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The Economics and Finance Letters

December 2020, Volume 7, 2, pp 276-288

What Explains the Overwhelmingly Positive Perception towards Microfinance Institutions? Application of Firth’s Logistic Regression in a Small Sample

Shankar Ghimire


Anna Valeva


Rong Zheng

Shankar Ghimire 1 ,

Anna Valeva 2
Rong Zheng 1 
  1. Assistant Professor, School of Accounting, Finance, Economics, and Decision Sciences Western Illinois University 1 University Circle, Macomb, IL, USA. 1

  2. Associate Professor, School of Accounting, Finance, Economics, and Decision Sciences Western Illinois University 1 University Circle, Macomb, IL, USA. 2

Pages: 276-288

DOI: 10.18488/journal.29.2020.72.276.288

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Article History:

Received: 16 September, 2020
Revised: 01 October, 2020
Accepted: 09 October, 2020
Published: 22 October, 2020


This paper focuses on analyzing small-sample business survey data. We survey 129 businesses in Nepal, where a majority of businesses express an overwhelmingly positive perception towards microfinance institutions (MFIs). The survey focuses mainly on how businesses perceive the services provided by local MFIs. In order to address the bias in maximum likelihood estimation in the context of small sample size, we utilize Firth’s adjusted maximum likelihood estimation procedure in the application of logistic regression. The results show that it is the borrowing of a loan from an MFI, not the actual business performance, which influences a business owner’s perception towards the role of MFIs in various aspects of rural development. While there is no strong evidence of the MFI loans helping with the actual business performance, and thereby influencing the perceptions, we discuss the potential benefits of owning a business that may be contributing to the positive perceptions towards the institutions with which they are associated. These findings have important implications from the managerial perspective of both MFIs and governing institutions in developing countries.
Contribution/ Originality
This study documents how businesses express positive perception towards MFIs because of their membership, not necessarily because they have more favorable business outcomes. Methodologically, the paper uses Firth’s logistic regression to address the bias present in maximum likelihood estimates computed from a small sample, something common in microfinance studies.


Microfinance, Microfinance institutions, Small sample, Firth’s logistic regression, Visualization, Mosaic (Marimekko) plot.


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This study received no specific financial support.

Competing Interests:

The authors declare that they have no competing interests.


All authors contributed equally to the conception and design of the study.

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