Trade-offs in South Asian MFIs: regulation and governance structure

ABSTRACT

This paper evaluates trade-offs and investigates the key performance determinants in different types of 468 South Asian Microfinance Institutions (MFIs) for the period 1998–2019. Three indicators of financial performance are compared against multiple dimensions of breadth and depth of outreach to evaluate the trade-off between financial and social performance of MFIs. To clarify the direction of trade-off, we run Granger-Causality tests and accordingly, we regress financial performance measures on each suggested indicator of breadth and depth of outreach . Simultaneously, we also investigate the financial performance in relation to mainly different regulatory structure and profit orientation of types of MFIs by controlling for financial ratios, country and institutional control variables. The regression results show that there is no significant trade-off between the financial and social objectives in almost all specifications rather we have significant evidence for compatibility of dual objectives both in terms of breadth and depth of outreach in some specifications. We also find capital to assets ratio and experience to be prominently positively responsible for financial sustainability while risky and costly loans and being regulated MFIs reducing the financial performance of South Asian MFIs while profit orientation does not matter once we have controlled for regulatory structure.

KEYWORDS:

• Microfinance institutions
• financial performance
• social performance
• breadth of outreach
• depth of outreach

JEL CLASSIFICATION:

• D00
• E44
• G21
• O16

Highlights

• We study microfinance institutions in South Asia.

• Financial sustainability is consistent with greater breadth.

• Financial sustainability is also consistent with depth of outreach (when measured with profit margin through MSBA (Market share of number of borrowers adjusted by market share of assets) indicator) while it contradicts with depth of outreach (when measured with return on assets through MSBA).

• Financial performance of South Asian MFIs improve with reasonable accumulated experience (of 4–8 years).

• While profit orientation as governance structure does not matter once we have controlled for regulatory structure, we have strong evidence for non-regulated MFIs meeting their financial sustainability objective.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

¹ The financial sustainability of an MFI refers to its ability to survive by generating enough revenues from financial services to cover its costs. On the other hand, social performance/outreach encompasses the entire process implemented by an MFI to generate positive outcomes for its clients and the communities it serves. These social objectives are often reflected in the term outreach, which can encompass both breadth, in terms of the number of poor being supported, and depth, referring to the extent of support provided, particularly to poorer clients (Vanroose and D’Espallier 2013)..

² The breadth (scale) of outreach measures the number of clients/borrowers that a MFI has extended credit to and depth (reaching the poor) of outreach implies the number of assisted poor people or increased service to the poor.

³ We choose South Asian microfinance programs due to their distinct characteristics. For example, MFIs are concentrated in this region and according to Microfinance Information Exchange (MIX) Market; the region has the world’s largest microfinance sector, dominated by India and Bangladesh. Along with that according to the dataset used in this study, the South Asian microfinance program has shown continuing growth in providing financial services to their low income clients (MIX market 2011).

⁴ The various ownership types of MFIs are non-government organizations (NGOs), shareholder firms (SHFs), microfinance banks, cooperatives (COOPs), and others such as rural support programs etc. NGOs are those organizations that are governed without any legal owner. SHFs are those that are limited by shares. These shares are held by non-profit or profit seeking investors that can be an individual or organization. COOPs are customer owned organizations like credit unions and savings and credit cooperatives. Non-profit-oriented MFIs include NGOs, credit unions and other institutions while the category of profit-oriented MFIs includes banks, rural banks and NBFIs.

⁵ Regulation refers to the set of standard rules applied to microfinance; supervision is the process to enforce compliance of those rules by a country’s financial authorities. Microfinance needs different set of rules from conventional banks because of their nature of business. The typical area where regulation differs are unsecure lending limit requirements, capital-adequacy ratios, loan-losses provisions, and minimum capital requirements because MFIs assets consist of many small and unguaranteed loan. Compliance with prudential rules is required to take deposits that protect the institutions’ financial soundness – it involves capital adequacy requirements and, rules of provisioning loan losses. Non-prudential rules like transparent reporting requirement and screening out unsuitable owner, tend to be easier to administer because government authorities do not take responsibility for the financial soundness of the organization.

⁶ Our sample is collected according to availability in the MIX market source.

⁷ The primary data was retrieved during February/March 2017 and updated in May 2022 from https://databank.worldbank.org/source/mix-market.

⁸ See http://data.worldbank.org/indicator..

⁹ When we categorize the MFIs into these subcategories, we counted an MFI as belonging to those specific categories even if they reported their status once during the time period. So, for some MFIs, their status is not reported for several years but then they started to report them. That is why the mean values for Dregulated and Dprofit (printed in Table 2) does not reflect the percentage for each subgroup we just defined.

¹⁰ We see that there are big discrepancies between the minimum and maximum for some of the variables such as OSS, PM, NAB, ROA, … Accordingly, we either dropped some of the data or rescaled the data and re-estimated our results. Please check the robustness section for more details.

¹¹ These data are no longer recorded in the new website for MIX market dataset. To be able to extend the data up to 2019, we calibrated some of the variables including Dummies for age categories and Dummies for regulatory/profit status as no firm change their status once they declare it.

¹² See Table 1 for the details about all variables and explanations.

¹³ Due to high correlation explained in section II, we drop this variable from some of the estimated models in section IV.

¹⁴ We only accounted for country fixed effects in our regressions as some major variables like indicating firm characteristics such as Dregulated and Dprofit would drop from the regressions when we include firm fixed effect due to perfect collinearity.

¹⁵ Tables for this section is suppressed but available upon request to save space as results are highly similar and consistent with existing Table 6–Table 8.