.19
Access to Env. Finance	0.5	0.43	0.35	0.31	0.45	0.39	0.32	0.26	1.0	0.15
Social Impact Programs	0.25	0.54	0.3	0.33	0.28	0.22	0.29	0.21	0.18	1.0

below presents the correlation matrix among the key variables, providing insights into their pairwise relationships and informing multicollinearity considerations.

Results show meaningful associations, such as strong correlations between green lending and environmental outcomes (r = 0.53), and between social impact programs and social outcomes (r = 0.54). Governance quality and access to environmental finance are also positively correlated with both impact dimensions. Additionally, the correlation coefficient of 0.64 between environmental and social impact indicates a moderately strong positive relationship, suggesting that MFIs achieving environmental objectives are also likely to deliver stronger social outcomes. These findings support the inclusion of sustainability-focused policy variables and institutional characteristics in the regression framework.

4. Results

To assess the impact of sustainability-oriented policies implemented by Microfinance Institutions (MFIs), the study employs a three-step empirical strategy using Ordinary Least Squares (OLS), Instrumental Variables (2SLS), and Generalized Method of Moments (GMM). Each method progressively strengthens causal inference, addresses endogeneity, and captures the dynamic effects of policy over time. The tables below present the findings from each econometric model, accompanied by detailed interpretation. These estimations evaluate the effect of sustainability-focused policies, institutional features, and contextual variables on environmental and social development outcomes. The analysis is based on panel data from 30 MFIs operating in nine countries between 2018 and 2023.

The initial OLS results in

Table 5. Ordinary Least Squares (OLS) Regression Results.

Variable	Environmental Impact (GHG Emissions)			Social Impact (Gender Empowerment)
	Unstd. Est.	Std. Error	p-Value	Unstd. Est.	Std. Error	p-Value
Institutional Size	0.145	0.082	0.087 *		0.014	0.140
Green Lending Ratio	−0.690	0.110	0.000 ***	0.468	0.075	0.000 ***
Macroeconomic Stability	−0.230	0.130	0.080 *	0.120	0.055	0.031 **
Regulatory Conditions	−0.150	0.100	0.140	0.230	0.095	0.020 **
Constant	255.56	25.570	0.000 ***	0.570	0.090	0.000 ***
Observations	180			180
R-squared	0.78			0.82
Adjusted R-squared	0.75			0.79
F-statistic	20.56 ***			25.78 ***

Note. Standard errors are in parentheses. * p < 0.10, ** p < 0.05, *** p < 0.01.

demonstrate that green lending significantly reduces greenhouse gas emissions (β = −0.678, p < 0.01) and positively influences gender empowerment (β = 0.456, p < 0.01). Macroeconomic stability is also significant in both models. Institutional size has a weak association with environmental outcomes and an insignificant relationship with social outcomes. These results offer baseline support for hypothesis 1 (H1) and partial support for hypothesis 2 (H2), which posits that institutional characteristics influence sustainability performance. The adjusted R² values (0.75 for environmental and 0.79 for social models) demonstrate strong model fit and further validate the relationships.

To correct for potential endogeneity,

Table 6. Instrumental Variables (2SLS) Regression Results.

Variable	Environmental Impact (GHG Emissions)			Social Impact (Gender Empowerment)
	Unstd. Est.	Std. Error	p-Value	Unstd. Est.	Std. Error	p-Value
Institutional Size	0.145	0.082	0.087 *	−0.021	0.014	0.140
Green Lending Ratio	−0.678	0.110	0.000 ***	0.468	0.075	0.000 ***
Macroeconomic Stability	−0.234	0.130	0.080 *	0.120	0.055	0.031 **
Regulatory Conditions	−0.156	0.100	0.140	0.234	0.095	0.020 **
Access to Environmental Finance (IV)	−0.200	0.090	0.030 **	0.100	0.045	0.028 **
Constant	255.560	25.570	0.000 ***	0.570	0.090	0.000 ***
Observations	180			180
R-squared	0.79			0.83
Adjusted R-squared	0.76			0.80
F-statistic	21.56 ***			26.78 ***

Note. Standard errors are in parentheses. * p < 0.10, ** p < 0.05, *** p < 0.01.

presents the results of 2SLS regression using “access to environmental finance” as an instrument. The instrument is significant in both models and passes weak identification tests. This variable captures the availability of external green finance resources that may influence the adoption of sustainability practices without being directly affected by observed MFI-level outcomes.

Green lending remains significant and positively associated with improved social and environmental outcomes. The results further reinforce H1 and validate the use of the instrument.

Table 7. Generalized Method of Moments (GMM) Regression Results.

Variable	Environmental Impact (GHG Emissions)			Social Impact (Gender Empowerment)
	Unstd. Est.	Std. Error	p-Value	Unstd. Est.	Std. Error	p-Value
Lagged Environmental Impact	0.456	0.078	0.000 ***
Lagged Social Impact				0.345	0.056	0.000 ***
Institutional Size	0.140	0.075	0.068 *	−0.020	0.012	0.110
Green Lending Ratio	−0.650 ***	0.100	0.000 ***	0.440 ***	0.070	0.000 ***
Macroeconomic Stability	−0.220	0.120	0.075 *	0.110 **	0.050	0.030 **
Regulatory Conditions	−0.140	0.090	0.120	0.220 **	0.090	0.020 **
Constant	245.56	25.50	0.000 ***	0.550	0.090	0.000 ***
Observations	180			180
Hansen test of overidentification restrictions	0.75 (p = 0.80)			0.76 (p = 0.80)
Arellano-Bond test AR(1)	−2.00 (p = 0.04)			−2.00 (p = 0.04)
Arellano-Bond test AR(2)	0.50 (p = 0.60)			0.50 (p = 0.60)

Note. Standard errors are in parentheses. * p < 0.10, ** p < 0.05, *** p < 0.01.

provides GMM regression results. Lagged dependent variables are significant in both models (β = 0.456 for environmental impact and β = 0.345 for social impact, p < 0.01), indicating strong temporal persistence. Green lending continues to show significant positive effects. Hansen and Arellano–Bond test statistics confirm model validity.

These results provide strong support for H1, as they show sustained improvements in both environmental and social domains where sustainability-focused policies are present. Moreover, green lending and macroeconomic stability remain significant, validating their continued role in influencing development outcomes. The Hansen test for overidentification (p = 0.80) and Arellano–Bond tests for AR(1) and AR(2) indicate that model assumptions are met. Institutional size, while marginally significant in the environmental model (β = 0.140, p < 0.10), remains non-significant in the social model, providing limited but consistent support for H2.

The combined results from OLS, 2SLS, and GMM estimations provide robust support for the hypothesis that sustainability-integrated microfinance contributes to improved development outcomes. Green lending policies consistently demonstrate strong associations with environmental performance and gender empowerment. Institutional capacity has a modest but observable effect. These results highlight the crucial role of both internal strategies and external support in driving the sustainability agenda in microfinance.

5. Discussion

The empirical results of this cross-national study provide compelling evidence on the role of MFIs in driving sustainable development outcomes. By applying a layered econometric framework, including Ordinary Least Squares (OLS), Instrumental Variables (2SLS), and Generalized Method of Moments (GMM), the study offers robust, triangulated insights into how institutional characteristics and sustainability-focused policies affect environmental and social impact.

The findings strongly support hypothesis 1 (H1), demonstrating that MFIs integrating sustainability into their operational frameworks, through policies such as green lending, environmental risk management, and social impact programs, achieve statistically significant improvements in both environmental performance (e.g., reductions in greenhouse gas emissions) and social inclusion (e.g., enhanced gender empowerment). In particular, the green lending ratio consistently emerged as a strong predictor across all models, confirming its effectiveness in promoting sustainable finance practices [10,22].

These effects were further confirmed through the use of instrumental variables, specifically “access to environmental finance,” which validated the causal pathway between policy adoption and development outcomes. The 2SLS estimates demonstrated that external financial access significantly influenced MFI adoption of green practices, which in turn improved environmental and social metrics. This reinforces the idea that sustainability in microfinance is not only driven by internal policy but also by the surrounding financial ecosystem [5,8].

Hypothesis 2 (H2) also receives moderate but consistent support. Institutional characteristics, particularly governance quality and institutional size, were positively associated with sustainability performance, though with less consistency than the policy variables. This suggests that, while internal capacity enhances the effectiveness of sustainability initiatives, it is not as critical a determinant as policy alignment itself. These findings align with prior research emphasizing the role of good governance and organizational structure in facilitating development outcomes within MFIs [11,21].

The dynamic panel model (GMM) adds a temporal dimension to the analysis, revealing that sustainability-focused impacts persist over time. Lagged dependent variables, both environmental and social, were statistically significant, indicating path dependency and cumulative benefits of sustained policy implementation. The GMM model passed all key diagnostic tests, including the Hansen test for overidentification and the Arellano–Bond tests for autocorrelation, affirming model validity. These findings highlight the importance of long-term institutional commitment and strategic alignment in driving sustainable microfinance outcomes.

In terms of contextual variation, the study uncovered notable regional differences in the integration of sustainability practices across MFIs. In developing countries, such as Afghanistan, Angola, India, Kenya, Ghana, and Peru, MFIs played a critical role in facilitating access to clean energy technologies, such as solar panels and biogas systems, while also promoting eco-friendly entrepreneurship and fostering community development. These initiatives were particularly impactful in rural and underserved areas, where MFIs filled essential service gaps and contributed directly to the SDGs. Conversely, in more formalized economies, such as Mexico, Argentina, and Albania, sustainability efforts were more concentrated on supporting green small and medium-sized enterprises (SMEs) and promoting sustainable production and consumption patterns. These differences emphasize the adaptability of MFIs in responding to region-specific development challenges and opportunities, confirming their versatility as vehicles for sustainable finance [13,19].

The study also provides new insights into the enabling role of macroeconomic and regulatory environments. Across the full sample, macroeconomic stability and supportive national policy frameworks were positively associated with improved sustainability outcomes, including emissions reduction and social inclusion. In contrast, competitive market conditions, particularly in financially saturated environments, were negatively correlated with environmental performance, possibly due to MFIs prioritizing short-term financial survival over long-term sustainability goals. These findings suggest that MFIs require not only internal capacity and mission alignment but also external institutional support to optimize their developmental impact [4].

Beyond the econometric findings, the implications for practice are substantial. Policymakers and development agencies should prioritize enabling environments through regulatory reform, financial incentives, and capacity-building. MFIs that demonstrate readiness and strategic alignment should be targeted for sustainability-linked subsidies, technical assistance, and blended finance mechanisms. Additionally, capacity development in areas such as ESG reporting, gender mainstreaming, and environmental literacy is essential for building long-term institutional resilience.

While the study’s empirical robustness is strengthened by its triangulation across three econometric methods and the inclusion of dynamic panel data, several limitations merit consideration. Moreover, it is important to note that small and medium-sized MFIs may not consistently report comprehensive data on sustainability initiatives due to limited technical capacity and lack of dedicated resources. These constraints can result in underreporting or fragmented disclosures, which may affect the reliability of some variables used in regression analysis. Such data gaps could introduce bias in estimating the true magnitude of sustainability impacts, particularly in institutions operating in resource-constrained environments.

First, although the sample of 30 MFIs is diverse, it may not fully capture all regional variations in the global microfinance landscape. Second, despite the longitudinal elements incorporated through GMM, the primary dataset remains constrained to a six-year window (2018–2023). Moreover, although the selected instrumental variable: access to environmental finance, passes conventional validity tests (e.g., first-stage F-statistics, Hansen’s J-test), the possibility of omitted variable bias or residual confounding cannot be entirely ruled out. Additionally, the IV may be influenced by broader institutional or policy dynamics that are difficult to fully disentangle in non-experimental settings. These caveats suggest that, while the findings are directionally strong and statistically significant, caution should be exercised in attributing causal effects without further sensitivity testing or triangulation with micro-level or experimental data.

Our findings confirm that MFIs, when equipped with institutional capacity, sustainability-oriented policies, and supportive ecosystems, can transition from instruments of financial inclusion to powerful vehicles for sustainable development. By providing empirical validation for both the environmental and social impacts of strategic MFI governance and policy, this study offers timely insights for advancing the global sustainable development agenda.

6. Conclusions

This study provides robust empirical evidence on the evolving role of microfinance institutions (MFIs) as catalysts for sustainable development. Drawing on a cross-national sample of 30 MFIs from nine countries and employing a rigorous, three-stage econometric framework: Ordinary Least Squares (OLS), Instrumental Variables (2SLS), and Generalized Method of Moments (GMM), the analysis confirms that MFIs can simultaneously advance financial sustainability and generate measurable environmental and social impact.

Key findings indicate that sustainability-focused policies, particularly green lending initiatives, environmental risk management, and targeted social programs, are significantly associated with reductions in greenhouse gas emissions and improvements in gender empowerment, poverty alleviation, and community resilience. Notably, the study highlights that MFIs play a powerful role in advancing women’s empowerment, both economically and socially, by enhancing female borrowers’ financial autonomy, decision-making power, and participation in community leadership. These social gains reinforce the broader developmental value of inclusive microfinance practices and align directly with the Sustainable Development Goals (SDGs), particularly those related to gender equality.

These impacts are further amplified in institutions with larger size and stronger governance structures, offering robust support for both research hypotheses (H1 and H2). The GMM results confirm that sustainability-focused outcomes are not transient but persist over time, underlining the importance of institutional commitment and policy continuity.

The use of “access to environmental finance” as an instrumental variable improves causal inference and demonstrates that MFIs embedded in supportive financial ecosystems are more likely to integrate sustainability into their operations. The panel design mitigates the limitations of cross-sectional analysis by capturing lagged effects and temporal dynamics, thus reinforcing the robustness of the study’s conclusions.

In terms of contextual variation, the study uncovers notable regional differences. In developing countries, such as Afghanistan, Angola, Kenya, Ghana, India, and Peru, MFIs were instrumental in expanding access to clean energy technologies and supporting eco-friendly entrepreneurship, especially among women in rural and underserved areas. Conversely, in more formalized economies, like Mexico, Argentina, and Albania, MFIs concentrated on financing green SMEs and promoting sustainable consumption. These differences highlight the sector’s adaptability to local development challenges and institutional capacities.

From a policy perspective, the findings emphasize the importance of enabling environments, characterized by macroeconomic stability, strong regulatory frameworks, and access to green finance, for MFIs to optimize their developmental impact. Targeted public-private partnerships, capacity-building programs, and sustainability-linked incentives can further enhance the effectiveness of MFIs, especially in scaling gender-inclusive, environmentally sound initiatives. Institutions that align governance and operations with environmental and social goals are best positioned to serve as transformational actors in the development finance landscape.

Nevertheless, the study has limitations. Although the sample was expanded and stratified, it may not fully reflect the global heterogeneity of MFIs, and the six-year panel window (2018–2023) restricts the ability to observe long-term structural changes. In addition, the use of self-reported data may introduce measurement bias. Future research should extend the temporal scope, include more geographically diverse cases, particularly from underrepresented regions, and incorporate objective environmental and social indicators. Experimental or quasi-experimental designs (e.g., randomized controlled trials or difference-in-differences approaches) would further strengthen causal attribution.

In conclusion, this study demonstrates that MFIs, when supported by institutional capacity, strategic governance, sustainability-aligned policies, and conducive policy environments, can transcend their traditional role as providers of financial access. They can become strategic actors in addressing global environmental and social challenges, including the empowerment of women and the reduction of emissions. By bridging rigorous econometric analysis with policy relevance, this research offers a replicable framework for evaluating sustainable microfinance and provides practical guidance for scaling its impact in the pursuit of inclusive, climate-resilient development.