DEA and SFA research on the efficiency of microfinance institutions: A meta-analysis

Fall, François-Seck; Akim, Al-mouksit; Wassongma, Harouna

doi:10.1016/j.worlddev.2018.02.032

Cited by 82 publications

(103 citation statements)

References 80 publications

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“…Van Rooyen et al (2012) also performed a systematic review of 15 impact studies, looking for evidence of the impacts of microfinance in Africa. Fall et al (2018) performed a meta-study of 38 studies on the efficiency of microfinance institutions. Hermes and Hudon (2018) accomplished a meta-study of 170 studies on the performance determinants of microfinance institutions.…”

Section: Introductionmentioning

confidence: 99%

20 years of research in microfinance: An information management approach

Nieto

Serrano‐Cinca

2019

International Journal of Information Management

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In the last 20 years, microfinance has moved from a promise to reality, although with ups and downs. This paper reviews 1,874 papers published from 1997 to 2017 to perform a scientometric analysis of the microfinance field. The literature review is based on bibliometric data: keyword co-occurrence networks and citation networks were exploited for knowledge mapping. Data analysis shows the two research traditions: papers focusing on clients (welfarists) and papers focusing on microfinance entities themselves (institutionalists). Institutionalism, which had little presence in the early research in microfinance, now exhibits great strength. A chronological analysis reveals the evolution of the topics most interesting to researchers: the first stage described the innovations of the microcredit practices and their impact; the second and very expansive stage in which microfinance institutions' peculiarities were analyzed; and nowadays the sector is mature but with negative aspects arising, such as mission drift. The keywords analysis discovers emerging research topics, shows the use of sophisticated techniques, and recognizes an emerging trend of the sector: achieving financial inclusion. AbstractIn the last 20 years, microfinance has moved from a promise to reality, although with ups and downs. This paper reviews 1,874 papers published from 1997 to 2017 to perform a scientometric analysis of the microfinance field. The literature review is based on bibliometric data: keyword cooccurrence networks and citation networks were exploited for knowledge mapping. Data analysis shows the two research traditions: papers focusing on clients (welfarists) and papers focusing on microfinance entities themselves (institutionalists). Institutionalism, which had little presence in the early research in microfinance, now exhibits great strength. A chronological analysis reveals the evolution of the topics most interesting to researchers: the first stage described the innovations of the microcredit practices and their impact; the second and very expansive stage in which microfinance institutions' peculiarities were analyzed; and nowadays the sector is mature but with negative aspects arising, such as mission drift.The keywords analysis discovers emerging research topics, shows the use of sophisticated techniques, and recognizes an emerging trend of the sector: achieving financial inclusion.

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Section: Introductionmentioning

confidence: 99%

20 years of research in microfinance: An information management approach

Nieto

Serrano‐Cinca

2019

International Journal of Information Management

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“…A SFM breaks down the composite error into two components: a normally distributed random error term V, which takes into account uncontrollable exogenous factors, and a non-negative error term W, which represents a firm's technical inefficiency [43]. The two error components are assumed to be independent in the conventional SFM.…”

Section: Copula-based Stochastic Frontier Modelmentioning

confidence: 99%

A Simultaneous Stochastic Frontier Model with Dependent Error Components and Dependent Composite Errors: An Application to Chinese Banking Industry

Liu

Rahman

et al. 2020

Mathematics

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The paper develops a simultaneous equations stochastic frontier model (SFM) with dependent random noise and inefficiency components of individual equations as well as allowing dependence across all equations of the model using copula functions. First, feasibility of our developed model was verified via two simulation studies. Then the model was applied to assess cost efficiency and market power of the banking industry of China using a panel data of 37 banks covering the period 2013–2018. Results confirmed that our simultaneous SFM with dependent random noise and inefficiency components outperformed its predecessor, which is a simultaneous SFM with dependent composite errors but with independent random noise and inefficiency components of individual SFMs as well as the conventional single-equation SFM. Apart from the statistical and computational superiority of our developed model, we also see that Chinese banks in general have a high level of cost efficiency and that competition in the banking industry of China mainly exists in state-owned banks and joint stock banks. Presence of economies of scales as well as diseconomies of scales were found in different banks. Also, the state-owned banks embraced most sophisticated technologies thereby allowing them to operate with the highest level of cost efficiency.

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“…Hence, the objective of this study is to evaluate the efficiency of MFIs by considering a Network Data Envelopment Analysis (NDEA) approach; which according to the author's knowledge, has been applied to none or a very few studies in the microfinance research. This is not to say that this study is the first to evaluate the efficiency of MFIs; but rather, a large number of studies abound that have successfully evaluated the efficiency of MFIs in a single country, regional or at a global level: Ayayi and Wijesiri (2017); Fall et al (2018); Gutierrez-Goiria et al, 2017); Kaur (2016); Kumar and Sensarma (2017); Mia, Dalla Pellegrina, et al (2019); Piot-Lepetit and Nzongang (2014); ; .…”

Section: Introductionmentioning

confidence: 99%

Revisiting efficiency of microfinance institutions (MFIs): an application of network data envelopment analysis

Nourani

Malim

Mia

2020

Economic Research-Ekonomska Istraživanja

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In order to achieve financial inclusion objectives of Sustainable Development Goals (SDGs) and provide continuous financial support to the unbanked population, microfinance institutions (MFIs) must attain efficiency in their operations. Hence, the main purpose of this study is to examine various efficiencies of MFIs based on their goals and operational mechanisms. By utilizing a unique production process and network data envelopment analysis (NDEA) technique, we estimated three different types of efficiencies (operational, financial and outreach) of 90 MFIs from 2013 to 2018. It was discovered that the overall efficiency of the MFIs was not up to the required standard and it became even worse when the financial and social outreach efficiencies were considered. However, operational efficiency (ability to generate intermediaries) was relatively better and remained high among the regulated MFIs. On the contrary, the financial and social outreach efficiencies were found to be better among the unregulated MFIs. Moreover, our results also highlight the divergence in efficiency between regions, legal status and regulatory environment; with projection analysis suggesting a simultaneous reduction in input, and an increase in output of inefficient MFIs to facilitate their attainment of efficiency. Policy implications are subsequently discussed.

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DEA and SFA research on the efficiency of microfinance institutions: A meta-analysis

Cited by 82 publications

References 80 publications

20 years of research in microfinance: An information management approach

20 years of research in microfinance: An information management approach

A Simultaneous Stochastic Frontier Model with Dependent Error Components and Dependent Composite Errors: An Application to Chinese Banking Industry

Revisiting efficiency of microfinance institutions (MFIs): an application of network data envelopment analysis

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