Microfinance Banks and Rural Development: The Nigeria Experience
19 Nov 2014-International Journal of Rural Management (SAGE Publications)-Vol. 10, Iss: 2, pp 147-171
TL;DR: The Central Bank of Nigeria (CBN) launched the microfinance banking scheme on December 2005 as part of government strategies to achieve one of the cardinal agendas of the Millennium Development Goa...
Abstract: The Central Bank of Nigeria (CBN) launched the microfinance banking scheme on December 2005 as part of government strategies to achieve one of the cardinal agendas of the Millennium Development Goa...
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TL;DR: In this paper, the authors explore new evidence about financial innovation in small and medium enterprises (SME) financing impact on SME development in Bangladesh from 1985 to 2016, and propose a model to evaluate the impact of financial innovation on SMEs.
Abstract: With this study, we try to explore new evidence about financial innovation in small and medium enterprises (SME) financing impact on SME development in Bangladesh from 1985 to 2016. To bring insigh...
36 citations
04 Mar 2019
TL;DR: In this article, the authors analyze the role of micro-credit in intensive farming to improve rural prosperity and to determine factors affecting farmers to access micro- credit and to adopt technologies.
Abstract: This paper aims to analyse a simultaneous role of micro-credit in intensive farming to improve rural prosperity and to determine factors affecting farmers to access micro-credit and to adopt technologies.,This paper uses a concept of technological change as the underlying theory. The analysis is conducted using structural equation modelling based on data compiled from a survey that interviewed 220 of farm-households. Samples of the study were randomly selected from chili farming community in three regions of Java in 2013-2014.,The results show that micro-credit provides positive direct and indirect impacts on rural prosperity. The indirect effect of micro-credit was due to a mediation of technology adoption. Farmers’ personalities and agribusiness environment determined farmers’ decision to access micro-credit and to adopt the technology.,Policymakers should introduce more advanced technology and provide credit facilities at the same time to ensure technology adoption and welfare improvement of the community.,Using structural equation modelling enables analysis of simultaneous regression models. Along with technology here, micro-credit played roles as catalyst and reagent in improving rural livelihood.
27 citations
TL;DR: In this paper, the authors analyzed the impact of microcredit and agronomic technology on farm households' prosperity and determined important factors affecting farmers' access to micro-credit and technology adoption in Indonesian intensive farming.
Abstract: The purpose of this paper is to analyze the impact of microcredit and agronomic technology on farm households’ prosperity, and to determine important factors affecting farmers’ access to microcredit and technology adoption in Indonesian intensive farming,The focus of the study was farmers engaging with chili-based agribusiness in rural areas Data for this study were compiled from a survey that interviewed 250 farm households Samples of the study were randomly selected from chili farming community in three regions of Java during 2013–2014 Data were analyzed using structural equation modeling (SEM),Microcredit provided positive direct and indirect impacts on household prosperity Microcredit indirectly impacted the well-being through the mediation of technology adoption Farmers’ characteristics and agribusiness environment determined farmers’ decision to access microcredit and adopt advanced technology Microcredit and technology have enhanced farmers’ well-being through pathways that enabled farmers to develop farming scale,The government should offer more alternatives to advanced technology and flexible procedures of access to credit at the same time to ensure sustained pathways of rural economic growth in Indonesia,This paper applied a SEM to a proposition of simultaneous causal interrelations among microcredit, technology and farmers’ prosperity
20 citations
Dissertation•
29 Mar 2019
TL;DR: In this article, a case study of two micro-finance institutions (MFIs)-a microfinance bank (MFB) and a non-bank MFI (NMFI) in Plateau State, Nigeria is presented.
Abstract: Studies on microfinance risk management in Nigeria are inclined to quantitative analysis of risk based on business and accounting principles without recourse to understanding and interpreting meanings from the lived experiences of relevant stakeholders. This thesis is an in-depth study of the contexts (economic, political, social and cultural) in which stakeholders interpret and manage risks based on a case study of two microfinance institutions (MFIs)-a microfinance bank (MFB) and a non-bank MFI (NMFI) in Plateau State, Nigeria. It is predicated on the understanding that risks are subjective and interpreted by stakeholders- board members, investors, staff, clients and community leaders as distinct entities. It aligns with the interpretivist philosophy in examining how meanings are created from experiences which are embedded in the contexts in which stakeholders engage with MFIs. Drawing on the Social Theories of Risk and Stakeholder Theory, this study adopts a qualitative approach and case study research design using data obtained from document reviews, observation, 33 individual interviews and 3 focus group discussions with purposefully selected stakeholders. Thematic analysis was facilitated using NVivo, a Computer-Aided Qualitative Data Analysis Software (CAQDAS), to generate and discuss themes based on participants’ perspectives. Its major findings show that risks are conceptualized in terms of unforeseen eventualities underpinned by social complexities in MFIs’ lending to micro clients which make their sustainability and outreach problematic. Major sources of risks for MFIs in the state addressed in this thesis include; low repayment rates, diversion or misuse of loans by clients, low level of knowledge and skills by practitioners, competition with commercial banks, inadequate support by the government, poor customer relationship management, low adoption of financial technology, influence of patriarchy, political interferences, recurring ethno-religious conflicts, poor orientation and awareness of the social mission of microfinance. Furthermore, the study found that risk management in the MFIs studied is hampered by their ownership structures and operating methodologies. The originality and contribution to knowledge of this thesis lie in developing a framework for subjective risk management in microfinance embedded in the identities, perceptions, behaviours and interests of stakeholders within the context of the study.
14 citations
TL;DR: In this article , the impact of financial inclusion, financial literacy, and financial initiatives on sustainable growth is investigated through the mediation of financial literacy through PLS-SEM modeling, and the results highlight that usage, digitalization, and FinTech emerged as significant drivers of FI.
Abstract: The present study examines how successful we are in achieving financial inclusiveness, investigating the influence of the drivers of financial inclusion (FI), financial literacy, and financial initiatives on sustainable growth. The drivers of FI considered are digitalization, technology, and usage. This study proceeds with a difference and investigates the impact of the drivers on sustainable growth through the mediation of financial literacy. The basic purpose is to understand whether mediation assists in enhancing the impact of the drivers of FI on sustainable growth. Sustainable growth is measured by knowing customers’ perceptions regarding FI success through the achievement of the SDGs, viz., SDGs 1, 3, 5, 8, 9, 10, 11, and 17, especially related to poverty alleviation; removing gender inequality; and promoting industrial growth. The study uses PLS-SEM modeling to investigate the impact of the drivers of FI, financial literacy, and financial initiatives on sustainable growth. The results highlight that usage, digitalization, and FinTech emerged as significant drivers of FI. The study assesses the direct impact of the drivers of FI on sustainable growth and the indirect effect through the mediation of financial literacy. This is indicative of the importance of financial literacy in accentuating the impact of the drivers on sustainable growth. However, financial initiatives positively impact sustainable growth in the northern region of India as well.
7 citations
References
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Book•
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TL;DR: In this article, the authors discuss diagnostic checking, model selection, and specification testing for Econometrics, including Diagnostic Checking, Model Selection, and Specification Testing, as well as a discussion of nonlinear regression, models of expectations, and nonnormality errors in Variables.
Abstract: Foreword Preface to the Second Edition Preface to the Third Edition Obituary INTRODUCTION AND THE LINEAR REGRESSION MODEL What is Econometrics? Statistical Background and Matrix Algebra Simple Regression *Multiple Regression VIOLATION OF THE ASSUMPTIONS OF THE BASIC MODEL *Heteroskedasticity *Autocorrelation Multicollinearity *Dummy Variables and Truncated Variables Simultaneous Equations Models Nonlinear Regression, Models of Expectations, and Nonnormality Errors in Variables SPECIAL TOPICS Diagnostic Checking, Model Selection, and Specification Testing *Introduction to Time--Series Analysis Vector Autoregressions, Unit Roots, and Cointegration *Panel Data Analysis *Large--Sample Theory *Small--Sample Inference: Resampling Methods Appendix A: *Data Sets Appendix B:* Data Sets on the Web Appendix C:* Computer Programs Index
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TL;DR: This paper showed that stock market liquidity and banking development both positively predict growth, capital accumulation, and productivity improvements when entered together in regressions, even after controlling for economic and political factors.
Abstract: Do well-functioning stock markets and banks promote long-run economic growth? This paper shows that stock market liquidity and banking development both positively predict growth, capital accumulation, and productivity improvements when entered together in regressions, even after controlling for economic and political factors. The results are consistent with the views that financial markets provide important services for growth and that stock markets provide different services from banks. The paper also finds that stock market size, volatility, and international integration are not robustly linked with growth and that none of the financial indicators is closely associated with private saving rates. Copyright 1998 by American Economic Association.
3,399 citations
Posted Content•
TL;DR: In this paper, the authors investigate whether measures of stock market liquidity, size, volatility, and integration in world capital markets predict future rates of economic growth, capital accumulation, productivity improvements, and private savings.
Abstract: Using data on 49 countries from 1976 to 1993, the authors investigate whether measures of stock market liquidity, size, volatility, and integration in world capital markets predict future rates of economic growth, capital accumulation, productivity improvements, and private savings. They find that stock market liquidity-as measured by stock trading relative to the size of the market and economy - is positivelyand significantly correlated with current and future rates of economic growth, capital accumulation, productivity growth, even after controlling for economic and political factors. Stock market size, volatility, and integration are not robustly linked with growth. Nor are financial indicators closely associated with private savings rates. Significantly, banking development -as measured by bank loans to private enterprises divided by GDP -when combined with stock market liquidity predicts future rates of growth, capital accumulation, and productivity growth when entered together in regressions. The authors determine that these results are consistent with views that (1)financial markets and institutions provide important services for long-run growth, and (2)stock markets and banks provide different financial services.
3,388 citations
"Microfinance Banks and Rural Develo..." refers result in this paper
...This approach is in tandem with similar works by Levine and Zervos (1998)....
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Book•
06 Dec 2013
TL;DR: In this article, a simple regression model with time series data and OLS asymptotics is presented. But the model is not suitable for the analysis of large datasets and it does not have the ability to handle large numbers of variables.
Abstract: 1. The Nature of Econometrics and Economic Data 2. The Simple Regression Model 3. Multiple Regression Analysis: Estimation 4. Multiple Regression Analysis: Inference 5. Multiple Regression Analysis: OLS Asymptotics 6. Multiple Regression Analysis: Further Issues 7. Multiple Regression Analysis with Qualitative Information: Binary (or Dummy) Variables 8. Heteroskedasticity 9. More on Specification and Data Issues 10. Basic Regression Analysis with Time Series Data 11. Further Issues in Using OLS with Time Series Data 12. Serial Correlation and Heteroskedasticity 13. Pooling Cross Sections Across Time: Simple Panel Data Methods 14. Advanced Panel Data Methods 15. Instrumental Variables Estimation and Two Stage Least Squares 16. Simultaneous Equations Models 17. Limited Dependant Variable Models and Sample Selection Corrections 18. Advanced Time Series Topics 19. Carrying Out an Empirical Project
1,503 citations
"Microfinance Banks and Rural Develo..." refers background or methods in this paper
...…+ Ui (7) where the subscript i runs over observation, i = 1, …, n; Gi is the growth rate of GDP per capita; MIFs is the respective microfinance banks impact factor indicators; C2i is the control variable; B0 is the intercept of the regression line; and Ui is the error term (Stock and Watson 2007)....
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...…is a time series for the period 2006–2012, and thus we adopted the time serial linear multiple regression model of the form: Yi = (b0 + biXi) + (µi), Stock and Watson (2007). where: Yi = dependent variable b0 = the constant term bi = coefficient of variation xi = independent variable µi =…...
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