New Research Results on Trade-offs and Synergies between Social and Financial Performance
A few months ago we presented a MIX Research Agenda to explore relationships between social and financial performance. Now we are ready to discuss the main results from this research, based on the social performance data collected for 2008. When reviewing the findings, the reader should keep in mind that they are based on regression analysis that controls for other factors known to impact financial performance (such as age, loan size and lending methodology) in order to isolate the specific set of relationships being investigated.
The research investigates whether social and financial performance interact to lead to important trade-offs or synergies in terms of MFIs' achievement of their double bottom line. For those who like to visualize data, Figure 1 summarizes the expected relationships between financial performance (FP, down the first column) and social performance (SP, across the top row) goals, with green indicating synergies, and red indicating trade-offs, as discussed in the original posting laying out the research agenda.
Figure 1: SP and FP Expected linkages
+: Expected relationship is positive, meaning that an increase in the respective SP is associated with an increase in the respective FP, and a decrease in the respective SP is associated with a decrease in the respective FP. In other words, the variables move in the same direction.
-: Expected relationship is negative, meaning that an increase (decrease) in the respective SP is associated with a decrease (increase) in the respective SP. In other words, the variables move in the opposite direction.
++, --: These are the areas where strong relationships between SP and FP are expected.
0: No relationship (effect) expected at all.
? Expected sign of relationship cannot be determined.
The main research results confirmed several expected trade-offs and synergies between SP and FP, including:
- There is a trade-off between targeting the poorest and efficiency.
- There is a trade-off between staff policies focused on social performance and efficiency.
- On the other hand, staff policies focused on social performance are associated with higher productivity by staff.
- A focus on client retention is associated with productivity and efficiency synergies.
These results confirm the importance of human resources for an MFI. Investments in human capital go hand-in-hand with higher staff productivity and better portfolio quality, but have higher associated operating costs. Overall, SP training and human resource (HR) policies have stronger synergies and weaker trade-offs with FP.
The question of targeting also stands out prominently among these results. The microfinance community has long known that serving small balance loans associated with poorer clients raised overall costs compared with larger loan sizes. These results also demonstrate that targeting poorer clients, irrespective of the loan size offered, is associated with higher operating costs. However, there is no apparent trade-off in risk or productivity
The implications from these results are many:
- For MFIs, improving client retention improves financial performance, and process discipline and staff support pay off.
- Funders should not ignore MFI investments in staff training, incentives and human resource policies, whether they are socially or financially driven.
- Critics of high interest rates and high costs need to be aware that exclusive targeting of poor and very poor borrowers is associated with high average cost of loans to the borrowers, and, most likely, high interest rates that must be paid by clients in order to cover MFI costs.
- Researchers and analysts need to control for SP factors known to influence FP, in order to better understand differences in FP between MFIs, including retention rates or social responsibility to staff.
- The Social Performance Task Force needs to refine its survey questions in order to avoid ambiguous attribution. For instance, more detailon the distinction between SP-focused training versus general training would help clarify if the above results are related to job-training, such as credit underwriting, or training on social performance policies. Additional information is needed in areas where just yes/no questions are not enough to quantify important trade-offs. Better questions will increase the attention of new microfinance institutions on social performance.
In addition, two new results emerge from the paper:
- Rural MFIs appear more productive and efficient than urban ones, contrary to the common belief. The main explanation of this counterintuitive result is that, rural MFIs do not necessarily operate in more dispersed areas, where distances and travel times would reduce productivity and efficiency. As MIX collects geographic breakouts from a broader pool of MFIs than those reporting on social performance, we were able to validate this results for the full sample of MFIs reporting 2008 data to MIX Market.
- For productivity and efficiency analysis, relative loan sizes and targeting policies appear to be complementary variables in explaining differences between MFIs. In particular, differences in loan sizes explain process differences related to the management of larger loans versus smaller loans, while targeting policies appear to capture the extra cost related to rejecting borrowers that don’t fit the targeting profile of the MFI.
Since this research draws on the 2008 MIX SPS Reports, a rather small sample of around 200 MFIs and fewer observations per regression, we have to be careful about generalizing these results to all MFIs. The best way to solve this challenge is by having a larger sample size, so keep those SPS Reports coming! The main results are summarized in Figure 2 below and the link to the full analysis will be posted here soon.
Figure 2: Summary of Results
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